20230627 08265200 1.0 FGDC CSDGM Metadata FALSE Streets 003 1866859.852690 2120276.905840 697896.280512 888581.395341 1 Projected GCS_WGS_1984 Linear Unit: Meter (1.000000) WGS_1984_Web_Mercator_Auxiliary_Sphere <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/3.0.0'><WKT>PROJCS[&quot;WGS_1984_Web_Mercator_Auxiliary_Sphere&quot;,GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Mercator_Auxiliary_Sphere&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,0.0],PARAMETER[&quot;Standard_Parallel_1&quot;,0.0],PARAMETER[&quot;Auxiliary_Sphere_Type&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</YOrigin><XYScale>148923141.92838538</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>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem> 20230606 10274400 20230606 10274400 FGDC Esri ArcGIS 10.4.1.5686 Street Centerline map 2010-04-01T00:00:00 2013-02-28T00:00:00 map vector digital data <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The City of Columbia GIS data represented is a product of compilation, as produced by others. It is provided for informational purposes only. The City of Columbia GIS makes no representation as to its accuracy. Its use without field verification is at the sole risk of the user.</SPAN></P></DIV></DIV></DIV> Municipal Columbia, SC Used for representational purposes. May be used for spatial querying. Should be used for representational purposes unless field verified by user. GIS Coordinator City of Columbia - IT/GIS GIS Coordinator Located in around the city limits of Columbia within Richland and Lexington counties. GIS Coordinator City of Columbia - IT/GIS GIS Coordinator 1136 Washington St. - Suite 204 Columbia SC 29201 gis@columbiasc.net US 8:30AM - 5:00PM EST GIS Coordinator City of Columbia - IT/GIS GIS Coordinator 1 -81.440754 -80.601829 34.275591 33.750742 This feature class contains an inventory of street centerlines that relate to city assets. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This feature class works in coordination with "The Addresser". This program created by Bradshaw Consulting Services aids in managing land record data, particularly address data. "The Addresser" was implemented in the summer of 2012.</SPAN></P><P><SPAN>The street centerline feature class has undergone a large update since April 2010. Attributes and geometry have been changed in order to use the data within a network dataset. Routing has been the main purpose of these changes. The data is being used in Cityworks. It is consistently being updated on a daily basis. </SPAN></P></DIV></DIV></DIV> GIS, Stewart Hall, Travis Woods Street Centerline Transportation Road Address Feature Class dataset EPSG 6.18.3(9.3.1.2) 0 Simple FALSE 0 TRUE FALSE Streets Feature Class 0 OBJECTID_1 OBJECTID_1 OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. OBJECTID objectid Integer 4 0 0 Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. JoinID joinid Integer 4 0 0 NameID nameid Integer 4 0 0 LeftAdd1 leftadd1 Integer 4 0 0 LeftAdd2 leftadd2 Integer 4 0 0 RightAdd1 rightadd1 Integer 4 0 0 RightAdd2 rightadd2 Integer 4 0 0 PrefixType prefixtype String 20 0 0 prefixdire prefixdire String 15 0 0 StreetName streetname String 75 0 0 SuffixType suffixtype String 20 0 0 FullName fullname String 75 0 0 suffixdire suffixdire String 20 0 0 LeftCity leftcity String 30 0 0 RightCity rightcity String 30 0 0 State state String 2 0 0 LeftZip leftzip Integer 4 0 0 RightZip rightzip Integer 4 0 0 Datasource datasource String 25 0 0 Ownership ownership String 25 0 0 GISEditor Inspection Completed String 30 0 0 FacilityID facilityid String 30 0 0 gisrevisio gisrevisio Date 8 0 0 lifecycles lifecycles String 20 0 0 datasetnum datasetnum String 10 0 0 featureabb featureabb String 10 0 0 LegacyID legacyid String 30 0 0 Comment comment String 100 0 0 LeftCounty leftcounty String 30 0 0 Felev felev Integer 4 0 0 rightcount rightcount String 30 0 0 Telev telev Integer 4 0 0 SpeedLimit speedlimit Integer 4 0 0 FTCost ftcost Double 8 0 0 TFCost tfcost Double 8 0 0 OneWay oneway String 10 0 0 CFCC cfcc Integer 4 0 0 LowAddress lowaddress Integer 4 0 0 MaintAuth maintauth String 30 0 0 highaddres highaddres Integer 4 0 0 blocknumbe blocknumbe Integer 4 0 0 CreateDate createdate Date 8 0 0 CreateWho createwho String 50 0 0 DateIssued dateissued Date 8 0 0 DOTHwyType dothwytype String 20 0 0 functional functional Integer 4 0 0 SHAPE Shape Geometry 0 0 0 Feature geometry. ESRI Coordinates defining the features. UID uid Integer 4 0 0 shape_leng shape_leng Double 8 0 0 created_user created_user String 255 0 0 created_date created_date Date 8 0 0 last_edited_user last_edited_user String 255 0 0 last_edited_date last_edited_date Date 8 0 0 globalid globalid GlobalID 38 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. 