20260912 20151200 1.0 FALSE ZCriticos_peat_LOC_2225 002 0.000 Projected MAGNA-SIRGAS_2018 Linear Unit: Meter (1.000000) <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.7.0'><WKT>PROJCS[&quot;MAGNA-SIRGAS_2018_Colombia_Bogota_zone&quot;,GEOGCS[&quot;MAGNA-SIRGAS_2018&quot;,DATUM[&quot;Marco_Geocentrico_Nacional_de_Referencia_2018&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,1000000.0],PARAMETER[&quot;False_Northing&quot;,1000000.0],PARAMETER[&quot;Central_Meridian&quot;,-74.07750776944444],PARAMETER[&quot;Scale_Factor&quot;,1.0],PARAMETER[&quot;Latitude_Of_Origin&quot;,4.596203222222221],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,11116]]</WKT><XOrigin>-4623200</XOrigin><YOrigin>-9510300</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>11116</WKID><LatestWKID>11116</LatestWKID></ProjectedCoordinateSystem> MAGNA-SIRGAS_2018_Colombia_Bogota_zone 20260908 10390100 20260912 20140000 150000000 5000 ItemDescription Esri ArcGIS 13.7.0.1901 ZonasCriticasPeatones_Local_2225 Identificación de las zonas en la red vial intermedia y local donde los peatones enfrentan un mayor riesgo de sufrir siniestros viales. Para ello, se analizan los registros de siniestralidad del Sistema de Información Geográfica de Accidentes de Tránsito (SIGAT) correspondientes al periodo 2022-2025. A partir de esta información, se identifican las zonas de la red vial intermedia y local de Bogotá con mayor concentración de peatones fallecidos y lesionados, lo que permite priorizar acciones de infraestructura, gestión de velocidad y seguridad vial en los lugares donde más se necesitan. Estas zonas están delimitadas según las ZAT (Zonas de Análisis de Transporte) que se definieron en la Encuesta de Movilidad 2023. <div style='text-align:Left;'><p><span>Zonas críticas en vías no arteriales por siniestralidad de peatones: Son zonas dentro de la red vial intermedia y local que presentan una alta concentración de peatones fallecidos y lesionados por siniestros viales. Corresponden a áreas que registran niveles elevados de siniestralidad y, por tanto, requieren atención prioritaria para mejorar la seguridad vial.