squiggle/packages/components/public/squiggle.svg
2022-03-01 10:59:48 +11:00

677 lines
107 KiB
XML

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<svg
xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:cc="http://creativecommons.org/ns#"
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:svg="http://www.w3.org/2000/svg"
xmlns="http://www.w3.org/2000/svg"
xmlns:xlink="http://www.w3.org/1999/xlink"
xmlns:sodipodi="http://sodipodi.sourceforge.net/DTD/sodipodi-0.dtd"
xmlns:inkscape="http://www.inkscape.org/namespaces/inkscape"
width="210mm"
height="297mm"
viewBox="0 0 210 297"
version="1.1"
id="svg8"
inkscape:version="1.0.2 (e86c870879, 2021-01-15)"
sodipodi:docname="squiggle.svg">
<defs
id="defs2">
<linearGradient
inkscape:collect="always"
id="linearGradient1298">
<stop
style="stop-color:#000000;stop-opacity:1;"
offset="0"
id="stop1294" />
<stop
style="stop-color:#000000;stop-opacity:0;"
offset="1"
id="stop1296" />
</linearGradient>
<linearGradient
inkscape:collect="always"
id="linearGradient1290">
<stop
style="stop-color:#000000;stop-opacity:1;"
offset="0"
id="stop1286" />
<stop
style="stop-color:#000000;stop-opacity:0;"
offset="1"
id="stop1288" />
</linearGradient>
<linearGradient
inkscape:collect="always"
id="linearGradient1282">
<stop
style="stop-color:#00de00;stop-opacity:1;"
offset="0"
id="stop1278" />
<stop
style="stop-color:#00de00;stop-opacity:0;"
offset="1"
id="stop1280" />
</linearGradient>
<linearGradient
inkscape:collect="always"
xlink:href="#linearGradient1282"
id="linearGradient1284"
x1="76.571401"
y1="151.27633"
x2="111.76118"
y2="151.27633"
gradientUnits="userSpaceOnUse" />
<linearGradient
inkscape:collect="always"
xlink:href="#linearGradient1290"
id="linearGradient1292"
x1="5.2482498"
y1="182.29103"
x2="186.45495"
y2="182.29103"
gradientUnits="userSpaceOnUse"
gradientTransform="matrix(0.67243307,0,0,1,1.7191531,0)" />
<linearGradient
inkscape:collect="always"
xlink:href="#linearGradient1298"
id="linearGradient1300"
x1="148.77826"
y1="127.45624"
x2="230.32274"
y2="127.13845"
gradientUnits="userSpaceOnUse" />
<linearGradient
inkscape:collect="always"
xlink:href="#linearGradient1282"
id="linearGradient1329"
gradientUnits="userSpaceOnUse"
x1="76.571401"
y1="151.27633"
x2="111.76118"
y2="151.27633"
gradientTransform="translate(6.8736031,-13.02113)" />
<linearGradient
inkscape:collect="always"
xlink:href="#linearGradient1282"
id="linearGradient1359"
gradientUnits="userSpaceOnUse"
gradientTransform="translate(12.804881,-23.027373)"
x1="76.571401"
y1="151.27633"
x2="104.2081"
y2="151.08932" />
<linearGradient
inkscape:collect="always"
xlink:href="#linearGradient1282"
id="linearGradient1389"
gradientUnits="userSpaceOnUse"
gradientTransform="translate(19.64349,-34.182031)"
x1="76.571401"
y1="151.27633"
x2="97.591568"
y2="152.79221" />
<linearGradient
inkscape:collect="always"
xlink:href="#linearGradient1282"
id="linearGradient1419"
gradientUnits="userSpaceOnUse"
gradientTransform="translate(27.881088,-43.504485)"
x1="76.571401"
y1="151.27633"
x2="89.349586"
y2="152.46567" />
<filter
inkscape:label="Rough and Glossy"
inkscape:menu="Textures"
inkscape:menu-tooltip="Crumpled glossy paper effect which can be used for pictures as for objects"
style="color-interpolation-filters:sRGB;"
id="filter1446">
<feTurbulence
type="fractalNoise"
numOctaves="7"
baseFrequency="0.02"
seed="55"
result="result0"
id="feTurbulence1428" />
<feDiffuseLighting
surfaceScale="4"
diffuseConstant="1"
kernelUnitLength="1"
result="result1"
in="result0"
id="feDiffuseLighting1432">
<feDistantLight
azimuth="235"
elevation="60"
id="feDistantLight1430" />
</feDiffuseLighting>
<feSpecularLighting
in="result0"
surfaceScale="3"
specularConstant="1"
specularExponent="25"
kernelUnitLength="1"
result="result3"
id="feSpecularLighting1436">
<feDistantLight
azimuth="235"
elevation="55"
id="feDistantLight1434" />
</feSpecularLighting>
<feComposite
in="result1"
in2="SourceGraphic"
operator="arithmetic"
k1="1"
result="result2"
id="feComposite1438" />
<feComposite
in="result2"
in2="result3"
operator="arithmetic"
k2="1"
k3="1"
result="result4"
id="feComposite1440" />
<feComposite
in2="SourceAlpha"
operator="in"
in="result4"
result="fbSourceGraphic"
id="feComposite1442" />
<feDisplacementMap
scale="7"
yChannelSelector="G"
xChannelSelector="R"
in2="result0"
id="feDisplacementMap1444" />
</filter>
<meshgradient
inkscape:collect="always"
id="meshgradient1448"
gradientUnits="userSpaceOnUse"
x="89.491364"
y="97.416069">
<meshrow
id="meshrow1450">
<meshpatch
id="meshpatch1452">
<stop
path="c 11.6532,0 23.3064,0 34.9596,0"
style="stop-color:#ffffff;stop-opacity:1"
id="stop1454" />
<stop
path="c 0,20.5553 0,41.1105 0,61.6658"
style="stop-color:#00ff00;stop-opacity:1"
id="stop1456" />
<stop
path="c -11.6532,0 -23.3064,0 -34.9596,0"
style="stop-color:#ffffff;stop-opacity:1"
id="stop1458" />
<stop
path="c 0,-20.5553 0,-41.1105 0,-61.6658"
style="stop-color:#00ff00;stop-opacity:1"
id="stop1460" />
</meshpatch>
</meshrow>
</meshgradient>
<meshgradient
inkscape:collect="always"
id="meshgradient1462"
gradientUnits="userSpaceOnUse"
x="4.9925599"
y="71.985107">
<meshrow
id="meshrow78144">
<meshpatch
id="meshpatch78146">
<stop
path="c 7.45327,0 14.9065,0 22.3598,0"
style="stop-color:#ffffff;stop-opacity:1"
id="stop78148" />
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
style="stop-color:#008000;stop-opacity:1"
id="stop78150" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#ffffff;stop-opacity:1"
id="stop78152" />
<stop
path="c 0,-7.39357 0,-14.7871 0,-22.1807"
style="stop-color:#008000;stop-opacity:1"
id="stop78154" />
</meshpatch>
<meshpatch
id="meshpatch78156">
<stop
path="c 7.45327,0 14.9065,0 22.3598,0"
id="stop78158" />
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
style="stop-color:#ffffff;stop-opacity:1"
id="stop78160" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78162" />
</meshpatch>
<meshpatch
id="meshpatch78164">
<stop
path="c 7.45327,0 14.9065,0 22.3598,0"
id="stop78166" />
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
style="stop-color:#008000;stop-opacity:1"
id="stop78168" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#ffffff;stop-opacity:1"
id="stop78170" />
</meshpatch>
<meshpatch
id="meshpatch78172">
<stop
path="c 7.45327,0 14.9065,0 22.3598,0"
id="stop78174" />
<stop
path="c 0,7.39357 -4.94039,18.0374 -4.94039,25.431"
style="stop-color:#008000;stop-opacity:1"
id="stop78176" />
<stop
path="c -7.45327,0.000373537 -9.96606,-3.24988 -17.4194,-3.2503"
style="stop-color:#008000;stop-opacity:1"
id="stop78178" />
</meshpatch>
<meshpatch
id="meshpatch78180">
<stop
path="c 7.45327,0 14.9065,0 22.3598,0"
id="stop78182" />
<stop
path="c 0,7.39357 -2.30707,17.2578 -2.30705,24.6514"
style="stop-color:#008000;stop-opacity:0.04350754"
id="stop78184" />
<stop
path="c -7.45327,4.76997e-05 -17.5397,0.779559 -24.9931,0.7796"
style="stop-color:#008000;stop-opacity:0"
id="stop78186" />
</meshpatch>
</meshrow>
<meshrow
id="meshrow78188">
<meshpatch
id="meshpatch78190">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78192" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78194" />
<stop
path="c 0,-7.39357 0,-14.7871 0,-22.1807"
style="stop-color:#ffffff;stop-opacity:1"
id="stop78196" />
</meshpatch>
<meshpatch
id="meshpatch78198">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78200" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#ffffff;stop-opacity:1"
id="stop78202" />
</meshpatch>
<meshpatch
id="meshpatch78204">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78206" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78208" />
</meshpatch>
<meshpatch
id="meshpatch78210">
<stop
path="c 3.87557e-05,7.39395 -5.90021,13.2054 -5.90013,20.599"
id="stop78212" />
<stop
path="c -7.45326,8.7306e-05 -4.06604,-1.66847 -11.5193,-1.6686"
style="stop-color:#008000;stop-opacity:1"
id="stop78214" />
</meshpatch>
<meshpatch
id="meshpatch78216">
<stop
path="c -1.24236e-05,7.39357 -3.88297,13.5848 -3.88284,20.9782"
id="stop78218" />
<stop
path="c -7.45323,0.000288371 -19.557,0.400607 -27.0104,0.4004"
style="stop-color:#008000;stop-opacity:0"
id="stop78220" />
</meshpatch>
</meshrow>
<meshrow
id="meshrow78222">
<meshpatch
id="meshpatch78224">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78226" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#ffffff;stop-opacity:1"
id="stop78228" />
<stop
path="c 0,-7.39357 0,-14.7871 0,-22.1807"
style="stop-color:#008000;stop-opacity:1"
id="stop78230" />
</meshpatch>
<meshpatch
id="meshpatch78232">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78234" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78236" />
</meshpatch>
<meshpatch
id="meshpatch78238">
<stop
path="c 0,7.39357 -6.01545,14.977 -6.01544,22.3706"
id="stop78240" />
<stop
path="c -7.45327,-8.01414e-05 -8.89105,-0.190004 -16.3444,-0.1899"
style="stop-color:#008000;stop-opacity:1"
id="stop78242" />
</meshpatch>
<meshpatch
id="meshpatch78244">
<stop
path="c 3.10527e-06,7.39365 -0.0382289,13.9513 -0.0379909,21.3449"
id="stop78246" />
<stop
path="c -7.45341,0.000383232 -10.0435,-0.642532 -17.4967,-0.642919"
style="stop-color:#008000;stop-opacity:1"
id="stop78248" />
</meshpatch>
<meshpatch
id="meshpatch78250">
<stop
path="c 3.5686e-05,7.39385 4.33284,13.6555 4.33284,21.0491"
id="stop78252" />
<stop
path="c -7.45327,-0.000221183 -23.9283,0.695979 -31.3813,0.696219"
style="stop-color:#008000;stop-opacity:0"
id="stop78254" />
</meshpatch>
</meshrow>
<meshrow
id="meshrow78256">
<meshpatch
id="meshpatch78258">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78260" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78262" />
<stop
path="c 0,-7.39357 0,-14.7871 0,-22.1807"
style="stop-color:#ffffff;stop-opacity:1"
id="stop78264" />
</meshpatch>
<meshpatch
id="meshpatch78266">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78268" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78270" />
</meshpatch>
<meshpatch
id="meshpatch78272">
<stop
path="c 1.32797e-05,7.3935 -14.0673,12.415 -14.0673,19.8086"
id="stop78274" />
<stop
path="c -7.45346,-5.33636e-05 5.17607,2.18213 -2.27706,2.1822"
style="stop-color:#008000;stop-opacity:1"
id="stop78276" />
</meshpatch>
<meshpatch
id="meshpatch78278">
<stop
path="c -0.000162493,7.39392 -3.454,15.1027 -3.45401,22.4963"
id="stop78280" />
<stop
path="c -7.45327,3.26943e-06 -20.6567,-3.33057 -28.11,-3.3306"
style="stop-color:#008000;stop-opacity:1"
id="stop78282" />
</meshpatch>
<meshpatch
id="meshpatch78284">
<stop
path="c -6.60986e-06,7.39337 0.470451,16.6207 0.470477,24.0144"
id="stop78286" />
<stop
path="c -7.45328,6.65414e-05 -27.8522,-0.821779 -35.3057,-0.8219"
style="stop-color:#008000;stop-opacity:0"
id="stop78288" />
</meshpatch>
</meshrow>
<meshrow
id="meshrow78290">
<meshpatch
id="meshpatch78292">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78294" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78296" />
<stop
path="c 0,-7.39357 0,-14.7871 0,-22.1807"
style="stop-color:#008000;stop-opacity:1"
id="stop78298" />
</meshpatch>
<meshpatch
id="meshpatch78300">
<stop
path="c 0,7.39357 0,14.7871 0,22.1807"
id="stop78302" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78304" />
</meshpatch>
<meshpatch
id="meshpatch78306">
<stop
path="c -0.000194003,7.39352 20.0828,16.9693 20.0828,24.3629"
id="stop78308" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3599,2.84217e-14"
style="stop-color:#008000;stop-opacity:1"
id="stop78310" />
</meshpatch>
<meshpatch
id="meshpatch78312">
<stop
path="c 6.84636e-06,7.3936 14.3325,13.6387 14.3325,21.0323"
id="stop78314" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3597,0"
style="stop-color:#008000;stop-opacity:1"
id="stop78316" />
</meshpatch>
<meshpatch
id="meshpatch78318">
<stop
path="c -3.28362e-05,7.39368 1.38656,12.8168 1.38656,20.2104"
id="stop78320" />
<stop
path="c -7.45327,0 -14.9065,0 -22.3598,0"
style="stop-color:#008000;stop-opacity:0"
id="stop78322" />
</meshpatch>
</meshrow>
</meshgradient>
</defs>
<sodipodi:namedview
id="base"
pagecolor="#ffffff"
bordercolor="#666666"
borderopacity="1.0"
inkscape:pageopacity="0.0"
inkscape:pageshadow="2"
inkscape:zoom="1.414741"
inkscape:cx="422.78116"
inkscape:cy="484.64466"
inkscape:document-units="mm"
inkscape:current-layer="layer1"
inkscape:document-rotation="0"
showgrid="false"
inkscape:window-width="1442"
inkscape:window-height="879"
inkscape:window-x="19"
inkscape:window-y="13"
inkscape:window-maximized="0"
inkscape:pagecheckerboard="true" />
<metadata
id="metadata5">
<rdf:RDF>
<cc:Work
rdf:about="">
<dc:format>image/svg+xml</dc:format>
<dc:type
rdf:resource="http://purl.org/dc/dcmitype/StillImage" />
<dc:title />
</cc:Work>
</rdf:RDF>
</metadata>
<g
inkscape:groupmode="layer"
id="layer2"
inkscape:label="Reference"
style="display:none">
<image
width="270.93332"
height="167.48125"
preserveAspectRatio="none"
xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABAAAAAJ5CAMAAAAHPrKCAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA b1BMVEX///+bm5vg4ODLy8sBAQHOzs7u7u51dXX8/P1BhfWvr6/29/lIifXZ2dmEhIRKSkplZWU5 OTlYlPXq8f7d3d3S4v1uoveSkpITExPo6OgnJyeGsfjAwMCbvvmmpqa81Pusyfu5ubmxsbG1tbWz s7MH9h/FAAAgAElEQVR42uxd6Y6jvBJlEaaEhX8hIUsWEiHv/4zXtRhMQpbu/nruMCnPSJMOHC+M fepUlU0XhRYtWj6+gOIVr/gPxcMPK1G84hV/XvzX2QW+1KDiFa/4vxcPX8brdb2u1/+V6+ku/PNm ZZAhFK94xZ8ZD4csAUcexgrM5YPiFa/48+Lza/ei4G0nQ/GKV/xJ8UVxowTgOG4AT/0KxSte8afE w4vYwKvwguIVr/gT4p9RyMM74GGzile84s+L/27RPViKV/x58S8I4y2c4hWv+PPi70TC9zlG8YpX /HnxB1B4UD0Ub2w8ULziFf8X449pA45FBjyqWfGKV/wp8fAoRLhdhDsx8U6IUfGKV/wp8NuWYng/ zAB7tOIVr/gT4n/tALEWLVr+rQIvQwyKV7ziz4eHQ1/i+8ygeMUr/jz4r7UEP6hc8YpX/F+Ph5fK 4fl1xSte8efFa9GiRYsWLVo+prw+SHivGe7eK6R4xSv+lPhX/sDzVxKA4hWv+NPi3ztMePgSAXg/ vKB4xSv+L8fDrY54cMjgVnCA4hWv+NPitWjR8tkRQHgSDoBXnoPiFa/48+K1aNGipbj7JSHHe4qf +A6KV7ziT4mHxzFEePK7Bp6dRP538eD7OtSNh5+3X4CN5X08/jXWwh8c/9bFo5vwIh1IN3jPm+0z KJZ1KO/13xoLOv9+AQ93X91gbt4fBE+yCf883tajc23rYgnb9AVvvtE+FHZy7rJ/i8tzPATnJlP8 ufFDEbs4wYP+N6Mbq/jTHO/xx+3bCm7aryKojp9r50oPr/sPxuMnHx988/Hz7xfwWr7gJfmx3Ypr 5En7ztXfqs/G6qYvdWBp29H80TGXbVs+mjG1a90Q/73Ee/yhwulHd9vdKhJoiP+GOJTq9YhNaDt6 yBHW6NT9Tfdf8a+KofXvxnF0GQMgKzTfI4CSCQB+SAC/OX4hAHhEAP0zAmjiDQcE4G4I4En7dmrb Kz3l9vFT1vmr5Y/w5AVX/dIMvupn5AKa9dDHGf09BWDKcygA+6A3ogCgLsvlqFcQF/kdAfipLHsh AP8W53b0IcIGnela/o8FTf3YyOtXUcm26MsW3ycAW57fBejJ0fcG3iUA8N7bt10AJIDLClMC+D0f 4DayAHcHjp5sKP4MfFzpbbfGUPpIABMGwfHr+lvtrwrgrfbxqzsC+OXxJwVwiIdEAEfpJvqzEsBB UooJ4FX7ogAe7l8Fnb8/wmv5QqkxfAW5bSpNtH5zXAaXqrIc9vL1Mk3XRiyi9UOc5L7uprnfjCSY 5jqFymYKIAKbCFxWYFV5a+ru0luOpi3T0hu7YJv5f6EdKgOxD1MXKpuFzvowdXWVTKap4l1+nkI0 or6qAEzoYictQIE1d7WHVKmN0G7C3sFDBWCrWHvsaSIAUw0epF3siQzV9B0GSqp4jTsQYrWxsxXV TQSANW1PJt7lITWBT9RWDcZJ4xij5KpSl8AMsYv1YKXTCIvX+Rno/NZAyG/hG4c2f7N/lxD9gSYl BXqUqYtLKYLOi3vQ+qt8FcR2myvfNdYpCwD+moDtxSB5V7h06LsyLv9arobuRgGgjZ16yU2Mg5UF EuR+V/M3EVYG7kP0Y1w/Swd6EKyb2VDbYc1zRGcHDgkAhpLvmCIdbVkA2AYWL2F2sEw1+WLGDtDF kAUBXS2txdbjoEkwyPON42+HYkj1BbtlAbbRBWaOCCtTn+KQdP7+uBo4qBWKw1869El4jAG4brC7 qvqVAAAqnoU8P9E9IAKY1sThzBN4/QJvJAKoxgzYIXDAzQb8Y2FnlyFGk/cM7eh2lWd/VW65ys4L AXBtrsZBlCtN1Ss24MqTlpzUtiqAnXrs897kWQDbbaNA935PANKBkKUB27WmCaMBNnkMPP52gJUA ZqAsAFAQcRsd7z5A2LglZ3X+fgcPX+GXB7997F/HUxagHVeJy7Z7meIsLeclKnGcmuMcwjKl1cgG 1k3zFT84L4G8yCNh5vUx4Y46/DguEVimNVWtS6wHUgJTmDteWiZ3w8mut+V1nugmmwgGG6D7F8sr tKUlOJpKerSItXblci1bichjS24KIdDF8lABUAXlEi5c0bYPAHoaRR2WkWisaJYIdpclypB57YDP FABWNAdSTR1uN5xvFUD0VJDylnlI+wCAWAb7SKObsGvMWuNloa8OcxY6f5/99CQ6sD9rdHfICD4L b8SmuXIKw4pNWQBKDJQVi3y29xQgjLLURs8XlyVOfLRqY3S/RTBPMtt5V5zH6R3EAsbbqqa21Cq6 D4aYYDR5X2kZXaJrb2nxDnGFoEIeMXRAngPRCZnmqe/rhmRMNJOGAVH7R/ffYwuVmPAa67fEXDg8 JoAtpARXsrwYPCjbnQKgCCWyHiBHIKFIEDAKiHntAOwIgCsaiS4hTxqQAsiyACsBBH58cZwYHoiO F3BNXQX8FQsXnb/v4rV8ofhuVZpuFP963QdA1lhcUJyuaNQGl4Q5cQGu9iuuOlj5BL9atm2FJt51 taIABvo/qpJpJxN5HwNITkHgrTJUK2/MhZpiCKwAKHgI7MdQKJOUAtvLgXuOC1cMqMWmTHG/D4By oRTfAKGcRAAU0jSJlpAJtxU9rxSXbwRKGwF6lgC5AsAHNxTZPgBxAajTvMSp/ZFzDbIlg2oIOk+1 /Fax/bT6ra1sTMGV3ZCRqq8S5wOat9HK4zVxoT3bUlwmaQ03wgkZEOJXF8tLkqU3rfqBydo6yjzs k2lpg5zslauEe9ZwA7ACCEz5ZJ03OumLZF4D2uLQ9SnEKTRy6wJgnxd5GNOmAOJSBmrFYs6QTxDd EMDMyao8BlCLz8qkYrMgIMcAsn0AogCIo4qsfc81hS0+oQTw0yji019A/Nl44oDoqbss5MwKIKkx MMZXzUWigH0yYLwYR5bHU5ZJnLbUXQJ2ogAu/H2Z7Bs7wPcKYODeGSaAhuX8xg+eVqhL2mQUz5kv mlWw1CIXwRpTDWG8IwBIDbpKfq5FAXTcQ0qIuEvjjUQNdwSQNkvlWYBUEX9mBcCStWqPFUAjsp8H wGnIsAmoOBA3Fzp/v4aHV5/hQdzw8DzhB+AxsU8hMLTG7AKk7H0zdynGjrKdLRIke1XyN9fUfik7 i4CAKZzfiQLgSlETpBOAuETWGAD1fltGhaUlQnbdp26jve7JNqe7/EpJRB6b4xEkdx+uU+qIz7MA sqYXiWWKBs+zAKZMccXQ25wAKAaQGCgjgNJLrQ2LHOzQcwVAwmQ9QdBwtzETIsIF75p1/r6NL16+ HvDlu4Y/Di+LwVPsuS+yrcBg5vy04CQuACt0yhGMHAqYi22bHSkAs+TApAD61SnoJPKP83/MNwKB 7KhH600EsFuhTACBNbr4GEgAVwbgYuKJkAgAmszDOXQBMAbo0jsMBjoLAOthIL+i3ZUc/lwBpH2/ TAC0bIk/U5ijh/ssgCgAWIOAK0ek9uNY6BmwN4aj2ysAnb9v5AtvXyECL6TC7nVkn4P3oZv6NRhe 4K488mt5KzBq8ClZwGvtJAawnRREF6AkSkhTFIqJ04B2zS6swGQBIVcAJLrHfG8tLTHZhYcEUBeZ AhACqHkfgKxaJIB58w+K3AWAJm0pmnDLUUYA24O5Ztv7+zFTABRX7FcKnHwB9wSwjwGsmxp7Wu4c A+DGcgWwnQZkBbD6QPgsl92pgqQAdP6+h3/mJOzfPPwK+wH4/ub0/iBZ/FUBcDqqqYwxdNLfpgAh i2v03wuJCsDq3k8SInNT472x4DYFMKwRslIWPRk7k/d4O1OXFEAjK5eaqFlIXFLgjxXAUsCeAFgB 8OsOXOh9HEAeBMyyAGSlV+W+vQ9AZEhhTVWzJ4BBxTonAEHtXYAtmJBiAGLc72IAHAQUF4Dbr5lL 0qkC2MUAdP5+Fa/lecHwnfP7n7vMBcBFn2fz9i4AxwA4DZc0tQQBIQPaLAYgBDBtBo7quM0CiAIo WAEQssmWaxsviwIgA3ykAAwpAOIOPPkj0uIwC5ClHVIQLu0DMIa24kN0hVpSLdve3jsXYBe9AGYQ u8UAqCt7BcAEkIf5iTCavQIYsxiAFi3/ZUEN72a7C8DXxeYCAM16WDUt6vYbF2Dk9Zz2qgROA3ph ixQOu1EA9Zbl8u5mJ6CY1kwBkMQupTbiLMgVQMEKYK04VwC0AKssgXigAGhEpRx8KndnAYxb83oF pyv3LoBohHwfQMjo0qw5C2G6PAYAKQuwZTE5sSppQHoz2W0QUMuX8n+w9x7gzVACFB+Dx/XqFi8v u6NtdqhGMRT2P/auRD1VHQgrCv3bKLZuuGvb+/7PeLOxBBIIWsCeTr5zrAs/E8IwmTURnMxeMmNd ptblJoACKA1A6q1STqgEvKIAUPqBPEmuAainXj6X7OvFYgLEBQEw0Y/uSTrupZviMtI+gCwMGH8X NYDUMTApCgD59kVX9BgagHzqZQ6UTjRElggUZ1Z9pB2Xk7R3pgaQ5QEkMr9BXhY/pZz235D6LpQG kPpJtQYgkxWVFJa5ShftCNUBxdwEIP5t40oc1QcM/ByL/zxeVfGM/5vMw4nKvRc5e2pSmsyl3R+L mhoWXtIY4TouawA6/2/NVCqt5OBYAcFC9VVU1AAUo49DxvbfqhagpJEbGgB09uHnnrHgEueBetMH YHECnnTiIH/qoUIcMgyRrwdQiL3Fp70uOSxoAHLWvsgiXiWDlI7xFc5ZQVExNICXhA9b8J2W9cja n88g2sssBHn9Mm/qFO6zVGBRrhh/c1sj+ErDMGUTgPi3HR5WF2Ft1OGP4vWaoGJNYJUKKJ9FuVJg zI34T1UmcEnD4VEhS1BpAIn2XfN3Y33UJS0PyoHCN1bQAJQ+EY/HinolESh1r2sNAEzJCX281LLf Chk2FR8AUh+AqvNJLpeLduWfLD4ANV/HyVivizhPw4BQzy+nO86WS5ur2Ebg8AHkl6VcIFKEZEsu qiiIvHZueaXVgPiMC1f3mY8BtCSzJgIR/zZJD8NnaM8qQl0u0t/AF0tRM4NfPr+i7C7Ky3DHui6g HAaUZwnTaPlYOwFZYgJDwwdQXIzYlgkY68T/VANQ5UBpybyc+JUGkC1h+g1TA0jzAFheHRyLSr7E CAOmr+wr62xsZAIih6vAPNSIxJM8CmDUAiRJVsfMskCLHttEX786Z5KuB8Avc5Kvy6xsgUoYkPi3 Fd6rMggW2wMtlhr6R/BsfUli1S5BHhoTn9+47nsSuwbE8XgOsYw9Z/P1OFZJahC19rGOIu7f5Bne +N/kv/Q3DYxEmREQcPw+s+fkifkP+7naFyC39SZqSX45f/IjdJ7Cfqz6+KXVbn76sXIyiGSd5DTS aYJxrDWAcSznYAQa+BkJjJA1vKtvJZbCXPVmwo+WU6/crUAVM6rr4E+mTsy5yAPB+3/Rl8P7lkxU z7+jLzWUWXJjpE7ALQMODHSsUZyCiQHVVyd+E1TeArV3wSRROwxIiaM2HSD+9cc/vlXA38Kz/TwM w8CoOsderYopFvaa75u3cQdbh4ERsi0CbUKaBeGcOe9pVcMD72XA7hiYaB2uo3qrEfLskXXZCQRh OA/yKlQ+IuW1PI3rxt4YSnHq8ggiKi05KlIXOZE8HtM84MS/rQIC6Vnh3l7Mqk78Dby7qholVyxq /Kw2hy2qtxWuG13eAqayYUxDPhjqJUndwNSuT1nqLuDwSNvmHpSG2O7UTucuoOmpIP5txsMK83dA /jU8KuMIlyXl5YyFu5bDy7sLdxdRlRkeZ4B5ZU1L0cAZcIJDeDQEtGrHj/jvp/GN0QG4ObeJd/9t vG1+x8j61ch+lF1TgIs+nP2HbbpEgyMYdk3AQ5mEi/dsgqZ+/EfWqhY0jx/x38/hK94E671FnXr4 F/GoOwXsSqvdWncYx/YbCS9NApVnusl5jLIEQQUPpzyBjZC5VBXqFBiU37jHj/jvp/ENqoBXWdHf xqPekvelX4eHd/9hhcCj/21U77bjB6/xA/HfgPi6ciFzXmtfavgX8KV5q+bZ9jLE0M4VYLXwYXff eV//o3jH+BD/PBfetgOVw+tc+gGEtz22NXjzCG/6aMaXE0Fg9Ri3678fvk3/G+hjRPw3CP+28g22 bH8Dj6ft/9CN+OeX4RvsQjSonYT3tas7xY9o/Anvg6dGjRo1atSoUSPTifCE//N4PHg2whOe8L8H j3uIgfCEJ/y/gLd8AYcYqd+FlPCEJ/yvw+NBA4LwhCf878WTR4TwhCd8DdShcMDvzIQnPOGfH2/Z Xcztc6gpMSY84Qn/+/A+2oNt8Sb4iCDCE57wT4l312TVrQ3jli6EJzzhfw/eSxWAXY3wViYIT3jC PyW+fhlL1Je1Fz8SnvCE/314V7pAo1xp2qOc8IQn/PPjW/3m6TkkPOEJ/zvwHgUCeHAnMcITnvDP iXes3ApPkG2VS8ITnvC/EN+wGU3dancNi9Qiisq704FF8MM/Sp/whCe8B97PwmjaBc4GmY9f3scT Zugt+0Rs8eq54t1j9AlPeMJ74UcuBaE5a6Dm0HAxPRymH1+sKJCS6eHkiX+UPuEJT3hv/6Dlj3sD AXjg9++7xdf3y+4QFI6cHKaHTz/8o/QJT3jCN+Hhqx7U+SDt+NNhdxphvZhe8t+ixVRrAM34R+kT nvCE98CnzkM0Zw9b1iSHC4/xdBHxP/Fukbsa4uniY3eCD/5R+oQnPOE98A7f4cheMey5tx1/iV6m sbD+vw67zB95ORzCD9MH0Bl9whOe8O3xduHhuf1MsXEBkDBpCUy1F3AU8tl/vRA+gLY7Fd9Bn/CE J7wnvuotgLcx4cLv36djoWJMMgGwf9nFbJ1pAOiWPuEJT3g/fPoZllUDvM9SxkdaAAgNQH7HLrvF GutF5gMQLXnviv49+GA/GpS+gY8CNij9Ah6MXZIVY8Aw9CuoIMKQ9Mv4ffAc/Kuy7wQXt8Q3lwdZ Vx2uzSOKYm4CQJoA6tj5YRefJpePXSJygzR+Me2K/h14TNaD0jfbPowGpS8b21xvxy1vr6/idXs8 3zarHunb8fpGDUa/jJ+HT8G/KRcHbfGtmi+KxcoJ+HbYqS9O0+mON/GaiSgtALqgfwfeKgB6pF+S oJNoSPpY8Ud/uVzOZrPXQuMfl8vt+boBOr7+GnyJxwfnnzoB0Pv9Y2Hwg/RRj6w722W6CLiwfplq LT9cLD74v930sPAXAA/Qb4+3CIBe6Zc0ACEAhqK/2pyXxaeef5DCIP9qe12h0+uvwbP0Rg1Ev/zd fPIU/KvN/yIX++EttofHmgIl86OCDxfTN66sfYhEoChMSwLWC+kETC0WKQC6od8ej5yvBqFv4rUJ MAB9Pvmf9aMupnuu91+v7x/7zfV85lZAJga2N60G9H7/pAbQ9fj746UG8AT8m0rHYNSy/900Fu8O cbKYivn+c/GhZ/35YlfMA2hvAnTYvEyA3tp+Eg1DeHM7ykd8KSz+62YlPDZ4/5BMg9Vmc7sdj8uZ 1ALOGzZED9kDJkAXza0BDMLFLQenujcAKhICtUqHHT8KYmHwL058mvg6THWvRBgQhgDoin57vBQA A9I38UUB0B99bM5bqfwvj9cVE05lyNlFCQAxSPwjW21u21d9FDNdyX2Mn8HjT8A/ygcwOP+mXBy0 wteVBRd0C2veYJ6HaDM5EE0u489AfBeFJx3TYvOwyNdCA+iG/h34igbQM33zAG4C9E9/c9yq2Z/P 7SguMcEFgMFsbHXVImB7XY16vn+pBtDp+LfAZxoAnoB/WM7FfniLPKnGCGC4DGq2JSodCBQMDvne LEmqmAA/Rv8OvBAAQ9I3DzR8AH3QB7uqyX+2vK1YKXdUCIDCvRSKAdscpTtAHA70ev+kAOh2/Nvg C1GA4fknc5DAD58nIKC0wVD+HSoyo1yDUMWjdA677FpMu6LfHj8qhJeHoF/C6yhAP/T5f7bZqsd5 e2XIC03075kGkBeg8JYqDLPbqs/7x7Sk7nT8vfFcAwifgX/1b1w9QuUpdONH3u7An1mwtHSwMgF6 pF/rBKl1Ava94GvZCdgtfaxuS/n4H+1+PSUAqoVlK+UymB036O/+mX6uofnHMw+gH/6B0wnYjgya gKh3SaAp2ABHFOBH6bfEZybAQPRNNS1NBOqFPp/LZ8Ktn0b2CmYbDAFQ9imBS47jUgYFWV/3T/i5 Oh9/fzwqJsCA/KOdgIVHryW+3k2AVsKkenAF35wI9Bj9VnhrIlCP9EsaQBj1Rh83ocrPxONfXi8W RQ0ANqsSyh+4PK56u3/eka5+xs+tAfTPPyiFSHzwrnygZh0BD+KzRKCB6Jv4ggYwCH0T78oD6IA+ E3P4bHllrvTyggaAqquaawFHmRaw6en+iShA5+PvjU+jAIPzbyUK4IkfslEiUL0G0MdVY7OVVvyq jh0ME6DqQWA3kRo0OzP0c6OeLBEofCouvicR6IH79hA+TQQair4pyu8SAF313zcT8EH6WIm039ny xlA3SRQ0ALspKWIIs9dmX+BP9L+aCDQg/0gB8BT8e790rFtQAG6tAS5fgj/eXg7cH31ThzJrAXqn b+K1E7Bj+sr793q8VjM5DT9AQQNAyQWmP69k+RAXJOb+9B30H3mkC6Oh+QcWDWBQ/pGD0w5f428d uZcRdbr42uANE2AA+ia+ogH0TL+iAXROn11lEO+8sp2gaJRKAQA7/excW1E4eN50PX7FSQ4D80/R BBicfytOQM/+u3oBi5vBqrHcj69qAP3SH1U0gAHpm++VD6Bb+qs0gofqnA8jEFDOA7A7E1Qs8YqO x4+lYcDB+Ve9K2oAQ/NPoVLKu//l9ygn9Y/cgUk8hi9qAEPQt2oAA9Evvd1neQCd0Ve5f8dNWWU0 tUeUnICwaatKW5BmgOlP+Pn+G5McBuYfpQFMnoF/02KgcN22/wM2igI4W+flwNhIo93Pc++MApSa iiicWcc3iqIAztZBrXSHqxh5CYDeVsFyCAAMMn75kmDd0FfP/3bjsg1heAXrBEBRwdQ5BWdWiGn/ eP9ZO0nd+f1rWA+gX/6pSkefdYcsuwb8z9617baO61BjBlOsDWdekp0Cg6JI/v8rT235IkqUTEqy mDmTPGxkp11dskwzFK/JFkKgHuAq/N4RyIaf4okPwICf+gAYC6Al//T8uxR+xH52aomCZAJG/MQl BTw3DXDW+kHKge3lx3cCmsuPd5AV4jMaJ/4+0GmsQzxrAXTkZy0AK36KWqMAJ/HPLnuavYuEJSA6 AuwxqdFpgNtp+4eDs1r3+xdYALbyMwZRAA0evDUoC1kU4akC6M+fOgKY8FP8ngnYnP9HGpbnf4we 9kRfmlAB+N/5QenXrAEunh+g/foPC9763r/VB2Asv4Edq8e/nYD/EScg3Pk/n/xb5gR0X0IPqgH+ BX6utxPwrQD+O7UAeMzn//H4DLj970gBhAeMScF83067UW8F0HxzwNuKvpuBhIjRBL8rABt+eoaN 2s335aeH8A/nAziBf33++YN/8AGGsBowcaQEgW4a4Iz9G5myTUv5WduCG8vvEofxsqQU+EiXFx8S VHjGAujKz1gAdvwUWHoEOORfnv9bql8LOzVKfgTATlJkA0hq3nNfcgb3j1gA1vKzHAGgl7iETyEL RCU+2xKsAz91lgRHgN787BGgOb97/r9vGYOfVPmkowCgdgNimh8NcMb+jVvzRgyvID+JPAAT+fHS JIX40HoDl8IRhB2H5BRdJX6rBTDipzu5zQWw4ad4EgZsx//zYF6m5x8085d49Rm5cF2BNfwbUfv9 w9oQZLCW380CeAX5dW9HegSQ4Eusg6ENXjEb8BT+IyegTRLgbgE059/9f9I/LswDYID3a5Rq0GT/ IPfW9rl/uZZg3eWHn5oipUHREsvxYTVgb35aMVkSBcBZ6xdGAXT8S5oeju9/YD9mOwIl+EUaoGT/ /AG4eAH52RUA7OUHktmAElWDY1WEavxmARjx030kCqA/f2ABECdgG348Lvvzjww+Oj6yCuAA79IN XbpBy/3DngpsLb/REcBefsZ4c47wzGjSOMc7azYU45daADN+gl+jAFb8FP/Bzgas45++kpfyv2RM KJzv4t7HCiDLv+Lvsx8AjfdvpBWv5vITRAGM5cezAGT4pNbHkAr4sj/S4veWYDb8iEcq/DbkD/HO AmjKP9XqOrcc2Pa+A5cuGvkAxPxryvH1ibb7t7a+h6n87j/y+gFYy4/vINHgwdkFYm8EivGrArDi J3iSB2DAT3+T+gBa8N++Lqnmv3HD/+A7JOsEBDcwALvT4fo4On+q9g/hMRfG8sPlAVjJD3c+EjkX wLNjSIyDCIf/qPHBcNDu/DH+RwGY8lP8agE045/b/37eaMAvcf+HsEh4UQBSfo98Zr2j4f5FA3Ct 5WeyAF5AfodlaMJvMf49F4DK6/91LcD4nPr/3FB22wvCgOuufhG90+ZGvWsBjDenVXyzVAGcEl9V KIAO8d1sKnBBmOcx2+JAGT5QAJri8jHuPFC5f2O1pm57//QK4Dz5gUgBHE0aReZcnmssrsaHCqA3 f6ItuA0/xXNRgAr+OSb/RBne7wgkxm8/d75HtNs/75iLV5CfKA/AUn5A56YJ8JJGwTlHXQV+rwWw 4ad46gTszx84AUlHoEp+3D6XyV0oWz+1AET4/Xg6Rx+f7fZvJGWb9vLz958vIb/r5vyhw3NuoEQZ AVOyiDp83Ba8Lz/B7z0BbfgpnjkClPPP0ztJAEC5/q0WQM7vux8mDXBX4tP750UB8Ary4ywAc/nd jwA6PNcPPuO4T5gqRXivGtCEPwAl5gL04qdvP7a5ANX8GJcAALi/J1l/wgeQx3veZhIKqN2//Zh7 2v7r8Gs/AGP59aYDa/CmDpQSJ+BpDhShE7BTgUfSCajnH5/u+atYeWowyOGlLoG778UCQYv9q3N0 t79/OifgyfJzuDmilBia0ZlyOqAaHzsB+/KHCsCUn+BXBdCAfwkAZNO/jtbPjgaT4FcfxBfThKJ6 2QwAACAASURBVLB0/9aUTZjLb6gAXkB+liOAGl87O6gMHyYC9eYP/Ke/TfnpW2UeQKYwZ/bCP1G1 fklb8CHhWsK2iG+02D/41YCvID+BBWArP3OhRDE50iVC4ekBLfBMOXBXfvrZnAlox0/xiWpAPf8U APj1PfIlO9L1Bz0B5fjtH88Mqd0/tnWTofzMCgDm8ru0E6FTUyR45g8i/3H8USHeKwc24Sd4rymo CT/9dGkIUs2P3fhOmpzH6/fHg6vw+9vJEXG9N9i/zdGN5APR9/6F5cCm8jN3BJLjjf0ohZmAJ03L e6lGMx+ZTEAF/xQAuHzeMRT0g4osgKppf84VeWuQg17d+r7x/VNnAp6YCCjykEL8E7C2SVqStPhE JmA3fkQKAHb89P/zEaCaHy4AEGeaKNcfRQHE+L26cPSrAmr2b/Nznbn/CvwWBrSVX0Y7KvGoVEB6 fGo0WC/+MgvgJH76eaYWQM4/d+S4PlC9fuIELLt+TKGAS2JsqGr/xsPRYH3v39oV2Fh+1xDJH2o8 wmyBRKfn9vjVCWjFT/F0MEh/foKffADV/LfPyxQAAN/rWLF+lwlYht8+mEMBkTpS79/gz754Bfnx pwNbyu/uA9Dhj3RFxYnlCC/qCnwiP/2GSnQF7sQfvPYjQDn/nIFXM6MPrAVQfFjFfT4E1O6f3AfQ 5/4l5gLYyE/cFRilt0v9+3p82RGgHX+hE/Ac/uAIcJwHcHiCvF8uuVJ8xfqPmoJmj1a+I3AKSYx1 +5doemMnP/F0YEP5UXhIUbg+VF4fhBZAB/6sAujNz1gAdfw3V4ODBuvPHgEE+NX3P2cEPlG3f4U5 26fdv9xkoO7yExS1C/Dppq7bB1xYES3wrhjIjp98uEQBzPjp//7ZioFK+cevKQNwRP369zBg9fXP boB73f6NpCegvfz4YUBz+UEwG/AQX2Z/YGiC9ywAE/7iI0B7/vCT/BHgGO8igKmxHNr1h0eA4uuf uoReuGOJpsaIs3IN5WfPBHwB+ZEdAfKBiDhlRGe1yPF8HkA/fl4BGPFT0N4UtAw/zBHA5QBQu36p EzBR2uxVp2DKBrikHJOi/UMYBbCWn7AjkKn8+GmScjxyzUHA+BRzmZgK/N4W3IafDmUMuwL342dS sz/+/KjhdxHABzA0Wf+eCqzHB7+1xQKL98+bgI1XkJ+//7KWX++XvH4AAjzrrEllGbEtmuvwy2Qg M37qHFm3zoif4nknoBg/9wD5GlutnykHVuH9/9xdcmL5/gXTgc3lx/MBWMrv8riTbikCvD8eiqsQ QroIAX6yRxH+RwGY8hN85APozE/xax5AGX6aAni5jkOb9dMogBZPvqam8iTXHaR0/+DVbWN4BfmZ ewLay++wzwVQ4NPKGokjCg5cChr8cgQw46dK0G2dGT/9D5cKLMc7O7vd+vMdgSTX72cDuPzEwv1b jwA4d/8VeFoMZCw/aQsg22tQMCkkV6hQiveOACb88RHAjD+yAMIogAY/RwC/0W79jBNQiKfuAPeV