20230606 /9j/4AAQSkZJRgABAQEASABIAAD/4RJeRXhpZgAATU0AKgAAAAgABwESAAMAAAABAAEAAAEaAAUA AAABAAAAYgEbAAUAAAABAAAAagEoAAMAAAABAAIAAAExAAIAAAAcAAAAcgEyAAIAAAAUAAAAjodp AAQAAAABAAAAogAAAMIACvyAAAAnEAAK/IAAACcQQWRvYmUgUGhvdG9zaG9wIENTMiBXaW5kb3dz ADIwMDg6MDI6MjkgMDk6MTU6MTMAAAKgAgAEAAAAAQAAAJCgAwAEAAAAAQAAAJAAAAAAAAAABgED AAMAAAABAAYAAAEaAAUAAAABAAABEAEbAAUAAAABAAABGAEoAAMAAAABAAIAAAIBAAQAAAABAAAB IAICAAQAAAABAAARNQAAAAAAAABIAAAAAQAAAEgAAAAB/9j/4AAQSkZJRgABAgAASABIAAD/7QAM QWRvYmVfQ00AAv/uAA5BZG9iZQBkgAAAAAH/2wCEAAwICAgJCAwJCQwRCwoLERUPDAwPFRgTExUT ExgRDAwMDAwMEQwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwBDQsLDQ4NEA4OEBQODg4UFA4O Dg4UEQwMDAwMEREMDAwMDAwRDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwMDP/AABEIAJAAkAMB IgACEQEDEQH/3QAEAAn/xAE/AAABBQEBAQEBAQAAAAAAAAADAAECBAUGBwgJCgsBAAEFAQEBAQEB AAAAAAAAAAEAAgMEBQYHCAkKCxAAAQQBAwIEAgUHBggFAwwzAQACEQMEIRIxBUFRYRMicYEyBhSR obFCIyQVUsFiMzRygtFDByWSU/Dh8WNzNRaisoMmRJNUZEXCo3Q2F9JV4mXys4TD03Xj80YnlKSF tJXE1OT0pbXF1eX1VmZ2hpamtsbW5vY3R1dnd4eXp7fH1+f3EQACAgECBAQDBAUGBwcGBTUBAAIR AyExEgRBUWFxIhMFMoGRFKGxQiPBUtHwMyRi4XKCkkNTFWNzNPElBhaisoMHJjXC0kSTVKMXZEVV NnRl4vKzhMPTdePzRpSkhbSVxNTk9KW1xdXl9VZmdoaWprbG1ub2JzdHV2d3h5ent8f/2gAMAwEA AhEDEQA/APVUkkklKSSSSUpJJJJSklQzeudOwXRkvexgMPtFb3VsP/C31sdVV/bco1dUdfn5OHUx jfspqJse7R7bm72vq2j+S9iSnRSVXKzBTfj4rIN+UXBm7gBg32PP9VSdbZjNfZkvaaQBtLWkO3E7 dv0nbtzi3YkpsJLOyeqvw7qRmY5rx8h7am5DXB4ZY87am3shrq22O/R+o31GeordGVj5D7mUvD3Y 7/TuA/NfDX7D/Ze1JSZJJJJSkkkklKSSSSU//9D1VJJJJSkklUzuoUYtlGO+xtV+W4sxzYDsLh7t m/6Pqbf5qvd+lSUvndTwun1i3Ls9OsuDXP2ucGzw60sDvSr/AOEs9ilg5TMzFbkVua9jy7Y9hlpA c5jXNd+d9FZmJk3dMzz07qTvUrzHk4WcQB6jjLvsWTt9jcmtv9H/ADMin/ha1n5HUq+iZ+V0/ozf tt+S4WtwGiKsZ7v5+22+dtVN3tt+z/6T1P8ASp0McpnhiLP8t1spCIsmnRxOq+jS/B6jj215FALH k1k02t7X15MfZ9lrfdZ6r2en+esZnXOgdP6s26q9uWG4jMV9GKx1zg+p7n1bHNb6WxrLXs/nEar6 u5fVnDI6/lOy9ZbjtJZjt8mUt/nf69i3aMDp2BQRTS1jGDhrQB/mtU3t4YaSkcku0PTH/Gkx8eSW sQIjvLf/ABXnOpfWI57se6jpfUKr8Oz1MfIbWwESDXYx9Vj/AH1XVu2WMUepfWe3Mw30ZODm4TvY +q5tHqBttb231WvDLPdXvr99a6up4IBcwVh2jRGpUzXWXEuALTw2Bp80uLD/AJo/48k1k/fH+K87 V9aemdVxfTfZUciqLXYe4tstsq/S10015Dafp2taj4eYzo/1e9R36fqVg9a2jh78vKf7a3N+kzdk 2+j/AMWrfUvq90rqLC3IoY+f32z9z/5xv+cueyuj9W6S014VhzMMlrv2fkvJ1YfUrdg5v85TbW8b 62vSGLHk/m5GMv3Mn/fq9yUfnGn70XoKsnJ6XT07p1z3dQ6jluIscXRAH6XLyOPbj4+7ZUz/AIml ald9NrrG1Pa91TtlgaZLXQHbH/uu2uauZ6NmYvUsnK6hXfYzKZWKsqi8RkY1VY3Ox6qwPd9ou32v yf6ih0zPyen9LxqsXEnqPV73XCu6WAG13rWve2HXenhYuz1X/wBj/CKCUZRJjIUR0ZAQRY1etSQq sim11jK7GWWUnZc1hBLXQHbHj8z2uRUEqSSSSU//0fVUkkklMLXiut9h4Y0uPyEqs/CxsvAfRnRl UXjdYH/Rgjd+jj6Gz/Bq2QCIPC57q2Fg9Fw7+oOvyXY9Xur6d6pNDrHGKqW1x6mx1n+B9X0f+DRj EyIiNSTQQSACTsGhm5+fi0s6FiZBys2z9LXkXtBfiY2mx+TZr62S3/AWfzn+k96s9DwMTEx/0ILm OO51r9X3P/Ovtd+d7lh0O9PKr6flWj9o9RJyeo2Ew4jluLX/AOe2t/4xdZTjvLWzDGQIaPDsr2QD FAY4/payl+9/L9BqwPuTM5bR0iE/rIjTbJA0+PCZjWMENHz7qW5VaZ+Jfe8D3H7k3qod1sAN7lDJ e0SRolwpBbHqqNhZYwssG5p5BQA4n4DkpvUHikI1sq7ed6zgWVZ9V+PZ9l6kyTgZv5tgH0sLL/f/ ALSNj5lnWXnOrsPT8xo+ydXc47rcVjZsLcBkbK25tn0sp/8Awf8Ao1pdSxqc/CsxrjtBG5tnBY5v uZcHfm+muRw+sPx31fWGlwfdhOGL1djOLscna3JH7zqvptcrXB7+L/WQ0H7P8f8A6bAJe1kA/Qnt 4PR9KzcbpzmljSyqzfX0/p1Nbjk5Dd+vUcj1Xeo71Nu717/T/wBJZZ+kXVLBeMXouHd1XHfWa7y2 x1zw+6+/eR6VbbHWb7Hu3eni0fQWn0p/UrMNtvU2sryLCXelX+Yw/wA3U90u32tb/O7fZvVBtNxJ JJJT/9L1VJJJJSlyf1ry2W9VxcSw/q3T63dQyR2Jb+jxmu/t7nLrF539YLqLLvrDkZTi2kvrxJbo 6K2TsZ/Kda5WeTjeQn92P/S9H/dMHNSrHX7x/wDQnIwaLOpZONn5FRezKtdkuvaZLdhLaMd/Dqqv zvZ9Oxd3jdTJAbfr/LH/AH5eddH+tGPiY9WJkUGuuobRZXr/AGnMK6rB6jiZjN+La20dwDqP6zPp NV+cIzGurRjOUDpo9S21rxLSCPJCuyhWdo1d+RZVdpGoMHyWT9ZL+v47f2h0y/fWxsX4zmNfAH+G r/P/AOMaq0sBGxbMcwO4eidc5xkmSkLnAzK84b9fOtgatx3ee0j8jkz/AK9decPaKGeYZP8A1TkP Yl4Lvej4vpTsix3J+QWd1Lr/AEzpjC7Mva13atvueT4Ctv8A35eb5X1i67lgtuzLA08trhg/8D2q niMrsv8ATvdDL/a6w67XH+bsP9V/0v5CcOX7n7Fpz9g7fX/rrldUa7GxwcbCPLZ97x/wrh+b/wAG 1A+qmfXX1QYl+uPnNNFrTwdwhqzsXpN2S6xu5jPR3GyXCQGg7ntb+czRCprvo9LNDHCtljS2yIBc 079ocp4jhFAUGCR4jZNl9X+pLKsjD+wZzfVyvq/kPqpc7s0gim3b9Hd6TtrHLrlxX1du9L645TW6 M6jh05EfygNpXarO5mNZZf1qn/j+qTfxS4oA/RSSSShZH//T9VSSSSUpeVfWhrjidVH/AJtnT8Nu i9VXnH1oxSLuvY0ah9GcwfySPTtP+crfJH1THgP+lFrc2PTE+P7HhNiLh3WYeVVk1/TqcHRJAMfm uj81T2JCsuIa0S4mAPMrQ4Wnb2/Sus0dRqLqwWWMj1KzyJ8D+c1aItWTgYNWBSK6mgOIHqO7ud5q 