20250606 14302200 1.0 FALSE GISOWNER.Flood_Hazard_Zones Server=MAPS-SQL; Service=sde:sqlserver:MAPS-SQL; Database=mapssde; User=GISOWNER; Version=sde.DEFAULT ArcSDE Connection 002 3618910.386815 3858558.216901 600136.732585 806179.644645 1 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_Louisiana_South_FIPS_1702_Feet <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/3.3.0'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Louisiana_South_FIPS_1702_Feet&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,3280833.333333333],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-91.33333333333333],PARAMETER[&quot;Standard_Parallel_1&quot;,29.3],PARAMETER[&quot;Standard_Parallel_2&quot;,30.7],PARAMETER[&quot;Latitude_Of_Origin&quot;,28.5],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;EPSG&quot;,3452]]</WKT><XOrigin>-124791100</XOrigin><YOrigin>-91255500</YOrigin><XYScale>3048.0060960121918</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>2</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102682</WKID><LatestWKID>3452</LatestWKID></ProjectedCoordinateSystem> ExportFeatures "FEMA Floodplain Data\Flood Hazard Zones" X:\Vertex\PROJECTS\PORTAL\EXTERNAL_atlas\atlas-sql.sde\atlassde.GISOWNER.FEMA\atlassde.GISOWNER.Flood_Hazard_Zones # NOT_USE_ALIAS "FLD_AR_ID "FLD_AR_ID" true true false 11 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,FLD_AR_ID,0,10;FLD_ZONE "FLD_ZONE" true true false 55 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,FLD_ZONE,0,54;FLOODWAY "FLOODWAY" true true false 30 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,FLOODWAY,0,29;SFHA_TF "SFHA_TF" true true false 1 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,SFHA_TF,0,0;STATIC_BFE "STATIC_BFE" true true false 14 Double 2 13,First,#,FEMA Floodplain Data\Flood Hazard Zones,STATIC_BFE,-1,-1;V_DATUM "V_DATUM" true true false 6 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,V_DATUM,0,5;DEPTH "DEPTH" true true false 14 Double 2 13,First,#,FEMA Floodplain Data\Flood Hazard Zones,DEPTH,-1,-1;LEN_UNIT "LEN_UNIT" true true false 20 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,LEN_UNIT,0,19;VELOCITY "VELOCITY" true true false 14 Double 2 13,First,#,FEMA Floodplain Data\Flood Hazard Zones,VELOCITY,-1,-1;VEL_UNIT "VEL_UNIT" true true false 20 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,VEL_UNIT,0,19;AR_REVERT "AR_REVERT" true true false 6 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,AR_REVERT,0,5;BFE_REVERT "BFE_REVERT" true true false 14 Double 2 13,First,#,FEMA Floodplain Data\Flood Hazard Zones,BFE_REVERT,-1,-1;DEP_REVERT "DEP_REVERT" true true false 14 Double 2 13,First,#,FEMA Floodplain Data\Flood Hazard Zones,DEP_REVERT,-1,-1;SOURCE_CIT "SOURCE_CIT" true true false 11 Text 0 0,First,#,FEMA Floodplain Data\Flood Hazard Zones,SOURCE_CIT,0,10" # ExportFeatures "Flood Hazard Zones" X:\Vertex\PROJECTS\PORTAL\EXTERNAL_maps\mapssde(GISOWNER).sde\GISOWNER.FEMA\GISOWNER.Flood_Hazard_Zones # NOT_USE_ALIAS "FLD_AR_ID "FLD_AR_ID" true true false 11 Text 0 0,First,#,Flood Hazard Zones,FLD_AR_ID,0,10;FLD_ZONE "FLD_ZONE" true true false 55 Text 0 0,First,#,Flood Hazard Zones,FLD_ZONE,0,54;FLOODWAY "FLOODWAY" true true false 30 Text 0 0,First,#,Flood Hazard Zones,FLOODWAY,0,29;SFHA_TF "SFHA_TF" true true false 1 Text 0 0,First,#,Flood Hazard Zones,SFHA_TF,0,0;STATIC_BFE "STATIC_BFE" true true false 8 Double 2 13,First,#,Flood Hazard Zones,STATIC_BFE,-1,-1;V_DATUM "V_DATUM" true true false 6 Text 0 0,First,#,Flood Hazard Zones,V_DATUM,0,5;DEPTH "DEPTH" true true false 8 Double 2 13,First,#,Flood Hazard Zones,DEPTH,-1,-1;LEN_UNIT "LEN_UNIT" true true false 20 Text 0 0,First,#,Flood Hazard Zones,LEN_UNIT,0,19;VELOCITY "VELOCITY" true true false 8 Double 2 13,First,#,Flood Hazard Zones,VELOCITY,-1,-1;VEL_UNIT "VEL_UNIT" true true false 20 Text 0 0,First,#,Flood Hazard Zones,VEL_UNIT,0,19;AR_REVERT "AR_REVERT" true true false 6 Text 0 0,First,#,Flood Hazard Zones,AR_REVERT,0,5;BFE_REVERT "BFE_REVERT" true true false 8 Double 2 13,First,#,Flood Hazard Zones,BFE_REVERT,-1,-1;DEP_REVERT "DEP_REVERT" true true false 8 Double 2 13,First,#,Flood Hazard Zones,DEP_REVERT,-1,-1;SOURCE_CIT "SOURCE_CIT" true true false 11 Text 0 0,First,#,Flood Hazard Zones,SOURCE_CIT,0,10" # Rename X:\Vertex\PROJECTS\PORTAL\EXTERNAL_maps\mapssde(GISOWNER).sde\GISOWNER.FEMA\GISOWNER.Flood_Hazard_Zones X:\Vertex\PROJECTS\PORTAL\EXTERNAL_maps\mapssde(GISOWNER).sde\GISOWNER.FEMA\GISOWNER.Preliminary_Flood_Hazard_Zones FeatureClass 20250626 11103000 20250626 13152700 150000000 5000 ItemDescription 20250626 ArcGIS Metadata 1.0 SDE Feature Class Enterprise Geodatabase Feature Class Preliminary Flood Hazard Zones vector digital data <div style='text-align:Left;'><div><div><p style='text-align:Center;'><span style='font-weight:bold;font-size:16pt'>PRELIMINARY FEMA FLOOD HAZARD ZONES</span></p><p style='text-align:Center;'><span>This dataset contains polygons representing the preliminary flood hazard zones for St. Tammany Parish as set forth by FEMA.</span></p><p style='text-align:Center;'><span>This data is updated by the Federal Emergency Management Agency.