</span></p></div> Oficina de Seguridad Vial - Secretaría Distrital de Movilidad Siniestros Accidentes Vías intermedias Vías locales Peatones Ubicaciones críticas Zonas Áreas File Geodatabase Feature Class 0.000 dataset EPSG 10.082(13.2.0) 0 Simple FALSE 0 TRUE TRUE ZCriticos_peat_LOC_2225 Feature Class 0 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. ID ID String 255 0 0 Area_Ha Area_Ha Double 8 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. 20260912 iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzt3flTm9eaJ/AvaN83JCEECCQ2CQwGG8dxcp1OOpW+PamerjtV XdX/5PwyVTPdVT3TfW/ixPEWg9kMEqvQggBJICS0a+o5BAwGbMxieMXzqVLZlkC82OZb5zzvc86R 12q1GhhjTALk130BjDF2VhxYjDHJ4MBijEkGBxZjTDI4sBhjksGBxRiTDA4sxphkcGAxxiSDA4sx JhkcWIwxyeDAYoxJBgcWY0wyOLAYY5LBgcUYkwwOLMaYZHBgMcYkgwOLMSYZHFjsyhQKBcjlcshk suu+FFYnOLDYhVUqFRSLRTQ0NIiAogc998svv8Dv98Plcl33JbI6wYHFLoSOBBgbe4WtrRVUKlUU Co14+PAb5HI5JJPLKBS8132JrI5wYLEzhRIFUGNjI/L5PLLZHVSrFQAN0Gp12NnZxJ/+1IfGxgZk MjlMTT0Tz/t89uu+dFZnOLDYqcrlMuLxGJaX51GtZiGTUT2qCrtdD4VCJkZUi4tZKBQlNDTsfY7B oMXISJuYEm5uNmJ7O3Pd3warIxxY7FTT0xPY2lrA8LAXGs3Jo6W2Nsux55RK+m8lh15PgceBxS4P BxY7lclkpjET1GrFuT5fo1Fia2sN1WpVTCcZuygOLHaqnZ0MdnZyyGR2RejodBoxFTwrlUoBjaZR tDdoNJorvVZ2O3BgsVN5vd2IxfSYm0sgFougtVWNgYFWKBQf/29D9S0q1qvVwO7uLgcWuxQcWOxU FDJer1c8aJRE7QvpdA52u/GDn1et1rC4uIF8vgHpdAH5/O6h16pIpZJQqVTiLmM4vAKLxQKr1QaF QiF6ud5HX5s+jz6Hp5a3GwcWOxMKi85OH8LhMVgsesjlpwdHLlfA1pYcfv9ddHbWoNVqD17LZrN4 8eIn6HQKZDIl9PXZRJ1rfr4AtdoKv79ftEQc9vTpLygWUzCZXBgdfcihdYtxYLEzczicqFaH8PTp aygUNbjderS0WCCTNR6ZCs7MxOH3fw2DwXDsPWiZDtXC/H4btFollEoaVQE+Xw3xeBovX/6KgYER 6PUGMeKi9ojd3SS+/bYHkUgSv//+DIHAIDQa7YmjMVbfOLDYJ2lubobT+Wdsb29jZuaNGB11dFig 16vF60tLCSiVThiNJ08b1Wo1Ojr6kUxuIRLZhFxegsGghsWig9NpEh9Do7hKhcJMj3IZsFgUotjv dlMLRQpTU8/hdvfA5Wrh0LplOLDYJ6OQMJlMGB19hEQijvX1BRFYhUIJ6XQN9+4NnxokNJ1ra2sX BXlaf7i7m0UsFsXc3BJUqiKGhjxwOEwol2l9YgXr69vw+doQCsWwsJAUzavF4i42N3NixEfrFtnt wf/a7NxoeqfV6hGLlVAqlZHPl1AuN5xpdwYKNKqL0cNstqKvrx/hcBgTEyFYrQ1oazNDr1fBYHCI