0LCE7gti46KUYXTWu3jFpDpmdjefuXCddxBj9XyWNENc/e34P967f1VzH1mYXdQZZGjqwAfgSgYU ujOzTg7FKnGtvtbTU3fY8w1oRm1Fzg1olzjAA7kro/q90kVWOynvD3gGsBurQfz/AH/nu/qIcK4y pbH+r1OHXXa8h5Yyz7Q3vYXt2NorSxLW9Zdi4LKGtxaqbH3VgEiuyH1UNJP+er/WMlmE/DutqFlQ tkkky0x9Jtf0Xva36G5G6X9YMDJcK9vp5FtuxlTRJcPzLXOgN+ihLbQKiD1T9Ka+v65YDD9JnTg1 /wAQYXeLieht+0fXfMtGrMOiuif5Ub3/APVrtlm82f1nlGP4jidHAKxj6qSSSVdlf//U9VSSSSUp cr9bMZlHUsLqFg/Vsprun5h7Btvux3u/q2rqlU6r06nqnT78C/6F7S3d3a7lljf6j/cpcGTgyCR2 2l/dksyw44Eddx5vj+V06/GzX4Lmzax+xo8ZPsP9pdZh9ExcSithra+5nudaRJ3+LT/JVa/Hy72+ o5sdb6M4Mya/9LW3+avZ+9vYt2h7MrHryKx7bWhwB5HktWU9B+Nfy/Sc7h3DTdUoGpaDqlA1JDIs ONo+j5Kj1npzsnCPpsL7qyHMA5M6Oatv0k4qR9xAg8n0v6vZT3usyQcdoEM43SdCQPzfaujbVTh4 p2gMqoYSB2AAVxtSlZiV31mq1u6t30m/DVMlkXiBcHrmBndR6divopLrNLLKxoRub/KWf9WMUUX3 9Wyhsx8CtxLnae+Po/2Wrt2Vrn+uWO6t1Cr6u4etYc2zqDm8ATurx/61n03pnu+kg6RAuUv3Y/pM kceo/J0/8X+Jb9iv6nkCL8+x1zp/lnc1v9lmxdYgYeMzFxq6GCAwRp4o6zMkzOcpH9I26ERQA7KS SSTUv//V9VSSSSUpJJJJTg/WLol+S+vqvTIZ1TFENB0bdX+djW/+i1U6X1PG6nU7YDVkVHbkYz9H 1uHLXN/78upXNfWTpfScjMrsqyvsHWy3dTZUC57mj/uRSwO3U/y3qzizihDJsPln+7/Vl/UYMuKz xR36x/e/9CTmryUTV5LGs651XpzBT1mk0g/zfUaGerS4eL2fSYhY/UeqOY92BkY+c2x5s3scC4T+ Z6L3Ncxv8lW4Y5SFiUa6G/Sf8JrSIBog/Y7vpeScVLHHWutVsLbcHdZ+a7a4D/NG7cp0db6rDBZ0 9zyP5xwDmz/UBG1iJw5a/R/xooE4eP2Ou2pEbUsy360dMxay7NcMaz82nc2yw/8AW6d7v85Z7uo/ WDr7vQ6XQ/AxHfSybB+mcP8Ag6/8F/XcojGQ1mRCP70jp/g/v/4LJEA/KOItnrnXjjv/AGZ0sC/q dojTVtIP+Fu/75WtT6q/V1vSsb1bSbMq4l9tjvpOc76T3KHQvq9h9Etayxm590FuQ47i6z89tzj/ AIT/AEa6NVs2YSHBCxDc380z/W/71s48fDqfm/JSSSSgZFJJJJKf/9b1VJJJJSkkkklKWPZbh9Gy MzOyWuNubbWGOY0vfZ7WUU4tQHuc5j9+2r+X6i2FF7GvaWvAIPYpKecZ1QX9WcAWs6Zk2PxaDaJq uyWCb7N35v0Ps2Ozd+mtZk2f6ND6h9V/qxffTXk0DEzclr3tbTPFe31Xbqx9Fu9i1X9BoOIcBjg3 BLmFtBaD6Yr2bG4zvb6f83u/roTt4+s78m9j2Y9GGKqLS0ljn2WGzIhw/OY2mhOjOUTcZGJ/qnhQ Yg6EA+bis+puHtFmL1i9lRJaIvIEj6TOfpN/dSu+ouFW0P6h1K51bnBo9a5wBLvos1c36SWdgUdR +s1IsrIwM/1Gljht9R9ePfXdlsY73fRyKafU/wCBRbRm5/QM/GygXZnSaX0l5B991W3IpyWfverT Vj2/9eUn3nN/nJfat9rH+6GVPRfqz0c0u+zuIutFLbtkN3ODnM3Wv/Ne5np/11b6l0PLzcJ3p5ey lzQ/7G1jW1ED3tb61ezK3/8ADet/1tVrelv6jiurwcvL9O8T6GQJqqdt9fHfQ+yttrfRv9F1ey2z /RrR6f0XLpqY27MtFDmg2YILXVscRNlNOQ5n2n7Nu+hXv+gopSMjciSe51XAAaAU1sb6t9PyKTW5 2XjOAaXNrybwwg+5j691jm/+k10DW7Whsl0ACTyY8U4AAAAgDQBOglSSSSSlJJJJKf/X9VSSSSUp JJJJSkkkklKSSSSUsWtLg4gFzfonuJ8EoH3p0klKSSSSUpJJJJSkkkklKSSSSU//2QD/7RcUUGhv dG9zaG9wIDMuMAA4QklNBCUAAAAAABAAAAAAAAAAAAAAAAAAAAAAOEJJTQPtAAAAAAAQAEgAAAAB AAEASAAAAAEAAThCSU0EJgAAAAAADgAAAAAAAAAAAAA/gAAAOEJJTQQNAAAAAAAEAAAAHjhCSU0E GQAAAAAABAAAAB44QklNA/MAAAAAAAkAAAAAAAAAAAEAOEJJTQQKAAAAAAABAAA4QklNJxAAAAAA AAoAAQAAAAAAAAACOEJJTQP1AAAAAABIAC9mZgABAGxmZgAGAAAAAAABAC9mZgABAKGZmgAGAAAA AAABADIAAAABAFoAAAAGAAAAAAABADUAAAABAC0AAAAGAAAAAAABOEJJTQP4AAAAAABwAAD///// ////////////////////////A+gAAAAA/////////////////////////////wPoAAAAAP////// //////////////////////8D6AAAAAD/////////////////////////////A+gAADhCSU0ECAAA AAAAEAAAAAEAAAJAAAACQAAAAAA4QklNBB4AAAAAAAQAAAAAOEJJTQQaAAAAAANFAAAABgAAAAAA AAAAAAAAkAAAAJAAAAAIAEcASQBTAC0AbABvAGcAbwAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAQAA AAAAAAAAAAAAkAAAAJAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAQAA AAAAAG51bGwAAAACAAAABmJvdW5kc09iamMAAAABAAAAAAAAUmN0MQAAAAQAAAAAVG9wIGxvbmcA AAAAAAAAAExlZnRsb25nAAAAAAAAAABCdG9tbG9uZwAAAJAAAAAAUmdodGxvbmcAAACQAAAABnNs aWNlc1ZsTHMAAAABT2JqYwAAAAEAAAAAAAVzbGljZQAAABIAAAAHc2xpY2VJRGxvbmcAAAAAAAAA B2dyb3VwSURsb25nAAAAAAAAAAZvcmlnaW5lbnVtAAAADEVTbGljZU9yaWdpbgAAAA1hdXRvR2Vu ZXJhdGVkAAAAAFR5cGVlbnVtAAAACkVTbGljZVR5cGUAAAAASW1nIAAAAAZib3VuZHNPYmpjAAAA AQAAAAAAAFJjdDEAAAAEAAAAAFRvcCBsb25nAAAAAAAAAABMZWZ0bG9uZwAAAAAAAAAAQnRvbWxv bmcAAACQAAAAAFJnaHRsb25nAAAAkAAAAAN1cmxURVhUAAAAAQAAAAAAAG51bGxURVhUAAAAAQAA AAAAAE1zZ2VURVhUAAAAAQAAAAAABmFsdFRhZ1RFWFQAAAABAAAAAAAOY2VsbFRleHRJc0hUTUxi b29sAQAAAAhjZWxsVGV4dFRFWFQAAAABAAAAAAAJaG9yekFsaWduZW51bQAAAA9FU2xpY2VIb3J6 QWxpZ24AAAAHZGVmYXVsdAAAAAl2ZXJ0QWxpZ25lbnVtAAAAD0VTbGljZVZlcnRBbGlnbgAAAAdk ZWZhdWx0AAAAC2JnQ29sb3JUeXBlZW51bQAAABFFU2xpY2VCR0NvbG9yVHlwZQAAAABOb25lAAAA CXRvcE91dHNldGxvbmcAAAAAAAAACmxlZnRPdXRzZXRsb25nAAAAAAAAAAxib3R0b21PdXRzZXRs b25nAAAAAAAAAAtyaWdodE91dHNldGxvbmcAAAAAADhCSU0EKAAAAAAADAAAAAE/8AAAAAAAADhC SU0EEQAAAAAAAQEAOEJJTQQUAAAAAAAEAAAAAThCSU0EDAAAAAARUQAAAAEAAACQAAAAkAAAAbAA APMAAAARNQAYAAH/2P/gABBKRklGAAECAABIAEgAAP/tAAxBZG9iZV9DTQAC/+4ADkFkb2JlAGSA AAAAAf/bAIQADAgICAkIDAkJDBELCgsRFQ8MDA8VGBMTFRMTGBEMDAwMDAwRDAwMDAwMDAwMDAwM DAwMDAwMDAwMDAwMDAwMDAENCwsNDg0QDg4QFA4ODhQUDg4ODhQRDAwMDAwREQwMDAwMDBEMDAwM