</span></p><p style='text-align:Center;'><a href='https://www.fema.gov/flood-maps/national-flood-hazard-layer' style='text-decoration:underline;'><span>https://www.fema.gov/flood-maps/national-flood-hazard-layer</span></a></p></div></div></div> St. Tammany Parish Preliminary Flood Hazard Zones from FEMA ©2025 Federal Emergency Management Agency - National Flood Hazard ©2025 St. Tammany Parish Government - GIS Division of the Department of Technology Last Updated: 911 Major Roads fema flood hazard zones preliminary <div style='text-align:Left;'><div><div><p style='text-align:Center;'><span style='font-weight:bold;font-size:8pt'>For planning purposes only. It is not a legally recorded plan, survey, official tax map or engineering schematic, and it is not intended to be used as such.</span></p><p style='text-align:Center;'><span style='font-size:8pt'>©2025 St. Tammany Parish Government - GIS Division of the Department of Technology</span></p></div></div></div> See access and use constraints information. Microsoft Windows 10 Version 10.0 (Build 19045) ; Esri ArcGIS 13.1.0.41833 true -90.248062 -89.630952 30.674625 30.277547 1 -90.263687 -89.495107 30.712420 30.137590 0 atlassde.GISOWNER.Major_Roads Feature Class 0 OBJECTID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. OBJECTID OID 4 10 0 FLD_AR_ID FLD_AR_ID String 11 0 0 FLD_ZONE FLD_ZONE String 55 0 0 FLOODWAY FLOODWAY String 30 0 0 SFHA_TF SFHA_TF String 1 0 0 STATIC_BFE STATIC_BFE Double 8 13 2 LEN_UNIT LEN_UNIT String 20 0 0 DEPTH DEPTH Double 8 13 2 V_DATUM V_DATUM String 6 0 0 VELOCITY VELOCITY Double 8 13 2 VEL_UNIT VEL_UNIT String 20 0 0 AR_REVERT AR_REVERT String 6 0 0 BFE_REVERT BFE_REVERT Double 8 13 2 DEP_REVERT DEP_REVERT Double 8 13 2 SOURCE_CIT SOURCE_CIT String 11 0 0 Shape Feature geometry. ESRI Coordinates defining the features. Shape Geometry 8 0 0 Shape.STArea() Shape.STArea() Double 0 0 0 Shape.STLength() Shape.STLength() Double 0 0 0 dataset EPSG 8.9.3(10.0.0) Simple FALSE 0 TRUE FALSE iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAu IwAALiMBeKU/dgAAIABJREFUeJzsfQecFOX9/jMz267QRMWKFbuiCEpHsCD2hl1j1MSosRsLxhJL Yv7+LEk0mqgx1ljoRbAiRezYBexgwUq7tre7M/P/PN933r3Z2d3bOwG9vZvn43nc7pR3Zt73mW// RlzXdREiRIgQZYDILz2AECFChGgpQsIKESJE2SAkrBAhfhJoSTHK5N65ZTTWMiOsJoOaCwOu/N9/ s/NuO01whiE7ugb/xz1MONzT4PbBPXhM/bk+W+FtZCseUo7FbWwAVt54jeznjnesZiaH68AxOEIj O/Tc4zmgWdE1LFiuDdcwvZGoe5F/Pfn7G44LmJacC97+eqx66hocq2vCNYpvr+DABj9zYLm8obnn V2N1YLqWOlbg+vWoHY7LNbz7mDtedRwTBm+292y4vVnofIHt9XPkp7yn2Xkg99eBmXc9TfdC7qk8 BBOGa8MxLLnS5uHAcfn8bNhGJDAbOC41El63aRSbW9krLHk+dbX6iIa6P3LP+RsF7o8NGwYs77r4 RDhWA5Y3S3O3l+fCI7sWHDmgdyddHieCSBvjuTZHWEJUsu5lSalJ60feAlc33fLIyZX9+BD0rAw+ UEVCTROnMLiwuJltcLlyujgFHjcnDalRfV9oQQYhU0e4Qk2iPDgmTCMNVyaQAZPbch22cOLwimwu UjvlEUzTK0AWKEnFiKklYDS/vbphvKYMTCcDx4p7izDna7kvjpuBmeY/fRt499k7uVyTEZxxJE2S tJOCKZuaclCTF8774z9ege1JMrJXxoAT4ddcoGpRkxDyYNsyJHlMMj84D2y4VkQWdvCFlAfXgOtw hnGkqQIvMBuwovLitF0zb/iyv/CqIgXwZVFsFrrcypE5zeuGaap1wXkh1y53q+m1y7niAhFHX2AG FgmcD81xYFo8RvB+uHAdF46Z8l6HnCUZoTnLyCD/gf2yaFuj4Xrly9500ThrFuz/PSoTLwjX8SYd H2CiEu463eDusBMSA/eAtcEGcKwILEO9xXIP7qDmiisQ+XGZ9xZWVKSOybetA1mR0SgynasR3Xgj YJddkei3B5CokO8tnjM4HtdF7ZgxsJathCFSRtPnru0fgwvbtGG5fNtZiFx+MSq32sZ/INT8516Y 81+FYYsMln2T2n37o/r0kwFvgRa/fyS5DJbvsx8i336fI7NyolvXXI2q0UfAQESuh0ui2PYirTpc MLw3FtJ7Dce6d/5DpD5NzCKdIYNvTzgGFW8ukHuuXwNaluUrhW/wxv33wbq3/T3nJWIgg7onnkDm TzfI9WrZh8dJ99gA3Z95FrCswtu7rixOm8Ih6aPnRljvsSfgVHeRhanmjo8MMhn8uEc/xOrqPalc SfE8T9eZz8Exo3mEHETjovdRf9hRiLh84XD2COtn71cyUY315jwNp3P3rEyTA9mc99VA6pNPUXPE EYiSRJu+9h6WkrQdkkw0hnTXrohvvTnM3fohceABMHpupjamZKxuNtIrV2LZyH0Rr18FwyVpKrIz kUHaMlH5yEOo2KmPbzAuav9xB8w7b4WNhEhl8kJzHTTGKlE1dRISm2+BtoQ2R1iWLA4DxsJFiN37 b0TsXMJSbxs9qclalkhUGdNEfTSGzH4jUf2nP8LcpY8s9hx6cR0Yjz6E+JKvmyQinwQA/dYSNdCU t7dtuahZbz3gN79Fp/MvALp2yR0P/+fYsB59GIkvvpEF5V/zQdgkHIPjjSF96q8AP2HxeLNmofKR R5ExqIJxexMRx0FtXT2c007Of2PnQZ0/9vknqFjyjbzF9S62YSDz43IlwXJBe2/T4Pb6dvj/keaN XLUM+PstMOKJptPxYDUpVE97HvH6GkS9Z+O9BpREZCr1wvmmd545JQML1vKVSCxcoO67SDxKvauv rcsl0ALbK5lZSXrOooVYNmYM1rntVjhmrKD8nPjkY1TW1GUJy0UEDY2NMhe0OlQcLlLjp6D640Xy 0lFErAhLU3TUiqLm2RdQdfgRokrnCYje//lU3HQSlQsXIuEjLL1NlgO1quCacObMg3P/w2i49DJk jj8enW+8AW739byp6yLSpRoVfXdH1b//rd78SkOG5ZhwTAf1j08CduzTdHDbhvPAfaj8eDFcvkBJ sCQ+C7BHn4jYJpugraHNEZZMVW2bENk5QFiiNVGK4MTiQlALO+rYiCRTsKdOQf2s2YiPfQSxEfvm SduWa8KUidpkw+Kksw2RNTw1UJQcmbpWxkVs6bdI/fk6/PjsTHSfNB5Gty4iYYgNQqQNW2w4Qg4B suJY1Wm4BB15Mzsi3meyNhs/1Py0EfHI06I06dnJKDWWvHtCiBmZpIab8cbjSUO8apM/nr2NY0dw ewO26XqT3JV7xedAInK+/xH1776Nit33hGFQ/4vKUevmz0e0vkbUV7GIGMpOx7sc5T1xKM9lcqUR /TzkPioxUsZKqccTK80C15u/vZoV/DclmsS/70b9XkNQefixMv580hJLl5Km5TwZRXw8XiF7l3zH Z2bBsBuRHvcYKmivE8pRz4jbmHymhotYJo3kpCkwDjvYU70LPF/OG95bg8cJCLVC2CYyYk8jIZJb KSkpWxPHmkg2wP3vvVi2cBG6PzkVqKoSzYDjT5x7Phr++18kGnldah+H5gfXROO4x1H9xzGiQRDp BQsRf/c9WJ6UrOdroxVFxUUXNElvbQhtkLA8CGnlg59a8iBo9DSFrJS2rsyKtMN0WrUSK07/HRLz Xwe6dS9+CjkgjcVqwqsJoRawTBg5D0EpJ4POr87F8uuuR7dbblbSeNYQ0jS6/MugGqjMwhGHxEgb Fs9HgmiegLRFoaQhv/jVBcalyTM47qbtXY+slMosomb2d9Rx0DDrRRi79RW1W9G7CXfeS4jymihf mso4T1VNL+aswajoJeQ6VTyhJY/8m782hZhjo/b3ZyPae3dYvbYqfN+yl9+Se6sIhFScem8B4u9+ INJKlOYnMTt4kowYkPjycmBOnwE0pGBU5hNW/rizrOuNg8SnXpZyf70b4pBMDUfsnyJtIYNOr8xF 3b13o/q8C+VlSVU90mtrNBw6Gs4TD4vKSvVOrsFwUfXhp0i+NR+JvgMAI430uCmoyASlOwOZAw9B Ve8dZX2VdkL8vGi7hFUMloHkhj1hZxrgLFsh4nREPGN8c9IzpFSQLl98gfrHxqLqd2c0ezj1FnZR s1UvJDfaELGaWsTe/wAxO+kZSB2kTBdxmxZdB9GHH4F5ww2wqxLw3o/FYVC8JltFZYIo4gKciCkq oUOjZgsg/km7ZduWghuYoHnnEmmTb2tSbFTsH3pBUdpKz50F94JzPQ+VMthm5s1Rnjq+QEQ64H7a iP7TEinkPqWbV68Lj99B1ferUHvqaej61HSgsgqrA2UiUOpietwERN1M1kzBe5Xp3gPG8u+EoNOm