aebWlgzffvvfxQiNgo6Cj8Pq9uF/cXYher0eJlMrXr+eQ2+vA7Va+VyNohRg7e3tYmeHtbUY3r6d h8kEeDxNf+wC0YBSqSQCS6lUXtn3w242Dix2ITSaon4tlUqD6enfxfrDdDoNq9V6rvejQntrazua m1swOfmbmGZqtSox6nry5P/hhx/+iffXusU4sNiF0QiotbUNCoUSweCs2NnhvIG1j6Z7KpUJ4XAC PT1OsTyI7jpyWN1uHFjs0jidTjgcjkt7P6+3B2NjaUxOhmGz6UULBBXr+c7g7cWBxS7VZYYJFeQf PPgaoVAQuVwYmUwSm5ubaGpqurSvwaSFA4vd+ACkkdv8/IqoZfGdwduN//XZjUdd7+WyGrHYGu7f P7psh90uHFjsxqMWie7uATid7eIuIru9OLCYJJjNZvFgtxsHFmNMMjiwGGOSwYHFGJMMDizGmGRw YDHGJIMDizEmGRxYjDHJ4MBijEkGBxZjTDI4sBhjksGBxRiTDA4sxphkcGAxxiSDA4sxJhkcWIwx yeDAYoxJBgcWY0wyOLAYY5LBgcUYkwwOLMaYZHBgMcYkgwOLMSYZHFiMMcngwGKMSQYHFmNMMjiw GGOSwYHFGJMMDizGmGRwYDHGJIMDizEmGRxYjDHJ4MBijEkGBxZjTDI4sOpUtVpFOp2CWq2BVqu9 7sth7FJwYNVpWM3NzSCfj6OxUQ2vdxB6veG6L4uxC+PAqjOVSgWTk+OoVOIIBFrFnxcW3sDnG+aR FpM8Dqw6UKvVEI2uIhSagkKhgNutQGurR7ymUMjQ0lJCMDgOv/8elErldV8uY+fGgVUH0uk0lpbe IBCwAWiAxaI78rrRqIVWu44XL37F3buj0OmOvs6YVHBg1YFYLAKbTQWr9eQ6VWNjAzo77VCpkpie nsTo6Bef/RoZuwwcWHXA6+3Cy5frMJnScDjMx16vVmtIJLaQSFTQ3d1zLdfI2GXgwKoDcrkcMlkD lErFiWEVDieRyajh99/l6SCTNA6sOmljSKWSSKUqosiu06n/eL6Gp0/fQqPx4N69e2hsbLzuS2Xs Qjiw6gDd+fvqq7/HwkII2ew6nE4TMpkC8nmgo+M+3O42DitWFziw6oTJZBL1qVCogkQCsFg6YbFo 0dRkv+5LY+zScGDVEepmv3v3wXVfBmNXhgOLMSYZHFiMMcngwGKMSQYHFmNMMjiwGGOSwYHFGJMM DizGmGRwYDHGJIMDizEmGRxYjDHJ4MD6jLLZrDjJxuVq4cXIjJ0DB9ZnUCqVkEhEsbIyDaWyhmw2 g+7uPjQ0NFz3pTEmKRxYn8Hq6jKKxTBGRtyoVKqYnY1gY6MJdjvvpMDYp+DA+gyjKzrN5tGjdsjl MvHo6DCJAyG+++5HsVsoY+xs+KflCtGZgC9fPoPfb4NarTxyik1Hhw7B4Ay6u/0cWoydEf+kXLFy uQSN5vg+6l5vM2Zm1rC2ZhY7gjLGPo4D6wrJZDIMDd3D5OTfcP9+B2Syd3cGqeDu9drw5s0M7HYn H3DK2BlwYF0xo9EIg6EVkUgS7e1NR15TqRRoa9NiYuIVBgfvi1ObGWOn48D6DLzeHiwtjaFU2jvV Zh91NTQ3m5HNrmFhIYieHj+3OjD2ARxYn4FWq4VcbkU0moDHc3SURQHV1dWMsbEw4nGzaCr90HFe W1tpWCzWz3DVjN08HFifAYVSW5sHz54twOk0HrljuM/ns2FxMQSz2QKNRnPkTmM8HkMms41arYRk cgVmswd+/wB3y7NbhwPrFLVaDfF4XDR3XkbbAY2y7tx5gGDwd/T3H1+ao9drYLfnMTk5hpGRB6Jg Xy6XMT09BplsGw0NFWi1aty71465uQSi0QhaW/nuIrtdOLBOCKqdnR1MTv4OpXIHCwsGPHr0p0up LdEZgQsLOiQSW2huthx5jd7e5bIgnV7FxMQ4PJ5OjI39Bo9Hg/Z2x5Gv395uweLiqpg+UrAxdltw YL23ODkWW0EqtYK2Nh2cTg/GxlaRTG7CZjtaezqvri4/otEJOBzVE6d0vb1ujI+H8fvvyxgaaoHF