DAwMDAwMDAwMDAwMDAwMDAwMDAwMDAwM/8AAEQgAkACQAwEiAAIRAQMRAf/dAAQACf/EAT8AAAEF AQEBAQEBAAAAAAAAAAMAAQIEBQYHCAkKCwEAAQUBAQEBAQEAAAAAAAAAAQACAwQFBgcICQoLEAAB BAEDAgQCBQcGCAUDDDMBAAIRAwQhEjEFQVFhEyJxgTIGFJGhsUIjJBVSwWIzNHKC0UMHJZJT8OHx Y3M1FqKygyZEk1RkRcKjdDYX0lXiZfKzhMPTdePzRieUpIW0lcTU5PSltcXV5fVWZnaGlqa2xtbm 9jdHV2d3h5ent8fX5/cRAAICAQIEBAMEBQYHBwYFNQEAAhEDITESBEFRYXEiEwUygZEUobFCI8FS 0fAzJGLhcoKSQ1MVY3M08SUGFqKygwcmNcLSRJNUoxdkRVU2dGXi8rOEw9N14/NGlKSFtJXE1OT0 pbXF1eX1VmZ2hpamtsbW5vYnN0dXZ3eHl6e3x//aAAwDAQACEQMRAD8A9VSSSSUpJJJJSkkkklKS VDN6507BdGS97GAw+0VvdWw/8LfWx1VX9tyjV1R1+fk4dTGN+ymomx7tHtubva+raP5L2JKdFJVc rMFN+Pisg35RcGbuAGDfY8/1VJ1tmM19mS9ppAG0taQ7cTt2/Sdu3OLdiSmwks7J6q/DupGZjmvH yHtqbkNcHhljztqbeyGurbY79H6jfUZ6it0ZWPkPuZS8Pdjv9O4D818NfsP9l7UlJkkkklKSSSSU pJJJJT//0PVUkkklKSSVTO6hRi2UY77G1X5bizHNgOwuHu2b/o+pt/mq936VJS+d1PC6fWLcuz06 y4Nc/a5wbPDrSwO9Kv8A4Sz2KWDlMzMVuRW5r2PLtj2GWkBzmNc13530VmYmTd0zPPTupO9SvMeT hZxAHqOMu+xZO32Nya2/0f8AMyKf+FrWfkdSr6Jn5XT+jN+235Lha3AaIqxnu/n7bb521U3e237P /pPU/wBKnQxymeGIs/y3WykIiyadHE6r6NL8HqOPbXkUAseTWTTa3tfXkx9n2Wt91nqvZ6f56xmd c6B0/qzbqr25YbiMxX0YrHXOD6nufVsc1vpbGstez+cRqvq7l9WcMjr+U7L1luO0lmO3yZS3+d/r 2LdowOnYFBFNLWMYOGtAH+a1Te3hhpKRyS7Q9Mf8aTHx5JaxAiO8t/8AFec6l9Yjnux7qOl9Qqvw 7PUx8htbARINdjH1WP8AfVdW7ZYxR6l9Z7czDfRk4ObhO9j6rm0eoG21vbfVa8Ms91e+v31rq6ng gFzBWHaNEalTNdZcS4AtPDYGnzS4sP8Amj/jyTWT98f4rztX1p6Z1XF9N9lRyKotdh7i2y2yr9LX TTXkNp+na1qPh5jOj/V71Hfp+pWD1raOHvy8p/trc36TN2Tb6P8Axat9S+r3SuosLcihj5/fbP3P /nG/5y57K6P1bpLTXhWHMwyWu/Z+S8nVh9St2Dm/zlNtbxvra9IYseT+bkYy/cyf9+r3JR+cafvR egqycnpdPTunXPd1DqOW4ixxdEAfpcvI49uPj7tlTP8AiaVqV302usbU9r3VO2WBpktdAdsf+67a 5q5no2Zi9SycrqFd9jMplYqyqLxGRjVVjc7HqrA932i7fa/J/qKHTM/J6f0vGqxcSeo9XvdcK7pY AbXeta97Ydd6eFi7PVf/AGP8IoJRlEmMhRHRkBBFjV61JCqyKbXWMrsZZZSdlzWEEtdAdsePzPa5 FQSpJJJJT//R9VSSSSUwteK632HhjS4/ISqz8LGy8B9GdGVReN1gf9GCN36OPobP8GrZAIg8Lnur YWD0XDv6g6/Jdj1e6vp3qk0OscYqpbXHqbHWf4H1fR/4NGMTIiI1JNBBIAJOwaGbn5+LSzoWJkHK zbP0teRe0F+JjabH5NmvrZLf8BZ/Of6T3qz0PAxMTH/QguY47nWv1fc/86+1353uWHQ708qvp+Va P2j1EnJ6jYTDiOW4tf8A57a3/jF1lOO8tbMMZAho8OyvZAMUBjj+lrKX738v0GrA+5MzltHSIT+s iNNskDT48JmNYwQ0fPupblVpn4l97wPcfuTeqh3WwA3uUMl7RJGiXCkFseqo2FljCywbmnkFADif gOSm9QeKQjWyrt53rOBZVn1X49n2XqTJOBm/m2AfSwsv9/8AtI2PmWdZec6uw9PzGj7J1dzjutxW NmwtwGRsrbm2fSyn/wDB/wCjWl1LGpz8KzGuO0Ebm2cFjm+5lwd+b6a5HD6w/HfV9YaXB92E4YvV 2M4uxydrckfvOq+m1ytcHv4v9ZDQfs/x/wDpsAl7WQD9Ce3g9H0rNxunOaWNLKrN9fT+nU1uOTkN 369RyPVd6jvU27vXv9P/AElln6RdUsF4xei4d3Vcd9ZrvLbHXPD7r795HpVtsdZvse7d6eLR9Baf Sn9Ssw229TayvIsJd6Vf5jD/ADdT3S7fa1v87t9m9UG03EkkklP/0vVUkkklKXJ/WvLZb1XFxLD+ rdPrd1DJHYlv6PGa7+3ucusXnf1guosu+sORlOLaS+vElujorZOxn8p1rlZ5ON5Cf3Y/9L0f90wc 1KsdfvH/ANCcjBos6lk42fkVF7Mq12S69pkt2Etox38Oqq/O9n07F3eN1MkBt+v8sf8Afl510f60 Y+Jj1YmRQa66htFlev8AacwrqsHqOJmM34trbR3AOo/rM+k1X5wjMa6tGM5QOmj1LbWvEtII8kK7 KFZ2jV35FlV2kagwfJZP1kv6/jt/aHTL99bGxfjOY18Af4av8/8A4xqrSwEbFsxzA7h6J1znGSZK QucDMrzhv1862Bq3Hd57SPyOTP8Ar115w9ooZ5hk/wDVOQ9iXgu96Pi+lOyLHcn5BZ3Uuv8ATOmM Lsy9rXdq2+55PgK2/wDfl5vlfWLruWC27MsDTy2uGD/wPaqeIyuy/wBO90Mv9rrDrtcf5uw/1X/S /kJw5fufsWnP2Dt9f+uuV1RrsbHBxsI8tn3vH/CuH5v/AAbUD6qZ9dfVBiX64+c00WtPB3CGrOxe k3ZLrG7mM9HcbJcJAaDue1v5zNEKmu+j0s0McK2WNLbIgFzTv2hyniOEUBQYJHiNk2X1f6ksqyMP 7BnN9XK+r+Q+qlzuzSCKbdv0d3pO2scuuXFfV270vrjlNbozqOHTkR/KA2ldqs7mY1ll/Wqf+P6p N/FLigD9FJJJKFkf/9P1VJJJJSl5V9aGuOJ1Uf8Am2dPw26L1VecfWjFIu69jRqH0ZzB/JI9O0/5 yt8kfVMeA/6UWtzY9MT4/seE2IuHdZh5VWTX9OpwdEkAx+a6PzVPYkKy4hrRLiYA8ytDhadvb9K6 zR1GourBZYyPUrPInwP5zVoi1ZOBg1YFIrqaA4geo7u53mrQsITuC2LjopRhdNa7eMWkOmZ2N5+5 cJ13EGP1fJY0Q1z97fg/3rt/VXMfWZhd1BlkaOrAB+BKBhS6M7NODsUqca2+1tNTd9jzDWhGbUXO DWiXOMADuSuj+r3SRVY7Ke8PeAawG6tB/P8Af+e7+ohwrjKlsf6vU4dddryHljLPtDe9he3Y2itL Etb1l2Lgsoa3FqpsfdWASK7IfVQ0k/56v9YyWYT8O62oWVC2SSTLTH0m1/Re9rfobkbpf1gwMlwr 2+nkW27GVNElw/Mtc6A36KEttAqIPVP0pr6/rlgMP0mdODX/ABBhd4uJ6G37R9d8y0asw6K6J/lR vf8A9Wu2WbzZ/WeUY/iOJ0cArGPqpJJJV2V//9T1VJJJJSlyv1sxmUdSwuoWD9Wymu6fmHsG2+7H e7+rauqVTqvTqeqdPvwL/oXtLd3druWWN/qP9ylwZODIJHbaX92SzLDjgR13Hm+P5XTr8bNfgubN rH7Gjxk+w/2l1mH0TFxKK2Gtr7me51pEnf4tP8lVr8fLvb6jmx1vozgzJr/0tbf5q9n729i3aHsy sevIrHttaHAHkeS1ZT0H41/L9JzuHcNN1SgaloOqUDUkMiw42j6PkqPWenOycI+mwvurIcwDkzo5 q2/STipH3ECDyfS/q9lPe6zJBx2gQzjdJ0JA/N9q6NtVOHinaAyqhhIHYABXG1KVmJXfWarW7q3f Sb8NUyWReIFweuYGd1Hp2K+ikus0ssrGhG5v8pZ/1YxRRff1bKGzHwK3Eudp74+j/Zau3ZWuf65Y 7q3UKvq7h61hzbOoObwBO6vH/rWfTeme76SDpEC5S/dj+kyRx6j8nT/xf4lv2K/qeQIvz7HXOn+W dzW/2WbF1iBh4zMXGroYIDBGnijrMyTM5ykf0jboRFADspJJJNS//9X1VJJJJSkkkklOD9YuiX5L 6+q9MhnVMUQ0HRt1f52Nb/6LVTpfU8bqdTtgNWRUduRjP0fW4ctc3/vy6lc19ZOl9JyMyuyrK+wd