IZJxYvl3qJ/5AioOPKAFfkA/lM0yZUWQOeUUGOttAOf774DxjyG2ohYxh8TlIGNRkosg6jqoHz8R zu8vgBlR4+EziV98LjLj/4domvqHMnFkTBcRN4XU42OBvv0A20Fq4uOoVG7wLFIRE5WXXCIG+hYI 9D87yo6w0t03QcWi94BIDOkli1F/wR9QOX2KUqG4gbyFSDQuUrNnoeqM3xRw1eeCzytxzpnocuaZ opI0zn8TyYMORmL5CpGKxMAq3jIgsmoZ0ku/RGSrbcQN3LzFw0D6lF8BIw+BK14vNS6RHV0Hldts X/qCtRDgj0n4iWhealEbZEhWHhnVDBqATnPnKq+Th+jcuUBjGkZCXbmZSsN49RVPzXKRMkwkB/dD pznz8gfciiywnyJTyn6iGjqoeuVFLL/meqxz4w3Ku/YTwefO52ykHWTGPo4K4XtD7hOl+8xRhyFz 339QkaZkaStbUsZC7eTxqNp/1E9bYa6F6FlnINK7jxyTts708L2RSacRtVWYgthyOR+XfAnTTcFF XEjVNS0kevfG8pGjEHtyGix6NLkd1wQJaeIEVN5wHVIfforoB+/rq8xKwI0jR6Fr3z40tPik+7aD siMs10yJ18SwoohutTU63f1P1Gz1DKobGjyVziMFx4T9+eeKxZpTxcVEY8A1Y4AVkzdcvN8eSB9y KMz775NjShgCyYlvOBJjKuUZWps30orBc7c+qDjiYJlIWZuZp0q1BFmtSv+xGhDOa177EXJS2xiI 9uqF5EvzUKWDOuiVW7kS9W+/g6o995Bd6j/4APHly0Qqkze5ZSC67Q7AnBebHBpa3Uw3liZdrQ9m R1zqepRaJtKdqNoq0CWaMZC47WY0DBuIxKiDfHEMnvdWRcKVvGfac9kw/y3EP/nYs3fxXjhIWxbs /UfBnTkT5ocfKY+cpwIb06YD6RQQqUBroBwPGRgmPd08lYlY336o33ZrRN9dkFVDxaEk04hyvueo 0PciEkXFBeeiccYMJGiqFG+wirVKLF6C5Cuvw549U1T8bLiJ4aA+EkXlHy6Ue6m83W2LrMqSsDzT sRcrasDo1h2RjXoAHy+Rbx2Dng4ajAEr1djskdTcUg/NchlzwgmXFpXGiMayq1smrY7dikQR33DD FgWJ8hsrQ5sY3/k0oKttxWng2RxaNCl+5nlDKUVUoS5dYPfYAMZXX2aZM2q7sGfPBvbspzyA8+aK qpIND9lwE7jdqjzJxLPDrK1xqjPKQiTEWeAzCSUyaSw/83eIznkR2GwTRIQMWyttKeePQ2M7Y708 CVRUt1gM1YP7Y2X//jA+/Mj3LB1UfPcd6ua+iKp992nV2TISxGooT65MO0PFyC2vFRMETRTiHvKe UXL7XujMl62eoh5pxoYORs2AgXBenKVspxydacuzqp86DemX56GShCXOFfFZIjNiBBIDBogNkuHC 9KC2NcoqO8JqevmqmenW18NY+qPyKjGKXAebGi4y66zb7GIXy4QbkRACMdkzzsqJwF28CO7ESV50 uTLIu1QrXBeZYSPgdunssZ3yODWH5NTHkf5sUfZvFWphoHGTTdH5/N/D4mRri+A12w4yu+8O96ul KqhSFruL1JxZqLz4ArnXqZdfRFS8mWq3TP891WLT6uda1yoYfkItisGfMZjptJJ+xQkAdPn6G9Sd /ht0njJVeWyjElbqDbD00eW1lErCHjde7HrUCCOcFaaJzG59gK7rIjJ0GOwHHxKyVDYvL7584nhg n73z0xmaAV9tKSOiPMi2CdtpQPLGmxH7eolIsSQfke0tG2lYSIwerYRSLxyI85X0bRgJWBedA3ve i2Im0Wo9t83MfA5VH33k/a2cWEkrjvilF8Ky4spjTq9nC+/Rz4kyJCwXBg3QjAKub8CyS69Cp2SN F23uUYy4gU1UDBygAkGLQK0l5frNvPIazMo4Ghcvhv2f/yD+43deak7TimvoVInENVcWSJYoMlbX ReL52bCemy3noeit0liAun79YJ5zdks1w58VOiPGTKWQGDQI9pTpiGTDAFxEXnoFaGiEFYvAfPFV RCid0gBtGYgMGghjyedynJaoXKs1zmwYgCtpMqkzfofYvfcgVt+Q3Ybe2Nis51Dz1xtRdfllOeTR ktHxuTW89DqiXyzxMigM5ahxDMSH7SWHiw0fiLRpwnDooFAqrWVbcKdNBm65FYjHWr7yHQuGZcO+ 5lrUdqlG5s13EFuwUGxRIAlSc3AcpA0T9SMPRNfjjvWcvyoMxNVhJQCqR47CD713Rue33s6GS/Cn +s23VJCozEeG5ACNQ4egy9ChyvTBEBbPA9/WUHaEZf34I1btMUAigSNfLEHnVXVqcYmeTqj4oWSi CrHjjympspH4qOZYDz8APPwAZGplScpFht4SF6hdtzsq7rkH8T32yE763HzEwohkA90ZBuBFL4uU 5aVatDGITUhsPBSXGmEOGyGqFheoRJ45FqIrl6Fh/juwNuiK6NdfSIAkL4WhINHBg2E/8okXKlL6 /qwulCOBz9CBtfXWqB9zGcyr/pQlWLr7Y+TTG/8P6WFDJAVHjUgFfZZKeeLzssc9iirhIhcZGrBd xioZsIcNkoUd22RL1G+1NRIfLfAi/ykpZZD48hvUv/IKEkMHSmaBBC6XUkkNGwmmy0yeLHFtKl4u G6EM2zJQE4vDOfl4dL3pZljxXBuZDsORgNV4JRLnnAv3tNO9ECDaYZu8zcr256I+GkXiwgsBmkKE cL2ksTYmXZUlYZmZNKree9ezKykJhx4NEYe96HCKyukxF6MqEEVeGE0u+/zPDSQ36QmccBw6nXk6 sOEWrRLv5SgSRKn+rRawCiAViattzgmPBQxk0hl03mUHrOixPrp8/ZW8vWnvoFrSOHcW7I03Rkxc /CpRuXG9ddFpx+3gOBHPzuMFd67FYUqOryaWTAZdLrwYy5+fheqZL8CU2Ch1h+PpOtSdfTYilDQK pEwWPUcylTUPiB3ImxmNVVXo2p/xTA7ciAkMHw58tDAnvipm26ibNAnm4MHyEhUnTMkz6ntGLcGn Vot91kT6mBOQuPh8RHfZuYR873m/Rx+LmutvQOdPPhFpUyXw+7cwkd5jD1SMzA+ybosoO8KioVdl n/N2q4ht6uAS42QCSTOCzDnnoesfLl0DkboeKfbYCOa6G3mhCa04Ju2lHINtwTDT2RoQfNulKLk5 XqJsG0I2JUSIgOJEHO7gQXCeeNyL6FbR7On5ryLyw2ZeJLYyDrv9BygbiBcKoO1aa3/EqjKHnU7D SSTQ6e5/o2bIAHT65geZG+qF5qJyIe02lBIVy4lqV0LESs6Zjdi3X6vZJsZolSZjbL0lUku+BCwu IQPxTTdFxogg6otbIzKTJsD9y5+BGCs7lJaoxcZECcnLp/SHghiug9S0SXA364noDtvBjFSWvDNW LIHoeWfBOf9iUWkjgTC8tGUg9oeLYFptM4yh7AlLZdR7iatMmWCgouUibcSR7LsLEpdfgc6jDoBD mZgxOS26/wZSFtUHQ1J8/Kj86gukLz4fK998E53uvhOItJywKPXZx40GRhwgEeSemV/OU929K1yL InizR8iqA7+MOYHGZQexoUORGTtebFUSVMqFtOAjJFfVoELyMT11cNAAMWwbEu0uDihPrVl78CrJ NP2boRmbb4bEHf9C4zHHIka11lER4sq2yVSVFkpYjMkb+wSqRET2TA6emht/+x1k+vRT1RlEaqZc Lxv4R4fY4i+QnD8fiT37l8xUbNrbRO22W8BavBRV9U35lIYBVNfWIHPTjVi+sgbd/34TY/ubP6Dl oPKkX2PVX25C9dJvAjcPaNi1D7ruf5A319o2WZUlYTVWVKLxgEPgRmy4EQuxruvC7dULkcFDsc7O O8Lw8qRarINLbpoF5y/XAjv3RvLM3yPx5eeI2l5JGYlNchB75AEk994LFSeemC15o8t7FINstudg xH91vHghVZaFFzMjkkrp1SwesKz6oySJnHPIQlKlSgyp5LBmJp2y76l8SWvYPiLB0iUuo3cNxBd/ huiq5TC9MBI74sAYPEx8HLrMz+pEurcUqrqA8l6qmCxG6ltS0WDZmWcgcvsdsFS9IqXp+oJgdXhC 7gEdlT7FL+pr4Eydpkq0aCeC9wLhnDDhJU1LiErB0SHuOKinStmfYSCllxuvgRHz8YcfhuFEUHP4 Yaj86ivlATdUiAXToOJ334WGow5BYvgIX3Wt/DAb2syMTp3RuP126BwkLEbl77YbjChDb9qePbVd EFa6WzU6P/Jf5cJ2MuJelvefRGmrdNzWgPvZtH3FuiK67yjgwf8gvff+iHqpMGqBmojZDlb89WZU jj4adjwuMTGFCswF4aXqei9mb+FIraaWBY+qBGjl7VIqcO6UlJxEWaxa8luDBOGFYMS32QyrNt0M 8c8/zdr7ovX1gOeNIwlnuqyDil12xC8PdZcYCLzOtddi+byXUfXGfMSkQJ9KHm4eVMcYg2Si7tmZ qPr+B5UPKo4duk0oOTJMwCvX02yOpHrCjVMmotN118NgOkaJFwpj9RyLr9AIIrvujPTfbkbmmGMl KDZiKzstj5qw06i5+VZUDNtL4vxMCbng2IuhRMRwmaDMCItVGqhGqeRcRvTq0npctNFSIk8AnrlY 7BypaEbKLiX6D8bKA0fCmTQl+1bVBf+qF76PhpnPoXK/UWL/IJo7HadIesYMpH/8URnYNAGq7EDY W2+Lbscf1wzpUUpRCcVY+A5qr7vakyayliYpdJeKWej2hz8q8l7DUr0cLhKFPWwYjM8+9bxIKpk2 Ww+WEe57DIAZ9ZWd+YUgEVBS18wFqjuj+t570DB0CKLLGfqiVLtm99cSouMgM24cKkUNVg4TEpcU 36DxW8Jl6GVrkmrEZuTo4pE6aAao+uhjJN95B7E+u7Voekq1UMsUj2bVQQdj+XY7ouv778Cmuu1V cJDKEM88i9THH8LYZltEy0Oja8eEVZD0OeX4plSR1aq8rfbcqFwFoxXHlQnmKWaMlpa0HtOCdfzJ cCZP9SYp37ZqkrPQWs39DyCx70jl69OFpYoMmBO88skZMPjD/HpxLVPlUCVulh1wICBxNP5R+4+j jDJ861a/twDue9erxeiDGJQ7VwMXXS6TvKRKWDKfL7eKgCprYiE6bDDs++8XVUjijJpcnxIRbQ0b ANdqMmJr7132UC0YVmtMvnr7nFHTKSABlCoURZ7vDjvBvPlmJH/7O1ToulPNRFtQhhJJpXYljGnT