oj/2MVqtEkplBtvbW1zPYrcKB9YhsVgUhUIEg4MusYSGdHZakUiERTBcRs2IalTRqAnr69twOs3H Xm9s3OvPevs2DIPhXS3rMOrnsts1WFwMwmL54sLXxJhUcGAd0tLixszM4pFplsmkxerqXtHbZDoe MJ+KQq+93Yeffvrf+Id/MImAep/JpENXVwv++tc3+Lu/GzwIz8MsFh1CoUUkk0lYrTzKYrcDB9Yh arUa1aoRa2upgxoTBYrbbcDTpz/jhx9+/ORRFtXEUqmU+L3FYhG1KIPBAJ9vCOHw+rE2h31WqwGd nc2YmloWNSytVgWlUi4+f3s7h42NDBoba8hkMhxY7NbgwDqEwqivrx+//vp/4HCYDsKJ6khm8xpW V8Nob/ec6b3oDh99fDweRmNjDsViA+7deyxaFvZ6r7oxPZ1ENpuHTqc+9vm1GpBM7mB3t4Bff52B Wm2ERtOIpiYtMpkiqlUL7PZWtLa2XvrfA2M3FQfWe2j043Z3HbmTRwFz924HJiYW0NzsOnXdH/VM 0YgnlVpHKDQJl0uLgQEHNBobQqE4EokYPB6v+FhahmO3exCPz8PrVYu7hPsKhRLm52NQqeRoajIj Hq/i4cPHyOfzWF9PIJ9Po69vb5cH+pr0oGvcf/CdQ1avOLBO4HZ3Yn19Skzn9tsJFAo5HA4lIpEV dHZ2ndiF/ubNa1QqSbhcOnz9tVdM4fa1tlrx8uUsWls9B4FisTRhaWkWbW3lg4+lEdfMTBgtLVaU SlXs7hpx/35AhJNerxcPQtPMhYVJKBR7o0ClUoFyuYZaTYFAYIhDi9UlDqwT6PUGLC/Lxdq/w6Fj s2kxPj5/EFjFYvFgtEXBVqmU0dysEesD36dSKWEwVLGwsIDu7m7xHE0PHY52zM8vwe93Y2cnjxcv ZjEw0IGmJiPC4U0RYO+HD42oVlcX4HLJxE2Bva9PoVnD9HQUuVwXDAbjlf4dMXYdOLBOQNM1rdaK UGgJgcC7GpFGQ6FDoTCJQiGLcHgZ333338SohwKLNuObmXkCu9107M4eBUpPjwuvX4fR1dV1MHLr 6PDip58WUKutiHD66quAGC2RtjYbSqWEaGKl3RyopkZhtbQUhNG4C4fDfKShNJPJQ6mkpT8nt0Mw JnUcWKfo6OjE06crSCbpLpzh4PnubhdCoQiamw2wWJwIBucwPDxyUP+yWDxYWEigp8d57D1pDaFS WUGhUBB3JAlN9b788hv88st/YGCA9sV6t8UMhVFnpwNTU6sYH38BtVqPbHYHGk0G7e3NR8KKpq+h 0AY8nmHepobVLQ6sU9BUr7f3Dp4//7/485+HDz0vF9M3CotisYyxsRkMDd0Vox96dHX1IRiEaFlo azt6yAR9Dt3po476/cDanxp6vX0ol9ePXQe1Vfj9LSgUynj1agZGowa9vR3H+rf22iWU2NxcF0uA eJsaVo84sN5Dd+JSqSRSqTXEYvMYHu489jH7YUDhZbMpsbi4gM5OrwgsmUwu9r968mQFen1WNHju 29rKIZ3Oo7X1eJjYbA5Eo2twOo8v2aHO9mx2F1arTizdOanZlHg8Nrx+vYBk0nlpS4kYu0k4sA7d 5Usk1rC8/BZabRktLSZ0dfUe2db4JBRoc3PLSKXMByFBo7MHD/6E5eVJKJUFsfZvY2MH8XgZfv+o aCB9HxXJNRoX3r5dQm+v8+Dr0lRvdXUDKysJDA93ibuVp8nnaf94M7Ta43vIM1YPOLAOjazC4WkE ArQflfLMUyr62N5eG6amXkOr/fpgLyu602i1evDy5W/w+ZqQSDRiaOjBqT1cNKryeHxYXVVgbm4G fn+bCKuVlXUkEmk8eND7wbCiO5pzcyn4/Q+O7KfFWD3hwPoDFaobG5Wiu3xtLQebTY2OjrMddKpW K9DVZcavv/4nHj/+4aDoTU2m29sBsRXM6OiXHz1ogkKypaVVTEUXF9dQLJZQLldw9673g2FFdxdn