bLd1NlQLnuaP+5FLA7dT/LerOLOKEMmw+Wf7v9WX9Rgy4rPFHfrH97/0JOavJRNXksazrnVenMFP WaTSD/N9RoZ6tLh4vZ9JiFj9R6o5j3YGRj5zbHmzexwLhP5novc1zG/yVbhjlIWJRrob9J/wmtIg GiD9ju+l5JxUscda61Wwttwd1n5rtrgP80btynR1vqsMFnT3PI/nHAObP9QEbWInDlr9H/GigTh4 /Y67akRtSzLfrR0zFrLs1wxrPzadzbLD/wBbp3u/zlnu6j9YOvu9DpdD8DEd9LJsH6Zw/wCDr/wX 9dyiMZDWZEI/vSOn+D+//gskQD8o4i2eudeOO/8AZnSwL+p2iNNW0g/4W7/vla1Pqr9XW9KxvVtJ syriX22O+k5zvpPcodC+r2H0S1rLGbn3QW5DjuLrPz23OP8AhP8ARro1WzZhIcELENzfzTP9b/vW zjx8Op+b8lJJJKBkUkkkkp//1vVUkkklKSSSSUpY9luH0bIzM7Ja425ttYY5jS99ntZRTi1Ae5zm P37av5fqLYUXsa9pa8Ag9ikp5xnVBf1ZwBazpmTY/FoNomq7JYJvs3fm/Q+zY7N36a1mTZ/o0PqH 1X+rF99NeTQMTNyWve1tM8V7fVdurH0W72LVf0Gg4hwGODcEuYW0FoPpivZsbjO9vp/ze7+uhO3j 6zvyb2PZj0YYqotLSWOfZYbMiHD85jaaE6M5RNxkYn+qeFBiDoQD5uKz6m4e0WYvWL2VEloi8gSP pM5+k391K76i4VbQ/qHUrnVucGj1rnAEu+izVzfpJZ2BR1H6zUiysjAz/UaWOG31H1499d2Wxjvd 9HIpp9T/AIFFtGbn9Az8bKBdmdJpfSXkH33VbcinJZ+96tNWPb/15Sfec3+cl9q32sf7oZU9F+rP RzS77O4i60Utu2Q3c4Oczda/817men/XVvqXQ8vNwnenl7KXND/sbWNbUQPe1vrV7Mrf/wAN63/W 1Wt6W/qOK6vBy8v07xPoZAmqp2318d9D7K22t9G/0XV7LbP9GtHp/Rcumpjbsy0UOaDZggtdWxxE 2U05Dmfafs276Fe/6CilIyNyJJ7nVcABoBTWxvq30/IpNbnZeM4Bpc2vJvDCD7mPr3WOb/6TXQNb taGyXQAJPJjxTgAAACANAE6CVJJJJKUkkkkp/9f1VJJJJSkkkklKSSSSUpJJJJSxa0uDiAXN+ie4 nwSgfenSSUpJJJJSkkkklKSSSSUpJJJJT//ZADhCSU0EIQAAAAAAVQAAAAEBAAAADwBBAGQAbwBi AGUAIABQAGgAbwB0AG8AcwBoAG8AcAAAABMAQQBkAG8AYgBlACAAUABoAG8AdABvAHMAaABvAHAA IABDAFMAMgAAAAEAOEJJTQQGAAAAAAAHAAgAAAABAQD/4QmtaHR0cDovL25zLmFkb2JlLmNvbS94 YXAvMS4wLwA8P3hwYWNrZXQgYmVnaW49J++7vycgaWQ9J1c1TTBNcENlaGlIenJlU3pOVGN6a2M5 ZCc/Pg0KPHg6eG1wbWV0YSB4bWxuczp4PSJhZG9iZTpuczptZXRhLyI+PHJkZjpSREYgeG1sbnM6 cmRmPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5LzAyLzIyLXJkZi1zeW50YXgtbnMjIj48cmRmOkRl c2NyaXB0aW9uIHJkZjphYm91dD0idXVpZDpmYWY1YmRkNS1iYTNkLTExZGEtYWQzMS1kMzNkNzUx ODJmMWIiIHhtbG5zOnhtcE1NPSJodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvbW0vIj48eG1w TU06RG9jdW1lbnRJRD51dWlkOjhDQzlCNEI3Q0VFNkRDMTE5QkU3QkE3RTEwQTlFNkZGPC94bXBN TTpEb2N1bWVudElEPjx4bXBNTTpJbnN0YW5jZUlEPnV1aWQ6NEM0MENGMzZDRkU2REMxMTlCRTdC QTdFMTBBOUU2RkY8L3htcE1NOkluc3RhbmNlSUQ+PC9yZGY6RGVzY3JpcHRpb24+PHJkZjpEZXNj cmlwdGlvbiByZGY6YWJvdXQ9InV1aWQ6ZmFmNWJkZDUtYmEzZC0xMWRhLWFkMzEtZDMzZDc1MTgy ZjFiIiB4bWxuczp4bXA9Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC8iPjx4bXA6Q3JlYXRl RGF0ZT4yMDA4LTAyLTI5VDA5OjAwOjM1LTA1OjAwPC94bXA6Q3JlYXRlRGF0ZT48eG1wOk1vZGlm eURhdGU+MjAwOC0wMi0yOVQwOToxNToxMy0wNTowMDwveG1wOk1vZGlmeURhdGU+PHhtcDpNZXRh ZGF0YURhdGU+MjAwOC0wMi0yOVQwOToxNToxMy0wNTowMDwveG1wOk1ldGFkYXRhRGF0ZT48eG1w OkNyZWF0b3JUb29sPkFkb2JlIFBob3Rvc2hvcCBDUzIgV2luZG93czwveG1wOkNyZWF0b3JUb29s PjwvcmRmOkRlc2NyaXB0aW9uPjxyZGY6RGVzY3JpcHRpb24gcmRmOmFib3V0PSJ1dWlkOmZhZjVi ZGQ1LWJhM2QtMTFkYS1hZDMxLWQzM2Q3NTE4MmYxYiIgeG1sbnM6ZGM9Imh0dHA6Ly9wdXJsLm9y Zy9kYy9lbGVtZW50cy8xLjEvIj48ZGM6Zm9ybWF0PmltYWdlL2pwZWc8L2RjOmZvcm1hdD48L3Jk ZjpEZXNjcmlwdGlvbj48cmRmOkRlc2NyaXB0aW9uIHJkZjphYm91dD0idXVpZDpmYWY1YmRkNS1i YTNkLTExZGEtYWQzMS1kMzNkNzUxODJmMWIiIHhtbG5zOnBob3Rvc2hvcD0iaHR0cDovL25zLmFk b2JlLmNvbS9waG90b3Nob3AvMS4wLyI+PHBob3Rvc2hvcDpDb2xvck1vZGU+MzwvcGhvdG9zaG9w OkNvbG9yTW9kZT48cGhvdG9zaG9wOkhpc3Rvcnk+PC9waG90b3Nob3A6SGlzdG9yeT48L3JkZjpE ZXNjcmlwdGlvbj48cmRmOkRlc2NyaXB0aW9uIHJkZjphYm91dD0idXVpZDpmYWY1YmRkNS1iYTNk LTExZGEtYWQzMS1kMzNkNzUxODJmMWIiIHhtbG5zOnRpZmY9Imh0dHA6Ly9ucy5hZG9iZS5jb20v dGlmZi8xLjAvIj48dGlmZjpPcmllbnRhdGlvbj4xPC90aWZmOk9yaWVudGF0aW9uPjx0aWZmOlhS ZXNvbHV0aW9uPjcyMDAwMC8xMDAwMDwvdGlmZjpYUmVzb2x1dGlvbj48dGlmZjpZUmVzb2x1dGlv bj43MjAwMDAvMTAwMDA8L3RpZmY6WVJlc29sdXRpb24+PHRpZmY6UmVzb2x1dGlvblVuaXQ+Mjwv dGlmZjpSZXNvbHV0aW9uVW5pdD48dGlmZjpOYXRpdmVEaWdlc3Q+MjU2LDI1NywyNTgsMjU5LDI2 MiwyNzQsMjc3LDI4NCw1MzAsNTMxLDI4MiwyODMsMjk2LDMwMSwzMTgsMzE5LDUyOSw1MzIsMzA2 LDI3MCwyNzEsMjcyLDMwNSwzMTUsMzM0MzI7Q0VDQzU3RkZBN0QwNkVBMTNDODk0N0IzNjREQTNG QTY8L3RpZmY6TmF0aXZlRGlnZXN0PjwvcmRmOkRlc2NyaXB0aW9uPjxyZGY6RGVzY3JpcHRpb24g cmRmOmFib3V0PSJ1dWlkOmZhZjViZGQ1LWJhM2QtMTFkYS1hZDMxLWQzM2Q3NTE4MmYxYiIgeG1s bnM6ZXhpZj0iaHR0cDovL25zLmFkb2JlLmNvbS9leGlmLzEuMC8iPjxleGlmOlBpeGVsWERpbWVu c2lvbj4xNDQ8L2V4aWY6UGl4ZWxYRGltZW5zaW9uPjxleGlmOlBpeGVsWURpbWVuc2lvbj4xNDQ8 L2V4aWY6UGl4ZWxZRGltZW5zaW9uPjxleGlmOkNvbG9yU3BhY2U+LTE8L2V4aWY6Q29sb3JTcGFj ZT48ZXhpZjpOYXRpdmVEaWdlc3Q+MzY4NjQsNDA5NjAsNDA5NjEsMzcxMjEsMzcxMjIsNDA5NjIs NDA5NjMsMzc1MTAsNDA5NjQsMzY4NjcsMzY4NjgsMzM0MzQsMzM0MzcsMzQ4NTAsMzQ4NTIsMzQ4 NTUsMzQ4NTYsMzczNzcsMzczNzgsMzczNzksMzczODAsMzczODEsMzczODIsMzczODMsMzczODQs MzczODUsMzczODYsMzczOTYsNDE0ODMsNDE0ODQsNDE0ODYsNDE0ODcsNDE0ODgsNDE0OTIsNDE0 