JAhWSgjJBbHyhoWGI0bDOPpwSbjXGQ8y7sZGRE47DTEGr3rg55TOGyZPRHy3XXOftVvMq0zzvJRY BCIRRI8+Fs7V7yrCpJpu0nHAkj8ZND78CKqv+VPWPlr8Fdr0qixntDnCIj14pmmlBgVtNtS1JYRB l0rxJ8i05HGoOChle/DIzpMWVIi2g6r99kHtOl1R9eNKr7RI04qITp0G5/sf4G6wnlfHXIU3MwBP jLlSNSLndN4vlU6hbDtqYefTq8qFo/tax5UJiXoGfLXOcmu003WvQzJ0jXL1py7g5guU9PLpsnFI UkZGc5hy92sVWEsiyh7loGLYUDRETFSldUqShol0xIU1cJAQm9wPQwUAyF2VChW+l0qhJ86XhZcY rrfSV9T89tm7pupveXXU/JxAp0vVyadg1QuzEXvoIS+9pcl+pfoA6Hp3atzcpnbGU4jXrPRq6jfl V8p2vz4JnfYfKcpnzghtG8v/dhuib7wlkegkFfUYXKQnToJ75R/hMEdQamepe08JX6l5vjHLbVD5 f7yY+BGHIXndNUhkWFOsyWHAWLPahx6De9llMCoSBStD6GetJEFf2aCcbUzv5a9qwrVltDnCkoWa bbyg4pX8E1dF9NK+xJJwEo7XKuhCaNqASgOrqr7JoE4lc7lVnWEfeBicB/8r4nmTAgZEG1LyVqu4 8DwvHUJNehp6GVSpqLYJwX9z/KqqBPKqqcqSkbe5HqNa9s1bH0xVkz1LRF7ZX8NCXCTE3PNLpSUp 3cQyPIogc7b3jkEpw3C0RdBFZKMt0NhrO1R98F7TMcVu6MKu6oTKXVnhlW9+9exECqDEI2SuYtF0 zl/O+CXv05HCgnS5K5VXrcq8ev5526vnJdXQpP59IXVPqVedb7kVq15/A50WfKDCGrTRnYRrmqgQ slf3h/ckM/4x7/75jslqBhWV6NxvgI9WfWM0TUQGDoXz5hte0ConlvIixhZ8gPTChYjvtLMnlcpd 8pkcFOT5eGq//tjadhukd98Dla++mE170qhY8hkaXngOFaMO8Qg3UGPeVZHslIJ1FLufr+S50B5n qRdpWxfB2hxhiXQhD1F5v4JvA7n58uaigZHE1Tozu1o0Xi1uL1mBx2s0LBXlTunAMhA/6jCkHn4I lRIZrN/3SgxveOhhuOedKTWtIh5ZcKEyIrwpsr0IpF4Xk1sNpGl4yP1SSYCS5qELxxWvXyWWMCl9 o4mS5KAKEFJVbIwoqS57bz1pibW5THn0nqQqta/U9llfgEPJqbGJZiNAbNhgpBd9kDMGViOrH9gX FZUVnhzFKrAm0kZMQiJYWVNLV6mIvpdNq0Kp+HxJRZWn0RsvHSGs1R60iuVt7yU/M2G9SXpoOr7y nTlA106I3/tv1I7cH4mGhqxOSX71ZoEYr10nDaxcBTw1U5w4rF3mR3KP3dGpM+OfCqxs3suB/ZG8 M46Yk0GGwe08phuRpPzGyZMR3XFnedFJcxFXxeP5E8TJ0UnLQoLbSEl4mikMREYfjIbXX0VECLBp unDf2vsfQ9XIgwpqg0oLSEllCUbn0/vpV9UzJudACoYbL9lApS2gzRFWVoXafTfUX32l2HyaYCBd XYUEqx2wkJkbad0FmCbS510Ap2a5Z5z1rGKWi3ifflIimF1COHkr9t4by6+8Cq6tkmn9w7OZ3rEq CbNrRHmPGFl/we/hcKK3oBEXJTl6guJbbB2wXxkwDj8YDb229hwMOuG4eaRjJAfeCZXib3DxPvQf JFMkCCdn7BVb95KYKTqsVIlmJ2d7KR0sEeomIhuul30gXN+xSy5D3ZFH5l6fA1RuurFqCEL7D+1b vz0NyZEHemToxYe7ESTW7Zp3PSIT7H8A6mf08jIXtG3MhhutzGlAUWh7igciyXB8vTbPd+uLkZrF 9SKSVpV+YRbqf1wm9187MIwYk42jqs4/LKnp5UwYiyRtXoH0qeoNNpHIdl3LPYjEAfth1YwZSIGB wh5Zetdvrd/N20c1hsMmm8B+cjrq/YRFidTKwNp8Sy8JmZubiJ98Kmp79wUrX/mfJ6VKs7LSO24B CVZeGBY633A9UisvzhMAohtuSEMHygVtjrBU3XIDiX57yk9zaHXPNMNElwvPL70Zn36iEutceUXL jhsBup5/USsHU+jEBroccQxwxGoexwS6DR5S4lz6l1Vye3kilHY26yk/xWEpm1GvHeSnJYiQPDfd FIlNN10r20vTLx3uYkTQebfdmtlW8WmiazeJb/opiHbqiu4j9iq5Hf0jVufOiI9o2Xli3dfFOi3c 1g/LFzxIAAAgAElEQVT1ArDQbfc+Ldq6raPNEVaIECFCFENIWCFChCgbhIQVIkSIskFIWCFChCgb hIQVIkSIskFIWCFChCgbhIQVIkSIskFIWCFChCgbhIQVIkSIskFIWCFChCgbhIQVIkSIskG7Iyxd 24kpiY6rkqRbky/lSPIvE6NVpwJbqkzqilteWZpmjicJ9mw+IXWqfPu1cDy6XZmqBZZbScphS/gS NX51bQT+LpQ2Lbm0jmrrrutzqeJ0uqBJbl1waW7lWlJtoLkCvC0FK7voGhxS7iRw/V6F+uBevrvu 3REv+bhU9ptX/yKbrBysm+bw+coWXtWNQMUCr8FOU5/FEicslfiuOorw2RYujqQ6l3tlXwpWEXWz heil5HMZ5P+tSbQ/wtILz2tMkF+RqsT+MgWYXc8aTmxIycUiLSc9AggeI/dv1t5WtaCaCsqhNeOR iarar6txeG3IpSV7CyaorDCSlaorljdaKSmiCxiqBaHK1KhiNsFaE7rxpy50s7qURXKwDRuWVzcr e9H6e3nj6OtVjbsdRzUGlUoQ3nptacM1KUej2zPoQmT+ElZ8uZhN7eULjVeXQRaC1ZVWi5+w2S/5 0lIVJlhyJr8ijDwLryikavOV2zfA9f5vSGmlNdd0pFzQ7giLE14qiLouGl58EcaSxbn1l1hny2aH mUJ7uzC23x7xvuzu7L1ZHRPJOfPgfvl5kzQiRMJJxWInAYnHseBaNqxd+iLSe4cWjMcGbK+7L3ev qkLloYfBjKhHI8UBpUyyC/vd+Ui//W4zk9SFXVGBiiOOgsUSKVzgwS3YL9Db33FTqLv8Shg/LJf7 IjWafIdmrST2rItssw2irKO0BtZGeulXqL/uRmkZZrKcj0eTMjaH5aptGKYFIxqDW1UJa9NNkd51 V3TadTdYFRXIWAYiLJQou5Qu+qtr0qXnvIDGB/8HQ9dc98Da/Kxl1rjT9uh27u9hWLlts3RVNrJ1 7XvvwL3rTnkWeZAp4cLN5B4/MBr5Lxk1sc4dd8GQWlv5W0uHQNdGzUMPwJz9Ys4WrrxAWYzPgXXI oag6+KAORVrtjrCkOYXUunKR+de/UfnoQ4EtdF3drKyf823ygvMQ372fFPxnqVwpvHbPXaj63yNe u+/cgnrZhqMe+DbmWz11w18Q7b29Jw20YDzeZK6PVcNZ3B/W+ptI+6iMYUhrdBJK/W1/R/UDwf1z RgO7xyYwDj8ErllRUCXUZ6OUk1n4CYybb0OVnVHt6b1ywXpDvseTm22OyBWX6ap+Ler00xyMlSsR vedeRNyUKnYo3Zm15qzVX1X+mOqaFMCzXKzq2gOZI49E9bm/R2a7rWC5quV8SRIVgcZF/d33ofqR h/I6fKty1C7sbj2A034NdA70+VO6uBCls+RzJO6+G9Gcyqa+yqNeBdrmYSLD+lv/+Ge2C1LO6aT+ mwnDTsL+0/WoXvypr4SV0VSH1nSw8suvUXXggUoM7SBod4SlanJ7heMMtmPKLQnbVAdcqxi5JYjl ncf64GD9bHblsVRLL4fTSxXIa7L2ZFea7/xemV8R91X5zqLj8crSK/VPqWsVqTokZ7+EyiNHy2pU +3L1ZoCX5nnVWJuuIWjSyoDVRKNSlbOQiiPWLbkJNtITxqMyk0aGpX1VrefcQnkukJo8BVWXsYs2 h7H6hCUNIpBRzSxEklBkLjYpqYlP6Ul13Bbl3LURSQOJ75fC/dftqHvkQdg3XIcuZ54hkkbpKpkG jFW1sJ6cmiUVqaefbUqonlFi1Xeoe34Wqg491NvNK0/NZ2lmYEnlTpKkvz6o3wThqamB56HLfWfv vn54ci/zJURtJmuY9zoqvlTSuJNtXgJPupMeY0jMnoXMd98j0mNdIfZy6Ny8umh3hFUalhKL2FuO C8VnZFb2en7PpR7JqSfv9W9QHXs8e482jOZOEnVEGt6z9rBmoOxcnoGVTVJYN3zOPICVPWVxe+3L v/oS1mdfeM0TvD55KF5BOdd07h+dciZYKQuZJx4XwpNyzNkWyqpJB4mV5BJ7az4aP/kE0W16Sbnd NbYetFHZKwmtm3yIPYlWJ9raKF36S6q7QGVtDZIXXYTalbWouvyikp2Pef9XPT0diZUr1f3yGmzo StDaQcLejxk2PD34UKV2eo4L1etEdeGRlw5tXT4xSpmkVLVXduzJO39A5BKSlWNL98TCT8lxkR73 OKoyypbHF0XTC1KBRB1LNqBhyjR0Ou3XXn8BOndCwmpXyEihbC4E1tN2EZdGEE09Wlg6Fyxva0QL tmGSBc6OTqyP7XitmHI2tJA2XbF90+NIW1JzqzxrlvcmOyddZs4swEnBsdgJRR09+dJcJOyMkIk6 i24wUVIHyRs/j9H47juILnjPayevjsHSz7I82UTWI8aEbSM5eSKiF1+SffuvSYg3U5piUIKIiu2G 9eWNrK0tyMh8Zmkkr78WjQMHomL4sOZPYNvIjH3c696sfacGMl4jXhKzVHTnQp8+DXZjLax4J+le q0agpKw0G19kIshIKWpKy14XbJPOGSX1WDbrmjb1ACAovTYZ+nkeGzaP4bVPyxsue2Yk6+FMmKTI Ul5k7E1JYq9E3K33xHLeJSAzdQKcX/8KptdQuL2jw0lYpIfUVtsgfcA+gBtDQ+CtaA0YLk0U1CRu aqmkwcmpJBADDdtsBWvkgQEvjtdGrF/f0sqTayC18YaILv1ObGUxIU8Dkfc/gPPdDzB6bCz2CbGx zHtN7GdKjTXQuPEGiHz5PaKyoFtOWlolTE94DJW2ajrKzkFUXWp22g5GOoPqBYs8T5ayv6UnT0TV hX+QTjtrfFV4Hr/6SAzuX66HudmWsGrq0fDu63AeHY9OS9mm3a/TKwkpkWpEzXXXoWLo4Ly67znX u6IG1lPPZNttOSbtglGsOvwgdB07sakOvWuiYvkyJF94AZWjDoLjmspD6dX+p2QV79cbjY8+rPoi