NPcov6No/xC1vjeWHzcZyFx+V3xyaMKh/A/+PUpDwHYXLcTvTUFt+Gm81HWaMuIP8f/4TUG1+Ofe gAtN1k+cgKXXvwvp1CbYpQSr92+xAPh0eZv7R30AxvLjaUcJPqERDtRRflq5Ah+3Be/LTz+lXYF7 8wf4j3kuAArw8zfsZXK0l+G59fNzAZTXj+2Ht5yFkt8/pDIB7eTHmw5sLz+BK1sh/xav92zA5Cs7 Giz/ukmaAOpe5bMB+a1O1AVKb9R7NmDyxTVMrL5dldojjZcpgPP4ZQqgEz99eR2BlPg51caPADZY /64A6q5/ezu1CPQnBWjw2o5AZ9+/dDWggfww2vGwlfAw5HKEDxeHcvzBaLDT+Qk+Hg3Wl5/ihRZA jMd6wEbD9SctAM31wzu2Y50UoL3/oJr6tP1X4IkFYCw/KOkKHJ0hBY5JZFSLGM/7APrxg7cAbPgD PDMXQIafG3A/0Hb9kQKoun6s0wqfKMGP7PQrO/nxR4MZyw9ctxQlHmlj4ShCiQo82Lbg/fgpHlFP wL784U+WrsBq/BQBdE1AWq6fdAWuuH7v9+/LwMCC/Qsc3dbyE00HNpMfcj4S4yMfpNZtWYgf2MEg /fghdwKezx/hSR6AHI/HL6bpTu362SNA3fVjbg7yWYBHkLFlLj97U1A7+UXWQ6p6KHu+3lGA5Es5 GWh9BU1AWr1aRwGGdVxYSbDiDEd3zeuFogCo6Jney72dUgAG/GEZxe+aquzG65c4AWO8awKC5uvn FUDR9YN4K/ZRIeL9A5/taic/QR6Amfzus9OrH3nQGgNWgef+hBSfsgB68QdZ1L9N+ekvxJOBBPi5 BujrhubrjxOB6q7f1alM8Qq2ZUke73UEwivIT2wBGMrPFAUIa4QEeFR+lRfivdFgJvx0SyqGg7Zf vy4RCP53Ktqv/+gIIL1++rPb1+XX9Qnt/qXaN1vJTzAazFZ+QPqlaaCJQcJswzquIVkJfisHNuIn eGIBGPAzFoASP35f5skb7dcf9AQsvH7/28fNDL66uUW6/Rv9KIC1/AxxGNBQfnYfgGL9gtHEiT4C GKrwiMKAffkDfMYH0IWfviUWgAzvnqcx3/CxaP1MJmDJ9UdBr6lqifQHE+3f9iV35v4r8F4moLH8 YPDzAEr54fUnQEYnMbkmWnzYEag3Py2s8ouBDPgJPvQBSPBzbo2LAETFcpXr59qCl1w/BtLlBJiz luifPtw/0JZgxvKDMA/AUH52C0CBt3y9w4DJl74YaB6/+33OLW0cBtz3/H7VzQoKjgAv8XqpYqBX q5R6K4DC14daAbhn6d+lAFzvQqXWelcD5jb0r3IpBrEc+K4ESDgPivDxaLC+/HEtgCU/xTMNQfL4 KQXg+hhxyvo3BVB5/aA9wteagLtm//a24DCWX1AFYCy/bnMzDpIEPmwezD2oGOLugmSYaSHeqwY0 4Sd4YgEY8FN8NBfgCE/ngLRd/+IDwNDq+j1Zf0yTQkYNHn5PwLP2X4Gfw4D28kvOR2J8zvXLtFwi Tgq/LWkRPo4C9OWn+PgI0Jc/8AG48eBi/JQC8Hk/a/1+W/Da6w+qgn4sl8vlqcGPa7jmzP1X4JNH AAv58c9Hh88fAs+z/20M+gEC92RkexTgQfoB9OcP8KTbtAE/xXsWgAQ/dwF5nrV/wWCQuuv3lzIP DN2zl2Trj3wAsJUflwhkLr/DOjWF/JXs85fVPQJ3ASrxaSdgH/7IBwBL/tgCkOMnQ3qaA4KT1s/M Bqy4fpIM5A4BQUYwDqIAZ++/Cs9YAFbyA3o+EtoWifYBSN2z8HeK8fCPAAb8FJ8dD96BfyAh2iAM mMeDywFuuf7NAmh4/duX0uy+fMrxNGXTXn72TEAYy88aBYDw+ZPoh3RWGYY6fNoC6MPP9AOAJT+9 qR98FIDHYwqmPX1ZaLx+bjBI4fUzghgGMPP4aAK2tfxEPQGN5AdeW3DZ83f8hZFxJmRrOIT4ZDlw J/5gsvpvU/7gCOBZAIf4KAWg7fqTg0FKrj9ICJzfP9cuRiL8buVieAX5iWsBDOWHdgSS4CNzAXmV Ae5PF+KZpqBd+Qk+VQ3Yi5/++q4AjvHj5zppByesn3YFrr5+7oO5N8hdih/jqi1T+TmoBuwqP4hb 20IWmlFEcYZm+Hwm4Pn84RHAlJ9zAso6+4YlNe3XX5QJKHdzzRnB11GIl2YC9rp/qTCgifzQhonN 80KL2xfzeHUqcGP+vALozJ8+AhzgFfn0+vVTH0Cr6w8LUqY6hosgI3gbD376/ivwilTg8+UnL8Us Pj3G1btPfPtSVOLDasDe/LQ5ctxrsit/cATwuwJn8bc5Bxjgmhw1Wv/WD+B/7F2Leps6DKYpI2qd hKRJWkK7tDvd+z/jibn6jg22xVI4l29L+CvbqD+SLEu+5s/vSdNmYa8bqUawBg/tVnfQ9XfAq7sD 4+gP3znVCq+PQhjutYoiDuM5CwBBvp47MeSrLYBB/NcL3wgoxPhtXADb+avePVAnMhytxq9xAdD0 pyEAdP1Vv8as8ZoII5jiODARr68JGEc+aAgART7/NVcRyIQ/03cnLQOoiLR7GL86BjBt/qA4pw40 lfETbPCCBYCuP6qagGj605VMtsZLmYf8Rg17N6hOdEzB17sAePKZvSjo8wAQ5Et4agFY4JsqAF8Q bP2g2wXwM3/uEAswP+XYlQcbwkNf9QrmoD80DwBZf5m1rNvbWOLtQxLDexNj8MqioBHl24dPAsuX 8UIqsA5fV9SA0Ounbg02bf6iFfCp3suQ8X2yG7b+di4Atv4Cax454+WCTHZjgQF8dtpmHMtk21Mm WQDh5Dviux1UJPk8Xl8QhMPTCODmHHz9WALwM3+Q+tN12QxDeNDUvcTSH6YewAz0p/OPrPGBLvKx zvP9c6/G2X/7PF9fM10QEPeCf7Mk2GeVQxe8tFuwikCs5jeVAYY1a6kIZFgc54pA2gNkYBep1ODh +5AeDkX51j5R8lCm5e3fh0yMAQSR74QHlQsQUb7idvVpQAEPpO8EFnT95DwAD/MXHV/yu6oQOoQH PmUTX380nYFw9AcUqcADlj9XLxykk8RMxKaPNohmi4xf7dP9drsrym1z169Duu4+4GMAIeS74HsX ANjD09Hkq/CVBTCI/813Agu1fkxFoIDzr880kiF8FegOvv4O+D4GgKS/LB6a3umW+HDX36LYQpLt 010zkufisAXY5ukzzMwFAIsgYHwXwKI5aBUBfD+Gf5gBXQAuumdX13heD2puLoD74vCbjlxlQjC1 KgATnryle6rBb0VrPF7+Pt7I/UQJoLutywT0Lt8Bz7sA8eUr8a0FYMQLOYAB10+1CzB9/n0Du+au Kh/wMzHjxePA6PrDWgD4+tMtjrP+W5G0KYjDXtk63VHv/29Z9AFfuHzsbnaAFAQMIN8Bz6QCA4Z8 NZ7ZBdA+Q5pA/05irJ/ZAvAmX8wHVOOJXBIMR38suwPH1B9QpEmO6hQoFCpVNhECA/5m+z/Q4PRH mZLuK7Ivi/KB9HjJBfAm3wnf0BNvPEWUr4rIUgsAzPgmB1BzrsPr+BsC8D1/EA+3kq5dqAHfHgYK uP5W+Ja1GBcA0PWH6Z1uhQe5gjBofw0UUUcNHigBVAZJmfbHWi+HsijWTKpingaSPwLPBAFR5Av4 ZhvQgG9yAKVnHGL8iopAXubP1BmtP2fbharx/JF3PP3px84VBMHWH2J4jZl3HfRsNOZc8c0FoARA LQCG4U+n50Oxh8GzANPlj8BrtwEjydcGATX4thXoYEdJD+MfEwQcJ5/WNvgiejww6e4h138QD0NB QBz9UWwDuuBh+O9gcz+QdfpGXYA/ZcrbS9cizcQYgH/5Y/Cq4HJM+fzfucYgKnydAwjO4xk1fiYP wOv85Y+YTkGanwd8zQtU/WFiAOj6K7gA9uM3dhJXbBVoWsQIH76la6rB1+LQeNirP1v6p8dDeuJK ggWRPwrP1QREkM9bAOqqwD2+ygE86sjM8/g5CyDk/OtzwXI+IIsXgoDo+qM4DoynP6QpmGiDh1Eh x4Fb25f97Td/VRkC++ap1fuCNwugMFgAvuSPwcvV1OLK5zxLGGoOenyROwGFW7++MYjf+SvUlBYJ Z/IBDb5aQP11wnNVgZH1B8Z1TgWWGYT2jVzlFi6bSIrOsulHp5z6AN9l8Z0kq+crgeeivGawzYsc uhtbAvAvfwSe6wyEIJ9P0updACUeqhxAwjWSDLZ+zC6AEKCfOn+5sj3A+aXe3NDiieQC4OpPmweA rL992yRLPJsoMI6MhCPsPBM9FEW+L6vX/p9DcUku+7TM94eifOQyAQPJH4FXFQWNKT8RXQAT/kwP zhxh2svEfvzqIODU+asPttEmB1V9QDDEuSD0+jvgpb4AmPpD9AESOxNCGysAqXlNYsRnD2WaFvub 4w//lentka3WRZqm+SPpb5RdAH/ynfFNKQU0+fwrT0oF5vB1L3DQnSDxPv6+JqC/+atjRzTBUdHm KOHb3w3asjGfH7sLgK4/2iQJO7zXC06/ssasa9R2K2j1jI4DJ//ScWCocgAh3mjCHgeWZqfKB+Qt gDldszoLMLPFmdQX4EcTgDEI2OYA3icBJPDOH3IULss8gB9JADCiWIKy2bBpv9AOr7oRVAQQSL4z nm8PHl8+j1dYAN2N5HddBxBCPj+5KGi8+Z9vBo68xQFqpsbWHzEGgKs/XIBkdEzGljWMlc1gGC9Y AH7lu+KdLIAA8vm/Go4Dw1m5VR5y/TQ1AYPNv44DwpAFAMkM9Kc/CwAz0B9LC4AdvxySYbcaBnsK a/HJMJ7pDehfvgu+q6eKJF/GX5juwMKpjnqnHMLK5/uMqLoDB5N/+8uxqnSkwTPR2gRff5ptQFz9 ZY5WVydanMbPrqXw6wtCEWdgy0WDGFgU8CDjEwHPFwX1LN8B3+UBIMlX4LmKQPzx+fPT09M7SZKg 8vkP+rLgUeYP8Hlzct5FWmgg7FY3oOsPJIwFgK0/bSKQNV5LDM6lQ8HiczAEAT3LH4FXdwaKJ5+/ uMYgvAHw8rR5OQeWDxoXACLNv+sXrOp9obJyEfWnigHg62+7OKdR+ETxppGCL8POCqgyjfXhCNVh IF/ynfGNBYAmn8df5IIgzc+lW4BfJPjzMwUBw8+/PhJwVOINwRqU58fXA8DUH0jYegB2eDDH7a2Y ZzS+yQREk8+viqxXkeSDrjGIyl8TDgHEWT/9NmAQ+VDvdGi2AonY/xJZf3SZgCj6Q9i+AE6vf9D8 XyIR4y26zGA1nrUA/Mu3xjMVgVDkq5D8LgDTPoP7xYBI68eWBY8wf3pxpUGE3hen8OvvgGcLgmDr D9s73Q2fTGCx0XibRKCQ8iUXAFO+YAEI3YGZ34vN6zG8fB4/IREIRkGgOxIAdjEARP0xJwJF1h91 wcS5XksmoJ4A1HkAx6qJbvTRxM0EbFRZeSQgWVKBB7R4lfw710IAjgRQl81NfgQB0K3AjepIwEIA LhbAQgD3RAD1QbmfQQAJdF0C5q3jiwWwEEAAAlAdBoKqdU7yIwiA1j3fKOMdiwUQlwACRjGsCCBW FEVHADhRwN4CYPDHl42yDljQ9ZtKAOPl191CYaIFEPz5DRBAVP0BuTswzGahBggAKdzuzQLwO36l BfDbdEw25PrZEIB/+dWppxdi+ZJD0x9FUVA8/XG3AMDuO2VKL0zEs+3BMeTzmdTGRKDw8s0uAL2t 6QUK+pNWocbPE0CM+TMuj3i6lXCl7/H1R28BxNcfUCe0G/BLDGCmMQA5CNjWAfsZMYDqkSiDnkt3 YJPbtAQB75YAPmM1A58NATTbnmTeOj6zIOA4LZ5qFYzD9wSAI5/DO/cFCLp+cgzAuAUYeP0GCSCQ fKg7oA/HADD1h54FmIH+TmDHMdWDzDeDEwGgyedu5jsDxZc/YAHQUpmb30QBCCAfXAggpHxQmD1i TcAI83e1APD0Z9JrbBL1ILkA/mKv44ynULFfyQI406Z5x2jybQkgtHxFgVAQTwMi688kF8D3+JcY wJ3EAMSqwPBlrJR7pzGApOmBxpkASwzAqMULAdwFAYjNQXWFQO+eAOqtQDJjHb//XQBYCCA+AfAx AHhXJsX9AAKQg58LAcSyABp9u1y/s7Hnus0sMkAAg/ip8gcIIK58kwVAK+WbmuWEXr9xBDBVfl0Y gFSnApkPrZk60vPTEgCG/rAEMHn92wnmZf62XSwAxBhAfTYezQNAtQCqAqGbMywWQGgXQFPAFy67 Ik3L/R8yDm9NAO74qfL1BIAgn8dwFkB9NJ5ElA8jCCCY/E9aBYkMEgCW/rQEgKy/XJN7v84iZH/z okjL9a/M70tosQDsYgCjTgHejQVQVQd7+fLykrt/C8BL40QFf2x3eZkW+cOvbBzeiQBQNncZApjB 5jJrAdTl8eLKn0QAvuWf+xrhVi5A3OcnVwVG1B+mKKgHgZwjcM1vnkBx2F1gDN5IAFNPuHrBjysL Hmr82WMfeD2/DhQCDb5+AwQQUn713RfbK1C2AHD1x+o0YKz1Iz6zpNgfu8sPNwNgty+LvT83YHEB 9C5AbwFUzYA/UUeD6wIIzRBmFwR8nJUW+18cWF3zQ5GW++8tya5lcVkIIGYMoMkBgh9MAElCo6Bt NtASAzC+qv0vzona/ofrKaM6uMrT7UIAMS0A0rbJ+6EEUDEfee0bIs6uHsC9WwDb/LDufumztx0s BBD+6vIA6ka5uAYAvgVQZ0KReboA934W4HJ9bNTv42PZBoztAgBSJfD5EEAVCiRVNtDiAmC4ANv9 rmlVfShPCwFEJoDPp977/bkWAHsaarEAAlkASivz8fm6K/OH6/P1en1Ly5Ur3oEAkHffJxOA1/G3 MQB6FOb1DNHljyCAoM8Pjr83m7opGrHIBIz5/FSZgGj644Ed+XH8V5Z0+7+k/6RpTsbOA6wtAJi4 OmPxLQFgyefvbC2ApkVmdPnjLYAw68dkAw3oePTnJ1gAuPrjnR3J/nAoikN15fut31jU4gLoXYDa AqB1gF6P6KPBdwGafEhaEoUsVYH9uwCm7L5tvsum4G0IYGJZQB94gQCiy1cRQN0bhyDI5z+xLwoa cP1qb2igKCjC86MEMAP9FSwA8MAB7c88rUC6c8qIO/zIzkDe5I+0AALJ5wmAugA08rWR6wDFkG+y AOLLr79tagMRdbo7mv44dwYKuH5gYwGAg7TLw+50ue7a64F4DXWMcQGChVosCSBSqKeyAMST8Gih JoYAEENddVWEiXEu/+N3cwECr9+gFjvK3x7S79t/7XW4eB22PQFEUDvj0kVX+yoRqDoI7yXsMvGH TI4BgJcJfG42m3cyZqs75POzyQSMpj/Ec+PEy9tue7MC1vU/67clESjSRS0AJvkF+ZpDEDCpKyO+ nJdEoGBa3DgHbDdGQgBIfWX0z2YrWsar+Ad0BOCKnypftXRo8nk8JYDPp6YeLoJ8UxAwunxoHVya EPyqJwAc/ekJAPD1hy7OJPmqP0K2JUn28fC9srZTQPM9mCwAZ/xU+XruRJDPf3n5lRH2DGxk+cqS YHjy20/prsjTp44AkPSnIwCYgf40ARJnfP+dshrQYZW9FWman2DwZ7t4G9w24Aj8VPk8fko1Ne/j zx4zl1YggdfPZhswxvMDWhvlRWHlYupPsw2Irr+1keTfkf2fvSvRblSHoVkMKHUI0LQT4zBZ2vf/ 3/iwyQLBgPHKtHjO6bRpFYGtXF/JQoJwh0gcUJRkKJoTgRxdTB583ggATOByphEDgKo4yvYYL6Y0 fvTTgAxZ4oQuwyVKijWhueabaQGA3VDqMAC4PAoIiyOrhAm+9He4AJ70PwdLjXyP/egHTQBwMX99 EVJV/WuariBlu39CzYLdzAA6R15sJ5EEPCUGwFeJlQc8woRW6ufXAyhIFIaEnAAyup4BwBEAsJ3u DDMAvK5SvTbQDACjGIDqlAdZUixRFodXTRdgBgD5izlvt7cKOHMMoDmqJikwA4AzBhCmKCMlCzgQ vSAgaALAP5ZEqSMPe0EOkEcXnAPAJJ535zUSt0rcyNb1ywKAk/nrYQCgDiopoekHpGh+HNgdAdhs jtOZmykxgIVSo9SZAei86aoocoDr24dh4jUDQMfgLbHzqTgAEwOA8I/XVultAJhSVeDRMQCJSjmP FAVQ4xXdCUglAGjJ6+pvyHcCgCP99XHZbDYX/PwL1/rlAcDD+kGx3W7+YG/6X385xACc2o+4v5Um WoZFmlQjDY3C1cwAOgjA+8Qi3ZNiAMBSJDaX2QWw7AI8i4wcCCLVSEIFeVADAAl5Xf29AOBaf02y NPDtV+hNf1teBQCszR9er5mHtAdP+iUBwI/94OBDT7/oUYCEJLvl8rQ8nb6wgvwoBuAv1FwBwARC 3VUF7CIET/q1GIDto5pqoXhtIPCgfzAG4N1+bCQC0cxQ4ePZBZACcZYE/HcdTmhuJuUClJvc/k85 RZ8TiQP+6EQgNsdrqu76gyYAuDx7FwGAB0CHc0kAjqsKACZy9q4MADauv9zk2Bxtj9iP/jEA4Hz9 XhiAEYyMkyS2A7YzAxCMKgconxlA3ybHywOep3E9/z4DGPh0hweUBqtVzv6Z9btuADCNbU4dAIxe P3D/ttYefArbXD8AOF4/tsnBvpYN5Nl+tPMATF6/uRjA813ziCBEeWuQli+gd8DcxwBAc+5Gyyv1 BQDj17+vItyhHAMAN/PXCQDgYf14oBt4bSA8BfsRMwBP9gPqfQG6ES6l95GERmBKxQWwDvMDDMDR NsMN+wKLlgvgdZsz4AKYu/7Kxh+dwrzbj5wL4Mp+JOqljXcrinJcy3/FGsDkLcwPA7UJALdrAQDM DwM9ElKr89pLhZT+7ecffxgIpBTf3GTNFkYgAADdJTQmLxEDsKq/GsfNlhcCFMYAHOjvZQDe9Df+ 9mbjvDbQfgL2Ix8EdDB/EBjobtF2LIJdmganUyj3dtKFLDsYAKhPh4b8EwD86OeDEdsjy3GTiAHY 0N/xC6EL4FC/iOVCZzaQ4/VrAYBH+xlzCgDSr1dRwCJFSa5zX5IxAF9Ms789uBumCY/TLfVjQBvX r98e3Jz8vfCtsGaCj/WTag/uav4UzrKgW/GNch0ITWhW7KiwIMig/P3bjhiAhryu/qa88Dkqh/oX VS8wlt8Ct+agrvV3yffFAJyv332Tq7KB9gvP9tPTHNTD+sG9MYj89Q+iQ5zQU5jSNX4bXxJszgQc M/ZV98saA5gzAQWv3d1cnjN9Bt/205cH4Hz9sGomYM9frmma4zQrFn1FQUFFSQ0AQPMi9eUVg4AG rx8u5Zb2tzpoEcYALOvvHj1BQPfr92AAz4iJV/vhDMC//Uq4AIpKWFVgnLLPfiJRFVitM9AEXCit zkBGrv8W164YQBA6198tP4IB2J+/Z6CbdQp7bZ7kfv2aDMAzZ7PROjnOsoAxAIhJVssF2RFYUgAA IABJREFUhtG+RWulKgBQl9fV35Af2xjEtP7ayTaIg4CW9Q8yAH/6ayxpAZWN8x/22832zx782o9i YxA78wfSjUHkkSaMUPKd0NNXhtK5KKg9/Ty37Z7cqswArIxpVQSqHXXzo0Ds93p+el+AcsITghAi BCWG33wGgLr+Y73W5QwAQzbOs9JqYdMZAIYYgLpvEEQJJTSLAkV5RQBw6061AcCt/ma1axYEnMgR gDIAWLr++kLhM3920qv9dAKAj/WrMwCDdB0HxbUIQqO3p8sATE/vWAZgWD+wIjfPJ9yHE4FcmpcI ALzB04MBsNGRDeRy/RQZgJ35k2cAMIEVbQKA5w1P2wXQ08/qANW8WYVMQIvzJ8UAXK1fw8ar+kng 037iYBL2W8mbjgF8JLQ+krksuKVRObNPQw7nikAyLJd3CvPcJuTnxQCgAQCEshBg+ekv/0s0q1TI AYAfKB39MJBJ/fB3y3KAni/oBAHNX/84AHDy3Pbj+VSWPdEsDOB4/VQfBrIxf9BIBTaCttfrV4qy XVEUhwwdXvvVKp1hggIDAPH3YE6+nwFY1l9Zce1Q99UFsH//8gzAvf5GPZCnjfP54th5wf7sR4oB uFq/LgYAagADLC91ldAC+MTTbHYB7LBabsT1V2YXQNIFWACvoeLxKPDH5wGsaXR7BiihwQwANkYj B0jIAGYA6F6o86Z0n/AMAHoxgG5eUJD0BgBZDwCAJgD4jqHqAoCOfnaWtWnuYaNjAFbnTwIA3K0f PFKB77ueiWwg0ASAqRRMs8AA4gQd8hCH+Q7dXABTN6vKAKxM9ggAMK2fZbMcmy/2MgDnxvYCAH6N vcVygedQYV/2M54BWJw/KRdgpH68JCiJdlGG6LfZm9BxAYxP4kgGYFB/uYNtXxtdDTIApx9CAQPw 38QRHo/CsKPAzdmX/ai5AA7SJI3pD0/VwwDJt2FuMccA+Lhs2mHsOQYwYpODz/ftSwzlt8YAxgYB 5Vosw/pttzu8xaOyByFfF6vG71fraxw2AWA66e5qAGCiGbAoiq3fGMTo9Ss0BrE3f9zNhYY8O0XZ XDzZjw4AWOCxZmIArUR5wNCoPjaIHPiUUJrtnmacH9gLSQHPdLduBgC9NEcWuUbJNwDAoX52jv3e KnDPGYDT+++Tb+cBuNU/uMnxPIpPP/YjAgAP9tuYHF39+lgFJ4KShJAHAoQ7hJKUknpRodkFWHS1 uJldgFELxWqEb//OLoCVY0AleXZ0AHCl6P55Lwj5AlilKAFhJqB3Z8DTMSA7Anw/t3qujAaA33MM KHRzMXuY8hN82M+kjgFx8KGnHsZcKnTLnwhdLQBHKLpd2KnKJjhRigUMwLj+8fL1FHN3+m9Ps7Xk e2IAlu6/T74BAB70d2xydflzVU7Bg/0wAJiA/UozABiBPDBcibTDT9uhiDmxS0LvF7a7Yg4ABD9i CYOtwZT1K8gLmaV1/Xu+c7V/VzEAl/ffJy9mAO70ixlAQx44kwIP9hMHk7BfET0CuUrEA6iDQxgF KXwDi9COfd6/KWn8No9Q2mIA02BP6i6ADvG8dFS0GeMC2J+/fhfA8fq1NrlK/pMXCPVgP/F6Evar GwPoHh9pVIw9Yw1TtGTXVVBUF8VLQt5gIYoBTDK2ZH3wMgCisrZzTcBxMYCqsbqXwgA/qx4ANE4J +Ldxgki2XMFLD6Je+fwGAGuKnvwB2NFAFD6piwAA2vrbR5IS+hXkHzEAh/qZ0W7OICBtDxfA2f13 yotjAO70g9DG2+vH8ikYmLq2nwYA+LPfx+Roydc+9483weuIEkTS0wcGkESR0gVY4ooBPDuLhwdE ovrG1sUAGvoXD3lxf3JT8jUG4Ez/fvNobfMin7cqMNq+/055qADAm/5X+a5Ad1UgFJzbT5sBeLHf +4d1NVoe+n6ufshPaYkBdHddCdoRCOQB76oYwH+UPF5f7RDZ5XV5cWMQGA6DDOlXkX8AgDv9uApc gWDK76cA7u6/b/1fXQCn+kG4ybXlebvg90/n9vMaA/Bkvw0GMEZ+0dug9I5HeH1IUEkDDoFUg2A4 8FOAxZJk9xdXEaGH5rZ2ZwCgGQ0xIq8RA1DVz48A9y3CPTYIaH/+BmIALtcPRM8C3ClA80jV0fw9 GYBX+719ri0EAauo3leUlX4AQkkhdZnfhH7wWOAtDwDCHaKnl1ji7w4C3ncsITmbg4AKca5bUpXz ICBMZ3KwCStu+6TxLiMEZYf1d0IyDBLyeYpSwCeeCRgfdmGJCCgq1mzAUE3A31IUlKev4o75m4uC dtt4FwCwrKrtcf+Li4JaYQDhW1J++mla5LiEggzFUhdyooRkiEcCvijKSy7AuouVJIKEMwPg45Pl AHUdXM/PAqjYeFUg1PGG/HNbg91vMCM0O92qguUpldRQsIf/luwQsEiyPI+yLKMZ+4JnAOAbGXuE tfPcenYBFBhA6QR4KBD6Q4uCPi2TJQLdDgNWGJcUXvYt8g9cr+YMty9yMQCV2sla8i8AYFv/vRkw DDMAN/ffx0MVAMDe/L0Guhu/e7hV7uxHDADO7ff2KROcZYHW2rPju9PNGNN7dVBZ+YHu5785BoCP m+323CmvUxb8p8cA+h54M1Eg9F+OAeDAbGOQBQ7DdZauQjZiQmOT7/2rXYBzfyHLOQag5OYCCAqs /iIXAIzHAA6l044IZf47pWhuDGJM28BONccA1BhAyay2owuE/uIYAAy9kFN2+M+C92wsR8v3OgKC moCj5HX1C2oCutLPnly5AHSmgb3EABzcfx/9lK8J6GD+6pucQL5dYcny/L0+C+DJfrvpEcimWAlf XQVvWXoNgnUQxLmm5wJ9DABUL9GU/DADMKefl7HdQ3eoRhgDsHv/wwzAm/7Gn2Bx/8tHOtzlpc+q 7fm7AYB3+x2mR4owkC+/sI78KBfAf7l5F/oZT30/9z2YoRoDsHP98i6Ag/nrdXNLTN3zNgvu7GeQ AThdP0PtwR9wmq8w5PmqHOWXPIeR8koxANCcBzX5ximAZf39GWtMXjMT0PD1jz4FsDl//W5uiQDn kgIcsTP7EZ0CeLDfxuSAKcBZpcn6I8qS/9m7GvZUdRisDjFbkY85N+yYH2f3///GKwU3UChtkxaH 7Z4zd5whpe1e3qRpUn+lISlgPWhdANicCUC0lcrvfF0AlYdcJ4nq51dW+j+hugC33Vnz4L9lFlxa