OTMsNDE0OTUsNDE3MjgsNDE3MjksNDE3MzAsNDE5ODUsNDE5ODYsNDE5ODcsNDE5ODgsNDE5ODks NDE5OTAsNDE5OTEsNDE5OTIsNDE5OTMsNDE5OTQsNDE5OTUsNDE5OTYsNDIwMTYsMCwyLDQsNSw2 LDcsOCw5LDEwLDExLDEyLDEzLDE0LDE1LDE2LDE3LDE4LDIwLDIyLDIzLDI0LDI1LDI2LDI3LDI4 LDMwO0IyOUFCMkQzQjc1Q0U3Q0M4MTczOUZFN0Q4OTE0RDUwPC9leGlmOk5hdGl2ZURpZ2VzdD48 L3JkZjpEZXNjcmlwdGlvbj48L3JkZjpSREY+PC94OnhtcG1ldGE+DQo8P3hwYWNrZXQgZW5kPSd3 Jz8+/+IMWElDQ19QUk9GSUxFAAEBAAAMSExpbm8CEAAAbW50clJHQiBYWVogB84AAgAJAAYAMQAA YWNzcE1TRlQAAAAASUVDIHNSR0IAAAAAAAAAAAAAAAAAAPbWAAEAAAAA0y1IUCAgAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAARY3BydAAAAVAAAAAzZGVzYwAA AYQAAABsd3RwdAAAAfAAAAAUYmtwdAAAAgQAAAAUclhZWgAAAhgAAAAUZ1hZWgAAAiwAAAAUYlhZ WgAAAkAAAAAUZG1uZAAAAlQAAABwZG1kZAAAAsQAAACIdnVlZAAAA0wAAACGdmlldwAAA9QAAAAk bHVtaQAAA/gAAAAUbWVhcwAABAwAAAAkdGVjaAAABDAAAAAMclRSQwAABDwAAAgMZ1RSQwAABDwA AAgMYlRSQwAABDwAAAgMdGV4dAAAAABDb3B5cmlnaHQgKGMpIDE5OTggSGV3bGV0dC1QYWNrYXJk IENvbXBhbnkAAGRlc2MAAAAAAAAAEnNSR0IgSUVDNjE5NjYtMi4xAAAAAAAAAAAAAAASc1JHQiBJ RUM2MTk2Ni0yLjEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAFhZWiAAAAAAAADzUQABAAAAARbMWFlaIAAAAAAAAAAAAAAAAAAAAABYWVogAAAAAAAAb6IA ADj1AAADkFhZWiAAAAAAAABimQAAt4UAABjaWFlaIAAAAAAAACSgAAAPhAAAts9kZXNjAAAAAAAA ABZJRUMgaHR0cDovL3d3dy5pZWMuY2gAAAAAAAAAAAAAABZJRUMgaHR0cDovL3d3dy5pZWMuY2gA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAZGVzYwAAAAAAAAAu SUVDIDYxOTY2LTIuMSBEZWZhdWx0IFJHQiBjb2xvdXIgc3BhY2UgLSBzUkdCAAAAAAAAAAAAAAAu SUVDIDYxOTY2LTIuMSBEZWZhdWx0IFJHQiBjb2xvdXIgc3BhY2UgLSBzUkdCAAAAAAAAAAAAAAAA AAAAAAAAAAAAAGRlc2MAAAAAAAAALFJlZmVyZW5jZSBWaWV3aW5nIENvbmRpdGlvbiBpbiBJRUM2 MTk2Ni0yLjEAAAAAAAAAAAAAACxSZWZlcmVuY2UgVmlld2luZyBDb25kaXRpb24gaW4gSUVDNjE5 NjYtMi4xAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB2aWV3AAAAAAATpP4AFF8uABDPFAAD7cwA BBMLAANcngAAAAFYWVogAAAAAABMCVYAUAAAAFcf521lYXMAAAAAAAAAAQAAAAAAAAAAAAAAAAAA AAAAAAKPAAAAAnNpZyAAAAAAQ1JUIGN1cnYAAAAAAAAEAAAAAAUACgAPABQAGQAeACMAKAAtADIA NwA7AEAARQBKAE8AVABZAF4AYwBoAG0AcgB3AHwAgQCGAIsAkACVAJoAnwCkAKkArgCyALcAvADB AMYAywDQANUA2wDgAOUA6wDwAPYA+wEBAQcBDQETARkBHwElASsBMgE4AT4BRQFMAVIBWQFgAWcB bgF1AXwBgwGLAZIBmgGhAakBsQG5AcEByQHRAdkB4QHpAfIB+gIDAgwCFAIdAiYCLwI4AkECSwJU Al0CZwJxAnoChAKOApgCogKsArYCwQLLAtUC4ALrAvUDAAMLAxYDIQMtAzgDQwNPA1oDZgNyA34D igOWA6IDrgO6A8cD0wPgA+wD+QQGBBMEIAQtBDsESARVBGMEcQR+BIwEmgSoBLYExATTBOEE8AT+ BQ0FHAUrBToFSQVYBWcFdwWGBZYFpgW1BcUF1QXlBfYGBgYWBicGNwZIBlkGagZ7BowGnQavBsAG 0QbjBvUHBwcZBysHPQdPB2EHdAeGB5kHrAe/B9IH5Qf4CAsIHwgyCEYIWghuCIIIlgiqCL4I0gjn CPsJEAklCToJTwlkCXkJjwmkCboJzwnlCfsKEQonCj0KVApqCoEKmAquCsUK3ArzCwsLIgs5C1EL aQuAC5gLsAvIC+EL+QwSDCoMQwxcDHUMjgynDMAM2QzzDQ0NJg1ADVoNdA2ODakNww3eDfgOEw4u DkkOZA5/DpsOtg7SDu4PCQ8lD0EPXg96D5YPsw/PD+wQCRAmEEMQYRB+EJsQuRDXEPURExExEU8R bRGMEaoRyRHoEgcSJhJFEmQShBKjEsMS4xMDEyMTQxNjE4MTpBPFE+UUBhQnFEkUahSLFK0UzhTw FRIVNBVWFXgVmxW9FeAWAxYmFkkWbBaPFrIW1hb6Fx0XQRdlF4kXrhfSF/cYGxhAGGUYihivGNUY +hkgGUUZaxmRGbcZ3RoEGioaURp3Gp4axRrsGxQbOxtjG4obshvaHAIcKhxSHHscoxzMHPUdHh1H HXAdmR3DHeweFh5AHmoelB6+HukfEx8+H2kflB+/H+ogFSBBIGwgmCDEIPAhHCFIIXUhoSHOIfsi JyJVIoIiryLdIwojOCNmI5QjwiPwJB8kTSR8JKsk2iUJJTglaCWXJccl9yYnJlcmhya3JugnGCdJ J3onqyfcKA0oPyhxKKIo1CkGKTgpaymdKdAqAio1KmgqmyrPKwIrNitpK50r0SwFLDksbiyiLNct DC1BLXYtqy3hLhYuTC6CLrcu7i8kL1ovkS/HL/4wNTBsMKQw2zESMUoxgjG6MfIyKjJjMpsy1DMN M0YzfzO4M/E0KzRlNJ402DUTNU01hzXCNf02NzZyNq426TckN2A3nDfXOBQ4UDiMOMg5BTlCOX85 vDn5OjY6dDqyOu87LTtrO6o76DwnPGU8pDzjPSI9YT2hPeA+ID5gPqA+4D8hP2E/oj/iQCNAZECm QOdBKUFqQaxB7kIwQnJCtUL3QzpDfUPARANER0SKRM5FEkVVRZpF3kYiRmdGq0bwRzVHe0fASAVI S0iRSNdJHUljSalJ8Eo3Sn1KxEsMS1NLmkviTCpMcky6TQJNSk2TTdxOJU5uTrdPAE9JT5NP3VAn UHFQu1EGUVBRm1HmUjFSfFLHUxNTX1OqU/ZUQlSPVNtVKFV1VcJWD1ZcVqlW91dEV5JX4FgvWH1Y y1kaWWlZuFoHWlZaplr1W0VblVvlXDVchlzWXSddeF3JXhpebF69Xw9fYV+zYAVgV2CqYPxhT2Gi YfViSWKcYvBjQ2OXY+tkQGSUZOllPWWSZedmPWaSZuhnPWeTZ+loP2iWaOxpQ2maafFqSGqfavdr T2una/9sV2yvbQhtYG25bhJua27Ebx5veG/RcCtwhnDgcTpxlXHwcktypnMBc11zuHQUdHB0zHUo dYV14XY+dpt2+HdWd7N4EXhueMx5KnmJeed6RnqlewR7Y3vCfCF8gXzhfUF9oX4BfmJ+wn8jf4R/ 5YBHgKiBCoFrgc2CMIKSgvSDV4O6hB2EgITjhUeFq4YOhnKG14c7h5+IBIhpiM6JM4mZif6KZIrK izCLlov8jGOMyo0xjZiN/45mjs6PNo+ekAaQbpDWkT+RqJIRknqS45NNk7aUIJSKlPSVX5XJljSW n5cKl3WX4JhMmLiZJJmQmfyaaJrVm0Kbr5wcnImc951kndKeQJ6unx2fi5/6oGmg2KFHobaiJqKW owajdqPmpFakx6U4pammGqaLpv2nbqfgqFKoxKk3qamqHKqPqwKrdavprFys0K1ErbiuLa6hrxav i7AAsHWw6rFgsdayS7LCszizrrQltJy1E7WKtgG2ebbwt2i34LhZuNG5SrnCuju6tbsuu6e8Ibyb vRW9j74KvoS+/796v/XAcMDswWfB48JfwtvDWMPUxFHEzsVLxcjGRsbDx0HHv8g9yLzJOsm5yjjK t8s2y7bMNcy1zTXNtc42zrbPN8+40DnQutE80b7SP9LB00TTxtRJ1MvVTtXR1lXW2Ndc1+DYZNjo 