ec9cuGPObFT//R+qQ45vrI2WhczDj8CNUqrSAzKkAzQdC7qGvB/8q+GFOYh9+603W0ngUaQtF9Zh B8F94vGstC8FoGfOhLFsBbB+F08tbN/ocIRFASq1W290+79bVOOGICl5TQKa4ObbyKT3oAt7lz7o dMvNAcuv09QZpySRuKjfajskGhtR+cNyIUOqEOw/1zB7FqqOPk41hcgYsOe9IOqqsiMZaOg3CFVf T8xvZJzh+bkQij1aB27aRnrs+OziotRB9Teyx0A4K1bAXLDIa8+ljP3RV19H6vMvEdtqozU+ZZTK 5Ip6buy7HxI795a7lnCOh3PZVag57deomv6kdFTWTRf0uONzZqFx0YeIb7+N11zXU/eoSrOJBYBV Uyajor5OmjHQgysNKSwDlb86GZnxExHN8OXDIdiIOUDj+MlwRx3oSbaeFdDkVUcQ2WhjxI88KnA3 gWQD20h4YQg+2KaJ6sMOA+KF1dbCjmoX6fFPoLNtexItezBmkN5me2DAQDhjx8q5IuI7dlHRUI+V M55C15OPbonTtOzR4QhLNU0lUTEORk3I1qg6yt6kwhDEoCqBTD4vIZeNZ0xvyTEdO4PkDtujcva8 7PFpYHXmvgJj9PHK5rTie0Tf/1AIkEZX9tGr67UlqtQV5V5foDN0Pkyk3piH+CeLPS2Fy9yWYxrD BiPyzVJkxj2BGKULr2tLxLaRmjIR0XPPaUkTn9VAU1gn76257jro8uD9WDloBKoXvpUXAxVnR+WZ LyC27baqHZav6QQVJpPhImPHqo7JjuqYLB2Lem2LLsNGYOU666Hi+29ybqH55HQgmYSbYCuv0k8x ELXWahU973j1SRiTp3qxf6rztvR3HDwYxoD+QrZ0WKju1rS9GXCnjId90jHK4B8SVvuCeqYpUcEs ZeH1fe61TWn2ACraUt5yXyxGzfhxeb51Rk5VH3Q43Cjf9M2HN1qNSUQHDIQx+yXpVajEPReZ2bRj ZQAritpXXkQsk5LtuSAb4wl022knz/aUu0iUptDMrHUB+/HxSDgZj7yVXJIyY6gYPBjpb7+HI96w tFIJPSeDPXkCcM7ZayB0tGWgjUiot1NXWOedBvvMc7MSlAbVWSx6V2KpdNPZbPs2ktb3S2HMmul1 UlbSnHhZBw+CG0/AGdQfmEC1sAmR75Yi+eI8VOy9zy+y9mueexbx5T94L0Y1AqrsxpBhqOy9C2rW WQ/x777x+ncqb2f02aclXMTp0q2N921efXQ4CYsMFX3zDSTPvQAuAxS1tMQW8fE4Ov31/+X1ovND mchV09T4qy8Dxxybt019NArzq+FwunUvOemtVBLmnn2RvkNFXXOSMiQhsmgh7KXfwNp4E2DeyxL7 QyIh0rtuj1hFp2AIWYtgNDYiOXkK4uKJUyofbR/JHbZG1YabwFx/A6xavxtiS7/PqrQkAOulV2B/ vRSRTTfB2kVTco6Sfg1U7HsAGs2LJHYraFNs/PoHVAtve34/kqs35rqJVAcbFfF6LCZR/sOGw7Bc RIcNhzNxUo6NjAGydfQW7r33Gog6ayVcB5mxj6FSJEnaw5S02BCxUDVkMNxYFGmS7cTxnulBEXGs pgF1Tz+DqqNHt3sRq8MRFm0hVR9+Cnx4e9OH8jozUF/dCfjLjc0SlhbTaQvLRgL4IOEGQoK0N6k9 mptEViqNyqF7oy5qojLFJaJyGRPpDBrmzkLVUcciPW+eZ2dSkeGJAcNgW9JMvgUqiJI6VGAo0PjK S6j44vNsjJZEersGosMGi4HfMCMwBg2CMXaiGrlkFbmIp1KomzYVnc/4rUfwdPkXy1hcHeR6u0SB X3cDJHXD1IBXNr1ypRd0y5ALRsozpozdp9lufiKqpHN3U7xaXaQSVUMHKQl56FA0WhFUOBlxtNCp IbbJqZOBm2/ybE9rmQC85yIK4KpVsKiSajICX1IGMjtsD3OjDeTFEmf37UmTEXXoydYvORuZSVNg HnXUz8ywPz86HGEVW+AtnZZ846u25qrNea4Hy4vtESOuMr7niQRBZDLA+t2Q2Xln4I03VYyUo/Lb 7NnzYIw6ANb899QY6d0jmQ4elJXESo5XEq5VPhzjrVKPj0cVOxp7YRGM3reZ+zh43yxRR4bsjdRE GqRNyWvjeCSKe9IkGKf/Vtq30/hfKsZsTUBG5FA9laCTvO+jibgXLqCeoeQ80gO3eAkis2fnbsx8 xB23hdFjfboYkNhhO6zccEMkvloi3jibLxk6Pb76Gg2vzkN88PC1z1fZxAsTddNnIL5yVVP+qXfF xoh9AIbZALCGjJDnznnIlCLlxzQQmfEUUNcAdKpGe0YHJKzVg45jEle4BKGqxa/BNvB0Q1OuaQkM 24ZpmIjstbcQlrZb0HPlvjQPte+/g3hDncThRGwDyWgUnQcMRN28l/Oi3AseXwzQjCGy4GbqYE+e 6O3nVYWgWhWJoHpQX8BOqu7Ng/vCRgQx2Fn7j6TZzpkD58dvgPU38tSsNS9fFVIQUx8tEkdEfpiJ gfjGG+a481VwqIO6ieMRSzfmkbc1dJjygDKTgSTefwDscUslfkqsZhKy4iA1YTIwmB2c1y5jieWN UpZjIzV+LKroKMh+yZdSBLH+fVXequsgvm1PrFx/fcSXfqtlZ5HOYquWofa551B9mBep307RIQmL E1XF0vgSbAxGPJeenDqVhnE7tVv2RGToXjnpF3xDJyMWqq2KFlYU8Ahv2BCkb70FcZouPLozP/oQ 5mvvwHLTisAY8b7jtkC3dZVNJmCELg4RBdHwwixUfLtUpnjaMBF1VbpRwgaSA4ZJcCQDamkFijlp dT1eZDzPnUg2oG7KdFSfepoYfddEbmEWRciXl5me9hQqHVukEE/m8CLyDWD77URKjOicdDH/uEiP HYeKwDH5pKMP/hf148cpidN1EVlZC5MR7N79VYHBLhqnTEfVjX8FYpTg1h5UMKsLLF+GyNPPNjlR 5BfV9Qzs885D7cV/hMVkcddA1Q/LPde2TvNiOIyFzMRxwKEHl3YclTE6HGExPqpmz36I/e5cOJSy fQ/XZKR3M/Yr2V/sN5bKf+vTD1V33x2YIA6YdkxJiaGBzb+h1QqjFFHZfwDq4nHE6+qzaTXxxhTs Z5/xYqLUiooOHiqBh158dklXutSf8io+pB8fiy5UB10al1XAqSQGOTYSS5YgLoZptWApKSpbioo0 5+JmqEPdlCnAKSfBiNC+s/oLg5QpCesSYpKtXqXisxjUuvhzOHfc6b1UtGrrEXAkiuiwvUXykHAS MbrbaPzsM0RefTn7YpF75ylaiWUrAf54INkpgVPlaOpSMtEln6J+/luo3LOfl/Su1c41LHF59c/q Jk9Dora26Vl6vxifFvnmOwD8UeOTu+TlqnoGCkQogc54Gqivg13ZScoiqWzS9mWE73CExYfo9NwC 0ZNGS0IrI44FLYxhkTewZztyuK+OxWraQtlRpHaVTkAudmCV+8WicU63rsjsvjswe072W3oG3ZnP K8JxTZXmMXCQV2FAL53m9UJVS8uAWVcLa+qTvs29VCAvcp7Ci+N6qTmGLQulKVeyaZfo888DK1bA XXd9X2LRT4dabir9hcZjKRjIhCeS1cIPseqE41C9/Bul+kh+Ju+7cjik+/ZF5c7biS3HltQ80VNh jx+HBANoaZmyHEVwkkSsYpr8uaNiixNyVOSlMhwcVGSA5KSJQL89GG/qJb6v+ZAOXdgxPeEJVOZU gdD3xz9/XBkrnykfGG1uHJeK1XJR+cOPqJs1F1Wj9pOxKudPSFhlDSnU5rJkS1TqPWVzAbPPtZTU oLP9DUS/+RrLnnuuQHkPijURdB0yBAYrzzV/NFUc0I0gNmwE3DlzswmznJexhqT3NgUylomqQYOV FJBbhKIolE3MRc3zzyO64of878WWxWWayUo4MiavWkEQTLitmTEDnU440VsLq7cguHdGri+D1J33 ILXBBrAaU0h/+D7Mp59B19oGVflCEtVVwIPtRpGMuoiPuQymEfMSpnX1iwwax48VdVDVIfOCUU2v kJ8XWa82Jz1SzGZ+H9VhRXJK0HSRnjwJ9nV/QtSJKWdLwQqgqweW0ME33yD6wgu+emv++5PrFXUY UiN5lhyLp8oKGTNbIIOGCRPg7r+PsuvJM2xf6HASlgQUMttWpAhKSMXqGugdsv/zQBVOqWOxuXMQ 23//gBueEpeNhuquML5bDFjNeW1UUKaUYrZMGHsNQebPBqKSU6iOplQUbmOhcbvtUN1jAyE4bTBv ZtDZf1Flyowdi0oyQwB1G24E6/DDxSbm1aAQe4jYTsZNRPXSr3OOF3FsJCdMBY4/qbQHtAS40CQM xDERMTKI3v0vT0WmWt2UL0fSEaeDqMaSuoyGE0/FOiP3y4YEKI+nAXvBIkTffCubKqM8q0rurT/o YER69sx9XrQLfv4JKqc+rYKJJX+SmRA24h9+jMxb78Pts6sksSuPcIG7nn15tP5+cNx1kxkvlm4q D+OVvklZJuzf/AaI+RPxDZl7yZdeRuWbr0vIiXIiKLIzn5wGNP4dRiKqpN92xljtjrCa5pRPQtCu Y536QsOy1Dkq/TydbAkR72giDdAADFgFS7uoZGIubNbTanot54/Hi+oCWJ7EclHVty9qOlXDXFmv zuHl+KmqATYig5joazQZwnMkQ31EL96bVQ/EDuXCWLUK5ozpEqeULT3s2WTcQw9E5W23qVw7XfLE iwGqqU/Cve++JhVK0nUA4/lngVUr4HTuUsrkV/gZeWoq1WlTYp+8pGa5VV58mU5W9upXefQj5191 wIFY55ab4Vqsh4WsukeyqZswGZW66qdXF5/qbT2DL2//GyKb9MwhHVE9P12Chhm9UJVWCcnKdmcg bttomDoZsT67SiVUpZzl1XDNSqQqpqrphqiXTQlzA0NNJkwAXTSqnI0rkj/naP0OvdDt9r8DUkXD O5T4OQzU3/8fOKf+NluPX91XA7HvvkVy7jwk9h3iPc/2ZYBvd4TFN7ZclMRB5Ral08WlxHCrC7iV YCxFHJRovMJ5HmsVtUqx6J4kH3tBiM2NRx/JqxXuVnVCuv8gJJ6ZIa5uqiqeEoQ01deB/TyyUdch 3jFfQT85ngQS8lPPMeAaqJk+A4kVTK42Re3RReYk5WPoUFlkykDtkQmJxDZhDh4A57/3icFZXZyS VBK1K1D7zNOoOuqYn/CEMiKhSjR/1majVTQvbkxUbmVvzBrEuYAr4sicfTa6X30d3IqI3NuokDMl XhNOhqVkHvPqxvMZK2lRFMVtt0Nkg40LMIcDq+eGcHr2hPPZZ5Kr6X+66cnjgCvGwDRVqEoB5d8L 