tiO9nWsGMCocEOwCKOqv8oCBtMyKkQlgbfwUGYAj+6n/LED9ImoFbsDR+OFPAxLKU5cHZ4v12QRY X9ob7Qbrg24DllUsXgcoaujjABBmbploydmRgMmfBbA3kI8JAEwleZ0PBOofv+HU9xuKguF/EgBM 6wL0/eWHL/Nme2GkyDEAAG4Z1S0AWNJfEdQB2dIJeD8OEjMAsFYAdzj1/fGSHczB+PVmBb5HB4m6 M6G+uV/7X+oDkAQ0SLKfdxQG0ZLH6m99vA0A9vRDeQr4cCUBXQDg9v5l8oMA4HL+WHesS5sCfD6X blZwMX6twiDjrd82AGjK9153F6fNFjNSDBs0AVxiaE9hEGr9Ilj9a3AcG1mB74ADmJoAVvovOw34 O8qvzxG+YLhS/yV1AZzP39VZALz1DmG7AemNGfsAbAysjg8AoX8j6tgOXkAeB+B6YXUkBR0PmJTM 3NLR8np0Mn4GPgB746e2CwDKWli4YxDufhqQ3qUcAJwXnHlz8fj6VMtZc2YAdxQjYcQAbPVfrfzd towH3LgYvz4AGGX+GoND4rx/S7Pi/O+SzSf1pwGRSsQhAKYAAP40IOohB5eMi/Y3Aye9DfiW8GKd 8ktLPADg2kYEqamYXn4bEDdRwFxtBU40JdjlesWOPZ2KU1Gc/52efCAQTkeVuV7hkz4OAL3GlbZb p8cAaFexXQL1cABQegAjpTXpTQA0y2VdBcM9AzAa8mWcJGn8Bh4AcCqOZYgq8wDgZo3fpgbxPgCj tkjzKqV/zDwAYDRs1Fek9wHg17iIBzx6AMC2MM55Gs/jhAdzDwAYDRqc1PsACNZ4ZXHBIwEA2gTo OKO6Trgo9R3O8+GkoD4jUH87KJxS9RmBcGu8lTyw8rkyy+N3ZxmBKB5j7V4UPK0CgFjCl6YoosUA ADkuRvKNobOjvzqipphX7coH4OD+ZZ/WZAB252+YATQKhkfVwUub43fLAEZZvzU6LheUuCLknnhd DwQS3boA/ixA4+evKIqUT6j5swC98josF+kHVDsLsLyL9duFjgTWDwAsEv6PAcxYkWe0XsCH8gHU pcBUHS/eB4D3Acz6KzB7H4DiOvze7/erIE9fTi+rPNj7QCDTq1cHVNXrKnoAIFnjIh7QbjCA5DTg naOjlHRUPwzlA4ABeW0A0JLH6pcVBiHWL7akPkFZXjEOANyMn0FhEHvzN1AYpPUDzOT5ASn63+0E dL5+r9CRCPPqfACr+lsjEIDCvMEwAAv5VN8s6hd5ADfq8oMMwKl52QEAY27XLDTkoarBZLH/ZibA eOmStPQDC5lIBMCqb7R85XFMANVTwN4HQG7mVtBr0Qh4gFDgS1ucvBPQ7NraB1O8D4DKzK2ML+8D kHIBkPwCZruPLOfnrzwXPgC4NVZkldh6zJwfEwAhj9Xfku9LCEKhv3JFtSQH5K9yAjq4f5l8CwBG 0N/xkAPV9SvyAzbrBVP3fyAhiNv5u00IMiTfbRNcPlS+hnFVHjgIgjohCAzaFE35/s82GYCJPFZ/ 660WANDqh6+6XiWoylcMwOH9y+WvGIBz/QpUDfr/eG6CAWj7XwHAyOv38l6rNJiKvIJttM7ydJ/z eczzJ1pXxhkAkLbZ3ygNVq1A0JH3pcGUzFxQ0cC+XvuCAXxpMNnV6v8XPFmzJFvOvvMUDOT77/TK B6Atj9U/8GAh0i9CAFT2oqHTBHB1/zJ5NR+Ak/mD/jXeK7+pLDBL/f8BgHHXrxwdMUhT5GnIVvy/ GWR8R+qxeAwnIBzFkRS9KfBOQEI/FxyiKPq0tRMw6YxAZVuWh4Hmwcd5HXBzhycgAcA62RwYOnP9 W5NDqTeBQKMeCyAAALr+mzi6P5+j6Ah2+q8GAI7mj6nSIw1Fbwnfh0WQrnecDx98Ag31XQAAet0H MvkaAMj1s68yLQWAku/v540rBuDg/mWf7AcAcD5/0FrjCs5sqFOxdGYIJeh/GwBGW79SdMQVYpjn wXyRBVk2VB7cmwAdly1DAPRr1NxdSjD40xMFxyh6tnQo6J5MADBexY3dxJu9ql2c7dmeBwHf14Cq J99CoebWRAMAjOSx+rvXFa3+KgsA05XvAACr9y+XFwxgRP2tNzqPvEvkxQ/iLNbBSv8FAIy9fi/y v/RIR34gSc2ZdO1mYfERf4OJfQGDDMBUHqu/9Yle7MTpL/OAfm205RsmgKP7R/gA3M7fLctV0CCS A/VlBsD1f728i/XbawKQcDdgIQA5C3wAE0CEAGz1Z8FnBe5d7EyhOGiHISuCsaZuAlwAgPhPlb0k nPP0BJh5wwGAfSeqHAAM9bPPyMz9fL0NOG5uIDwAkEZsLfQloSoWuLXQfyUAcDV/YhUDrX5YZ2VW 8PwnEtgzAOVrHgxCADwDGABVw2C34+tzZKNS0NRPA0K4Cnh8Kv6teBD7jEB6BsBPHlDdgfPHgYdY rgEbe35GBgP8GROAtC0zXog1/J23twHRtAYJALS0Sh8ABvVvvkoPoJG8SiSgO7OgGwBGMkuMk96I ysyNrGxE/TcGABvj15MVGKW/4JdDgKppwT0D+DUA3s02n30oMOVDrl7q5Y4MvREweQbwlNV1AWaZ blrwxwYAUZhmCx4A7sDMrQpbvNdlArwPQH3gAHZpMGfnV5jnifcBaLRP5VKgHQDgnYAWHnLlpuzr ZsoAQM0Adh+reJXkQRZ/xOeXuU8JpmEAVPloPQOgfsgtTdc4iPRg78QBLZMGgOu04KEHANXLbTAZ 6cHvApCu8cs0bEzjMh7VBNjNzwzg9+uDkcYYTRkA2CeqJo1nAHbW+NkIiN630wUA+zWuPQNQNADK lWZubnofAC3LvZwLZseIeifgEdKCP8VplsRP4AFA+UmjloXKA4DrNV7uBLySGgHTZwBhzHORGJi4 NOB0AQBEFhDM0RNvAliaKNhE1fEsOgC4p7oANhgAm+d5Es/jJM9ffvkUqrhT/d0UAKj0m66rQf1i B6AMAQLT/ksZgJX71wAA5/rb67HeBQAzvVAbAeiTbWDMACyOn5J9JNPfkZ58keQf5VoOPxTiAEDy PxUGoCWP1d8BACT6qx2ALab/FQNwef8yeXUG4GD+pGtcQZ6JQiFA1v8WAxhv/XYxABrG/sTTt8qB knFafjFVEwDKYye4BFTeB2CN5UIVDkRmzk4+FLjIV/ViTPiTBwCFJgwAFMn0PgAra7zaC6h2Atgk AYBZOQ2YVEcAQu4ZgErblI7mAy7ezAcCSXwA2In6SRDoGYCKRbJIg/QtZOE61T4LANL/DgPAgDxW /yAAGOkXpcC/ANf/Th+A1fuXydcAMJr+loNFY42DxAhQ2QlQ6r8EANzPH8h8AKaPpG8e5Ema5AHx aeBpMgBsCJD3AdhnuUAZDjT9QCB2Snke5Dz5nnkAGGzb954aFN4HcDcsF8qdAKpwoLuKAzAbHPlA sKJYn+Yf8+9dX/VCQAKAqTxWf0veAAC69FchQIDtvxIDIL1/AwBwpr/nIYfQ3zICcP03ZwAWxk+L ASjqfSsrA+NdCQgG4CT3lAQAdPTX+ecB2f8WAxg3JTCeAVDnblvg9YOo18Ao+j8MAA7nr3NwAKez 4HwJVvosAQD3a74NAKb6MVmAKH0AtOOnDwAW509pF2A4X6PYCQCC/ncCwFiYfWEApIcdknwfMsaA gT8LMHSRSxYg7Eh5H4BNH8Cs3gmIKPyAkw8ECuM8SON52V58RiD5NY5RmXsexmcAEwYAIkc3HKLo +X0zMQCwsQvQyApUpQUnozeGAGCHXqkDQL/+Mt3E66ABoNJ/GQNwTy/bADCySwL9kKvPwhinbAEk ANgcP5XB0S5TN19dWsxIOz210mCb9yiKDp2FgLCFQXxpMBwAQMc7WxGxie7/XZUG63OQoEqDsfDS iAusT8wEEPUniWLMvQ/AAcs9kOQHm7oPICxeCmant9MCADi8np8oRFkTvQ/AxRoXFYM3UwIAch8A 2+dn25+/gAeAofZbCNAzgL/ykHsvN21gQgBAzgD+5QHPeJCvPQAMQSVp7Ul/GtD2Q07M1KYkbUjQ niYDqMeEpUFyWp+yYKXpVgAVDahAIAL9EgDQlod24Tls/4cZAPX9y37bBQAu9Xc95JD6qw+wOnAT 03/DQCA743dZxUbyXSHpWVCcX/Z5pg4axgxgXE83kgFUweVA1X8TE8De+KkxAEfz1/uQAwN9TBRw RiXp+wGAsSO2gd4EgHUWlJdd5tyGH3A6JgCuDpA3AUYzc9kGmb/97rIC06YFX3PxN7rI+c4DgGzc zw+ScgeQDAG8E9C+mVtNe7l3g9oLnJIT8Gb9LjPxN7pTBABAAsCYJAoDACIE+J0R9t9sG9DW+KkC gIP5A9kaN9LfSA5iJN9gAOMbAeQMoB8AQKXHIP3VMAOAgV8BnXwnAKjJQ28SEOP+1wDg8P5l8r1O QBhh/ljDCUihX5bDWUVexgCcz98VOoLWpTvCJc8mwPf393/7nO/Pr6cCSPFrIk5AEEdLj3j6hjQB HsQJCH3HgU0rMV/8N9NwAtLWuD4zAF62oHpJQtJb0k0KanVIFZKC9kmWnuTOEGDz/oeGhUHsjJ+p D8BK/xk6KeiNGyCKurM4ghYAjLt+68FZ0hYGWWd5s2Uh6U0oOQFdDWIfdg7Lb6NnyblSs/7/MoB7 AAGME5C8/5p+LgX9Io3bp6n8gBPQ7fzdDg6g1EK4a7YQSLs9jYxANYME0v77jED9f67q5e9UNd2m B/qjGYHAICMQzK6zC8JVtswZVO33TWh8bFD+2l/xKy8AACGP1d+SLwFAXx6qJGBHaMgh+y/eb9UF cHL/Evk2ALjXfyX/tKDTX8/btgnimvJnALiH9fv7GNOTH7NNIQ5g81UlASLujY8DwDEA3ck/mgdy TuosgA3mAhoAgM2lgZAXAKAtf7VygGpMGyaAo/uXfVYZAFzMn8wHYKgfoHIDbEzkmwAw4vrtHRxb z/nB6y6KYnFlGe++F015FAOgxipdBlDRKJFa8kDWf1BnAC6tTP3DQBbnr1zjQK5fWHI6uQEAyQCs jJ9G3TSw3FM2z3ierXZNebbi+//ZuxrttkEd3DVJp17cNYuTNGvaOffsvv8z3gCObWyM+ZMgLTk7 Z11mVRjkz5+EkNxdAKrt5ZX79jL0AYDI4/dkAEjzF+QCxB4/80Hq5avq3Uyd8EUGsMoHqXUuAHio ADcJjTy8nU6v29Np21fIA/ZrffoxPHg12xkoXL+7/BAAbOXhKNpLTJKyQse/uAsA2Ou3wACI9S+w 3Djrz3dzq4O7vIYBpLDf4eRAVFABH7HN6/rHA3y8nz56bNqu16e3EAbgh6Vga1d7V3lxBOhYLyR1 eo1/4AIQ3b8FA0imX/mpdQGirz/jhwJ2tbP8kgtAuX5gjAGADxos907RXvH39HvPOf/65+3x+OBJ hacf0xgAin53+RkAMMhDU4kAIDimXNuMv2MAZPdvuswYA6BePzYqCBJBf1sdRLehsyxvBgDi9Zu4 AFa9j8B2NDNEdyp/Zfs/rxYMf0/vHST83n5s9Qwgvn4PeQkADvIiANjWAIg+/rkgIN79m+R7AEij X5HpXnLR9N9+Pix3CtDIv2yysN85/8ju/t0QaPkg09PPtegh8O+9Y/n71R+2Xf8Yytu4AH76PeQd GEDrM/IuABe2EJD2HH9XEITs/h0YALl+lQHIw0AR9Xc/Cki/gJu8OwNAnD+wYQDgBwXz7sRU/un6 qHMA+Hhfs/6qp23nAoAxCBis30PeZhtwKF+LnWPmiaZL49cHATHv3/S5AUAq/aOFeoysf0DqKt7a yU3+ZZOF/c64ALHCEY4Cf7brv1xk9b5+6uWvDMAjCBgQP3GRd+wMxHgR0CODB7ucSud2TKUz0IPB xiPbb8+gLyKs4ySfVWcg/yNt4c7CyAV4axnAgCIPGMAiAEDg7DnLj6ZuSb55NrcBDBy/wgBI7t9k MR4AgLd+drkuHvpFkdBzy+vs5fUAQG6/8sppgGRJHgea2C8ZA/jf+2n47dUxgBEA5HLk3TETUAYA H8I/YMcA0r5aDACQ4tjmI5Z+EP0duzLBdvJhZwEizx9Ge3AvJHpbb7kFvyn1xJ+2J18XAN/YLACg B4v6+Fy5d5Z1yQPQxQCSgWVQHkDs8fvbuNWpgMN8meCZPIBVFvZrEQOgPP337/19L2KBP0cMIAQA UD8uDKA+ix1jxFktpwH9bDzcDID3Ctk5lAn+6s1BPQ14u94y9uN0us7Oy6+fT84xgIwBAOQRwBpz NKUvQCobFwcDK4fVzakvAIRMDgRep3pT/36v1+/r0xuDh/+8r/8MYgAwAwBR9bvLOwCAfEcA5vwZ GABQrJ8BABLot2IA0fSzAb+zkL8xgMT2O9gjxXVEbD8f29+/X388iZ9eWwB4e/13/wyg8xIxZ7K4 AAlZrojwXGwjPJm5AK5lbazPP84cWTLI/3kcpslo5Gd2AWLpd5Pvp25B/iBOjgPu/E1dAOz7N8lr AYBQ/2ihHnH18z2ealLnfVZ+AgBp7LdlL5tHN3lLSgB+/wfmK20OAwXpd5E3YucghUoUkBweGUEZ /4gBENy/NwOgXr/xQiHol05eYydvEwMgW78ZepS8+p/+c48uQH2erR0V1QXYFBfAMQYQVcdFG+bJ 3wVAnRxIDAC426jLAABdiNiveqSLkC4GkG4bXgIAJLcf2zhXuP7rOk96hkIgAFDMn2vBxMIAnBiA rB0Z1Eu2MIB7YABtsxCrlf4+DKAAgCwaY1k2KgwAyi7A3DoR5bqw87Odr3ffiUDGMwPGwCOEy18B IKn+h3FLhQV5kQCkpolijV/sApDev0lePQ5Mr19n4+j6a4kAi/LzzUETrJ8CABbyhQG4MIBmWi+i uACUS0TLcvl+7/M5tDfgHbgAYBEjMNUT9JZvASCZfkV+uR6A2B2+nQCC2PrNmYD492+dCZhA/6jw 7Z5I/yDjwyBvlQlItX4QmCYZTA+c5DUMgFS/hgGYskOOixXjYo3fnwHgzJ89AyBYP4sDb5H0i3SA pbYPah5AOvsdTk4kkop+MwsuAO1kThmAagzi+R+XikAZP7QAkNqYenk/FwBp/NZxrgj6myvp2y0k Bc+6ACnWb9rdItMcoHuLAUCbAEQ1mrILYFgowp2uS1/52YoBpJ4bj8nx7UQeQb5rD55Iv/KDORVY hIQHZ0QBef4WXQCgXD8NAEAy+xmxXFT9AKL0Y2OS9wsCIo1fPSjh9tjTJ3r5HQeOjGRWDADOy2kh UcfvwQAQ58+KAdDVvXyk0w+8+5N55V2PA6POX0kEwgEAmQAEvVeF7VmVgiDJXQAYcj/mEQP48v7R twEAXiy62jWMcDQlD2DBBaCzC3H801AhqADAVwcAmQDckIZTSxAwGxuHw7nvAZs7ABQXID4AsE+R AMhIR1MYQEY2zneAn88HuAMAgM2eQEkseU8AwIm2zAGAOBquFIiiiPaYAIA+2qQCQM7RWhz9Min4 oJd3BgDM+bNBx4Au5eD/W3TyLgCAod/Krvix0Fs2GKb+BRcAaPXrASCVfkXeL9nNS79aBk6JA4Aj ANCs33weQKj+b+sCXKrquSLm/8UFyCkGIOMAAgFY/i5AiQHEBAAA/v7f0T//JQiYmY3LTHBtJPCL BgF9q967yNs2B8XSbwIAcX3dxf+AeP6etC5AqvULbA4ad/zMuTlooH7R3lYggDYjaLk5KOH6aZuD ZkP5740BJIn/FwaQKcsVXoBmL+DO+wJMgQLI5PXHgSHN+LvjwKA8/47+f6zxBxyFkreHAAAZ5UlE QVQHRpg/p+PA2OvHNvsE+qGNA5wPRgBIZ7+3yYl4HPh7MwBo4/8syWgKA8iOAdwigXXGDCC8YCLp Hu9sQZAU4x8WBBH//vSJ/8cav+9ZAJz5cy0Igrp+gNkB23w28LCTCAAmBpD2+fMtCgp2l85uh3vJ D4qCJtGvyI8YAGvj/6CoQNS/yABI9WsAIKF+RZ4NF4pAP3TUHGRG0FFtCyXqAaS339Zs5wFAKz+H P6GtwOzkJwyAWP+EAfTyhvgfkn71vwwxAAr9YGAACfTbvuTw9d/2AkDLAFLa7+019hggT03xPGIA eBRLYQB8/0/bIJaK4s3FANJQzB4AMugOFOTmBo+/zQoeAsAqC/u9Tc4+WD8EDihoF4BU/4O2LwDw kvC28X9AGr9tDABI5m8+BgD068eMpe9R9Yva0MdhjSCYBgET2a9nDCDpJ9ddgPpYWVSDRf2UXYB4 ca5oigccYNAe5v7zAEAbKZiLIJgbmDjJq30B6PWrC9vtAgg/j/v/QKlfvW4cA6DWrwOAdPqV7yd5 AAT6YRgK5PUBeIMY0ABAOvttY1dXdHSRB+W/YXTL0N/66GFRpsVb/nWdVr8qv9qLv4CXgq661tB0 +hX5KwOgvn+D/DgGQK1/HOdKoX9QDq4WGSK8b2DbGCQL+5V/+lRgG/niAkzIE7vsRAPwxPNTTgPa xQDSmIo4I1K1nUO/yWlAjPClcz0AzPFLABDgLur/A7H+hRhA0vB7BACIMP7be87LxkM3v0B5e8oq MfJokEM9APz5Y8Z6AIH6wOEXWskbAIBE/xQAZPj/Cu30+pcZAKV+mI8BJNCvsXF6/Z0bDaJfwE6U C4cZAEhlP7cgYKj+7+kCyPY/i/3/SFyAsgtAz3KdXoqN3AyAUhDk6wCA3OBRw/+JPqUvQMYxAGkv t82i71AVGMmBsQYACgcKVp+7mTZQCRxwlQGkzr8LBYCo4/fY6o6lX/1b8MXnz80qC/s1MYBcjwdn xQDYufPqMpiwsguQOcsVx5JExPj48TUYgE1UwlhV111eAYAE+hXOfameDcXf0fWPvnCvCow5fzZV gcnWD/RBQGT9w42A7iv2af3SoFg/0xaJdVVgSrapYwCJ2O5BhP/Of0KbtsYavzcDQJk/BwaAv37m lxy2flCeNyY3AwanRhJ7azFjAPi3YnYBCKcSGpH9/1nH5P5BvyvCLkDE+fNyAZDWz/o0IIL+6Ves 4QhwtZxMXmWDybmDumC5xABk9s/u8ymfqEmJAWQeA+hGI0+OHQ95PG/UWySQGABioCw/3sWzf/+7 96AOWOO3ZABEb5lZAEjxlhtWBEpEuId+AGxE9NiveHT08actlhAIAGlWs+aHf/jrP7itYszx+zAA vPmzYwBE6wexsl0jyb+sRE5Q9XnIwH6i7gK4dRLzkF/YBUDX/yDPdfAiTw2bbi9T6J+7ZMQAIO36 2QAA2frNAACd/tG1LyuQIeRjA8ntZzg5uXUCzDEGINO5qvOBQXBLhRID+Jpu7jID6A4HpU8ijxUg oWFT8wBAxebELk51qWGUYJa89F3gLkDk8TsDAOb82SA15frxVGBgIo28OteJ7YctFwXV6tIUDIF5 +gOR5AUApNPfnv3ZHdiwLDjh/RvkBwwgiX71og4AUugfy4Na9Cah/cqvOAOA1piedweAlPbTMwBb +SVwGI/PFchM8osuAKZ+Dto8+nc7+6/tDox7/4sMIJ3+3nagBYBE+qfyDi4AyfzdDgMxUUpK0slk 9sO6ckkx9H/lGICs6iJbf1gzyxIDyOADGcYA2oCSTCdtIN3TFjY5zvnRgfJjACDUz0TuH8/9h961 pL5/w+UdA8hi/SwBgGb+5m08zfqJGIA0qval0uUFEq/fpL9V7smA6RiAqPzDMziZU2ypMIAMPnOF b5MxgE3vLjGZEjDeECScnE04PaKLYEZoDOIlDxeZvtmwob80aAySfv4CdgEQxu8EAOjHcSI0v4kp r3QGgoOoGLw712nsJ6/XWJ4MQNZ1vxI1lvHUlYpARgaQVQxgMzIv8XbZNXWZnBwBAGq5938+ZI2d xQUwvOTyBoC2SoChtsQ9T869NwdljXj9a3K27ACArDnopjQHnZHP7bzLywamHFPkBFxqoF6/JQaQ V1iQngEcPtvXP2TuPZWqwPfqAogh1heZGNhQ5waXqsDG2ZF7f8dGV/ijxADuxgXY5w4APMtMkoDP ugBANgAgojO87Q+D7O2qMIB7jQF0kQBZK8ivTsCXoUfZAICA5Ep0/WNwBy+WEgS8ZxdAQoBMNnne NfpGU1mj41c7Ddgysmo3X/avnAacl8/sNOAj5GG/LQCs5uTbdFPuc1LNH7ifBlwaCeDJWzCAKPqB x/5E2Z8Dc3QtUe/fggGk0q/K+zMAhPE7MQCC+TN1BqpFyhnPOatp5m88OZB1OjCNC3B9/I+Cip0P zIidxQUoMYB4LkCbHCz3A67GR7MhUIKAUxD+lCB8bsxFvwsAFACICwBytExuPfP3D9z95ER2rZwB wF0/u+xaN4zBPRWa0W8DpgpNaDoDJbMfALTuV37yL6sFAi/PB8i289jzF9I1BRxFIFheBYD4+tt8 jKsLdlmWn4sBIN6/4d+3IGAq/eqXWgYAieznZuOQ3H5VBmB6ug5yQ6A6H2pAnT+YxADs5MEJMMDy yiX5HgAw9Nct96qObTYGGOU1AIB9/4ZvBAAk1K9+OwIAcv3qt5t9Uv3j7/t6AIZrWSMPoAtPFG/+ wGovCywhAp1VcQDAaiBVyxnnaf9G3wsCYwBI47eOAZCsnyEGQG8/KstN75WYYwD9+6g5Vy0dPQDa +GPUA6CbVrQ8AB57bX3/9vG3KBJQ8gBm5XPLA8goWDOTCqz5hvUQYN6PegjKA9hHsT+aD9YuQP25 a8l/Yx95LbsAXgyA/nNfuwDDgUN9iwXszkg1g759KjDwpD85yaLdx4N1SdQCAAUA/ABgZW2bAKxu t6WqY1NDDpPzf/auRDt1HIYWcBIVv2yFgAkUaDv//41jJaEkZN9sU6Q5500bepHtyLIWWy5UIx9w fHkMPhcDmIg/j9Lz/rjpN3orlWhvwqMCUNz/BnzmAoAZ7689BqBOfqAyBqBFfnMxgAY8FD6UOuDm nkoR3cDE7X/YJw19dEDh18dAYVPgcjA+swAm4g8QXdK4//vH7rqp+a5afLEmoJL+N+ALFoAG/tBq AYAu+Sm5udrkt9oFgMrvzE9UTAlg2TBppF6jUlJgVPuhKkcK3RMfT+wCbC7plr9k2+XmrfcBLHIB nsQFmCrQrTwGkBe26C6s1yl3CL5qDIDLAcXrGZOs/+OBX3hGBUD1AP5MDKB6h090vcWqdsfpCoi+ ZlXg36Rf4lbxYaevyQJ4Fgtg9bwWQMG830TXmxkg5XaamgG9tWPR4YBCOAJatRmMw0sFMJp/kl39 d8utZLP/dgdipTtV0/5bEFBh/xvweBZAJ/8ivq4oKOiQn5ymBr3ym+JzRUEb8VUXe+JJoVR633dZ OGBc+3nuitt2/PC4AEyCb70arAXPEx2azf7dNXfNT9tux7E1AWHu8WtxAUDt+ytZAKBRfnj3q8GU jN/dAoDOwHxMMzqmu1bQe71suuUGa9vf0QKAod2HkeoDGlyAnngeJVG/tNBPsuEP2jc5Q6MLAIr7 3/BZjQJQxr9GAWjiX/ibOhlXL79FBTBo+mPyCjbXY+YLvO+SvMDg9rcdlRzuZsDIb6nE94gBPOB5 JMcsM54+jp8XDj3GfEhNwFn63yMGoJp/kwUAeuVnUAxgxvHrFANo3P0PkMjze7aDRcrzBga2n1vb Wfo/Dw0LAgIa/rt//9K1v1lj9gqfUBagswugk552J2DjcgyZRZtksqRFe4n4XxicqRUAYLb/49+/ e8J/I00omEK1URaAFMAwBWBN1C/gm6x6HeqAj0E7BCYYnLF7hnrgKxUA1Dg3HM2k1Or/h5uo0nw/ 5PZQDt5OWVAACvvfgM9XBAK97w/6KYDZx483a2rl7+/BAmjH55MGmeDetgljVutXyiVhcGuz4d17 UDU4emKjXfDdsgAAm00UfR5v+RK0kHbXqFtFlQksAC3jl3MBdL+/7haAGvmBnlmAucevLQvQtazH PQW4uRx3WWYgSw6gFujU/orBgYHd711QuD++MQuQ4nkUXa6fu1uQFCf/8Zo/5AtvtXudYZQCUND/ BvyAGMCM76+TAlAlPx2zAMre380CGIaHastgI83d3/QgHm45fl6j5mjXQxYAnqAoQHMMAIN9n8fj x23u4zDgKMx0zQrdDfgkMQD+R2MAJdpEl8/f/GC69n1eW4KDfyMIiD2XXZdmUGHyX6I+3tBzKwDK AjyNjA/OAjTa6FngK3N+33NaYHc8fl7qigko0Y5dTaPz2S1oq+1aPoDGfQA8UXofH7+B/qyE0vWC oRCASZKYY+8GVFFvqkkBqK9XNn4fwIT40TI+cft7WwDQ50OMfuOCuPu4zweMDn4k5vCme4Bkiv73 QR4CIQTzf/dJg+0wwZi/ggcLANWcpOhS6GTaT+zlJZ35U9RRHHsxiELJr3QBtM28TAGYcC3AGAtg nvZ3VwDthRfqcIB64IKb3+6h8Nu2IekVRHIC8eQYTOPgwPih6vwV3BOx5/nMt3MPnL18kJtmvoii 1NovzPwkC7pLln2ebJXsz35A+/sXVJ5x/KBmH4Ay/jUWgCb+hed8xCI3R/u7FQXtxb9uYwu6BBgS LzjH6ZHiND4QRSs3M5X78J9eM8IqZGfAf3+yB24oFhwsXz6+KwD/42HmvyczH7uyqT7PBLO1f0QM YIaVpVcMYPaVuSUGoNYyKC9yei2T3GnA8fzbvipZ5Tmay8djUQ0km2PSCMHn9Xq5oDbYcF2yDAsR HuT/HBFkT9YilBMMPOHf1ZP/sOinSmzD85XUqnnA9O1PFYAZVu7wLMA87e8eBFQwflNZuVPhCxbA