2WzZ8dp22vvbgNwF3IrdEN2W3hzeot8p36/gNuC94UThzOJT4tvjY+Pr5HPk/OWE5g3mlucf56no Mui86Ubp0Opb6uXrcOv77IbtEe2c7ijutO9A78zwWPDl8XLx//KM8xnzp/Q09ML1UPXe9m32+/eK +Bn4qPk4+cf6V/rn+3f8B/yY/Sn9uv5L/tz/bf///9sAQwADAgIDAgIDAwMDBAMDBAUIBQUEBAUK BwcGCAwKDAwLCgsLDQ4SEA0OEQ4LCxAWEBETFBUVFQwPFxgWFBgSFBUU/9sAQwEDBAQFBAUJBQUJ FA0LDRQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQU/8AA EQgAkACQAwEiAAIRAQMRAf/EAB8AAAEFAQEBAQEBAAAAAAAAAAABAgMEBQYHCAkKC//EALUQAAIB AwMCBAMFBQQEAAABfQECAwAEEQUSITFBBhNRYQcicRQygZGhCCNCscEVUtHwJDNicoIJChYXGBka JSYnKCkqNDU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6g4SFhoeIiYqSk5SV lpeYmZqio6Slpqeoqaqys7S1tre4ubrCw8TFxsfIycrS09TV1tfY2drh4uPk5ebn6Onq8fLz9PX2 9/j5+v/EAB8BAAMBAQEBAQEBAQEAAAAAAAABAgMEBQYHCAkKC//EALURAAIBAgQEAwQHBQQEAAEC dwABAgMRBAUhMQYSQVEHYXETIjKBCBRCkaGxwQkjM1LwFWJy0QoWJDThJfEXGBkaJicoKSo1Njc4 OTpDREVGR0hJSlNUVVZXWFlaY2RlZmdoaWpzdHV2d3h5eoKDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uLj5OXm5+jp6vLz9PX29/j5+v/aAAwDAQAC EQMRAD8A/VOiiigAooooAKKKKACiuC8afHDwj8P7nZrd5eW1sjiOfUItOuJrO1J/57TohjjHqWIA 7kVDpfxSm8QePfEfhuxtbS2XQmsmkvLy5+W8huY/MR4Qo/2XXk8lfSgD0OiuZ8U+MBomueH9Ct1j fVtbllW3ExOxI4k3yuQOTgbQFGMlhyBmprnVLvwxb3l7rd7azaZGqCN4YGjm8xm2hMbiG3FlC4wc nHPWgDoKK898S/FS58D61o0fiPw/NY6Hq15Hp8WsW1ys6W1zIdsKXCYBjV2IQOu5QxUEjINdZoni rSfEd5q1rpt9FeT6TdfYr5I8nyJ9iv5bHpna6Hj+9QBrUUUUAFFFFABRRRQAUUUUAFFFcl42+IOl +EtR0PRrrUrbTNW1+drXTHvkcQSSqAxQuBtDlc7EJBcjAzzQBL46+JXh34bafHf+Ib5rGxaZYZLl YJJY7csCVaYop8pOMb3woyMmrHgbxVB448LwazZ3Ntd2lzJMILmyffFKiyuiurZIYEKDkcHtXmnh PxJqHwo8eSeDfG9wNQs/Ed3JJoHiuaNU+3SNljp91gBVnRciM8LLGuAAykHz3X/iTa/APx94n8Hf DS3Hi/V9ZmXUIfCNugjs/D9w4P2iea4BxFFIdsnkgZDlyMB66sNha2Lqezoxu/wS7t7JebMK1enh 4c9R2R6N4R+K66Jo914U8Z+HtUsNd0xXt5mk0920/UoskC4juseTskX5mWRlZSWDDjJ8ZtPjh8LP hr8WYdR0/WrfxRHH4YttCm0rw1Zy6jNHPbzu8RRlUx7FSWRc78/Ktbel/s6698YrmLV/i94nn8Tj d5kei27NbaRAfRIFIMuP7z9cV7poXgDwh8OdEddN0a1tbW2TJjtoVRfptUAV7DwuAwnu1pupPtHR L5tNv7keasRisRrSiox7y1f3L/M+c/iN+0Q/xEutA1PSfhf8RtO1bw/em90zWIbCBSpZGjkjkikc b4pI2KspwehBBANVviT+05e+N/CF5pOteB/HXhCYC3urPUoNDF2lveQTJPFM4SUkx741DJxwTznB r6v0y9SSOKSe0hsopmCxRmL5mJ6duPxq3JptrPcSGdIZYm+7EYVG3/gXU0nXy9Ozwz/8Dd/8i1Tx nSqn/wBunzrpf7U3gz4w+FzZXOoaU2tWIS/k8NrO8N3qFzARLHBDHcJH96RExkk9vet3wd4ytvgj +zyL2fbrPju7UajeaUvyXF3rN/P8sTKcMoNxKIwSBhE9FrrfiN+z14G+Jti8Or6JY3hYHBuoA5U+ z8Op9w1fPPin4PeO/g3bPZeFr6Xxb4XaSOYeDvEV2zgtE4kjawvvvwyIwDKrHAI79KqOAwmNX+x1 HGX8s7fhJW/FW7sTxdbD/wC8w07x/wAj6A03xLq/wl0f4d+C9Su7jxz46164ZbqaWfZtQZlvLrJB 2wRbgqLj+KJM5Oa9R03XNP1ie/hsb23u5bCf7LdpDIGMEu1X2OB91trqcHswr5k+DfjLRPil4l8U +L7PXtRs/EMFlHYazpWsx7NW8PWcChntoYwPm86XfI0464QAZVcV/hp471n4b/DDw3Y6B4RZ/HXj 7WZtRSy1cvbRpJcSGaaR1wZTHbW+wOxABKKoYlxXhVqNTD1HSqxtJdGepCcakVKDuj6xorN0nxBp 2s3F9a2eo2l7eadKLe+itZVc28xUNscAkqdrA4POCK0qxLCiiigAooooAranerpum3V24ylvE8rD 2UE/0rl77wVo/jTwJeaX4rEfiTSdUTz7lL0AxBWAYeXjGwLgFSDuBGQc812DKHUqwDKRggjgivnj 4r+CfDPwK8G614xl17xPNodiDLa+DW1Zm02a5dsRQJGRv2NIR+6D7B/dwMVrSpTrVI0qavKTsvVk TnGnFzk7JHDeM/Hninwno1p8KPDviCTxJ4qvGF9baxrVur3HhrS8Dy5LmQEia4HzCN8BiNpbLcno Pgd4B0HwdoB/s2KS4tpZTLLqN2d9xqk+fnuJXPLAtnHb045PiOhzDTvFWn+ENe1WI+OPFztrfiq9 aTbJIMZWyiPbA+QKOiq5Havq7R9AnntoGcpZWoQCOJByEAwAB0AxivucVTjluGjhKL1lq338/T+V dFru9Pk8PUePryxFX4Y6Jf1+Pd6bI3f7bJYAH2wK0YJr5ZHRBsIxkt0P0qOzggsYgkSADuzck/jV jz/evmHT7I932xK19cwoftDLycDb3qMang//AF6zdZ1TyY1j4LPzg9QPas+Zri3iWSRCqHv6fWod I0jU01Oi/tIf5NQX722qWklpdxLPbyDDI38x6H3rChuXlLHDBF+8xU8VC2pAMcNkdjTVNxaa3Kcl JWZ88/GPwLdaT4+0rVNI1EeGvHtuGbw14oAxDfqvLWF4OjgjjDZ4ORxkDX8O+MLv44XTeLLK/l8C eKIIv+Ed8bTTuZrzw3BGGkZNPQqVjFy+Cbht2AiHBKjHpXxH8Naf8RPBepaJqMot4pE82K9ztazm T5knVu20jJPpkd6+RvB3xhuPDN9pvxk0yZLrVPDcqaF42trNsx6pphcKt0APvNGdrBvTHYGvrfYL OsFZr97DRPvfZektrdJWasmz52NV5ZilTb/dz28u6+XR9tN0fRXws8Z6P8MJoHtrWW2067+02Xhr wbpGnyPrGuR/aAW1W481t53hd3my7FwzMzkuoH1Wp3KDgjPY9q8EuotD+BPg3WfH+kXWmvZ6o8d5 Lqd1FPqGqav5rDyolkMgaRzuCRRD5eVAAGa9M+FV34w1HwfBfeOLeysNbu5HnGnWKnFnCxzHDIxY h5QuN5Hy7iQMgAn89asfXHYUUUUAFFFFABXyd+1b4rt9W+K3hbw9eOP7A8J2M3jHVlJ+V3TMdqjf 8D3Nj6V9Y1+d/wAf9X0vVNZ/aD1fXrqW30x7m08PeZbkCXZDBkxp/tGRhx3719Tw7RVTFSqP7Mfx bUfwTb+R89nlZ0sMor7T/LX9EeS+B9Fuvij4k8OeLdY0qW6tdc1CbWpdVt3DPAYmZbe2fJBjjAG4 lclmODjFfdnhn4ltJEkOqZdhwLlByf8AeH9RX50/B39qDSvB3h/S/D+r6FLZWVlEIUvLBvMB9WeM 4OSTk4J5PSvqnwL8RNC8bWAu9C1W21KIcssT4dP95D8y/iK++xOGpYumlPVr8PQ+EoV6uFm3HRfg z6ittThvIw8EySoe6HNZ+r+J001jCnzz4zg9F+teVafqrQsGSRkb1U4NeSftI698UvDVt/wmHgbW vtlnbQhdR0S5tI5wirn9/Hkbjx95c9sjvXzFTK5Rdov7z6WjmUJfGj6Lm1mS5lMkkhZz39KE1iSN wwkOQcjJzX5xQft5/EiOICW28PTN/fNqy5/APio739uj4n3SYgj0OyJ/ijsS5/8AHmNZf2ZW7I7f 