6CW5KruRv3ZHKaS/XoL4rFn61Sjj5nOjFhAZsr+YFvxjNoTXXUQHDpVSy9UpSmZN30cdoG7qRFTs PUxU5Z8nkernQ7sjLCm8JuqB1ADI1iEiJPSQAZkm3cMtM0hI0wCX5UFMZCxGuOdWKC0c8kCKsaQ6 QHPj4f9pSBdDs2RMm4gNHwbjmadVlLPQg0qhySCOxOC9ss0tXIOVRb0l7XuROyL2sW5WRHXtcRul smiFRwRKMlNEnYxGUDVkmCwOetO0m5xkzske7T8IacuCmaF0oa7b9tKHMgwiPeJwIFADvRRcV6kq vC+SoBysd+W9FZQ0x6BWE8kuXYFDj0TFuWeiauddPIeGSqMRyYaSo+2g8b03EF+w0CN1BlZSlWSt +oik4Uhl1cB4xHDNQNgBA2B8ygqfueWPo+99iNSHixDfYYeCqVBi55eAU93Iwn8ppTMRGsdPQCKV zkrTZCTeGQYIu3uxt0DuSTMyxx1EN98EdRttDONzjtl/ThfOpGlw/vpXuIzUD1XCtg1NDhHbQt1O 26BhRG7wn+QLb7+zqviY7WpTHCSE5A7bIMnjSByQ3ZzTT0WgmwbSFTF0ol2oxHjcHhugk8uqVvQW AhixD77Z+3lEpM660lkzXKDrr4tqCZL0ShyvuxGW7TU8r0Z5prorqljaWTxEJlyWVOm7Jxp23Fla S9FepBaeAXTpJOcnaYjrXkfwexwY23or1FxzDew0Y7IUmekyLeja2St33DqY63dD6oor4XhhFUEz C0NG5PPqCkTWXw9Ory3RtXcf2Ik4TINkp6RGSskWjc6kbRmaBSfpwLliDBo8kheVTNz7FhIHjfLI MVdFkrI1JLLfnIb6LbfOSrwaJM10Y53UNdXPI2d+MJZtx96ov/oKr61b0yZpepG1F7rgfHGR6bEh kldeBRgkLb4YSX4ZpMwKdBk+IrgDxFvJOWVFYVz7Z9R9sihnCz5Hvugyq2pgrdcd7Q3tTsJiWyq5 qAiw4aVjgEvGBLbQva1attQMK4Iel/0RuPSK1g9Gp7o0Ox61nX4Q1X13R/X06UWPl+WagQPQ5amn ChtHfIYlIxpBt0suLjFQidnP5vFlHZuMqh9TYLyrgch6PdDt6j+2er+mZa9eMepvb9R8lhZQNWAA wJ9WQDr0AKgcMhzgTyvBSp8Vu+4sP62GYaDbcce2ZgeIDY0vQAPoeuJxeVu09woz7Y6wciAxUmvi OC0nuDUynpZYsmVM7c1CEWJ1YbTzW9i+CStEiBDtCiFhhQgRomwQElaIECHKBiFhhQgRomwQElaI ECHKBiFhhQgRomwQElaIECHKBiFhhQgRomwQElaIECHKBiFhhQgRomzQYQlLlW9RzSf8cBxHVWps Z6VlS113sc9DlDdcKamc/0zL9Xl3WMKaNWsWfvjhh7wHtu2222LHHXdEe8V///tfzJ8/P+/zIUOG YPRodg4O0d5w3333FX3mRx99NMoJZUdY6XQa3333XUHJiD/FsPHGG8OympKFr776asyZMyf7ptG4 4oorcP3116O94tlnn8X//ve/vOsmfsrk5XFWrVqFadOmFfz+wAMPROfOnQtKdG+99RbefffdvH24 /WGHHdbqsYTIB+87n/kjjzyS9zkREtZaxqeffoodWEwtsOC06FtoIRIrVqxAly5d1vbwOhx4z7/9 9luceOKJBb9fuHBh0fs+ceJEXHfddXmfb7fddiFhhWgfEpYmpULEVIys9H4h1h6au/eteY7hcwrR rggrRIgQHRfthrBY+bG1b/kQax82O02HCLGG0G4Ii2RF20csFitKaCF+fjTnCAkRosMSFvHEE0+s 1ZAEvfhIju+99x4WLFiA77//Xv7u3r07tt56a+y2226IRtlNuHU2mfr6enE906mwfPlyOcb666+P nXbaCdtss032OKWOxzGuXLkSjz32GF577TUsW7YMG264IQ466CDsv//+iEQizTon2ir0ePmb9/2N N97A+++/j6VLl6KmpgYVFRVyv3r37i2eyfXWW6/g/aKHefbs2a22lfG4fL7+8WgP6csvv4x33nkH n3/+ucwHPoNu3bph8803x/Dhw7HnnntmPdStGQ89pfx85syZeOqpp8RDfsMNN8i16u31OOhUevzx x7PPfKONNpL7oJ95e0H7uZK1DE4KLoxbb70V99xzD77+mh2R87HOOuvgV7/6FS677DKsu+66JY/7 ySef4M9//rOQbW1tbd73nJhbbrklfv/73+N3v/sd4vF4s8d7+OGHcf755wvp+fGvf/0LBxxwAKqr m+tE3bbx73//G9dee62QVLGgSP6dSCRw7rnn4k9/+lOexM0wip/iyv/HP/6BrbbaKns+EtMJJ5yA F154oaDaq18K/L3LLrvInOHLLDjeYuPhdpxvp556qhCRxpgxY4Sw/HjooYdwwQUXCGn5A0Lvuuuu sn/m7ZqwmvMc/lTvE/fnG5MxQ0ceeSQWL87tAxfEjz/+iFtuuUWIg7Eve+21V0GVlMd94IEHhIgo XRVTnbjdxx9/jAsvvFC2nzBhAjbZZJOCx7vjjjtwzjnnFD3O1KlTZTH/nNLVTTfdJMRdyBs4b968 Fh+H21MSCb4oCoW38H7+9a9/FemHROO/V37JpDUIZj+QHJ577rmix/FLhJw7e++9t0g/vXr1yry7 2LEAACAASURBVDtuofHw8xtvvFEk5ULjcD3J6p///KeQc6H7QDA+rtRLrpzQrgjrmWeewaJFi/Ie HNUq2rd+Kqim7bfffjJJWwqK+occcgief/559OvXL+/78ePH47TTTmvxwuF2b775JvbZZx+88sor onL48cEHH+Dii0u18wJSqVTR468NkGS5wIKEvLZtijwnpcqzzz4b22+//S8eLkFp6corr8Sjjz7a 4n1uu+22Zr9fsGCBPPNSKn6xZ16O9sV2Q1h8YJRCgtBvqtUhrLPOOkvsAsHj+heB/42qf9fV1Qkp kWi0HYGf08ZE9Y4TJjjRggvZbzcjKG1RLeCb1Q/aNgpNTNpO+IallPPFF18Undhra/IWi5lr7fn0 vaJ6c/DBB8sLhC+iHj16iIrIxU1pRB9X/6Y6xayGUtDPsxCxUiqlHaqQCrrzzjvjiCOOwIABA0Rl 5P1mBsUf/vAHSf3yH2/KlCloaGiQ47XEFkmSa877fcMNN6CxsTFvvATPwWf+5Zdfoj2h3RDW2gKN qRT9g+CEoyGbNhUayG+//XZ5owcnFyWf6dOnyyLT+z344IN5BKhB29evf/1rUS0vvfRSyXkMnvf+ +++X9CHaywgugkmTJhU83q677irn5+TlgmG+II235QZe9+mnny5qb9euXXOkChqY/+///k8M08H7 SuO8H1TRef1BwqD0wxdbofMy/5L2Jz8Yvc9nM3jw4JxtOSaSKKVyzg0Nfp5MJsVZ07dv3xZfNx0J ++67r9jiXnvtteznzT1zjvXJJ58UxwPNAEcddVRRKavcEBJWCTz99NMFP+/UqZMYO/mboK2EBliK 6X5wovoJi3/PmDEj703OyT5ixAh5axJ8W/P49DT5JTH+m5OV+WHHHHOMfE7vIu02weMRdBKQrPg3 VdRRo0Zh8uTJ+Lmg3/iFbDTFpK9ioMeNBm5eO18ifBnQM0dyoDRbCLR5+cmpkO2PycF0fBQaNw33 XPBBgiOR8IcSDO8nnwHTkPg3f4LPV18rpcGWqKeU1GhK4FwplIs5f/58IcBCoA2VYyPoKRw5cqS8 rNoDQsIqAS6GYpKLJis9wfm2DRIWwYmswYn32WefFTwm1YpgwjaJ66OPPsrblrY6vdiLif0cE1WZ YDWKnxP0cFI68Ceea9DT9s0337T4WFS1fvvb34parEm81OIvJU2S+GjnKgR6AS+//PKC35EsLrnk EpGqtZewJeRLSacl4+Y2lKJJVoXwZZFnzuP65xH/pjkkJKw2Bj4YevFojObi8L/Z6VYOgtu0ZIIV e4sFJ5J2pxdCUBynhFQIVHX8xyOCLmwN2i70NsWOV1lZKWThv86fO/6KCc7FYuMovVxzzTUtOg5V O0qHWpLk8/WrhfSc0mYUfF7NefEYx8WQAr8dSNuM+PJhGEUh5wDJ8uSTTxbHiZak/N47zgOq65Tu CkmWzUl8/vFRdSxGbMlksuC18Zn/lDjAckG7krBoXOXiKGQM/6nwS1F+sEJBEMWkBS2eaxR7a9Kz 6IdWIYodU7+pi5Ea47ro2vdfQ6mwjLaKP/7xj3lkxBABxhrtvvvuYoxngC2lr5aA95UqMh0gQTBA dOzYsUWzJhgoSrLyzy0+B9ofzzjjDJGMGdJyyimnlJx/xTx8/KzYcyWKvRz1M/fPsSVLlqC9oF0R VqFKoav7himmQr399tvyBmUUOUEbStBArhGUMHhMGvODoNGYthQ95tdffz2PxPR3fmLmAtGSQdBb yYVHIz7/5sSlTaTcIt0poRa6t4w5GzZsmPybgbItWZg6Tuvwww8X+1fwPtCYTqlQR8r799O/aUML 2qhoJ2SpHP1MGHvV0ntc6HmUqnq78cYbFz0Wg5B1yAzvCW2o7QXtirDWBug+LzTxMpmMpE6w4B/D Bv72t7+JSlII9CZq8Fg8JidVEIx6ZpQ81Q2++XnsYqojVRYtYfXp00feuIXUBC5qqlNciAxmpau8 nNQETTBB970OiiQZ8zvatvhMSoFEQ9sUXwYk+WCUOqW2O++8s6DBnyTHe1coHo9eXabQcDvGA9K2 tbovhuZCP/r06SMSWNDZwvMxkJRGeUpZLNbIZ95eEBJWAMEJTPWAxKRdyHoCcju6mYtVxtQSz9Ch Q7HHHntkP+ckPvbYY0V9pQrpj7PiD0mFP8XA/Rkd71cJqqqqxAtZiAQ5oYMxW+UkXfF6eX2akDV4 3yg5aNVH1+IvBYaK0ABdjAxeffVV+QmC6iHjrXTeaBCcDwzqpf2IxLkmXgrNPafKykp5EVKCJvzz qNAzby8ICasEOAEoPTG6vDUeLe5HwysNt8HPuQCZW3booYe2OoCS9ppCnisarxlzU8y9X84gCTC1 pVAZZn3/6GzhdoVsi36QrFaXTCgh06ZWCFrKo9rv9w6vabiuK04LxlsFpaz2jJCwSoCSUs+ePcVu QZWAIQaFIqKDtgfuw7cfDcHB7wlm0TNNg8mtNJLq7wrFZ+l9GPTIfQoZXLlAKJlR3dFew6BRmOoK SZTjKmbobe1iLhVLpb8v1qWnEAp5zhifxjg3Lk59PH0MquRMAWKYQZCw9D3Vx2zu2TUHfzIz46NO