Z1Pw+e5yOwOraxxYf6CQaWvrQTJJxfIupFJB0dd0uF5E08bT1hLSWYM9PWaEw0uiT2u/67y7uwde r+/Md+6o56q1tQcrK2Pw+13Q6VQfHO3lcgXMzSXR2XmX61as7nFgHeJwOMWDTmteX1/E+voW4vGk aOSMRDYxObmKb77xi4XI7zeVUqY4HAbMz2+iWGyHSqUSz+/fPfy062jG/LxaHFjxsanp0tImmpq6 xJ1BxuodB9YJcrms2HV0YSEt7v5Fo0ksL69DqTQhGk0hFstBLldCrW5APl9Ef78TGo0Ky8ubKJcN ovZ0EdSb1dUVENslDw66PzgdpNdUquOLpxmrRxxYJ6A2BVqr19HRK3ZnCAanxB28gYFebG6uiaPn qUm0VCrj2bNfxEgsmwXs9h6xJcz+6OoiqP6VSm1ieTkBn4+aRPd2cKC61s7OLlKpLHK5MjKZKkym iwUkY1LBgXWCQGAA3d294uAImpJRi8K+96deTU0OpFI0yhoUIba/tcz8fAidnZ1QKs8XXntb0PTi zZsk5uYiSKezyGQqYpuapiYn7PYO+HwOsSyIT89htwUH1gnobt5Zj46/d2/04Pc0Fdza2sKLFz/D 5VJhfr6I3t7zH8dF19DdPYTNzU34/VbRrkCjN+5iZ7cVB9YlooXJs7Pj6OjQiYXLk5Pr2N3dhU53 /kZO2pb5MrZmZqwecGBdIhr5UE+Ww6EXxXCzWYaNjTXodHub9jHGLoYD64KoN4umgrQ3Fk39GhrU Yl8rvV4Nl8uM8fGFI5v2McbOjwPrnF6+fI5qtYx0OiVOZJbLK2hslEGlqsJs3ivM0xbHtC6RalAO h+O6L5kxyePAOidaQ6hQZBAItBxMBd9Hz9OdvDdvpjiwGLsEHFjnZLc3iz2vaK3faQeeEmoolcsL Yg+sixTfGWMcWOdmtTYhk+lAMDiNkZHjh1Lsow4Ep1OPRCKOzk7fZ71GxuoNB9YFls+43W2YmXkl Rlknnc68z2zWIBJJibYHLr4zdn4cWBdATZyBwH0Egwvo69urZZ2E6lulUlIsqubAYuz8OLAugAKq vb0DL14si/WEdIrNSWj0pVCUxNpAl8v92a+TsXrBgXUJU8O9UdYMpqcXYLOpROOoxaIVJ+BUKlWx 00M8Tnuy85Iaxi6CA+sSmEwm3L//UBzflclsIx4PIxbbhEpVQ6FQQbmswf3738Bo5N1AGbsIDqxL rmmpVHZYrXQAagn5/K4YgdF+VfQrY+xi+KfoCtASHQovCqm94MqLJTz0oOfodfp1//eMsbPhwLoi FFRv306gVstBJqtBJmsQgUXnFhaLFVQqDajV6I6hAkajGTqdHlar9czb2jB2G3FgXZFKpYxaLYOu LpPYuWG/42Fv9+Sa+JUK8tlsAfn8Gt6+nUR393243a3XfOWM3VwcWFeEFkI3NChEMB0+eWcvuPb+ TIel0kEWW1tZmEy0iyivN2TsQziwrshekV0puuBp2ncaOsRicnINQ0N/4ukgYx/BgXVFqJiu05mR zW6IvbFOQyfyrK1lEQyGRGDR+YVra2uinkVtEG63+8xnGjJW7ziwrpDNZsfr11Ow23Wn3g3s6HDA 4TBhd7eIYjEnDkbt7dUCyCASCYvNAdvb23lJD2McWFeLRkgGgxurq0m0t598KjMFmV6vEQ9Chfh4 fG+hdDK5hURiEisr8xgeflAXjafxeAxLS/Po7e2HxWK57sthEsOBdcVrDe/cGcR//df/Qmur9dgo q1qtIZvNQ6dTHxTmV1c38G//NoFSKYf+/jYMDZmRz5exurqKQCAAKdvc3MD09HP09Fjx5s1zPHr0 HU932SfhwLpiVJdqamoW+7wbjTTVeyeR2MLk5AZ0uhoePuwSAed22/CXv4zAZNJBrd4rwtM08cmT IHp6eiTZMU/T2mg0isXFcdy50wyrVS/60GZnJxEIDHHzLDsz6f3vlyCdzoR8flsEFk35YrGkOPKe GkgtlmZEIlGkUjuwWg1iZwen8+hUSatVwePRIxqNiJOopSYWi2J1dRKDg04xmiTNzUbkcptYXV0R