7So+f3H6TzeIrq7OGlZu21OP0FeffEf4+eC/hRYtP4j12C2lHC2UB865kP8AdEa8j6nA96/NnxV+ 0T8T/GUbxaj4y1GO3fgwWLC2THp+7AJ/OuQ8KWdrqOufYdWnaO11L9xJdyksYZT/AKuYk9drYz/s lq6aeUtv339xzVM0UV+7j957f8fv209c+LkE+iaNG/h3wq5xJAJM3F4P+mrDov8AsLx6k1ifspeP bXTvijH4f1QrLofie3k0m8hf7rB1IX+ZH41514W+FGo+J7nUYhc2VoNOErXXmXCl0SMMXdUzllBA GR/eGM1k6NYanoB0zxRHY3MdlbXsbRXewiNpUIfYH6E4Br36UHQp+zgrRPnqtT6xU55yvJfh2P1f /YotLLxL4OHhHxVbLqXiP4T65c6fYS3DE+XGykQzBc4LeWxUMQSB0xmvraviz9nbWRpX7YniiGMN FbeLfC1hrBibj96q7ST78HP1r7Tr83zmkqeNm1tK0v8AwJJv8bn6JgKvtcNCT9PuCiiivEPQCiii gAr8rP2ooJJvCXxWXkkfEuQuPbyhj+lfqnX5x/tQ+FpE1f49aKE+dLvTPFNuo53RsgjlI+jZzX2P DUl7WrHul/6Ul+p8xn0W6UJef6P/ACPhH7D7CtbwdrV34J8U6brtioNzZTLKI2dlWUDqjEc4NWvs Q/yKdHprTypFEu+WRgiJjksTgD8zX6N7I+J5rn238KfjLpfxO0uSezSSzvrbaLqxl5aInoQRwynB wfbnFeiw6rx14x0ryfwH4Fsvh3o0dnY2qR3Dopupx9+aQDkk+mc4HQV1MepMowcg1u8LzI8z6yoy 02NKHwV4Qtrg3EfhbRUmLby4sIs59fu18KfHXwkvhv4t+JrWJAlvLcm7hCjACSjeAPoSR+Ffbp1X ivmL9piza58f2l2yEJLYRqr44YqzA/zFZPC8mp00sTzyseC/YfYVb0jw1e+INUttO0+2a6vLlxHF Ev8AEfr2HcntitmDS3up44YY2lmlYIiIMlmJwAPxr6M/Z5+EqaPqF1r9xeRXlzGrWiJbDdFGxxvx J0ZhjadvAyRk1KpLqdE6vKiHw7+z1p/gfT9O1CeSK8ktbW8GpREENqDSw7Ft4+RheoHck560nhLV ovjhN4V8KWuhQW3hyy0q7uNQs4kLx2Vzskit0LEDBGQw4yS2e1d/8YvElv4EvfB2pX+lR6hp8eoF mdpG3QsF5dYhhXYKSVJPBzxzmtj4X/H/AML+K7iKy+znT9avtQNrb2FvCWedP4JnbAA4yTk8YNZV naLcFoZ0oyk05PU2/hZbT6b+2R4CtZP9bb+BY4JwTyGEhHP4g19318U/A+3/AOEm/bd8YX8fzW/h 3SLXSQ4HHmbC7j8C9fa1fl2eyUsWl2jH8Vf9T9NyuLjhlfuwooor549YKKKKACvlj9rHw5baD8SP BnjC8jH9g63BN4O11yPlSKfLW8jewk3DPuK+p65P4q/DrTviz8Ptb8J6oCLXUrdohKo+aGTqki+6 sFYfSvTy3FLB4qNSXw7P0ej+a3XmjhxuH+s0JU1vuvVf1Y/IDxN8O9S8K+Nb3wtLA0mpW919ljQD /W5OI2HswINfWHg74JaH4O0LTraTTbW81O3ImlvpYgzmbuVJ6AdAPbPWuZ1zQNc8Qwi6ntxH8XPh 1KltqtoBk6lbIcxXKD+IMvIPuR6V7xoV7beLPD2n6xZqy217Csyq4wVz1U+4OR+FfrlbEtQi/vt3 3T9GtV3R+Z+wbbX9f0upx9xpOTnbVKTSefu13s2le1VJNJ5+7ThjPM5Z4XyOJGkc/d/GuH+M3w8l 8VeDXNnaPdanZyLLbxwrl3yQGUfUHP8AwGvaxpXP3akj0rB+7WjxlyI4Zxd0fJ3ww/Z61u+vZrzW 4ptDhSMpASFMxZuCQM/LhSwBPQkHHFfRcGlad4H8Kv5McdnpmmWrFUzhVVVJxn1J/Mmuyg0rkcVN feFLTX9NmsL+3FxZzgCSIkgNggjpz1Ariq4xN67HbDDuR4P8cPAfiT4m/Djwtc6To0lxfAreXNnG wV4g8Q4AYgnBOMda4L9mHwrH4e1zXviDrsLWuh+FLKeR5ZlwDPtOVGe4UH8WHrX23aacSQSPxr5+ +OF/N8Y/iBpfwZ8NjzLJJ4r3xNPAPlVAwaO1yP4nOGb2ArkWPTpzpz0ildvsuvzey82ejSwTlONt +x6Z/wAE/vCV9/wheueOtYiMer+K76XUZQ45USNuVfwXYK+sKxvB/hq38IeG7DSbVFWK2iCfKMAn ua2a/LcViJYuvOvLTmbfp2XyWh+iUqapQUF0CiiiuU1CiiigAooooA8K/aL+COp+KLyw8feBGjtP iHocZSNHO2LVbXq1pN9eSrHofrkch8MPiZo/xU0yb7PG+ma5Yt5GpaJeLsubKYcFWU84znDdD9eK +pK+av2kPhj4F8SeM9OvLHxUvgb4tNAZbG901GlnnhXj/SYUBLQ5GN7ADqMnGK+mwGZwUFh8U7Jf DLfl8musfxXS+x4WNwDnJ1qC1e67+fk/zN6bSueVqrJpOD93rXjd/wDHHxv8MbRNN+JmjPpanH2b xlolr9v024HZpIx8yZ74PHoKzdA+InjW6sr6Xwp4h8PeNYbu6a7+0Wk6yTx5HMYhdgyL0+XHFfX4 fB1a0OeNSNujvo/nt8nr5HzFacKUuWUXftbX7t/0PcxpPP3akTSefu15DF8Z/iNp1jLDqHgZpr05 EdwttNGq8cZQZz69RmrmhfG3xuy2Ud54BuLxkJF1PFHJDvHYoCMKR7k59q6JZbjUm1yv/t6P+ZhG vh72d/uZ65DpXI+UVoQaYFGSAB715jqn7T/gzwlYyS+KJ4/D96MCPTFuo7y7lPoI4SxB/wB7Fef3 PxE+K37RVydK8B6Ld+B/DcvEmt36f8TCZO/lR9IuP4mOR2xXj1KNamnKu1CPdvT5Wvzekbnp0oxq O1Jcz/rft8zpvjj8en8OX3/CDeA401r4gXq7cIN8OloePOnPQEdVTqTjPv6j+yr+zvB8HvDRvtQd 77xFqDNc3d7ccyzSvy8jn1PYdhVH4F/s9eH/AIDanBbXlis13qGHj1eeQytPdcl1mYj/AFh6qeh+ YDBAB+i6+Wx+YRrR+r4e6p7tveT7vsl0XTd3Z9LhMJ7D356y/Ben+YUUUV4Z6YUUUUAFFFFABRRR QAV5FqOqeHvghr/jHxTrltO+oeJNQtFt57W3ae5vj5ccEFnEo5LKwciMY++zd2I9dqG7s4L+Bobi JZomBBVh7YoA+c7T4oJr3xXukjltrXwBrV7PoGmtqMXmWeq6tEoM8oY/dGYzBGoIEjxzt8xCg5vx A/Ze+DHiDXNHs9c0KPwx4u1iG4uYYdGMmSINpmcNGBgLvTk4+8B1r1S++BGmzeFJPCNtOkPg9pre SHSngDfYFhMZRLVgR5YBiVgSCVYlgcmsy4E8f7Tl5rWq2V5aaLpfhaOx0+/khZraaae5aS52sAQG VYbcHOPvH0rejiK2Hlz0ZuL7ptfkZ1KUKqtUimvNXPFbT9jbw81tHeaD8X9ftbB5GhTy9cdVDj7y cscMO69R3p2sfsL+G9NhjuPGHxH1qeyllWBf7V1qVY5HY4VBllBYngDqaXxv4E0v4l/tMaQl3prx eDPFRuoDbTxmL7fPBpl1HPeojAEfLcwRh8AsYQegUnU1OPxJ8QvgH470XXUkm8U+AdLudMe4lhOL y/tytxBdpx83mRRW0mRnBmZeCDXo/wBsZh/z/l9+v37nKsDhV/y7X3FjR/gt8GfgjLpE48P3Miah qEenR6mLPbCJXR2QtK/JVjGUBBPzMo6HNdb8S/gbr3jzwXcG08XCz0yWFbgeG4bSOOxlVcOqmePb cB+BiUSDnqpGVPM6n8Lp/if4UurTwt4r8XNZ6lH5h0rXow9hp0nli4tpIHkiWRTHN5LLtdxgFTwO PRvh98Ftc0TTbSDUvGOrxaPNAklz4UjkimtbWVgDLBDcmMT/AGcMWCoW4XABA4rzKlWpWlz1ZOT7 t3f4nZGEYLlirLyOY8M/s3+FfEekSWcs/jDw/cRpE8kWn+J9QW3lVgHjkjDSsvbOOqsCPQn6DtYP s1tFCZJJjGgTzJTl3wMZJ7k96fHGsMaoihEUBVVRgADoBTqyKCiiigAooooAKKKKACiiigAooooA KKKKAIpLWGWeKZ4o3miyI5GUFkz1we2aeqKpYhQCxySB1NOooAKKKKACiiigAooooAKKKKAP/9k= This feature class was created from legacy GIS data in April of 2010. The original origin of the data is not known. This feature class was updated in the summer of 2012.