NEFqaDQG4NcauKTm87/3EiVBgp2S6wgrO8A95qEEn0WceQB75uCD71jctVLo57IbiR8DoC15SVuB B1sAaon/tSxAbwUEOWMAw2epQfDgFiRBgstMc6U9huUwDyf6V8yyra0ec3BlP8XsLtl+nKT2kvgF dJ77ME/7eygABctMowJQvsy1Xg2m0kwZnwactv399wGMq8oBZacgzRVskmwBRggwh5YcKrrMNIPa 5TdgC2Szihm/aYQ9/mSF7HBXACquB39SC4D2AdR6wa+yEaj/yEg9gHWt0v0Dl+vnNZpDKXaJw0kF cOapArBLCiC3D+B7bQ55C4Mas9ifDWqNHxvUmPN+vzaJjGrOOZPiTHq246b6cMrmO5xuLgAGBfDB Ku8CLAQjIiKajfbaAjXpfMeYXzEI+BWLnG17XhAREc1G2rwTWLAAL7jfMz97cBb+IVn0Q96c2YN8 /dT7LzV/0WeTUKl4a8+dxc34qflD9c4xZfxbvkgn/0p7FrS9v6waJUzK/0HIAcqP0i2CleWG1dn6 dXSKhdQ+B194mKuQc34VilMSG/C4/qi28qxIp7QO8R/I9CXlBwwV4+xn7ohwtXJEvJTKIPBtzAOG J0s+sKpfOgy8ybDhk571HUZnIUfyfyP+4xozlr9m+YGuWUKo0pxQv4FYD618wQSLMRfwHTOpBqyA MSHiBZ+8gTDyc938gfj/6fcz1cprXIGP5ga5+yBwvtDed71kV6C7dwLnx27WuDDP2M01oED413Xe 9MoPtFgsoPdt4s+2/eDu2wc+ZVtAszQC4V8ar01+oKgFoMJ9AAXznYiIiIiIiIiIiIhII3VMIhhG fOseuEGtsZYmncGxXTNaw5fukpskNe7BFCkHe+tuuSmt4QeDGtNl9FzHDwPPkFN4/OT4vp8mLsyY /3v/y4R2bPf4lixz5v+3vzDkJfGfAGVmZcakO+yD+QV4ylCp6zMRCuYvNfEvfnAKWezHLF5zLfzL dBbirJN/RktHjosQvquJ/yMerDA9V6Jdft/e1jELpcyEJ/3yizU3BIulAH/zGflPSgGLV9tTrO/M UkGZ+yywDq7DMknXvv7L11mhANSbaWcRfy9PvvAMWXXlpBuhAKaVGcEcdynXseBgwIv6FmyxtaQA H96eg5Z+IuCeMKLcxEHqcQC5vIiTCc1ZSevICAWA5znksvGfCF0TVg87wB2mjhnKaMXCJZokLFzp bwz3BOqh9BTOUxBfnfkbwF74JkjWNvBQc25D8WPC4Ozj8ByYoACWcfyVumtGBCTcOPQ8UyyAVYC6 EVwR6l80ALbfqKJPoXCfRAHg2NnWOWQLY9qDdhRqc/0a6bRYHnwTFIBc3nBFuRV5026Q7FewTyvO GiIyePbdELdR6qKfgAXL0V0aEUDoh+frUBQdKLX8S5+6TQEmUDt+9qMFADre3yqVbjtIa7rplh88 Ar8Y+I5mGr9VnIuP6JVfN4lIDryWBPq2dQK8vZcKILOfdPAvhyWkOwd6+Jfwdj8LYKbxO6WXOXGn TQEoe3/SAqiKAeiSHytM81gmyO8pjFkszSPD9wK4eySMm4C9tJzUxtRn4yatcVMFyuIvrYPH19iY NM19MCIG0NMCUGHn7k2JAaRzjoXGON38sFzEYjFBrnWA8dIdv8ZioBhbTh7zOAkzK+RfpH1SmnQN b/wrZLGrnH/xDfrYmLRuYs4CAH3vz03D/31iADOPH7oAXKf85t/XOWb+AXTKbwEHeCdPyIfgc4XK fh9Axef32Mdg/MoJJH3bp+/kWcACtfyL+BM2JrCAr2O0dpXzL3zOF9gYXODgwQJQw7+Md+PERVti FkAH/zI+sQBAH/9cDR6+FyILYWmT319dZP0k0b+FiPkQvAbjMqkU9GaHWDhQv2F5ikXgmuQ82b4h +wAWyZVOsTEXYJiTBTgL4ZhyLuGQOmncq6672z8OMTv+4GPGwpZKdKWF/+N0Y+GP5Uqy38wYv/4x gDnGD5NcFkjp6rDbTcn7a8gCqJafQyz8k4tCw7XLL1beD784SD/We5LzQLAWIgx8wTwTTjCtpesd hrH878uQ8THDAsDIaBiEQnN0tGgBGLIT0EtkRoqMb8BxIMAQth/EadZmkOopXMtdKtj74JzASDw6 vKeYsbRwqHr+j3jn9zqVtRb+ZRfwtg9AMf9HPHcxMBn+xzXxL+MX7DHTBXrkx7+JTLJZUq/8yn+s QEiN5GyhN77OFIFmMwVG4uUvB2sJ9V88M3+oDaZq5d9c2E0B/xKeW0uuk//DZ9B2k4Ay+dXLv1wF 1La2fAL+REREr0kwvlTyU+MNGT8wa/yA5Odp5Beo3v0fwE8gBYQnPKkBwhOe8ERERER91QR00yWE fwE8yc+4iWV2+2FkCIHwfx4PNH712Gfvf813Qv5HeLx3AAj/Svg3Gr9aPPzB/hMRERERERG9PFEy hfCEf108jQXhCU94IiIiIiIiotfz/MtFxIDwhCf8n8UTERHR+j9UVxCe8IR/EjyFRglP+NfF02AR nvCEJyIiIsd/zN8TnvCEf148GUCEJzzhiYiIiOpVBhCe8IR/BTwRERER+U6EJ/wL4mncCE/4V8BD C/BeYQwIT3jC/9/O+fc4qkIBVC3iTQkgSRORNCS+3e//GR/2x7zdaTfpbl82g57T+cOixyZ3WrgX 0Y35AAAAsGM+30Ekrx+Oj49fuf9HEwaCj49frf+73htzCPj4+F/el09bf35/AT4+fm0+AAAA7Ah5 82B8fPx6fQCAv9B74OPj1+vD1jv4afR+/RvMvWl2KYbBrsvJ7ZhSyLpsnSYfgzuVRju2y5icnttQ WqzwFat7bP95NZG8vpwIfxO+T4Wo1ChXX7RXKSQVbWNyjOs+Z2QJl8bQi2QVUkzDwd9aiH9V/k+6 vJIz3M4qTxYk4Vfvi+37Ppcfsr3vPsZk9TmooVlSdJ0dYtTWq/Fgel/6AuNU9MdvZ6/8wZzG0kL8 K/QBPrBjTIePd20s43yTx1YPaizZfz/6eVK+dBCSU5jnUfk1D7gcJeVgTQABKqb8pNN3abpjzvnY N7akA67Xs+5DXMqoYTo7h5jX8eOcUtel2JpGl26gbXPrYqIDAKgY42LMZh3MC6ltZElKpZLZL6UW uHURKlwyhG8pdPZS9ndBxQuKDqB25De38Tflm0mVIV0a0wYfwrgYLTqHqJxk5buiGm0Oyp/Ws5RK QOdLXWBjmr4ty/d/jmfiX6V/mxh43iYPkwj4G/VNVvE+j7e2zW6t9vUQoxwvHcA8hKW/TAE0nVeT GaJr1gwgLevFQec64l+j/0aWgL8h3xyjGjqtjbkdM/u1PzBTTHJO8Sy6TanXaS0S5lLwHyTE43Xe wOnmNPxw9YD4b9eHrdIHpcaVfP+qTDEOkwvKNadReTemOGnjVHDtGFNrzPXKv8kxDc7HlA1B3OJk AP4+/DaqK+5+gjLOq/Iqqb2cfdlK01wyfrfO9/msG6uu1/1KZlAsfzRC/BnmoVa0tX1vy0t/VJHG nvPZru9lPuTFXoZ4fVryoTPr3lvRr0/n49oCNQ70v3rY+C9mDh+a8Tfii8hD03+Plrnuva85lQ/h ZsjDxxD/L+8/SRoe1g/L855C8LflP8nepXnh4bOPn0P8q/RfLh3kzdID/wv7f6GcJP6V/f9ht8Uh XxtomBBlQpj47c5/d8UQft3+S7NGxG9bvjzfkvv9w4K/G/+HywHy6kPmiV/dPpkP/v95LuK/78oP AOqCPhMff18+McPHJ88HAAAAAAAAAPgM8y74+Pv1AYAsAB8ff4P+u091w8fHr9cHACBjwsffsU/E 8PH36xMHfHx8AKDEx8fH364vbx6Jj49fr/+iJA+Ngo+Pv3GfFAkff+c+AAAAAABsGAomfPw9+UQM H3+vPhdR8fH36wPAfvkXjzVwOU76j4UAAAAASUVORK5CYII= "
id="image961"
x="-29.030926"
y="45.787094" />
<image
width="152.65045"
height="43.603603"
preserveAspectRatio="none"
xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA1wAAADyCAYAAABZG8THAABJsUlEQVR42u2debzV877/z72mDFFI QjIkkjFTSSoZojKToULGyDyEQqQImSqVUjI7JUNlyGmQmQZKKCRDJUMO95x7//z87vP9eyw3WWu3 1m7v9t5rP/94Ppp2e/iO79d7eL3/9j//8z9JREREREREyp6/eRBEREREREQUXCIiIiIiIgouERER ERERUXCJiIiIiIgouERERERERBRcIiIiIiIiouASERERERFRcImIiIiIiCi4RERERERERMElIiIi IiKi4BIREREREVFwiYiIiIiIiIJLREREREREwSUiIiIiIqLgEhEREREREQWXiIiIiIiIgktERERE RETBJSIiIiIiIgouERERERERBZeIiIiIiIiCS0RERERERBRcIiIiIiIiCi4REREREREFl4iIiIiI iCi4REREREREFFwiIiIiIiIKLhEREREREVFwiYiIiIiIKLhEREREREQUXCIiIiIiIqLgEhERERER UXCJiIiIiIgouERERERERETBJSIiIiIiouASERERERFRcImIiIiIiIiCS0RERERERMElIiIiIiKi 4BIREREREREFl4iIiIiIiIKrqvPbb7+lZcuWpSVLlsTvPSYiIiIiIqLgWkP++7//Oy1fvjy9/PLL qWfPnunqq69OU6ZMSf/85z89PiIiIiIiouBaE1asWJHGjh2bWrZsmWrUqJE22mij1LVr1/Tll196 fERERERERMG1JtWtefPmpZNPPjmtv/766W9/+1uw//77p5kzZ8a/e5xERERERBRcHohS8Ouvv6bh w4enbbbZ5g+xBVS7PvroIwWXiIiIiIgouEpb3Zo9e3Y6/PDD0zrrrPOH2Np0001Tr1690tKlSz1O IiIiIiKi4CoNOBHedtttqWbNmn+qbh1yyCHpjTfeSP/61788TiIiIiIiouAqDbNmzUp77LFH+o// +I8/xNZmm22WevfuHdbwHiMREREREVFwlYKff/45de/e/U+thP/5n/8Zs1vTpk1L//73vz1OIiIi IiKi4CrN7BZ7tho0aPCnVsItt9wy3X777emHH37wOImIiIiIiIKrNNAuePHFF6f11lvvD7G17rrr pjZt2qTp06frTCgiIiIiIgqu0vDLL7+kkSNHph122OGP2S1+rV+/frrnnnvSjz/+6HESEREREREF V6HgOkgrYevWrf9U3dpggw1Sx44d05w5czxOIiIiIiKi4CoNX3/9derRo0c4EWbEFtUtql0PPfRQ WrFihcdJREREREQUXIXCzq2nn346bOBxI8wIrvXXXz8de+yx6fPPP3d2S0REREREFFyFgpCiXbBT p05po402+pMz4RZbbJHuu+++9Pvvv3usREREREREwVUo2LzfddddaZtttvnTkmMqXTgTzp8/3+Mk IiIiIiIKrkLBKOP1119PzZs3/5PYgk033TQNHTo0PsZjJSIiIiIiCq4CWwkXLlyYLrzwwrThhhv+ SWwhvnAmXLp0qcdKREREREQUXIXy888/p2HDhqXtttvuT2IL6tatm/7+9797nERERERERMFVKP/+ 97/T+++/n9q2bfuXVkKqXd26dUtLlizxWImIiIiIiIKrUJYvX5569eqVatas+ZfqVtOmTdO0adNC lHmsREREREREwVUgb7/9dtp9993/IrY22WST1LNnz7Rs2TKPk4iIiIiIKLhKM7t13XXXpQ022OAv Rhm4FU6ZMiX913/9l8dKREREREQUXIXObmGG0aBBg79Ut+rUqZNuv/12nQlFRERERETBVRo+++yz 1K5du1hqvLLYqlGjRurUqVOaNWuWs1siIiIiIqLgKk11a/jw4al27dp/qW5R8Xr44YfTr7/+6gUj IiIiIiIKrkJgyTE28IccckhaZ511/iS21l133dS+ffv04YcferGIiIiIiIiCq1Cwge/du3eqVavW X4wyGjVqlEaOHJlWrFjhxSIiIiIiIgquQlsJJ0+enA488MC/VLewgT///PPTokWLvFBERERERETB VSi4DrJba9XZLYwz9txzz3At1AZeREREREQUXAXyz3/+M73wwgupWbNmWatbPXr0SN9//70XiYiI iIiIKLgKZf78+enss88OcbXq7Nauu+6aXnrppTDU8CIREREREREFVwFggjFmzJgwxVjVBn799ddP nTt3Tt99950XiIiIiIiIKLgKgarV7Nmz04knnhjialXBtfXWW6dnn33WJccileieZZbyX//6V9yX YPVZREREFFyVlF9++SUNHTo01atX7y9iC0455ZQw0/DiEKk4gcV9umzZsjR37tw0atSodNNNN6U+ ffqkfv36pQEDBqRHH3002n4nTJgQe/R++OEHDW5EREREwVUZArnPP/88nXbaaX8xyoDNN988jR8/ 3uy5yFq6H6la/fbbb5HkQDjhDHr33Xen008/PbVp0yY1adIk5iypRsMGG2wQ8HebbbZZOIw2bNgw HXfccal///6xpPynn36Kz+t9LCIiIgqutcyvv/6aRowYkerWrfsXsYUVfNeuXeNjvDBEygfaAXEI pSL1wQcfpGHDhqXrrrsuHXXUUalBgwZp4403zpoMyQeE2O677x5mOKNHj04LFy4M4eVxFxEREQXX WoIArGPHjuFEmG12a+zYsWbFRcoBqljffvtteuedd9IjjzySLr300rTffvtFpWrdddctlcDKBff3 VlttlS655JL03nvvRXui97WIiIgouNZCZp12pW233TZrdevUU09NX3/9tReFSBnecz///HMkOl58 8cV05ZVXpubNm6c6deqUucjKBi3Cxx57bHryySfTkiVLFF0iIiKi4CpPmBFhLgRxtWpghgijBYks vBeFyJqBeQXVrKlTp6b7778/nXvuuWnvvfeOdsFs1eXyBGG31157pXvuuSctWrTI8yMiIiIKrvIa zscMI9vsVo0aNSIgxEzDDLjImlW0vvnmmzRu3Lh0xRVXpEMOOSRadZmtWttCa9UKdv369VOvXr1C CHquRERERMFVxhBksXcrW3WL5ccEiFa3REo/n/XFF1/EfcTcFBWlmjVrVqjIygarIPr27evaBxER EVFwlSW4lD3++OMxN5Kt3QiL+Pnz51vdEilFReurr74K589OnTqFQ+Cmm25aJkKLyvP2228f4u2g gw5KRx55ZDr++OPD9Oboo4+O2Sz+nqo1FbR8zTR22mmn+H5xSvQcioiIiIKrDFiwYEHq0KFD1iH9 LbfcMnb+/Pjjj14MIgW06C5fvjyWDp9zzjkhYhBIayK0+L8bbrhh7NRCVNH+9/zzz4er4cyZMyMp QhUNAw7af/k9DoRPPfVUuuWWW1LLli3zEl48B/jYGTNmeC5FREREwVUWw/sDBw5MW2yxRdbgq0WL Fmn69OmRqfdiEMnvnpo9e3bsztpll13WSGjx/1hevM8++6QuXbqke++9N4w2Fi9eHFbufC3uTQRe tgo0//b777+nFStWpDlz5qRrr702ZsZW93VZlty7d+9wUPScioiIiIJrDSAbTnVrvfXW+0vQVatW rXTDDTeEXbQXgkjJFS3ED8uKBw0aFG1+66+/fqlEFkuNN9poo7Tddtul4447LlY10JZYFi1+VKqH DBmSdt5556zzmit/D7QjTpkyxVZiERERUXCtSSYeq/cGDRpkdS074IAD0iuvvGJ1S2Q1hhjYqT/3 3HOpR48eWWch86lkkfSghffggw+O6tikSZPSd999V+aCB0OMAQMGhCthSZU3qt4333xztEZ6nkVE RETBVQrImp999tmx+2fVYIvB/ksvvTQsrL0IRLInLLg/WFiM0KJqlK1SvDqhlTG/OPzww1O/fv3S +++/H+2C5VVZ4vMy48X3jKjKJbr4WTDfePfdd026iIiIiIKrUHAmZO/Wnnvu+ZeAiz/vtttu6Zln nomP8yIQ+bNgYbYJswpabvfdd99oASx0TgsDC1YunHTSSWnw4MHpww8/TD/99NNaaeFDLCKkTj75 5Pjec32PW221VZhzMDPmuRcREREFVwEsW7YsAqnNN9/8L0EWsye4oM2dO9cLQGQVofLpp5+mkSNH hgU7LYCFCi3adREy7L0bM2ZM3Ge//vprhbRCsg6icePGOee5+NmaNm2aJk6caPJFREREFFyFZOjf fvvtdMQRR2S1gsfFDCt4nM28AET+P8wyvfTSS2HzjvtgvrutVq5oYYTBvizur1mzZlX4ritaC886 66ysbcUZSMrcdtttkaTxOhAREREFVx58//33sZeHLHu26hauhR999JHuZCL/8/+t1T/++OOwSafa s8kmmxTsOsh8V7du3aIyxowW4q0y3F9UuXBBbNKkSc4qF98/82UkaaxyiYiIiIIrj9mtV199NRwI swVYOKwNGzYsdvd48qW6z2pho45bIPbsVHpKslLPBuLs0EMPTcOHD48F41SNK5sBBQmYiy66qMQq F8kZ7O7dyyUiIiIKrjxmt/r06RPLVLPNa2AAQDbfEy/Vvao1b9681LNnz6j+4CRYiNCiVXePPfaI VrwPPvgghEplrRjzfT388MMxj1bSz8Pi5S+++MLKt4iIiCi4SgqscEJr06ZNzqAKq2hnt6Q6V7Vo s8PBr3PnzpGYKMQUgwpYvXr10gUXXJDefPPNMMOoCgIFUUi7ZEkVPMw1Jk+ebFuhiIiIKLhyQfD3 yCOPpLp162YNqAgun3rqKU+6VEuhxe6rOXPmRPsfxhYltdhlm3OqWbNmOuSQQ2Kdwg8//FClfn5+ 9uuvv77En3nDDTeM6jjW9V4zIiIiouDKwqJFi8JhjeAwWzvhYYcdFi1DnnSpbixZsiQMLaj+1q5d u6BZLfZYUR2i/RBDjKrackeVa6+99irxZ23btm04G3rNiIiIiIJrFdgfNGHChNSwYcOcw/1Dhw6t dAP9IuV9X7DU98477wyr90LaB2nBZYUCy4NfeOGFSuM8uCZVLtooS/qZd9xxxzRlyhTnuERERETB tSq0OF122WVh+56tutWyZcswCfCES3UBgYFj51VXXRVzV/kKLe6XTTfdNB188MGpb9++aebMmTH3 VdWPB8mWIUOGlGgQQjVvwIABIVS9hkRERETBtRIsWd1nn31yBlEsYq3oJawiawvs3tk/RQthNsfO kkwxtt9++3TuueemiRMnhutnMVV7EI+NGjVabVshVUGvIxEREVFwrcSIESMiK58tgMJEg+DRdkIp djCOYVaJFsLmzZsXZPfOx7Zo0SI98MADUQ0uxl112Nd37dq1xNZKZtxefPFFrycRERFRcK0cRJ16 6qlZgygy9kcccUSaO3eucxlS1HAfjBs3LnXo0CFmr9Zbb728xVatWrVS9+7d0/Tp06v8rFZJYPl+ //33R9W7pCpf7969TdCIiIiIgisDZhlbbbVV1uCJwBN3NndvSTFDuyz3QatWrdIGG2xQ0LwWRjMs MP7qq6+KfgcVQvKVV15J2267bYnHpVOnTtrDi4iIiIIr00J14YUX5mwRatasWXrvvffMVkvRCgjm jQYOHBjW7flWtbhfaCHETIbddJjOVJcKMLbvhx9+eInH58ADD0wLFy70GhMREREF19tvv5323HPP rEETmf7LL788fffdd55oKUqxxV45ds+x9qAQobX77rvHXi0WIRd7VWtVqHZjolPSMaMCNm3aNK8z ERERqd6CC+vmO+64I2fgVL9+/fTYY4/pTihF2UI4f/78dMMNN6SNN944bwdCWm/ZqzV+/PhqVdVa GcxAxo4dm7bZZpucxwpnxyeeeMJrTURERKq34KJyddppp2XdvUVwSbvUm2++aTuhFFVVC1OL559/ Ph1//PFpiy22KMjuHYGGA2F13jPFzz5p0qS00047lejY2KdPH/dxiYiISPUVXGSpn3322WiNIphc NWCqWbNmuvLKK92nI0VVmaGqNWjQoJhNzJZoyAZzXeyo69+/f1q0aJGi9X9FK9b52OaXdMywj6cK 6LUnIiIi1VJwIaQIiDbccMOsAdOuu+6annnmmaLcJSTVj99++y299dZb6eKLL47KzLrrrpu33XvH jh1jCbLi4f/48ssv05lnnpnWWWedrMeNv2/dunUYbHi8REREpNoJLjLUkydPTvvuu2/W6hbZ6RNO OCF99NFHnmCp8uDEOWXKlBAIm2++eYlLe1eGeS0EGi6dCDaP5f+B+Lz99tujEp7LXKRx48YaZ4iI iEj1FFzsx+nbt2+qU6dO1mCpbt266a677nKPjlT51jeEweOPP57atWsXRg75iC3mjxo1avTHvJYz jH+FJdEsQK5du3bO48gOvzFjxrgwXURERKqf4Jo1a1Zq37591p1DVLyYb5k6daqBklRpfvzxxzR0 6NDUpEmTvJcZI8pOP/309Nxzz6Wvv/662lm+58svv/ySBg8eHBXDXMcSQ5KHHnpIwSoiIiLVS3AR /DCPQrtPruw+rVdfffWVJ1eqLDgR9uvXL5wFs7XN5hJbnTt3Tu+//37MLppwyA22+lQOV2cNf/PN N0dLp8dMREREqo3gWrZsWbRKEQxlC5JoMyRQZbmpJ1eqGtiQ0wbYo0ePvPdrYfCwyy67pAEDBsQi ZCsy+SVu3njjjaiGl9Sa2aVLl/T99997zERERKR6CC4y9u+8805q27Zt1qw/gScBFLu3PLFSFee1 XnrppZjXyuW+mc0ghtUIw4cPj7kkj2X+xxtTHRwcc83FcWz5dxwNPWYiIiJSLQQXTmuPPfZYzoWl m2yySVQGtL+Wqhb8f/PNN+mBBx5ITZs2zTqbmA0qYK1atYp7QrFV+DGfPXt2OuaYY3IeX6z3Dz/8 8Nh95jETERGRaiG4li5dmm666aac7YTYYDvkLlWthZA2wIEDB6bddtstr3ktPqZevXoxrzVjxgx3 zZWSzz77LAxGcu3i4jjvv//+sf/M4yUiIiJFL7gQUZgB4E6YLUAiONprr71iLsOTKlUBzBjefvvt dNVVV4WNez6VLa59lnr36dMnzZ071+TCGrBkyZKYB6Uynut477DDDmENr9ujiIiIFL3gwlXsySef jAAo17xFp06dHHCXKgEtgLhtHn/88WE/ns9+rcy81j333BOW74qtNYM9fRzLkqzh2dPVq1cvWzZF RESk+AUXAQ8zLrkWlZKlvvvuu81ES5VIHiC2MHjJ1xxjo402SocddlgaMWJEWrx4sZbvZXQeHnnk kbTddtuVOCd33nnnpe+++85jJiIiIsUtuGj/6dmzZ84AlcoXy449oVLZEwdUavfbb7+CzDGOPfbY 9PLLL8cyZMVW2UByZvz48VE1LKmqiFPhxx9/7DETERGR4hVcGAu88sorMaOVq/Xq6KOPtp1QKjXs kKMKu/POO+c0asi2fJdF3qw6wKXT41h2IFyZ+WzRokWJBiWHHHJIzNp5zERERKRoBRdVgbvuuiva qnLZNw8ZMsTMv1RKmLXC4OKSSy6Jxdz5zGvxMdtss0268cYb08KFC53XKicWLFiQunbtmjbYYIOc 5+HAAw9M06dP93iJiIhI8Qqub7/9NgwxcgWnDRs2TPPmzfNkSqWDqhTW7SeeeGLOhEE2J0Kuafdr lT/Lly9Pt912W4nGGbvssku0gVJp95iJiIhI0QkuqlYErE2aNMmZgSZDzQC8J1Mq03WLCx5zV8wA 5Su2mFE84IADwszBFsK1Y5wxePDgtO222+Y8J7hIIsqYn/OYiYiISNEJLrLK999/fxgHZAuGatSo EQGTJ1IqkxnDl19+GaKpbdu2eYktEge1atUKc4xJkybFji6P5dqpQA4bNizVr1+/RNOSHj166FQo IiIixSm4yCpTwco197LllluG05gnUirLvNann36arr/++mhFy8eJkBnEnXbaKWa8MGewsrV2xfG4 ceNyVtCB+a6zzjorRLTHTERERIpOcM2cOTM1btw4ZzBE+9WcOXM8kVIp2ggxx7j66qtTvXr18moh ZH9cq1atYsfcZ5995h65CuDdd9+NHWc4EuYSxFQeZ8+erTGPiIiIFJ/gevzxx3O2E1L1Ov/889MP P/zgiZQKnwXCYrxLly5Rdc3HiZB5rXbt2qWXXnopzBsM5isGXCA7d+4c7cm5njNNmzZNEydOVBCL iIhIcQku2rOwxc4VvLKjaPjw4bZgSYXyyy+/pKeffjodeuihOZMD2Spb7I578cUX04oVKzyOFQhi l6XqPE9yna9dd901PfPMMzoVioiISHEJLlzeTjnllJxBEHMvLEQ26ywV1UL4xRdfpP79+8dS7nzm taB27drpiiuuSO+//77mGJUAEjYPPvhg7D0ryamwX79+VtNFRESkuATX119/HTNauYIg5i6YmbEV Syqi+srs4AUXXBDLjHPN/2Sryvbq1SstXbrUZcaVCIwzGjVqlPO8rb/++unss8+O9kOPl4iIiBSN 4HrttddS3bp1c85VEAB98803nkRZq1UtWghff/31MFLI1/Kd+aCDDjoorOLd51T5wB3y4IMPjqXT uc5jy5Yt05tvvmmCR0RERIpDcGFCgLV2rjYtWnyGDBkSwa8nUdZWVWvx4sWxt6l58+ZhF56P2Np6 