O14wdhYcWJ8BdbLHYmEsLW1gZ6cCo7EZ3d1fi9ESTYmi0TURZO+PSkolOtiiQYSYx2NDKBSFy9Ui qWlUKpVCMDiGkRGXCN59hUIZW1sZrK8vcmCxM+PA+gzMZht2d3tgsVih1dK2M8oj06Dvv/8B09NP YLHoRTjl8yVEImlsbpahVgN+v12cwKNSFcUpPVJqMKXvc39qS6hmF42mkUrR9HeIO/vZJ+HA+gwo pHy+0/d9p9HU9nZG1LCo0fTNmwhaWvy4e9eFiYnnotZFtS27XYvFxaCkAovubDqdXoyPT8LjsWJt rQS7vROdnW6xQJyxT8GBdQPQD+7ubg1PnwYhk5ng842gublZBNjAwCjGxl5idzcmQiufjyKZTIrG Uimg78Hj8YqO/mRyFwMDAahp2MjYOXBg3QA0RRwaegiNRgObzXZkukijs9HRLzE1NYbFxSL0erfk lvBQaPX1+a/7Mlgd4MC6Iaib/TRUZB8cvCemjhRmpx12wVi948CSCO5VYowDi90AGxsbMBj0Yitp xj6EA4tdq5WVFUQiE1CpLLhzZ1RSPWbs8+PAYteC6nGRyCqWln7HgwdeseB7auo1+vuHObTYqTiw 2LWg49DW10O4d88DhUKG1la6O5rCwsI0Ojr6uEeLnYgDi312dBjH2Nhz9PUZDrrg9xZ+U2PpFp4/ /yuGhr6si+102OXiwGKf/TQh6ilzuWSw2QzHXnc6TdDrVfj99/+A1epBS4sHRqNJcr1n7GpwYLHP OrKan5+DUrmNzk7nkdf2drFIYXs7D7fbgkePerC5uYOpqafo6RmFy+W6tutmNwcHVp2iXRJmZ2fQ 09N3o5bxFAoF2O2aI82vhUIJ4+NRGAxtaG52YmpqHB6PSuyFr1Rq4HBIZ+0ku1ocWHV4921paQnB 4HPcudOG2dmfUa1qUK1WYDa7xQ6o19n82tXVi5cv/yZGW+vru0gmd+Dz2WA2t6Kvb0AEmdH4GHNz b8V2PHfu3Of97NkBDqw6Uy6XMTMzhtHRDrGzZ1OTUewAQdu6vHy5jP7+gWvtmtfpdBgY+ALLy0G0 tQ2itbUBi4tv4fW6DkZddIfwzp0h8b1IcYdVdnX4f0OdoR4mlUon9tUitAEgHdaqUOhgtVYxMzMN vz9wodDK5XJihKTX68/1+bTAmx77Ttsuh8OKvY//R9QhqluFw1Po73+3oJpGL8PDPoyNRbG97YbZ fP4Ta5aXl/D27Ws0N9ugVOpQqylw//7DS7p6xk7HgVWHnM5mrKxMiDtvMtm7kRRNCxsa1Odes0dT tHQ6jVwuiZGRNtGCEA5vIBLJXuLVM3Y6Dqw6QoGysrKMxcUQ1OrSkUL8xsY2nj5dwfff/yj23TqL YrGI+fkQmpqaxBSQdj+12RTw+11imkltCBsbwNDQF1f4XTH2DgdWHcnlslhamoXLpYDZbBfTQGoZ CIXWsbOjxHff/SMMhuPNmu+jgKNzEFdXg9DrS4jHV6FWK/DVV+1QKhXi9XB4E+FwFV988TUvo2Gf DQdWHTEYjBgd/RrpdBLh8CJqtS3odCrs7Chw797DMwcLBRKNrvL5XXR12cThGIf7popFOvGmAQ8f fsUd6Oyz4sCqIxQqFFr0MJutePXqGdLpJWi1TZ90V5A+1ufziVFVOj0vzks8jPZnl8nUn7yrAgXh /q6pjJ0HB5aE1uBFImE0Ndmh1xuOPE9d7bRQmEY729vbqNWq4kixx4//XrxeqVQOWgToz4lEAm63 +6Nfk0Jvb1q4BZmsARqNSpwtSPWrbHZDdK1/yoESCwvz2N3Nwu8fONIMStcXiURER/55WyXY7cCB JQH0A/3ixVM0NKSxuqrHgwdfi9HNzMwM4vFF2O1qLC3tjXysVjXy+bJoynQ6nQfTQCqar62tYWZm QtzlU6u/P9ILdRKtVofe3hHE42HQjHBxMYbh4RYxQqLgoff8FFRfU6kqWFrSHTn2jN4nFHqL3d0M