Oukkud/BsfDffE40uFNdDUrswfuhJcNicWrN3aPttttOxnDcccflPXN9vfqZF5K+y0nS1ggJq4Xg 5GCKDSOtGfnMoMVCoArJyUrbESWp5kAC5ORnoB+JqJB0wInXv39/SeXhxGwuB49eL9pmGL/DN6+2 tdBAT+8Vj8GIcNragpM1mJTbGlA90UneQTR3DxgUG9xPk30QTMOh4Z2kxCRoSjKUqLg/JQ3Gm3FR Bj2yW2yxRQ5ZUj1nZHxrFyvj4fy49957JcaMErSWvHlcRuPTW/jSSy+JOSB4nqAxn5IhHQeFxtOS fMuDDjpIbJT6mesqHex7wOdN2x6fOWPe/OA9Cb5MywFlR1i8yWsi741Jya0BJw8XJnPE+EMPIUlL S0d0q3OSMB6oJdCLaNNNN5VodE4qlprhD9U6xonRVsJctWCic3PHI7EyQp5vdhrumcPod3FzMfFn TYHn5TXQ4Nza/ehg4E9L7z8NzZR0KU3wHjFcw1+JgC+SUqAktiZAsqQaftVVV8l95vXwPvslG/6U AgOQWzsXC0la+pnzJcWx+Z85TQjFAmDLDWVHWG0FfJvqkIY1AU48Sjn+t57fld5aVY2ER6LzqzLt BVSJm4tR+jnB56ZzG39pWN5Lrj0jJKzVwJqcpIWOtbrH1/u3hcW0JtHWrqetjac9IySsECFClA1C wgoRIkTZICSsECFClA1CwgoRIkTZICSsECFClA1CwgoRIkTZICSsECFClA1CwgoRIkTZICSsECFC lA1CwgoRIkTZICSsECFClA1Cwmrn8NdpChGi3BESVhsGy+hsv/32Bb9jKZGW1HRiizN2eAkRoj0g JKw2jg8//HC19me1yVC6CtFeEBJWO0c5lsENEaIYQsLqAPDXNA8RopwRElY7B2uIhyphiPaCkLDa MCgV6aYCQejuK+yhx96IwUaj3JfdiNkUtBhh+XvZvffee1iwYIE0K9C999hQY7fddpMa4RqFut+w vnqwjTw/535s4OpvNMqGDaw3zsYaLAfN7ZqT/nRXGdZxZ2OHzz77TNqxs/wzOwWx7Rnr1pcqBa1V Y56fjTr4mx142CSDjStYj58NK1hmOETbRUhYbRysF14MX375pXRpSafTed9x4bEF1GabbVZ0AbMj MBtgsEcim2oUM9qzUQQbV5AAC+Gmm26SNu1+kDgGDRokJMXv2GTD3z+P37MlGbvOsElpMdJatmyZ dIRhgwnd8EPvz2tgXX02BWFzWRJXMcydO1caRrDjTjG7Hsfz4IMPFj1GiF8eIWGVKSjVULL66quv CvYx5CJn89FCEhGllrfeegtHHnkkFi9e3Ox5KBmxDRnJ75FHHsm25fL3+SvWm5CfnX322bj77rvz Oh3xO5IDJSWSZqF92VaN10hiDh5f/02iveCCC4QY2eaL5Bfcjp1y2O6KxF6MrHgdQSk1RNtDSFhl CC5+NumcP39+we/ZUv3iiy8uuv+nn34q3Yt138KW4LvvvpO+h2xJxV6KpUACICm++OKLzdrQ/vWv f0kX5WC/vi+++AIHHHCAnLclYNfrMWPGiCQXPM5ZZ51VUAoNUX4ICavMoFuUBzv5aomHPer+85// NGsX4gKmqlWsw7Q+T/A3pbrTTjtNJJ/m1C9NqrQ16WPq8QQlrVQqJR2dR48enXO+iy66KGtP0+Mj KClRyqMqycaq/uOxyS2lLbZg09uPGzdO7F9ByYrNZdlolFIV7XfPPfdcGAJSBggJq8zw2GOPibpX CDRmc4E21235nXfekcUZBBc4uwhfe+21Yiy//fbbRfoJLnQ2j50+fToOPvjgFo2XDTxJctOmTcP5 559fcJuFCxfm/L1kyRJMnDgxbzuquHQiECNHjpSmtX67GMlnwoQJYs/yS1iF2r6T9EjcmqiZOUDV M0TbRkhYZQJKEq+99poY2YuBkhUlrObw9NNPF/ycXZTZPZi/iX/84x8i+dBz6AcXfksIS3eEJgHS AUASIQG+//77edvS+O/f76mnnpJW9EGQpDRB0VbFVvGUjggtaVH6CzotCtmtSHz0sB5zzDFiy6Nz omfPns1eU4hfHiFhlQloXD/qqKNEvSkmydBAXQq0XxVrma7JSqtwgwcPziOsQhJRMVAC0mECJCIS QiHConQTlOKC4P6XXHKJeAT1+AqBRnh/eAPtbiTN4DmIN954Q35470hctH/16NGjRdcW4pdBSFht HNp2dPjhhwtpBaUFLtx9990X11xzTYsCRIPxUn510g8eiy3hC4F2p+AYCiE4nng83qLtVq5cmbdN 0PYV/NuvFvqPx+RvqtBXXHFFzr3z789/0wv6yiuv4OWXXxbPZRhs2zYRElaZeATpcStki9l8880l PIBG8OYCJzX8UpQf3377bd5nDK4sBAZa+rGmF3cwNGF1cemll2LgwIH4y1/+Iva7Quom8cknn4iq SHIL0TYRElYbhSYmegRpSA6qNJRqKioq8Pjjj2cDOgsRR9DLxujwQnj77bdFnWIgJkGpjl64QqCH bW2B4914443zPuf1krhpw2vuOknIhYh76NCh8sNr5D2766678NFHH+VE+/Nnzpw5a+3aQqw+QsJq o+DiYR0rqjPFJJjq6mqJtyokeWnwO3oWdZwT468KbUupgzYwShdU3f72t7/hhx9+KHhMehPXJnRw ahC8H7Q17bPPPtl7wmvh2OfNmyepRAxp8BMWwz+o7tLDSO/nBhtsgPPOO09sW7169co7R1jdom0j JKw2CkoUlHCKRZFTMqAaV0iVC8IfNMlFTWKaNGmS/K2PTQmOXshihnuOh9tSStljjz1KnlNH1LcW OqVn5513FgO9PgZ/M6+SnkJeA/MQSayUmOgEYBAs7U+UzvwEz/zDv//97yKF0olAkuK1MAA2eH1E nz59WqRah/hlEBJWBwMXI6UnGpiL2aiK7ce8QgZsrm3Qs0hbEiWpQk6Cjz/+WH5aA0qLwdiuYKBs ZWUlTj311NUYeYi1jZCwOhgoSTC84NlnnxXPI+04XLjFpCEdWMl9xo4dK5LNz4EBAwaIOnfiiSdK nJaWeoLj1OMrpRYXuj6/JEV7IOPYCqmJIdoOQsLqoGCAKYMsmc7CSgiFYp8Iql+nnHIKzjnnnGYj 6NcGmEv47rvvSjWIRx99tKhNjTaq4cOHS6BqEHQy0KtZTJrkNdGexXzGUkG3IX55hITVRsG3P0mC waKrA0oWVOUKSVpUgRiIyR/agkhauoQLDfqsEcXgz1K4+uqr5acU6O1sKbRNiSREGxQrRlAaZOAr o92pNpJsSKiMUi+W23jmmWfKD/MSqUbyN+PIaP/isdnkg2EUoc2qPBASVhsG1ZPVVcFa6vWid02H NLRFkJAoARXqItSSa6SXVHtKtSoYtkArP4SE1Uaxpt74rTlOW5cyio2vtePW27f16w2Rj5CwQoQI UTYICStEiBBlg5CwQoQIUTYICSvEGkPQ+B0atkOsaYSEFWKNkRVTZ9i0ggnIrMW+1VZbSRJ1sF57 iBA/FSFhhWgRdE4jpSYmGzOIk8XvWFDwww8/lJAD5u0xOZmBqMcdd5wUzmOyNVtr7bTTTlKrimTG lBvGgGmE3roQLUVIWCFaBJIVk4yZkMwAU1ZUWLp0qTRaZeAmP7/wwgvx5JNP4owzzsAzzzyDc889 V/5mX0N+z6aq3PbGG2/MBqXyNwNbQ9IK0RKEhBWiaIS8rtBASYr9C9kxmZ1mqOpRqiL5MHqche8Y 4MrkYpZvoUTFqp0slsccPdZop4rIKgyUwljX6vPPP5eihKwuylxBfudPrQkJLEQhhIQVoiBIGCQj 9j4kuTDCnE1RSU5sZEHJiiktffv2xdFHH51tREoio9REexZJT1cnZfka7ksbF0u7MM2Gx6Pkxf1Y O55NIahCFquKGiJESFghckCJiuQyZcoUUQG32GIL9O/fX9Q55vQNGTJEigaSeNi1hqVqdFcc5vmR wNg8lZVSSTz33HMPRowYIWVpunfvLoX0+JuSFdVFEtWhhx4quX0kLFZoGDVqlEhqwV6JIUKEhBUi BzSmsxYVk4qHDRsmqh1VOhbtY0UD9iu88sorpTUW/+Z3LBBIyYi/SVhsA0apid5BFtVjwjF7/lGi Yr4iSxSTAGmY53ZUJWkPY/E9Fgi87777pIDfgQceGD6dEDkICStEVrJisTz2JiSxEKxvTrWQ1Q6o /rHKAY3ttGmxJAsJio1KWbuKti22ySKx3XvvvaImUopi1VTuwzLN9Azy3zzX3XffLe3lJ0+ejGOP PVZsZCyBzKoRJEtWUr3//vtx/PHHS2njUNIKERJWiCzYkJTq2e677y4NKagSkqhoGNe9Bam2UT08 +eST8cgjj0idLEpFbB/P0jEssUzbFkMdKB1RuqKaR5Xwn//8pxAbCevPf/6ztCzTDVRJfCQkdobm cWgzoxGf0hY73bBtPcvdhAgRSlgdHJR2tCGdNilKNosWLcJvfvMbaY/FGue6NpWOw2JddXaG5jb/ 7//9P1H9SGQ0uOtONJSoqPaxsB7DFtj1me3qqe7RkE/VUPcpJCmxZDMlLlZBJUmyIiq789CAT8mL lUeb64EYomMgJKwQIk1RlaOdiWohJR0SDI3h7HlI4qKtiSohyYdEQ2P6Aw88gHHjxuU0iyjWwIHh DbSJsekrA0rfeecd3HrrrRL6QK8hQxoYu0XCJDnR6D537lypg0WSokR3wgknhE+rgyMkrA4KEgwj 1hmVTrIiYVAlpEp31VVXyQ8lJNqU2GqMUhX3YbAnCYcli0lihYrnFfqMVUJpjJ8xY4ZIZVQ3Dz74 YDkWz0V7Ff9Nmxb/TbWT0fMkLUpjHB+JjeolEdq0OiZCwurAoIpGciEpUR0766yz5Ic2qdtuu03C C1g+mZHp/fr1k7AG1lkn+axO/z5KUQx7oJ2KUhZtWSSqF154QQzzNMiTsJjOs2zZMuk5SImLddlJ qoWqjoboGAgJq4OCalyPHj3ETkQphiEG9MbR63fdddeJp5DGbnoK+W/2K2QIg1b9/N1qqLbtsssu Ip3RDsamECQ0EgztWjS80wsY7GLDOC+qnUzlYceaXXfdVWxXOq6Lx+R3DLVg2AMlshtuuEHGt6bb 2YcoD4SE1UFBexE9fAwSpepHaYZEwqBPSjv08JFMKH1R0qIX0Q9uSwmJZMZGGSQ/XU4mqK7xM3oe qeqRmGpra7PfUS1lbBf3YarP5ZdfLjmJvXv3lqBV3WmaMV8ktP3331+Ik+QVouMhJKwOBko2M2fO