663D3OWdd95xBqiS8u2336Zu3bqVKKB33nnnmONyZlRERESKQnAtWLCgRKtmXMOmTp3q/JasFRBK 8+bNSzfddFPacccd83IhpFqy3XbbpWuuuSZ9/vnnthBWYkjw3HHHHZHIyXU+aR0dNGhQ+vnnnz1m IiIiUvUF18svv1xiYNu+ffuY3/IESnnz+++/pxkzZkQLa0kB+aozPxhp9O3bNxYhK7Yqf6voo48+ mrbddtsSbfzZsfb99997zERERKRqCy6CU9oFN99885yVg65du4ZDnCdQyhOqGezJYl8WAXc+LYSb brppOvLII9Po0aPTkiVLnPmpIkyaNCns33Mlefh7rgMXIIuIiEiVF1zMZZFJZldRtsCnZs2aqXfv 3uH05gmU8qp4ZOa1WrRoERWrfCpbtWrVimQA7a6sNfBYVh0+/PDDmM0ryTgDQYYwcxZPREREqrTg onJ1/PHH5wxy2b/1xBNPxNyFJ1DKGkwRPvroo1i6TYCdz34tgvTGjRvHvNasWbMMyKsgixYtSscd d1yJ57tBgwZp/Pjx0WbqMRMREZEqK7hYCNusWbOsmWbaejDTwPHNth4pjxbCF154IZ188smxkiCf /Vp8DJbvY8eOTd99951GLlWUFStWpLvvvjtnKzPwb7Q787EeMxEREamSgov5LayXqWJlm6VgjqZ7 9+6xFNmTJ2XZQogZAi50++67b1xn+TgRUg1p06ZNiLRff/3VY1nFr4GPP/442gpznXvE9amnnpq+ +uorj5mIiIhUTcH1ww8/pB49esScVq79W9g3Ox8jZQXtf3PmzEkXXXRRVLXyEVoZc4wTTjghluHa YlYc8Pw58cQTS7wG2Mf1j3/8Q+dJERERqZqCizmKTp065VwqW79+/TR8+HDnt6RMoCpF8MzsTj6L jDNVre233z5deeWVMevlvFbxgGHPpZdeWmIrKWY+AwcO9BkkVbaSm2nHz/x+5fb8Vf8sIiJFKLiw XD7iiCPSuuuumzXYadSoUbQcOicjZdFCyO4lWghzXW+rVrWovLZq1So9+OCD6csvvzQwKcLrYujQ oalGjRolXgsdOnSI5JDHTCryWqXKSsIHSB79+OOPsYqCWVLa7nlGYULF4nV+/80336RPPvkkzZw5 M82fPz/et8xMY/TDnwG3Tv7M/6F1ls/D//v222+jAsz8Iu9fK7wiIlVUcPECeeWVV9I+++yTtaWH v8OcYMqUKQa6Umpo/5s3b166+eabY7l2PlUt2GyzzWJ+h+uPSojHsjihRbSkBciZSjuVUY+XlCcI GwQOLfTLly+PVSgIKFqg33333fT666/HnsAXX3wxPfLII2nAgAHpuuuuS5dffnm64IILUpcuXdJp p50WbbL8/pJLLgkHYOZOO3bsmNq2bRsziySR+DMccsghqXXr1tEuzYqL888/P9r8qfzecsstacSI EWnChAmx+gKxRpWf5e6IM75PhZiISCUXXGTpaBckmMkW5GATT8BLFs4TJ6VtGSNQPvfcc9NWW22V 17wW1K5dO5111lkR5FhdLW6ofB5++OElXg9UwHr16uXsnpQJiBRaVBFUVKJICPGsee6558LIB/fM /v37x6oKnl1UWA899NCozu++++6xkoIkAXOltEbzrqRqT2sszzjg97RDZ9plcyU1V/49H4tbMP8P Nt5447T11lvH19xvv/1CmCHSeC8j8O65555Ym/DGG2+EEKNKxs/EfWKSVEQUXJXkG+GFQ4auTp06 OS2Zb7rppmib8MRJoZliAplRo0alo446KgKTfMTWRhttFBXXa6+9NtpvFFvV41rp16/fatsK999/ f5M/UupuDhKMVIWmT5+ennzyyXTffffFc+bss8+OihTrT5o0aRICB7Mo3n88txBT+SaK1gYZYYbQ w3SI75ll8ccee2w6/fTTo+JGInXcuHHxs/IcJvHls1REFFwVBP3hPXv2jNatXEtHR44cqUmBFBxA I5auvvrqyASvLpDOUKtWrWjDoV2HGQZbZaoPM2bMiKXXJV0fmGcwy+fzSFYnrpivonJK5erll18O gUXy57zzzoudk7vsskuqV69evPsQLlSnKpOoKo0Iy1TG+JkwGeLZS/siz9Rbb701Pfzww9GeTask FTCfryKi4FpLsAOHvnEe0tn235BRdn5LCoFFxq+++mpkjamc5rPImGCB9hxmFhgu/+233zyW1Qza oDp37lxi0Mu/tW/f3p1ckrVbg3Y6nj0Ii+uvvz6uJwyh9thjj7TDDjuECEG05/NMKhb4WdlxSLVu u+22i3c6z9nbbrstjR49On3wwQeReFV8iYiCqxx55513Yng3W5BDxu/II48MUeZJk3wrpg888EDa e++9I7DJd78WYosAYOHChba9VGNjFarpzO6VdL0QND7//PMmgar5/BXGFlSwMJEYM2ZMmEtgSMHO NhI9tAJSWa/qlavyEGA8m6mCbbPNNmGKdfHFF8cxxCmR8QEryCKi4CrjlxZuS3vttVfOWZpzzjkn 7G49abK6Fh4sjBkwxxgj3wwyrTxNmzaNIfXFixcbRFfza2ju3LkRNK/OPIPKBXMpHrfqI7AQAcwh YQzBGgHeTVSvdttttxBXVHFoqVNcFS7AeA6T6GB29swzz4zq4N///vf02WefReXQ57KIKLjWsAVj 8ODBkeXK9iAmcMYByfYuKSkQoqqFQxaOggQ9+bzkCYywh+fFjjOY15gAAfVDDz0UVaySrh9mb4YM GaJjYZEKb54rnFvmsGgTfOKJJ9JVV10VhhCIApz7KoOwWtlVkEoaYLDBc5DvEagkAfsEqSxtueWW MRuNKQd/l/l7fuXjSShkXA9p9edzZ77G2vqZ+Tp8T3vuuWe67LLLwnwDsxos6HU/FBEFV4HQOnD7 7bfnbOHZaaedIsvlCZNsQREtPbSg4C5HC2G+xhgEEcxUEDAvW7bM4yl/uq4IsJn/I+AsyckSge8i 7OJJ3CC2McqhhZ0kDO+e+++/Px133HExf1RRc1eID55ZXHMIJ9oVSVIimjB5waqdHVusNcCNlR1c iBSq/Tj8ktRkpgybed63LH5n9yV/h0PwnXfemfr27Zvuuuuu+D8XXXRR7OLq1KlTuA5iekEXAEYf mGDw9XlnI84ygqw8hRifn+QrDo78PJwXFjU79yUiCq48IdjlAU87RrYHLUPGCi7JFhwRGD3zzDOx 0JNMbb7BEFlcXtyPPfaYi4wlp+kKLWMlVbm43ho1ahTW13y8x61qimsq20uWLElvv/12JGAQGwgX jB0QNYiKtSG0Mg5/VKh4RiEwEFTsvjrggAPS0UcfHe6GvC+xkuf5NXbs2FiCjOkE1R/a71iQzM/D s40OEn6+TEKA5ybzqSv/OVPNo12Sf+P/cD0jZphPW7RoUZgIMadGcgu3xXvvvTccB9nBxW4wZrCp RDEHiyAsLwt7PidJNarLLGom0cb35cyXiCi4VgMGBd26dYv2hWwPVwIattt7wmRlsbVgwYLI1PKS L6kKser1RBBD5QKjFlvBpKRrjGsEwx6C4FzXFNdeu3btop3VgK9qmV0gSgjWn3rqqaiakIShcoPg WRvVKt55tMwhHphhZqEx1xILhXHwo9r0yCOPpBdeeCG9+eab6ZNPPgkXTVocudYQShVRWc3sEkOY cQw//fTTEGQTJ06MShprOHAdPvDAA/9wZCwP0xA+H1U2jtnAgQNjFpzKJCLRmS8RUXCtApk5WiCy PYwzlvC8FD1hArzoeanefPPNkf3N9yVOYEzrDfNa/H9dCGV1EEz26dMn5l1KurZoNevRo0dUGAzy Kifc71RtEAck8KjQXHPNNRGsN2zYMKoy5VnF4nPzNfhaCKszzjgjnXvuudH2x/eC4yUVNvYGsrML YYVoWLkaVRUgiUXXCuKQyhuzkFdeeWX8vBjR0I7I/ZJtBcyathsyV3fSSSfFecXtkOOIOPWeFJFq L7h4EE6bNi36wnPN2dBGQTXDE2brD0HIc889Fy9vWr3yCZB4GdNueMwxx0S2mN1J9vxLvkE6QTBB HG1lJWXaEf/MxzgPWLmeGSzX5Rwys8TKB2ab9t1337T11ltH2155iayMwKLCQxWetrvevXunp59+ OqpVzAjyLMJVlda/YnwmZRY/4zDMz5uZiaNyxxJkWiURX2VZUeRzMZ5Acg1zE9aDkNS1dVxEqr3g YqEx/enZHp64LJEFpJfcE1a9q1q0d5ENxuiCwfF8jTEw0qDP/6233gp3K7OdUghUGWjpoj2qpNZC Aj2MC5ipIcj02FVcuyD3OQE+LW69evWK+SJmgalUMv9TXuYOPG9oSeQ6wGwCgYfAwpxizpw5UTGt zu56/Nz8/MxbZc7Pgw8+mLp37x6JVZ7VtAiWhQjmHBM/MFNGBw2GIAg+K14iUi0FFy9HXkY8aHOZ G/DC1K67+sK5f+2116L1h4xxvsESwTFzEaNGjYrKmC2EUlqYCbn88svj+ltd2yrzN7inWUVdu5VI qigzZsxIw4YNC9ML5rHYjUUAXx4zWZk5LKopVNsx2eBd9eSTT0ZyB+dKEoU8v6paW+DaTKTR5kmV j1ZP5iAzjpBUBsvqvHFfUkk7+OCDo0UY4aXJjYhUK8FFtmnEiBE5d3DxssQ1ypdV9cxU8yLm/FMB zdfuPVNtwMGK9hVfrFIW1+LkyZOjclFSlSuTJEKcIdI8duVbLcH4gnlMrM1p+8RgiXcGz4rysCnP 7IVq0qRJLOalasJuLq4N2t551iCwFNtrZmZCqyXVL8w3qCzT0VAWVS+uCQQyiThmLjHZoOpofCEi RS+4mHegrz3bfAQvt1122SX63T1Z1SuQIjP87LPPxtxVrVq1CqpqMZtBwKsxhpQlBIKYG5AcWt31 yAA/84JW5svumUAwzvGkWs1MFmYMuI0yH4UIKutZrIxFO06CtKWxiwqjHp5LH3300R9zVxXlFFgd zjkVMCqFtGXecMMNMetdt27dON9UF0srqDPnlnfFKaecEvN9GN4U6yydiCi4IiuIAUK2lyUPRRyN dCisXvMyOEthPkAWMt8gKpN5btGiRbQQMsPh8ZTySBAxb8JsyOquRzLz48ePd55rDaodPA8wveA9 QeKNavepp54a81hUPcqygkUATusZyT/az6iWMVd01VVXRSWEc28wXrHvBpwPmafk/YD5CQnZNd2R xv/lfNMRwX6z6dOnR3XalSEiUjSCiwwWYqpNmzY5gxZaN5iH8GQVP1S1eJmefPLJMdyeTzDFx/DC JTi68MILYwbAqoKUJ1OnTo3gLJ/db8ymYvet6CpsHguRxXOfxb633HJLOvHEEyP5VsgMZyHzPcxg NW/ePGaHLr744nTPPffEcl8WCHvuKuc1Qrs5lS9MtWj1LQtbf1pRcbDMtBtmzr8VTBGp0oKLdgEe ati35gqmDzrooMhqebKKe3AaxyoWVxKg5rufhesDu3dmNx5//PHo+7eFUNaGicukSZOivWl1AR6z hK1btw4nVq/N3Ik3qhdff/112HcjdBA8VJdo5aOaWNbtglSzCNB33HHH1L59+zRo0KD03nvv/WF0 UZ2dBKsSnCeqUczQ4WDLzk5afvNJhqxOhCPwzzvvvDBBwWGSJID3sIhUScHFS5aB43r16uUs9eP8 xIvYk1WcgRZD5v/4xz8iS5nLOCXXtUEwdsEFF4QjmFUtWduB3siRI+MaXN21SqsrgRtJBQO2/0uy ECgzZ0lVevTo0VFVOPLII6OVGGv1shZZJHIwNKEdEZtwWgU5hzNnzox3keel6hss4WaLWGcuq2nT plG5LG3rKf+H/0tCmArrnXfeGYucmSG0tVREqpTgolTPC4/2sVxZSFo8eMB5soovYCXYYill27Zt IygtJPtI2we7tfgc9tpLRUAi6MorrwyDjNUlB+rXr5+uuOKKqHRV1wWsiBqq0LNnz45dZTjQ8Xyn PXPnnXcu85msTNBMJYuWM5bgYrzAOwdbcGzkTdQUZxJv7ty5UYVmRQDGKtx/q3MXzWe/GtcqtvLs hKQSqvASkSohuHgwsnMj124bHpDnnHOOG+KL7IVIawZtQ127do1scyHtH8xrsVD0ueee085XKnyO BLc6Zn5Wt5+LZxntr0cccUQEgbSuFXuwRhWLe53glyr2fffdF1bqHAOWl3PMaLksjyXEJHDY48TX wgWXXY/seeKZ4UxO9al6ca4ZSaBllNZRHA7XpHLKfUyChSThNddcE9VZ3Es93iJSqQUXL2P2mORy /CKr1LNnz3hxe7KKQ2x988030fLBXi32oRQSbBFAUVGgqmULkFQWUUG1BKMXKjSru4axGN9pp52i fQ7DoGKqsGRmsWjtogLw4IMPxgJiglPaBLHgxpSgPEQWSRuCaY4tX4/q97hx46JdkA4J3yHV+73z 448/RnKE6ibuhrQCr4nw4homYdCqVavUv3//aDVEzNsyLCKVUnDxEERw5VpoS7/9U0895YkqksCU oXTmJho0aFBQewcvt3322Sf2GvFSs41DKlur3LRp08K8JZ/W2EybG8EayQec0Kp6Cxc7jFgyToKM NkHMb2gVR4SWVxUrU3FgTodOiGeeeSbOA2sleLdofCGrXqtUvKguY4TBOhps5XPFH/m+m9gTicEG n4/dcFx/trmLSKUSXGQemWvIFXzzwmbmwRNV9cUW2WbmKHi5FbLEmKx1t27dYjeK9sxSma9x9kR1 7NhxtTu6Vp7tIqnEQD4td7QmVdZkQmbxMBl8BOZnn30Wbb133HFHCE0qWLVr145KE/dteQiszLJa Aly+Hi1izGRNmDAhDDg4B5lFxF6Tsrr7lb1qVGKZySJBUMi7Kdu1ifjiHjj00ENjTxgVbJIRJghF pMIFF0PLuHflesiRBeal7omqui81huSpTLEnq5CXF0EVwSuZSIIpgyipCjNdOGZizsD1W0jwxiwj s2BUaRAztFvTblgR1z1fk3sXAcgCce4/gkeexdzLzK6w1JmW4LJ2Elz1OYCAQ5Qy/4bIYtceXQ/M Y1HFsoVLyqJCTWKXNl+usbLa50XVC6t6Vt9wD3E/K75EFFwVAr3+2IHnerjxQicA8URVvWFlHJzo a8chiipVIXbv2MN37949Fp86eyFVrW2JlqLzzz8/bb755gWJrkxFlxmka6+9Npa6zpo1KzLxBIWI i7IUYHwuPieVY74G85WAmMHhDUOjm2++OUQO1Wm+N57Ja+L2lm/Vj69FwHr88cfH4uNRo0aFmEWI mnyR8jJzou39pptuSnvuuWdUq6harWnLK7PHvM9IFLBnDvFlu6uIgmutwuwCL9RcDytsWAnaPVFV B1ooeKkMGDAgllYX0h/PxzZp0iSCPLL8vpCkKouuSy+9NOyoS5Mtp7LDYD97qQgAH3vssWidIyAk UcV9RgUKB1cy5winTMsfSQoCOv4eMq12/B3/D1HF/cXnQlhRterVq1cIK0wumMGiIo3wwbioPKtY mUoW9z6mGgcffHC65JJLwnADJ9OFCxeG2PRZIGsLhBf7vLjvaA9E/K9Ju2HGAIxEIntFb7zxxqh6 LViwICrIVmlFFFzlDsOr9P/nepCxEJkea09U1ahqEcg9/vjjIaKxzs03UOP8E2yxrJIWQowxPKZS 1WFP17333hsLWHEnLG3Fh1UIPAt32223qH7h1Dlw4MCwumaP3ZgxY9KLL76YJk+eHL8+++yzsVCe ZcJUhvgzAR73Ft/P5ZdfHk5trVu3Dnt27j3MLcjGl9f81ao/E+Yi/EwIO0RW586dY+6FObjMPJbX kFQktKxi+87CY95N7Ior7X288ruOa5/WRWaTMc0h6bF48WKNNkQUXOUHDxl2MeV6wZPhxXLZE1X5 Z7XImGPFzIukkKoWLzD+z+233x527y4ilWLLluPed+yxx8Yc0pqKmYwA43OR1IAdd9wx7iFWLdAK hfMaf0crExU2RA1/j2U6XQOYepR31SpboMnXxaEUoce8DC2LtFnhLEi2332LUhkTiVSFeTcNHz48 EhV0YXAPrum9zLsPY7D9998/Zr1IVuL2ydez6iWi4CrTthvmE9jcnuuBRLBA24snqvJCkDR+/PiY xWPwP99ALtPbjpUusyouMZZihRkpEkc46hGsFbLouyrDPc7M1+677546dOgQjrRU3KhiLVq0KJ4d JGu876UqtAlzvdIqjOMuVWaE0ppYyq86t0hihH1+tDJSoSY+ImGj0YaIgmuNM0cMQfMyzvUgotWF j/FEVc7MHy1TzGphqUubRL4ZPz62TZs2aciQIWnu3Lkxi2LQJcUMGWvuF9r7unTpEtWmNW1PqowC C4e3XXfdNR122GGRhOH5MHHixKgQMHuG+PRel6oMrX+0z7PKIeNsiGAqiyowzwTMdmhfZN6LJMWI ESMiDrICLKLgKnXGCBc6skS5HkCU23moeaIqFzgQ0iZ15plnRktTIa5lZLyparFXi4Fhs3dSnbLk CA6MIJi1Ipgi4VRVhRdGAAgsTAVIoBB8Dh48OIyOSKQQlDIH4zyWFGsShSTC1KlTU9++faNbB7FU Fi6emb1eGcfOZs2apf79+0d1mPev95SIgqug4OOTTz6JIfCSdtMgyjxRlWdWa/bs2WFZXWiGnpcQ cyS33XZbZLvtUZfqLLy4lwicCKCoAuGGlu/C5IqC1ifueToPeG7jbEg7MBUsrORJoJSHfb1IZRde XPskGbgfMKXB4GZNLeVXfX+u3HbIexQXTwSf71IRBddqgw7sw/fdd9+cDxkctDBj8ERVfPsgwSE7 0Vq2bFmQ0MpYPjPD8fbbb/tyEMkCKzKwQsdcA9MLdgBx3xC0lbdr4Mr3KqKKyhWuhRhsMEfbvHnz sGrHUQ1HRJzbli5d6r0skmNmc8aMGenWW2+Nqhf3Ee/MsryPEWBU03gfX3/99fFuZjk5Dp8kPewc EVFw/SmIJwBniDzXQ2W77bbTpbASDArPnDkzXASpUBGMFbJLCGMMlsB+9NFHZr1FVpMp/+6772Je 4+GHH45Mebt27cJxkPZq2vcI3LgHC7Vv52MzbUp8DkDQ4bbG56VqRfac3Xlk0DH4IFuP1TxJL+Ys PUcihc16ff755zG3ed5558VsI4kU3otlKb64p7mHaU+mzZ+2Xp4h3LeZnX0mR0SqueDCgZCBU2e4 KqfYYgbj0UcfjeoUL4p8XxK8ANixw/9j4Jesm8dUpLDnIyKHgI15SfZtXXfddbEP6JhjjondVQRw rM5goSqVqIzte61atcI2noQVIoqPIxijm4BZK3Yf8nnYfdW9e/doDcTy+tVXX01z5syJ+5X1DCZI RMruXcouPBKXHTt2jLiHJEchCcx8EyuILz4/zwmSnezeI3GCwyLuoHSruH5FpJq1FFICZyloSRUu Fx+vfWhJYM7q5ptvTg0bNixoCJg5FPYBsZMLW1vaKzymImsuwMhU43RI5ppk1dixY9PQoUMjo01i g51Wd9xxR7rxxhtTnz590rBhw+JjnnvuuQj2GO7nnvzqq68iAGQVA8EXws4MuEj5xzzca8yuM3/F vUoFm4QI7YHlsRuPdzfJ0n322SeEHgIMgw+SOCRXeA4wf0Y1zgSLSBELLoZMGRbP9bDAGpVWNE/U 2mtp+vLLL2MHSKdOnSJbXshAPY6FJ5xwQvSTu1dLpPxFGOYbkDGqIMFBAIU4y+y48j4UqXziix1b JE5o3b3lllvCiIYW/LJYqlyS8yEVsMaNG8e86KWXXpruuuuueOczm4n5De9u1zdIZbtfeN9lfqUo wHsuY9REwqAqGDb9rSK/OIPiZF1yPSBol2HOywuu/C9mHrITJkyIFiMexoUYY9AWQQsDLw1eIO4L ERERyS/RSaWZWGfkyJExu9mqVatIeJaFxXxJ1S/McUiU0nqMwQetxpdddlkaOHBgVMaZoV+8eHFU 5hBhVsKlPONQri9WiVB5pZODe4JqMBVZEvnPP/98dHLcf//90YFFzImZE10etM6OHj06vfDCC1HM Iemo4FqJBQsWlCi4yMTQEuPFWL6DvVQRsZmlFZA9WYVk1/h42iKefPLJGPjXHUlERKTwgBNRg8Ch 2nTfffels88+OypfJEExuSnvtQ8YemA/z3wZXxMR1q1bt2hTJkYYNWpUODASECMSSa76zpdCujKo RFHdpbUdQzb2NiKSEFI49V5zzTXprLPOSscff3xq0aJFJPNpuyUpwCwyYy7MLdOGC1yrFGfwDWCV FO7m+Acw1oJ5DFUwBdf/wkB4SYKL7AsZHy/U8rnwmQfh+HIOWK5Y6N4QLnRmRdjNZVVLRESkbKpe BIoEpcxasSi9Z8+eUfliJqs8K1+rVsEyTqYEt8zV77fffuFkes4558TydhxVqUIQPJN0pbJAItfz WH1jS6pUVKhIHFAlnT59elSpBg0aFGsMmCWkpfXAAw8MYY+Iop2WOJRrDS8AxD9JgELba/l4uq6o EJMwoPJFrFsZWg0rVHBhWUr2JNcB5YDffffd9hKXQ1WL1r9zzz03MgOF2tTSbohLGg9aslyeHxER kfKpfPHOpiqA4cbjjz8eQSsW8KzVWdsL0zOVsMxaCYQYLql77713VBawwKfNiwD7tddeiyoDSVmC cM9ncVRhSbDzK/Ef7XtUPdmri8CiStW1a9cQO+yUZJ0Qi8ARUzjobrLJJnHNIopKI6gKXZnQoEGD MIqhKlvRsWqFCy5Kh7kOOCcEK2SzJWVzo2AFy9zcTTfdFA9qHpqFZA0QWlhL0ztLG6LnRUREZO3O ufDuRcB8+OGHkfik0nTEEUdEUMt7mspUobv6ympxOl+X74HWRNZT0AlDBeOMM86IYJzvl4rd/Pnz o4JH9YGqGPEJPxc/X8YgwWRuxVxbtP0tW7Ysxn5wE2c9E063zPZl2v04nwhs2vxo52NfJBVQRHjm 2luZtZkUWPW6pNpFSyw/U7UVXPQqc9JKqqRQ4bJHeM3Ku7QmYAdNaZWHcqEZMYQvNxRZi2nTpsXN 6LEVERGpHC2IJLAxviKwPO6449JRRx0V1QWqCmW9bHlNKg58L7RFMpvTrFmz1Lp163TxxRdHFYLK GGYdVErowiFuwTmZn41gGZFJdSUjzhRkhQkqnGs5flRLqU7RAsrxRVhRqWKWinPAzB5to8z1I5YR 8pml3RV9DZUWZsC4tiqyUFChgmvp0qXpqquuyrn8j7/nxHOReMMUfnMhtOj/Zmkqg7c8eAt56PKx mGJg3c8ALz25il8REZHKOzKAQKFyxOzMgAEDoiJBVwsjBJVJgK0ca1AVoU0R10RWAjHbw4wP4pEl 7bgn0l1DLIKNPeKACh8/Z0aI8StxD+1uJIYRZsUes2QqgYhufl6Ow6piCrt/KlWTJk0Khz9aUlkJ wEgPM/xHHnlkGFQwR5WZnaqqwqqkeUTacCn0VEvBxY1BBYuezlzZkB49ergVvcCbjxuOzNCQIUPi QUtJv9AbiGOP4wtzXpSTrWqJiIhULXh3kyx95ZVXop3vhhtuiH2ZVJhoAaPtj/a/yibCsgXMfI8k gam40MKGicgFF1wQovKhhx6KeJK2t0ceeSSNGTMm3JOnTJkSs2+MUyxcuDBgnidj7pFpocu0M1aW OG7lvVPY8hPXAZU+WjH5mZiNe+edd8KY4tVXXw2nv6FDh4aZGQIVoXrqqafG+WbuHrc/TClKa0hR 1WGei+NULQUXFw+uJVwAuYL+iy66SAe8AtoHuRGxbuUG42FaqPMgNyH9rocffnjsNsBJ0qqWiIhI cYwYUPGg/RCRcvvtt0dwTgsZQTlCjDYyWsgKjR8qqk2RGHLLLbeM6h1krMKp2NAWh+jAVZGxCGDX GSMWjz32WHr00UdDpLDDidkyzB+YUaciBAgbqiLEoRnhQwWN31NRo5pEtxbw93RkIeYyS3khYzSR qTwhmvg9rX1AlY6ZNip2mIwwuoFARiziAEksRmWK6h4z+IhMztcxxxwTorNNmzZx3vh5qRBSxKBD rDLMUJWlWQvO5ZxrzjG/IrwpDMBOO+0UP3tJDp4cF855tRRcVK6effbZuEhyHWAuqEWLFvmwXM1D lJuZJXFUBMli5GrTXF37IA+nW2+9NW56HigeXxERkeLrhqGqQ+zw/fffh7CgBRHRQcses2BdunSJ gJ72PhK4OBIyA17VWs4IwomJEGf8np+B4JwgnWCdGXXiUEQLe0WxLGcMg8TziSeemLp37x5VNCpo d955Z1TR7rrrrmhxvPbaa9OVV14Z4zGIOBLeiFjiKExCKCrw8XfccUeMyBCjXX311dHW16tXr6g4 IqBYOs3cHce7efPmqWnTpumggw4KozL2TvH9AkIDf4Niq1Dx83COgNZSBD9VTNwvSQRwTjh2LDvm 2uRXBChCGdGMeyfHnes019fg85JkqJaCi0wAzidYR+YSAVx0H3/8sQ/IHA9Msir05XJz04db6OLi zKwctp08NPhcPHytaomIiFSvmIJ3P7EZFRjmf2hZe/755yOwRTggFkiE405HFYmWRCoPxTL3gyBD mGUqQ/yenw+xQ0WFDiAqaPwZUUDMReUkszAakcAxQZxyfIC/5/8hlnDx42P5fYa1ZZNeWURVxkWT Y4dAQtC3b98+hCddbbiTI25pCaUF8M033ww/AiqBmcpgZvF2pi2Ua5biDJ4DJQkuRm2qpeCiX5b5 ILIKuQQX1RoqNz4M/wwlavp2WYZIBoQbvFAHGY4v/4/SNL2/tCNq9S4iIiIru9sRc9AmR0scs0ME