Hj36DhbL+VsuWH3jwLrhtrbSCAYnYTTm0NfnxcrKOv793/8nAoH7iMUWRCGc9pOiH3qaEtKDgmtq ahYajRozM1MiuBYX5wDsYHCwHZWKHhMTY/jmm+8+eKAFvUb9WvTY2xImj/n5ddjtOthsjmM1MbpL SXUvsrGxDpVKCYOBdl8wIJvNQi4vYni4Az/99Fy8d0dHp/hYmibq9VoMDZkxPf0rurrui2tm7H0c WDcUBQRNoXZ2omhvV8FmaxPPt7U1IZ3eQSj0HN3ddGz9fkf7u7oQ7TFlMJTx4sXf0Ndnxc7OIvr7 LbDZ9hpJq9UatraWRGH9rIV4ev87d4axuhpGKDQvCu/5fF4stdm/3mDwLVKpJajVKtDblkoyTE3l 8O23/4hMJoOmJr24tseP/ZiensPOTkp04gO0BCcvtpHxeq3Y3t7kwGIn4sC6gWikMjExjkIhIhYw Hz7qfXMzg62tHB4/7odKdXrRW6+XI5dLQaVywmzWQaF4909NIaFWy0Q961NaEmga2tnphcPhFKOi /bCi63327DeYTHncvdsqlgXR16BRVKWSQDqdwvr6GiyWvf4v+n7u3GlBJpMXgSuXKyGT2UUoajQK RCIb5/ybY/WOA+sGisWiqFQ20NvbimKxikolL37IqWtdLm/Ezs6u6K+iYDjcyX5Yc7MFX36pEj/8 r14F8ehRAN3de4V2Chu5XHXuloT9oCIUeuPjr6DXb6Ovr/3YFJOmj+PjT5FO00jLe9B9TwFKi7Pf vU8FicQ25PIG1GplUdDn/i72Pg6sG4hGMFRo39goolIpo1zOolCIoblZh5WVBLa3S5iby8Jo3EZP T/OJ70GjFeqfogeFm8v1bk+sXK4AhUJ/KT1UqVQSCsWOWLd4Uj2MRncejx7R6BoWFtZEXc3jsR0Z NdL1BYMbqFSMkMsriMXWIZNNYWRk5MLXx+oLB9YNRCOLwwVpCq3Z2Vk8fTqJhYUQ/vKXf0Frazt+ ++2v6OgoizaDD6Hw2qsV7aFRjk738Y73syiVijAa1R8s3qtUcuTzWSSTDQgEevDy5QyKxSza203w +ZxYXU1Bq22Fz9cj9u3y+QY/+Q4kux04sG44CoLGRqoJydDU1Cy2junq6vlj94WHePLkP9HVZRcF bZpm7exQ8VpzZKpIO3fG41swmSpQKqlOpEQ0OoO+vv4j07uzojChLWay2W0sLU0gELB/8ONtNqOY ovr9Q3C7W9HS0iamfG/fTuHJk3no9Xbcvdv1R7DStJeP+WIn48CSAPoh9vv96OvrE1PF/dGMyWTG 4ODXSCTiWFtbEUGVyVCtKwWFgn74aYRWRSZDU0u5aGdIpxcxPNyGQMCJ+fmg2CjvQ6Ojw2i0F4/H kUwmUC6noVZXMDLi/ugIj24UaDT2g62O6etRw+nQ0Agymb2g4r2v2Fnw/xIJoR/0wz/Y9Ge6/U8h RrtpPGJ+AAABr0lEQVSM9vUNYWSkX0zTKFxoJESvUa2KtpShj5+cXBe/0jmAr1+vif6os3aX093A n3/+G0ZHXWhpsYobAGdBdTSVKnssGPe2QzZ94t8Cu804sOoAhdY///O/imCiEDhtjR8FWKGwK7rW aYppNDYgldo4c2DR+/744z9hYuIparUk2tqsB/1fVBfbb2V4Xy6XR7mcQzKZ5P4qdiEcWHWA1uWd 5aAGakGgkdceWoQsg0LxaXcKqebV3/8F5uamkU6viKI5hdbiYhyZzC6GhryiRrYfYuvrW8jlitDp XB9dCsTYx3Bg3SKFQh5zc1HE4yl0dFiQzVIB/9OP0KI9tYaHR7G0tIjnz4OiTpZMptHX58dvvy3C 6dRgYyODclmOclkBm40667f5zh+7MA6sW4QWM//44/8QU0da9jM83HPuYjeNqrxen3iQ/bWM29te sXtEW5tZjMbo+TdvnqGhIYFQKIRAIHDJ3xW7TTiwbhEKp/2dEC77fML9WpbJZBKPfTQF7e4eFLuh UkMsYxfBgcWu1N6OD2bxYOyiOLAYY5LBgcUYkwwOLMaYZHBgMcYgFf8f1iG1M1rDd6AAAAAASUVO RK5CYII=