lIoJ9OhRuqLap71vVMloO6IKxuBNhiEw2VmrgNyOhneGJjAnUHer4ffsuMPodRrYGdrAqHZ6EElG JBv+XHbZZRJ4Sm8hx6IlNpIWpShGum+++eY5pEcj/0knnSQGfjY6pVeRIQ8k2hAdCyFhdUBQFSNR MECTLdx1nJUGiYWSF6UZ2oz8hfiYpEyPHaUzvx2Lx2OjVVZmoARFuxMN7CQaP5hbSA8kVUzaqZji o0FCYhgEg1CDIHkyqXrJkiVCWiRdHiNEx0JIWB0MrLhAozWlGcZDMWShECjFkBT8NiuqYfQOMrGZ sVH8jGEK7A/I2ClKVJTAGLJAWxhbh1Hl04So1UX+UM1kFDxTejgWfR7mKQ4ePFgIKgieiyoly9aw 6gOPoWO5QnQMhITVwfDZZ5+Jukf7U6FOyVoCo8rnh06vYZkYEh29hfTgMS+Q6TO0ddHoTpAQBw4c KInR3I4ERWmLaiITohmawM8YFMrPqd6tWLFC9mUcGCUsSlNByY9jpreS9rXTTjtNHAcMbA3RcRAS VgerwkBiIHFQAqIhuxCuuOIKIQ6CEhMJjpIVPXMkEsZiUf2jzYrkxPgqps5wn0QiIV2amYbDzyg9 MYyBSdT09lFdZK4hVUd6JWnsZyUH5hMSlLSoTlI9HD16dF4PwZ49ewphUlVlOERIWB0LIWF1IDDl hkZ1kglDDQp59Ci1MPLdD0pKuvICPXfch79JZpTYKGkxLIJJ0ZSASIgMNCW50etItY25g4xUp/TG MjQ0rlMyI1j5gZ5GkqAGY7/4WXB8PD5DJBgLRnIM0bEQElYHAqUSSjokJRrbgyCBUfrR9iSCOYIk FIJqH21LzD0kgTHZmdIW/819WUaG5NSrVy+xlfHflKJIbEcccYR8xu0Yq0XS0ZHrJCVG0zPxWZ+b NjHmF5Jcg6DERvsVK0swjoxezTDyvWMgJKwOBHrkWEWBXj4aroOJxCQLSj5+7x9jogiqk/ycBMXf JD+GFdAmxTAESlAE03UoRfFzlpihhEWJigGoDIegNMZjUULjZyRESn30WNLrx/MTPAftY4UIi8Z8 lr1h8jWN79tuu21IWB0EIWF1EJCMqEIxHYdBnoXUKQaHauKhxEJpTBfRo1RFomD8FCUq2qZYOZR2 KYYq0BhPAqRUxdzAu+66S6QkEg9tYPQs8ry6+w6Jiyof47a06sekZ79ayAoShdRWkhiJjWVpSJCh dNVxEBJWBwEXN1U6GrcZKR4EiYE2Kj+orumwARIWiYfSDCWirl27StAoP6MERQIjCfI4JDqSGlVP NqzgZ++++66UV6bRn95BBq1SpSTh6PPr8+nPmNZDYvN31eFvSnb8jCQcpuh0LISE1UHA2CjGN9GO RJLR0J49EgHVPD9Y7lgTBeOpGLbAcjAkHNqXSFokQhIYvX8kM3ofuS0LAVJio/pHYzzPQ4IjwfCY VC0psdHuRUmMx6ZXkV5HLZnxOCS2PffcU/5meRsSGs9HAqVExvI3tI+FUlbHQEhYHQRUx1iRgV42 1r3SYDIxy7oQTFb2g8ZxP0gKWlIj+ZCISEwMHOVxaWAniZH4GH5AKYvJzMwLJKHRZkXbFUmI2zG/ kKVjWGFUx3DxexKWBlVUnpe/qc6ykgRBYzu9kIUCTEO0X4SE1YEkLKpkJCUSAD10jHWiTYr2JXoC GVflB0lFg/sw3or700tHKYfExehzGr6pEtLzx3Ix3I/bcRuqeSQtSliUqigZ0eZFyYuSHT/3B4j6 z0lQheQxeQyGUHD/8847T0iOYREseUMJK0THQEhYHQSMEidJUTKhlMTIdabXaHsR/2YTCT/83kKt opFQKEmRbEhA9OTRzkRyYn4hqy1Q9WQsFkmSEhCJjFKYDl6lWkcDPcfBz/xhFME6W5TkGNXO5Gge h04AqrSU4CgxUl3kuDimEO0fIWF1EFAiISlRQuECJ0g6DBJl4TxtzPaDROQnEpIVvYKsd8U8QKqW l1xyiZAKDfYkKBIiE6QZjU5Jimk3JCZWhSCpUDXkefhvEhU9jX6Ppf+cBM+pm1pQbaRUx7HSVnbM McdIsb8wCbrjICSsDgKmsLBzDdWnN998UxY9E5xJNlTrCBrB/WCskwYN4mzbpbs00/bEEjX8jF5C GtxJhCQjGuSpylHVox2LMVmUhCghsbYVvX/chtHw3J+F+jRIqH5wTPQ6MtqeIPkRlOi0xBii4yAk rA4ESjskKy52EpZWo/Tv4OInqWjpiiVnHn74YVHnGIDKMjA0umvQBkZCoqrG77XqR9JiaANtVWPG jBGvHqUqlpahREbpiSokQVsa04cIqozcl6qsvy+h7o9YV1cnEiMlvWKNL0K0P4SE1UHAuCVWRmDk Oo3YDNb0g4s+GFVOMqAKR/sT9+cPDe6sk0VJilIWv6MERPAzFvuj1MbwBEpPJEiqi/RSknhojKfU REmNn/nVUMaHaXWV42FidFBN5ecMl6DkRs8hxxSi4yAkrA4CSizsjsNQAF3ORZOBlk6YA8hQBnrj SAyshkDDPKUh/k3VjTWyKG2RXCgZMQ2HoQ0srEeJiHYrljom8VA6YmoOJTeeX1ch5Xe0RVEq0+em PYttw7TRnZ+TGP1/++1cHAtVU52MHaJjICSsDgSqaLQBUcphFDolKh1bxTQYet9YdcFfC+vmm2+W KgskHEo89PqRRChpkawYM0XiI0lRXaNURVWSRELCIqnQ/sXtSVSMyaLkRjuWH1QPOQYNjotGdR6f KixtZBokRzoRSK5hR+iOhZCwOghIAJR+aAAn0eh4LOb83XnnneJpYz4gK5Cyb6A2blP9YqwWyxL7 O+UQVBdZKYESGQmJaiDJioZ1SmckNgZ6Ml+QNixKZ7RTURIjsRE6pIF15f0hDSwASHKkdMckakp/ PC+lNNrHdFgGvZShhNVxEBJWBwHJgNINDd+MlWKrLJYnpnpIDx77EDL4k5UXmPJCktL7kRQYAKqb Q5AwGCxKiYtR65TUSICMXKdkxdgsGsVpQNc2MBIgVUgSIEmOhMZ/8xis8c6UHz9YXJCqHw30zEOk h5NkSkmPkhrDGoLNKkK0f4SE1UHAhU2VkOVc6N1j52VKQ7QpESxLTFKhusYmp6yaQNKhShDVNAAA BjRJREFUBESpiEZ6hhFQ/WPxPBrQaQej8ZvEQwM8VUKqeiQpfk61jQZ4Eg9VN+YxkrzYYozHYDwX bWp0BPi78jDcgWTKGCvavxg4ylrv3Ic1s1hb/n//+1+e4yBE+0dIWB0MlLImTZokwZokGqpW9BpS oiJJUNJhFQVW/DznnHOy+1F6IlFMnDhRPHOsRcV0GYYy0H6lq4/qxGoSlk5ipnpHcuN+3IZBoEx6 JqFRFdXR9gRJ7I477hD1lMZ8lmZmnBg/Y9FBxoYxop6eRkpYIToWQsLqYKAtiAudNidGjpOcdKea U045Rap4klRoaKe0petTUdJitDrzEdmMgl462pgo6ZDkSEy0kVEKoqRF6Y1ERsmKNjNKVlQbKYmR 3Ci96bb3BD/jD6UqHocExVSh008/XaqLUqJj8jPVVRrnSYIhOh5CwuqAoJpFMqK6RmM4y8iQTC64 4AJJvbnmmmtEgrnnnnvErsXQBA3apWjzopGcrez/f3v3j5psGAQB3NZD2HkPbyDYChb2Fl7AA4hg Y2flGTyE5wq/Bza8vsQkknTPDEj+fEZTfBlmZ2d31+v1ZLVatXKT4lL+1XEKyolSMnOo00eheR8J e5mw8ayiNckUl2vSTP7FYjE5nU7Nu/JaAqmV30K2CYz2hxBWZ6jzWso15jk1o8xzlp5yUoIp55Rf DlWYNUQivKZSWjp1yIUKooAsBaS4lJRDE7wIyfP5X4jHwHINPQNVVTvdmfu6lspKr404XYr22pfL pSlDRIf4MuzcJ0JYnULXz5phf/gUi3lA3pJZQw8koaxTsokl7Ha7ye12e3oNakoEggoq1UNNSb4j JYpIF1HGqkq/8TYGpaIuocwV38zP8cUoPF9Tcn5Pqk5H0Wsi3KBPhLA6BYIx98fEFsrUfZN5ko+S o0JkykG+Fe/oeDw281vZyP8q1I52z/X4CXX4gqrim5VnZU7R70NZ8dQETnlcXtNWCL+PZoEOZtAv QlidAsksl8t2+p2qMSaj7Nrv9+2AKdVEafmekhCh6CiaFdRVtJ+qrjW/C2a9PJj3rDuIDlcw9K2T oegk7JGpeUEjRT4iMN3N8bWfoB+EsDpF/dEjDVs7dQWtoLGFlJGOsPzb4XBoq11carZpga+kfFOq 6SB68Ld0/b6DUlG+yvsgJs/nW/mahya4SslRW9QcIhN74FsJjyo/EWaCon0jhNU5BEF1+xDVdDpt pSICQVZIi4+EVEQMmPGeK2bARzIy43OqCMGIL8hXSbEjRLkrXhQ/TMRBh4+pb8jZHKDuI2PfzyhF Lf6j6qTolYTyVhQdiFwEQQirc1AsjG/L+KglRELJOEyBPK7XayMjvpaSTGBUR5G3JIHOaFdS8pZs GTWaIyNFQc1ms5aZUlaKT9i+IOel/KPWkKCSVCeQOW/wGpkx6Ckrr2vucLPZtAhGEOR/QdAg0Img BEGRjhEe3T0bQKktHTo+lis7/K/7/f55wUY8QmSBKS89L3hKPSkfXcpBeP6N8qK2HLNAeMZ4vA+C U/aZH1SOIjolIMXGTxt3FoN+EcIKGupWoLk+KsgKF3knysa6GWe8lIYFJaHyTmdP17AORCgDhVIR EPXEsDeorCOodLRyBmHZtCBUSkWJRhiIRnpiCzw1DQFKbrgdIghCWMETeE+1vlg2i7ekqycdr5ST ilcGMs6tqlEGIjLB0O122wjnfD63so6/heyQmVlFpCRo6ud5V5QX0vI9C/2oNoPWxm+G+6+CoBDC Cp5QakbpRj0Zt/G9ymsxz6XV7VVnihufMS9Ye6t4TjJTyji+lLlChMYjQ1AMfd+TrWKy86oej0db IWOTqZGcxBaCVwhhBV8CSSnh+FfUD1KhniggJr3yDwHJTIkiICdlIm8KkZkZNGKDiCgrio0fpQT0 Ggx4n1Njcla6j3UcIwheIYQVvET5R7wtZENVMdMt0FMC8qsQl891DM35UVLIyWJAe7eUiVSaWAJV xWhHaLJb8/m8LRKkuEJUwW8QwgreWgDovJeHLh4fCjlRRub9fDQ+o3RkqussikXYweVoBSWG4JSV w/P0QfBbhLCCt1BKSBeQqT6EEo//pBzUYbR51OqZIPgvhLCCf0OZ7XVBenxTMAgmf8QHQ3t3uAzk xZsAAAAASUVORK5CYII=