wk8//XQaMWJE6tevX1TDcEHeY489omKEqKgKLYlSPsIq09rH7xE6VOmo4GHWwa42qlU4InINTZw4 Mdo4EUyIqiVLlkS7Zsb0JF83Sq5PKmG5vi9EMPvhqqXgAqpXKNtcBwj1ixuND77/qwpyYVLOXpOt 82QZsIzlQYkdKA9TLVZFRERkdSIs44pH7EBwjBEFs2EkyGlLRIgRXDNftN9++4UQY/aGqkZlN+iQ wsRVZgE2VT8KAGeffXbshjv99NPD8p94FUt24n3EFKKd7qzM/jXi2rKIPxFctGbm+l65FmmdrbaC C1OGTp065bz5KLdSWqws7jEVOafFA42HGHsrOC6lEVocZ5xaaB+cOnVqXKAKLRERESmLlsSVlzNT tcAlkaoYrYljx46NmO78888PMwuqHljW169fP1rvMjNilWVxbnVl1ePPOaFiSbWKFkpm3phzo1JF mx6Fkddeey0KApl2P37NmIeUlahanSMnQi9bZZVrC/fKinTcrnDBxc3IjZdLPKCccZSprk6FPLi4 aLmY2UdBdqg0N09meTHtg5MnT3a3mYiIiFRYmyLBL/M4WLVT/WBMAgMEXBOpjjArdthhh6X9998/ ZqNwIiTZTLsisSHxEPNVVMyIIYtxf1RZCqhMq1/mV+JCjh0iiuOIkKJKxSgPif2TTjopVgvheo2w 6t+/f5iC0JaHoyJui5VpATViH1dHjDYy1wI/J51gF154Yewlq8jvtcIFF2VFnFpy7eLiQqA3mI+r jkKLYcFrrrkmsgmlyfJwM3EDHX300WnkyJHRH+sDX0RERCojtJlRHcPAi6Q8Yox5f9wThw0bFm50 2KNj4kF8hJMgAiGzWwxzC+KeTAtjRqRRPVtZnFX16lnm+8/sKMO9EDICKmOdnjGmwPUQx79mzZpF ex1Cig4zXBgxQ2HEBOdw2kI57sSgiCqgdbQqmKnxPeMkmVn0jfM2bpLz5s2r8E65ChdcZDhQzLms HCkNcmFQpqwurYNc3NizcvFzc/CQKPQm5OZjSBHnQi6+mTNnukBaREREqnR1jFgmY6jA+hpmgmhb JG5izxLW37S5YR3O+ATmYlRozjrrrDBVaNmyZTrwwAPDBRuRhj088RJzSAg0xBmihQpQRsAQi65c GVq5mlaoaFu5TW/lz7kyGcHE98L3hHjE5IwqH0KiUaNG8b1TzcGZr2PHjtHBhIA67bTTYo4KG3oE KqZotPvR1ol4JZ5m7xf7xRC1tP1ldogVy/gNjttcC+wyI6auDFW4ChdcnGD6elHfuS5M/o0yYbE/ RMjoUNFiX0PGEKPQEjkfT0aDm48+aRb3MZjonJaIiIhUlzkyxBhiYuWlw7QvEhfNmDEjgnECc3Y4 PfDAA1EJYZ8WLY1nnHFGjHHQ2kiXVYcOHaK9kT1d/D0iBzMQ2h2pHO2zzz4hgDK/Yh6BMRmVFn4F jEP4dxLpLVq0iGIClTnm2Gjd4/MiCPm1W7duUXViJokqHp1gffv2jUQ8i5Bp68MpkhERfh4EJy1z iCjgZyX2q87+B1wLlSn2/VtlUKOYN1DizCUimD3iAivWuSN6YHFO4WfkZkYwlcZOlYwIN3rv3r0V WiIiIiJ5xKFUzBBnCDNGWNhBRhsaAg0hQ1WIuGrWrFnx92+99VaIHUC4URTA3pxfJ0yYEL9STMCd D9dG4M/8/RtvvBHJ9ffeey/m1uhAIgbk8+IaDYx/ZPZNkYzne0NAQmWam5IqJLiAiwy3mlwig+HI c889N8qExXYCuIkwxDjzzDNjKJRScmkMMVhCSFZm3LhxcZxcXCwiIiJSvhWUXBCHZfZIZf6sUFJw VSioeMqk9KfmapOjZDtt2rSiOfBUn/h5KBNTeqY6VZqN6PTy0rdLeZmMiIuLRUREREQUXH+Z43rm mWfSbrvtllNc0GaHJSXirKofdBa/DRo0KNxTGIQsdE6LuTaGKDHEYK8Aw48VuVtAREREREQqseAC +mIZSszVVkg1ByMJqkJVsV2O/mC2sCMszznnnFjyV+jiYoQW9vnMu7G5e86cOdHPa4laRERERETB VSIMBtJehzNfLsGBZWefPn3C4rEqCa3PP/88nAexIMXms1ChBVjD01b54IMPhhuNFu8iIiIiIgqu vKFqhcMLlpm5dhrQeoeF5uuvv17pZ5Ww4sSac8yYMWHRjtAqzVI79j+wo4yqGI42xerUKCIiIiKi 4Cpnvvjii9h3UJKBRMaxEGfDythaiBBkkRytjyzaY5leaTaZs7i4YcOGsQuC5W04D9o6KCIiIiKi 4FojsTJixIi0/fbblyhSqPhgoMFit8ogQhB+LNZjX8NLL72Urrvuumj/ow2wNM6DderUiX1cHAv2 P1jVEhERERFRcJUJH3/8cWzc3mCDDUpstWvcuHEIEuzVK1JosSCPJXZDhgxJF1xwQbRE1qxZs+Cq Fh+PY2HLli1j2zlL9RBxXqQiIiIiIgquMjWZYKfULrvsUqJooRK03377xYzU2hZdVOKoPLE5/Prr r09t2rSJqhutkKVpH2S+q0WLFlEZe/XVV8M2nhkwL1AREREREQVXmUPViPmnkqpcgIV8kyZN0n33 3RfOfeVppEFbH26D48aNi3ZGZqv23nvvcFUsjetg5vtHWF599dVpypQpMafl4mIREREREQVXubfq vf/++7F3a3UVI5wLqS6dcMIJ6dFHHw3RUhZmGggszC/4Pqi4DRgwIFodEUhbbLFFzGcVurB4ZaG1 ww47pK5du4aA43u2oiUiIiIiouBaayB4XnnllbTHHnvkNf9ENQyzDSpPtBnOnTs3/frrr3mZaiDQ fvzxx/TJJ5+kqVOnpvHjx8di4ZNOOinttddeadttt422P5wDS9MyuLLQqlu3bjr11FNDaC1atMh9 WiIiIiIiCq6K4Z///GcsDGbhcT5Ch49Zb731QhyxZBj7+BtvvDE98MADaezYsWnGjBnpww8/DCfB wYMHRysilatrrrkmHXfccdGeWK9evWgTpIJFq+CaCKyVvyfEIKYazH19/fXXOg+KiIiIiCi4Kh4M JBBF7KSiQlTayhL7u7baaqtUv379cANEBCGoStsWmM/XRLg1a9YsXXXVVSHyfvjhBy86EREREREF V+UCoTJq1Kh08MEHl7gUuTKAiEPQtW7dOt19991p1qxZacWKFS4tFhERERFRcFVefvrpp5itOvro o0u156o8oUpWo0aNtPXWW8cerZ49e6b33nvP+SwREREREQVX1flm2bc1ceLE1Llz53AmLG2LYVlB W2KdOnWibZDvidZH5sSoyJWFU6KIiIiIiCi41ipUjebMmRPteh07dkyNGzcO98C1IbAybojbbLNN Ouigg9Ipp5yS+vXrlyZPnpwWLFgQVTiFloiIiIiIVFnBBcxDUUWaPXt2uA9iBV8eFS9aBTHboIq1 2267pXbt2sVC5uHDh4d9PNbzVrNERERERKSoBNfK/P7777E/a/To0enMM8+MvV2YVmBeUYiw4uOZ w2I+rEGDBqlt27apS5cuqU+fPmHYMWHChDRz5sy0ePHiMMFQZImIiIiISNELrkzFCxH0xRdfpDfe eCONGDEiXX311emss85KJ554YurQoUM64ogjYonxoYcemo455pioVtGSyL9TtbruuutiBuuhhx4K cTVv3rwQV1SwWKDM3iydBkVEREREpNoJrpWFF5Un5rx++eWXtHz58rR06dIQTl9++WX6+OOP01df fZW++eabtGjRovTtt9/Gni9mr/h4hBXLlhVXIiIiIiKi4BIREREREVFwiYiIiIiIKLhERERERERE wSUiIiIiIqLgEhERERERUXCJiIiIiIiIgktERERERETBJSIiIiIiouASERERERERBZeIiIiIiIiC S0RERERERMElIiIiIiIiCi4REREREREFl4iIiIiISPXm/wFSErNSDXsBIAAAAABJRU5ErkJggg== "
id="image1043"
x="-298.96762"
y="-8.7064028"
transform="matrix(-0.74414597,-0.66801704,0.79460447,-0.60712744,0,0)" />
</g>
<g
inkscape:label="Layer 1"
inkscape:groupmode="layer"
id="layer1">
<path
style="fill:url(#meshgradient1462);fill-opacity:1;stroke:none;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 5.2482498,182.29103 C 69.583346,183.56401 82.485045,73.027846 116.79166,71.985107 c -2.75128,46.856053 -1.50208,99.465793 -1.67259,110.162433 -22.212238,0.008 -97.946143,0.74423 -110.1265101,0.74107"
id="path833-9"
sodipodi:nodetypes="cccc" />
<path
style="fill:none;stroke:url(#linearGradient1300);stroke-width:2.465;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;stroke-miterlimit:4;stroke-dasharray:none;stroke-dashoffset:0;filter:url(#filter1446)"
d="M 5.2482498,182.29103 C 69.583346,183.56401 82.485045,73.027848 116.79166,71.985109 c 15.58537,-0.473712 17.06758,15.702599 24.12626,20.303528 7.418,4.83513 17.90821,15.208343 20.3857,21.080593 2.9573,7.00952 1.93957,9.23726 6.80781,14.57425 5.86121,6.42556 22.08685,8.39957 26.08132,16.74497 1.68244,3.51502 -10.84471,12.61503 -6.61248,16.06903 10.5626,8.62031 25.47481,0.19017 42.68128,9.1484"
id="path833"
sodipodi:nodetypes="cssssssc" />
<path
style="fill:none;stroke:url(#linearGradient1292);stroke-width:0.216963px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 5.2482498,182.29103 H 127.09763"
id="path1070" />
<path
style="fill:none;stroke:#00de00;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="m 52.717353,182.34768 -8.913188,-15.4381"
id="path1072" />
<path
style="fill:none;stroke:#00de00;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 65.820993,182.25579 51.989198,158.52573"
id="path1072-3"
sodipodi:nodetypes="cc" />
<path
style="fill:none;stroke:#00de00;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 79.807798,182.35283 58.923763,149.13446"
id="path1072-3-6"
sodipodi:nodetypes="cc" />
<path
style="fill:none;stroke:#00de00;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 91.471038,182.49528 66.056517,138.71713"
id="path1072-3-6-7"
sodipodi:nodetypes="cc" />
<path
style="fill:none;stroke:#00de00;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 100.36066,182.21658 71.500532,130.07008"
id="path1072-3-6-7-5"
sodipodi:nodetypes="cc" />
<path
style="fill:#00ff00;stroke:url(#linearGradient1284);stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 111.6461,182.10922 76.686485,120.44344"
id="path1072-3-6-7-5-3"
sodipodi:nodetypes="cc" />
<path
style="fill:none;stroke:#00de00;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 42.089874,182.33631 36.40449,172.98324"
id="path1072-5"
sodipodi:nodetypes="cc" />
<path
style="fill:none;stroke:#00de00;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="m 33.057288,182.3678 -3.569299,-5.93946"
id="path1072-5-6"
sodipodi:nodetypes="cc" />
<path
style="fill:none;stroke:#00dd00;stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="m 25.794471,182.36212 -2.156562,-3.41675"
id="path1072-5-6-2"
sodipodi:nodetypes="cc" />
<path
style="fill:#00ff00;stroke:url(#linearGradient1329);stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 118.5197,169.08809 83.560088,107.42231"
id="path1072-3-6-7-5-3-7"
sodipodi:nodetypes="cc" />
<path
style="fill:url(#meshgradient1448);stroke:url(#linearGradient1359);stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1;fill-opacity:1"
d="M 124.45098,159.08185 89.491366,97.416068"
id="path1072-3-6-7-5-3-7-3"
sodipodi:nodetypes="cc" />
<path
style="fill:#00ff00;stroke:url(#linearGradient1389);stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 120.54988,123.11869 96.329975,86.26141"
id="path1072-3-6-7-5-3-7-3-6"
sodipodi:nodetypes="cc" />
<path
style="fill:#00ff00;stroke:url(#linearGradient1419);stroke-width:0.264583px;stroke-linecap:butt;stroke-linejoin:miter;stroke-opacity:1"
d="M 121.94375,106.45794 104.56757,76.938956"
id="path1072-3-6-7-5-3-7-3-6-1"
sodipodi:nodetypes="cc" />
</g>
<script
id="mesh_polyfill"
type="text/javascript">
!function(){const t=&quot;http://www.w3.org/2000/svg&quot;,e=&quot;http://www.w3.org/1999/xlink&quot;,s=&quot;http://www.w3.org/1999/xhtml&quot;,r=2;if(document.createElementNS(t,&quot;meshgradient&quot;).x)return;const n=(t,e,s,r)=&gt;{let n=new x(.5*(e.x+s.x),.5*(e.y+s.y)),o=new x(.5*(t.x+e.x),.5*(t.y+e.y)),i=new x(.5*(s.x+r.x),.5*(s.y+r.y)),a=new x(.5*(n.x+o.x),.5*(n.y+o.y)),h=new x(.5*(n.x+i.x),.5*(n.y+i.y)),l=new x(.5*(a.x+h.x),.5*(a.y+h.y));return[[t,o,a,l],[l,h,i,r]]},o=t=&gt;{let e=t[0].distSquared(t[1]),s=t[2].distSquared(t[3]),r=.25*t[0].distSquared(t[2]),n=.25*t[1].distSquared(t[3]),o=e&gt;s?e:s,i=r&gt;n?r:n;return 18*(o&gt;i?o:i)},i=(t,e)=&gt;Math.sqrt(t.distSquared(e)),a=(t,e)=&gt;t.scale(2/3).add(e.scale(1/3)),h=t=&gt;{let e,s,r,n,o,i,a,h=new g;return t.match(/(\w+\(\s*[^)]+\))+/g).forEach(t=&gt;{let l=t.match(/[\w.-]+/g),d=l.shift();switch(d){case&quot;translate&quot;:2===l.length?e=new g(1,0,0,1,l[0],l[1]):(console.error(&quot;mesh.js: translate does not have 2 arguments!&quot;),e=new g(1,0,0,1,0,0)),h=h.append(e);break;case&quot;scale&quot;:1===l.length?s=new g(l[0],0,0,l[0],0,0):2===l.length?s=new g(l[0],0,0,l[1],0,0):(console.error(&quot;mesh.js: scale does not have 1 or 2 arguments!&quot;),s=new g(1,0,0,1,0,0)),h=h.append(s);break;case&quot;rotate&quot;:if(3===l.length&amp;&amp;(e=new g(1,0,0,1,l[1],l[2]),h=h.append(e)),l[0]){r=l[0]*Math.PI/180;let t=Math.cos(r),e=Math.sin(r);Math.abs(t)&lt;1e-16&amp;&amp;(t=0),Math.abs(e)&lt;1e-16&amp;&amp;(e=0),a=new g(t,e,-e,t,0,0),h=h.append(a)}else console.error(&quot;math.js: No argument to rotate transform!&quot;);3===l.length&amp;&amp;(e=new g(1,0,0,1,-l[1],-l[2]),h=h.append(e));break;case&quot;skewX&quot;:l[0]?(r=l[0]*Math.PI/180,n=Math.tan(r),o=new g(1,0,n,1,0,0),h=h.append(o)):console.error(&quot;math.js: No argument to skewX transform!&quot;);break;case&quot;skewY&quot;:l[0]?(r=l[0]*Math.PI/180,n=Math.tan(r),i=new g(1,n,0,1,0,0),h=h.append(i)):console.error(&quot;math.js: No argument to skewY transform!&quot;);break;case&quot;matrix&quot;:6===l.length?h=h.append(new g(...l)):console.error(&quot;math.js: Incorrect number of arguments for matrix!&quot;);break;default:console.error(&quot;mesh.js: Unhandled transform type: &quot;+d)}}),h},l=t=&gt;{let e=[],s=t.split(/[ ,]+/);for(let t=0,r=s.length-1;t&lt;r;t+=2)e.push(new x(parseFloat(s[t]),parseFloat(s[t+1])));return e},d=(t,e)=&gt;{for(let s in e)t.setAttribute(s,e[s])},c=(t,e,s,r,n)=&gt;{let o,i,a=[0,0,0,0];for(let h=0;h&lt;3;++h)e[h]&lt;t[h]&amp;&amp;e[h]&lt;s[h]||t[h]&lt;e[h]&amp;&amp;s[h]&lt;e[h]?a[h]=0:(a[h]=.5*((e[h]-t[h])/r+(s[h]-e[h])/n),o=Math.abs(3*(e[h]-t[h])/r),i=Math.abs(3*(s[h]-e[h])/n),a[h]&gt;o?a[h]=o:a[h]&gt;i&amp;&amp;(a[h]=i));return a},u=[[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0],[-3,3,0,0,-2,-1,0,0,0,0,0,0,0,0,0,0],[2,-2,0,0,1,1,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0],[0,0,0,0,0,0,0,0,-3,3,0,0,-2,-1,0,0],[0,0,0,0,0,0,0,0,2,-2,0,0,1,1,0,0],[-3,0,3,0,0,0,0,0,-2,0,-1,0,0,0,0,0],[0,0,0,0,-3,0,3,0,0,0,0,0,-2,0,-1,0],[9,-9,-9,9,6,3,-6,-3,6,-6,3,-3,4,2,2,1],[-6,6,6,-6,-3,-3,3,3,-4,4,-2,2,-2,-2,-1,-1],[2,0,-2,0,0,0,0,0,1,0,1,0,0,0,0,0],[0,0,0,0,2,0,-2,0,0,0,0,0,1,0,1,0],[-6,6,6,-6,-4,-2,4,2,-3,3,-3,3,-2,-1,-2,-1],[4,-4,-4,4,2,2,-2,-2,2,-2,2,-2,1,1,1,1]],f=t=&gt;{let e=[];for(let s=0;s&lt;16;++s){e[s]=0;for(let r=0;r&lt;16;++r)e[s]+=u[s][r]*t[r]}return e},p=(t,e,s)=&gt;{const r=e*e,n=s*s,o=e*e*e,i=s*s*s;return t[0]+t[1]*e+t[2]*r+t[3]*o+t[4]*s+t[5]*s*e+t[6]*s*r+t[7]*s*o+t[8]*n+t[9]*n*e+t[10]*n*r+t[11]*n*o+t[12]*i+t[13]*i*e+t[14]*i*r+t[15]*i*o},y=t=&gt;{let e=[],s=[],r=[];for(let s=0;s&lt;4;++s)e[s]=[],e[s][0]=n(t[0][s],t[1][s],t[2][s],t[3][s]),e[s][1]=[],e[s][1].push(...n(...e[s][0][0])),e[s][1].push(...n(...e[s][0][1])),e[s][2]=[],e[s][2].push(...n(...e[s][1][0])),e[s][2].push(...n(...e[s][1][1])),e[s][2].push(...n(...e[s][1][2])),e[s][2].push(...n(...e[s][1][3]));for(let t=0;t&lt;8;++t){s[t]=[];for(let r=0;r&lt;4;++r)s[t][r]=[],s[t][r][0]=n(e[0][2][t][r],e[1][2][t][r],e[2][2][t][r],e[3][2][t][r]),s[t][r][1]=[],s[t][r][1].push(...n(...s[t][r][0][0])),s[t][r][1].push(...n(...s[t][r][0][1])),s[t][r][2]=[],s[t][r][2].push(...n(...s[t][r][1][0])),s[t][r][2].push(...n(...s[t][r][1][1])),s[t][r][2].push(...n(...s[t][r][1][2])),s[t][r][2].push(...n(...s[t][r][1][3]))}for(let t=0;t&lt;8;++t){r[t]=[];for(let e=0;e&lt;8;++e)r[t][e]=[],r[t][e][0]=s[t][0][2][e],r[t][e][1]=s[t][1][2][e],r[t][e][2]=s[t][2][2][e],r[t][e][3]=s[t][3][2][e]}return r};class x{constructor(t,e){this.x=t||0,this.y=e||0}toString(){return`(x=${this.x}, y=${this.y})`}clone(){return new x(this.x,this.y)}add(t){return new x(this.x+t.x,this.y+t.y)}scale(t){return void 0===t.x?new x(this.x*t,this.y*t):new x(this.x*t.x,this.y*t.y)}distSquared(t){let e=this.x-t.x,s=this.y-t.y;return e*e+s*s}transform(t){let e=this.x*t.a+this.y*t.c+t.e,s=this.x*t.b+this.y*t.d+t.f;return new x(e,s)}}class g{constructor(t,e,s,r,n,o){void 0===t?(this.a=1,this.b=0,this.c=0,this.d=1,this.e=0,this.f=0):(this.a=t,this.b=e,this.c=s,this.d=r,this.e=n,this.f=o)}toString(){return`affine: ${this.a} ${this.c} ${this.e} \n ${this.b} ${this.d} ${this.f}`}append(t){t instanceof g||console.error(&quot;mesh.js: argument to Affine.append is not affine!&quot;);let e=this.a*t.a+this.c*t.b,s=this.b*t.a+this.d*t.b,r=this.a*t.c+this.c*t.d,n=this.b*t.c+this.d*t.d,o=this.a*t.e+this.c*t.f+this.e,i=this.b*t.e+this.d*t.f+this.f;return new g(e,s,r,n,o,i)}}class w{constructor(t,e){this.nodes=t,this.colors=e}paintCurve(t,e){if(o(this.nodes)&gt;r){const s=n(...this.nodes);let r=[[],[]],o=[[],[]];for(let t=0;t&lt;4;++t)r[0][t]=this.colors[0][t],r[1][t]=(this.colors[0][t]+this.colors[1][t])/2,o[0][t]=r[1][t],o[1][t]=this.colors[1][t];let i=new w(s[0],r),a=new w(s[1],o);i.paintCurve(t,e),a.paintCurve(t,e)}else{let s=Math.round(this.nodes[0].x);if(s&gt;=0&amp;&amp;s&lt;e){let r=4*(~~this.nodes[0].y*e+s);t[r]=Math.round(this.colors[0][0]),t[r+1]=Math.round(this.colors[0][1]),t[r+2]=Math.round(this.colors[0][2]),t[r+3]=Math.round(this.colors[0][3])}}}}class m{constructor(t,e){this.nodes=t,this.colors=e}split(){let t=[[],[],[],[]],e=[[],[],[],[]],s=[[[],[]],[[],[]]],r=[[[],[]],[[],[]]];for(let s=0;s&lt;4;++s){const r=n(this.nodes[0][s],this.nodes[1][s],this.nodes[2][s],this.nodes[3][s]);t[0][s]=r[0][0],t[1][s]=r[0][1],t[2][s]=r[0][2],t[3][s]=r[0][3],e[0][s]=r[1][0],e[1][s]=r[1][1],e[2][s]=r[1][2],e[3][s]=r[1][3]}for(let t=0;t&lt;4;++t)s[0][0][t]=this.colors[0][0][t],s[0][1][t]=this.colors[0][1][t],s[1][0][t]=(this.colors[0][0][t]+this.colors[1][0][t])/2,s[1][1][t]=(this.colors[0][1][t]+this.colors[1][1][t])/2,r[0][0][t]=s[1][0][t],r[0][1][t]=s[1][1][t],r[1][0][t]=this.colors[1][0][t],r[1][1][t]=this.colors[1][1][t];return[new m(t,s),new m(e,r)]}paint(t,e){let s,n=!1;for(let t=0;t&lt;4;++t)if((s=o([this.nodes[0][t],this.nodes[1][t],this.nodes[2][t],this.nodes[3][t]]))&gt;r){n=!0;break}if(n){let s=this.split();s[0].paint(t,e),s[1].paint(t,e)}else{new w([...this.nodes[0]],[...this.colors[0]]).paintCurve(t,e)}}}class b{constructor(t){this.readMesh(t),this.type=t.getAttribute(&quot;type&quot;)||&quot;bilinear&quot;}readMesh(t){let e=[[]],s=[[]],r=Number(t.getAttribute(&quot;x&quot;)),n=Number(t.getAttribute(&quot;y&quot;));e[0][0]=new x(r,n);let o=t.children;for(let t=0,r=o.length;t&lt;r;++t){e[3*t+1]=[],e[3*t+2]=[],e[3*t+3]=[],s[t+1]=[];let r=o[t].children;for(let n=0,o=r.length;n&lt;o;++n){let o=r[n].children;for(let r=0,i=o.length;r&lt;i;++r){let i=r;0!==t&amp;&amp;++i;let h,d=o[r].getAttribute(&quot;path&quot;),c=&quot;l&quot;;null!=d&amp;&amp;(c=(h=d.match(/\s*([lLcC])\s*(.*)/))[1]);let u=l(h[2]);switch(c){case&quot;l&quot;:0===i?(e[3*t][3*n+3]=u[0].add(e[3*t][3*n]),e[3*t][3*n+1]=a(e[3*t][3*n],e[3*t][3*n+3]),e[3*t][3*n+2]=a(e[3*t][3*n+3],e[3*t][3*n])):1===i?(e[3*t+3][3*n+3]=u[0].add(e[3*t][3*n+3]),e[3*t+1][3*n+3]=a(e[3*t][3*n+3],e[3*t+3][3*n+3]),e[3*t+2][3*n+3]=a(e[3*t+3][3*n+3],e[3*t][3*n+3])):2===i?(0===n&amp;&amp;(e[3*t+3][3*n+0]=u[0].add(e[3*t+3][3*n+3])),e[3*t+3][3*n+1]=a(e[3*t+3][3*n],e[3*t+3][3*n+3]),e[3*t+3][3*n+2]=a(e[3*t+3][3*n+3],e[3*t+3][3*n])):(e[3*t+1][3*n]=a(e[3*t][3*n],e[3*t+3][3*n]),e[3*t+2][3*n]=a(e[3*t+3][3*n],e[3*t][3*n]));break;case&quot;L&quot;:0===i?(e[3*t][3*n+3]=u[0],e[3*t][3*n+1]=a(e[3*t][3*n],e[3*t][3*n+3]),e[3*t][3*n+2]=a(e[3*t][3*n+3],e[3*t][3*n])):1===i?(e[3*t+3][3*n+3]=u[0],e[3*t+1][3*n+3]=a(e[3*t][3*n+3],e[3*t+3][3*n+3]),e[3*t+2][3*n+3]=a(e[3*t+3][3*n+3],e[3*t][3*n+3])):2===i?(0===n&amp;&amp;(e[3*t+3][3*n+0]=u[0]),e[3*t+3][3*n+1]=a(e[3*t+3][3*n],e[3*t+3][3*n+3]),e[3*t+3][3*n+2]=a(e[3*t+3][3*n+3],e[3*t+3][3*n])):(e[3*t+1][3*n]=a(e[3*t][3*n],e[3*t+3][3*n]),e[3*t+2][3*n]=a(e[3*t+3][3*n],e[3*t][3*n]));break;case&quot;c&quot;:0===i?(e[3*t][3*n+1]=u[0].add(e[3*t][3*n]),e[3*t][3*n+2]=u[1].add(e[3*t][3*n]),e[3*t][3*n+3]=u[2].add(e[3*t][3*n])):1===i?(e[3*t+1][3*n+3]=u[0].add(e[3*t][3*n+3]),e[3*t+2][3*n+3]=u[1].add(e[3*t][3*n+3]),e[3*t+3][3*n+3]=u[2].add(e[3*t][3*n+3])):2===i?(e[3*t+3][3*n+2]=u[0].add(e[3*t+3][3*n+3]),e[3*t+3][3*n+1]=u[1].add(e[3*t+3][3*n+3]),0===n&amp;&amp;(e[3*t+3][3*n+0]=u[2].add(e[3*t+3][3*n+3]))):(e[3*t+2][3*n]=u[0].add(e[3*t+3][3*n]),e[3*t+1][3*n]=u[1].add(e[3*t+3][3*n]));break;case&quot;C&quot;:0===i?(e[3*t][3*n+1]=u[0],e[3*t][3*n+2]=u[1],e[3*t][3*n+3]=u[2]):1===i?(e[3*t+1][3*n+3]=u[0],e[3*t+2][3*n+3]=u[1],e[3*t+3][3*n+3]=u[2]):2===i?(e[3*t+3][3*n+2]=u[0],e[3*t+3][3*n+1]=u[1],0===n&amp;&amp;(e[3*t+3][3*n+0]=u[2])):(e[3*t+2][3*n]=u[0],e[3*t+1][3*n]=u[1]);break;default:console.error(&quot;mesh.js: &quot;+c+&quot; invalid path type.&quot;)}if(0===t&amp;&amp;0===n||r&gt;0){let e=window.getComputedStyle(o[r]).stopColor.match(/^rgb\s*\(\s*(\d+)\s*,\s*(\d+)\s*,\s*(\d+)\s*\)$/i),a=window.getComputedStyle(o[r]).stopOpacity,h=255;a&amp;&amp;(h=Math.floor(255*a)),e&amp;&amp;(0===i?(s[t][n]=[],s[t][n][0]=Math.floor(e[1]),s[t][n][1]=Math.floor(e[2]),s[t][n][2]=Math.floor(e[3]),s[t][n][3]=h):1===i?(s[t][n+1]=[],s[t][n+1][0]=Math.floor(e[1]),s[t][n+1][1]=Math.floor(e[2]),s[t][n+1][2]=Math.floor(e[3]),s[t][n+1][3]=h):2===i?(s[t+1][n+1]=[],s[t+1][n+1][0]=Math.floor(e[1]),s[t+1][n+1][1]=Math.floor(e[2]),s[t+1][n+1][2]=Math.floor(e[3]),s[t+1][n+1][3]=h):3===i&amp;&amp;(s[t+1][n]=[],s[t+1][n][0]=Math.floor(e[1]),s[t+1][n][1]=Math.floor(e[2]),s[t+1][n][2]=Math.floor(e[3]),s[t+1][n][3]=h))}}e[3*t+1][3*n+1]=new x,e[3*t+1][3*n+2]=new x,e[3*t+2][3*n+1]=new x,e[3*t+2][3*n+2]=new x,e[3*t+1][3*n+1].x=(-4*e[3*t][3*n].x+6*(e[3*t][3*n+1].x+e[3*t+1][3*n].x)+-2*(e[3*t][3*n+3].x+e[3*t+3][3*n].x)+3*(e[3*t+3][3*n+1].x+e[3*t+1][3*n+3].x)+-1*e[3*t+3][3*n+3].x)/9,e[3*t+1][3*n+2].x=(-4*e[3*t][3*n+3].x+6*(e[3*t][3*n+2].x+e[3*t+1][3*n+3].x)+-2*(e[3*t][3*n].x+e[3*t+3][3*n+3].x)+3*(e[3*t+3][3*n+2].x+e[3*t+1][3*n].x)+-1*e[3*t+3][3*n].x)/9,e[3*t+2][3*n+1].x=(-4*e[3*t+3][3*n].x+6*(e[3*t+3][3*n+1].x+e[3*t+2][3*n].x)+-2*(e[3*t+3][3*n+3].x+e[3*t][3*n].x)+3*(e[3*t][3*n+1].x+e[3*t+2][3*n+3].x)+-1*e[3*t][3*n+3].x)/9,e[3*t+2][3*n+2].x=(-4*e[3*t+3][3*n+3].x+6*(e[3*t+3][3*n+2].x+e[3*t+2][3*n+3].x)+-2*(e[3*t+3][3*n].x+e[3*t][3*n+3].x)+3*(e[3*t][3*n+2].x+e[3*t+2][3*n].x)+-1*e[3*t][3*n].x)/9,e[3*t+1][3*n+1].y=(-4*e[3*t][3*n].y+6*(e[3*t][3*n+1].y+e[3*t+1][3*n].y)+-2*(e[3*t][3*n+3].y+e[3*t+3][3*n].y)+3*(e[3*t+3][3*n+1].y+e[3*t+1][3*n+3].y)+-1*e[3*t+3][3*n+3].y)/9,e[3*t+1][3*n+2].y=(-4*e[3*t][3*n+3].y+6*(e[3*t][3*n+2].y+e[3*t+1][3*n+3].y)+-2*(e[3*t][3*n].y+e[3*t+3][3*n+3].y)+3*(e[3*t+3][3*n+2].y+e[3*t+1][3*n].y)+-1*e[3*t+3][3*n].y)/9,e[3*t+2][3*n+1].y=(-4*e[3*t+3][3*n].y+6*(e[3*t+3][3*n+1].y+e[3*t+2][3*n].y)+-2*(e[3*t+3][3*n+3].y+e[3*t][3*n].y)+3*(e[3*t][3*n+1].y+e[3*t+2][3*n+3].y)+-1*e[3*t][3*n+3].y)/9,e[3*t+2][3*n+2].y=(-4*e[3*t+3][3*n+3].y+6*(e[3*t+3][3*n+2].y+e[3*t+2][3*n+3].y)+-2*(e[3*t+3][3*n].y+e[3*t][3*n+3].y)+3*(e[3*t][3*n+2].y+e[3*t+2][3*n].y)+-1*e[3*t][3*n].y)/9}}this.nodes=e,this.colors=s}paintMesh(t,e){let s=(this.nodes.length-1)/3,r=(this.nodes[0].length-1)/3;if(&quot;bilinear&quot;===this.type||s&lt;2||r&lt;2){let n;for(let o=0;o&lt;s;++o)for(let s=0;s&lt;r;++s){let r=[];for(let t=3*o,e=3*o+4;t&lt;e;++t)r.push(this.nodes[t].slice(3*s,3*s+4));let i=[];i.push(this.colors[o].slice(s,s+2)),i.push(this.colors[o+1].slice(s,s+2)),(n=new m(r,i)).paint(t,e)}}else{let n,o,a,h,l,d,u;const x=s,g=r;s++,r++;let w=new Array(s);for(let t=0;t&lt;s;++t){w[t]=new Array(r);for(let e=0;e&lt;r;++e)w[t][e]=[],w[t][e][0]=this.nodes[3*t][3*e],w[t][e][1]=this.colors[t][e]}for(let t=0;t&lt;s;++t)for(let e=0;e&lt;r;++e)0!==t&amp;&amp;t!==x&amp;&amp;(n=i(w[t-1][e][0],w[t][e][0]),o=i(w[t+1][e][0],w[t][e][0]),w[t][e][2]=c(w[t-1][e][1],w[t][e][1],w[t+1][e][1],n,o)),0!==e&amp;&amp;e!==g&amp;&amp;(n=i(w[t][e-1][0],w[t][e][0]),o=i(w[t][e+1][0],w[t][e][0]),w[t][e][3]=c(w[t][e-1][1],w[t][e][1],w[t][e+1][1],n,o));for(let t=0;t&lt;r;++t){w[0][t][2]=[],w[x][t][2]=[];for(let e=0;e&lt;4;++e)n=i(w[1][t][0],w[0][t][0]),o=i(w[x][t][0],w[x-1][t][0]),w[0][t][2][e]=n&gt;0?2*(w[1][t][1][e]-w[0][t][1][e])/n-w[1][t][2][e]:0,w[x][t][2][e]=o&gt;0?2*(w[x][t][1][e]-w[x-1][t][1][e])/o-w[x-1][t][2][e]:0}for(let t=0;t&lt;s;++t){w[t][0][3]=[],w[t][g][3]=[];for(let e=0;e&lt;4;++e)n=i(w[t][1][0],w[t][0][0]),o=i(w[t][g][0],w[t][g-1][0]),w[t][0][3][e]=n&gt;0?2*(w[t][1][1][e]-w[t][0][1][e])/n-w[t][1][3][e]:0,w[t][g][3][e]=o&gt;0?2*(w[t][g][1][e]-w[t][g-1][1][e])/o-w[t][g-1][3][e]:0}for(let s=0;s&lt;x;++s)for(let r=0;r&lt;g;++r){let n=i(w[s][r][0],w[s+1][r][0]),o=i(w[s][r+1][0],w[s+1][r+1][0]),c=i(w[s][r][0],w[s][r+1][0]),x=i(w[s+1][r][0],w[s+1][r+1][0]),g=[[],[],[],[]];for(let t=0;t&lt;4;++t){(d=[])[0]=w[s][r][1][t],d[1]=w[s+1][r][1][t],d[2]=w[s][r+1][1][t],d[3]=w[s+1][r+1][1][t],d[4]=w[s][r][2][t]*n,d[5]=w[s+1][r][2][t]*n,d[6]=w[s][r+1][2][t]*o,d[7]=w[s+1][r+1][2][t]*o,d[8]=w[s][r][3][t]*c,d[9]=w[s+1][r][3][t]*x,d[10]=w[s][r+1][3][t]*c,d[11]=w[s+1][r+1][3][t]*x,d[12]=0,d[13]=0,d[14]=0,d[15]=0,u=f(d);for(let e=0;e&lt;9;++e){g[t][e]=[];for(let s=0;s&lt;9;++s)g[t][e][s]=p(u,e/8,s/8),g[t][e][s]&gt;255?g[t][e][s]=255:g[t][e][s]&lt;0&amp;&amp;(g[t][e][s]=0)}}h=[];for(let t=3*s,e=3*s+4;t&lt;e;++t)h.push(this.nodes[t].slice(3*r,3*r+4));l=y(h);for(let s=0;s&lt;8;++s)for(let r=0;r&lt;8;++r)(a=new m(l[s][r],[[[g[0][s][r],g[1][s][r],g[2][s][r],g[3][s][r]],[g[0][s][r+1],g[1][s][r+1],g[2][s][r+1],g[3][s][r+1]]],[[g[0][s+1][r],g[1][s+1][r],g[2][s+1][r],g[3][s+1][r]],[g[0][s+1][r+1],g[1][s+1][r+1],g[2][s+1][r+1],g[3][s+1][r+1]]]])).paint(t,e)}}}transform(t){if(t instanceof x)for(let e=0,s=this.nodes.length;e&lt;s;++e)for(let s=0,r=this.nodes[0].length;s&lt;r;++s)this.nodes[e][s]=this.nodes[e][s].add(t);else if(t instanceof g)for(let e=0,s=this.nodes.length;e&lt;s;++e)for(let s=0,r=this.nodes[0].length;s&lt;r;++s)this.nodes[e][s]=this.nodes[e][s].transform(t)}scale(t){for(let e=0,s=this.nodes.length;e&lt;s;++e)for(let s=0,r=this.nodes[0].length;s&lt;r;++s)this.nodes[e][s]=this.nodes[e][s].scale(t)}}document.querySelectorAll(&quot;rect,circle,ellipse,path,text&quot;).forEach((r,n)=&gt;{let o=r.getAttribute(&quot;id&quot;);o||(o=&quot;patchjs_shape&quot;+n,r.setAttribute(&quot;id&quot;,o));const i=r.style.fill.match(/^url\(\s*&quot;?\s*#([^\s&quot;]+)&quot;?\s*\)/),a=r.style.stroke.match(/^url\(\s*&quot;?\s*#([^\s&quot;]+)&quot;?\s*\)/);if(i&amp;&amp;i[1]){const a=document.getElementById(i[1]);if(a&amp;&amp;&quot;meshgradient&quot;===a.nodeName){const i=r.getBBox();let l=document.createElementNS(s,&quot;canvas&quot;);d(l,{width:i.width,height:i.height});const c=l.getContext(&quot;2d&quot;);let u=c.createImageData(i.width,i.height);const f=new b(a);&quot;objectBoundingBox&quot;===a.getAttribute(&quot;gradientUnits&quot;)&amp;&amp;f.scale(new x(i.width,i.height));const p=a.getAttribute(&quot;gradientTransform&quot;);null!=p&amp;&amp;f.transform(h(p)),&quot;userSpaceOnUse&quot;===a.getAttribute(&quot;gradientUnits&quot;)&amp;&amp;f.transform(new x(-i.x,-i.y)),f.paintMesh(u.data,l.width),c.putImageData(u,0,0);const y=document.createElementNS(t,&quot;image&quot;);d(y,{width:i.width,height:i.height,x:i.x,y:i.y});let g=l.toDataURL();y.setAttributeNS(e,&quot;xlink:href&quot;,g),r.parentNode.insertBefore(y,r),r.style.fill=&quot;none&quot;;const w=document.createElementNS(t,&quot;use&quot;);w.setAttributeNS(e,&quot;xlink:href&quot;,&quot;#&quot;+o);const m=&quot;patchjs_clip&quot;+n,M=document.createElementNS(t,&quot;clipPath&quot;);M.setAttribute(&quot;id&quot;,m),M.appendChild(w),r.parentElement.insertBefore(M,r),y.setAttribute(&quot;clip-path&quot;,&quot;url(#&quot;+m+&quot;)&quot;),u=null,l=null,g=null}}if(a&amp;&amp;a[1]){const o=document.getElementById(a[1]);if(o&amp;&amp;&quot;meshgradient&quot;===o.nodeName){const i=parseFloat(r.style.strokeWidth.slice(0,-2))*(parseFloat(r.style.strokeMiterlimit)||parseFloat(r.getAttribute(&quot;stroke-miterlimit&quot;))||1),a=r.getBBox(),l=Math.trunc(a.width+i),c=Math.trunc(a.height+i),u=Math.trunc(a.x-i/2),f=Math.trunc(a.y-i/2);let p=document.createElementNS(s,&quot;canvas&quot;);d(p,{width:l,height:c});const y=p.getContext(&quot;2d&quot;);let g=y.createImageData(l,c);const w=new b(o);&quot;objectBoundingBox&quot;===o.getAttribute(&quot;gradientUnits&quot;)&amp;&amp;w.scale(new x(l,c));const m=o.getAttribute(&quot;gradientTransform&quot;);null!=m&amp;&amp;w.transform(h(m)),&quot;userSpaceOnUse&quot;===o.getAttribute(&quot;gradientUnits&quot;)&amp;&amp;w.transform(new x(-u,-f)),w.paintMesh(g.data,p.width),y.putImageData(g,0,0);const M=document.createElementNS(t,&quot;image&quot;);d(M,{width:l,height:c,x:0,y:0});let S=p.toDataURL();M.setAttributeNS(e,&quot;xlink:href&quot;,S);const k=&quot;pattern_clip&quot;+n,A=document.createElementNS(t,&quot;pattern&quot;);d(A,{id:k,patternUnits:&quot;userSpaceOnUse&quot;,width:l,height:c,x:u,y:f}),A.appendChild(M),o.parentNode.appendChild(A),r.style.stroke=&quot;url(#&quot;+k+&quot;)&quot;,g=null,p=null,S=null}}})}();
</script>
</svg>