20140625 11092000 FALSE 20240828 10145100 20240828 10145100 1.0 file://\\WB-102485\C$\Users\nsandhar\Desktop\Refugio_Beach\Not_Assessed_NHD.shp Local Area Network Not_Assessed_NHD 002 NHDFlowlineToMeta Relationship 0.000 Geographic GCS_North_American_1983 Angular Unit: Degree (0.017453) <GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' 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>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],AUTHORITY[&quot;EPSG&quot;,4269]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>11258999068426.238</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4269</WKID><LatestWKID>4269</LatestWKID></GeographicCoordinateSystem> ExportFeatures NHDFlowline C:\GIS\ArcMap_Pro_Projects\Tribal_BU_Map\TBU_Map_Extents\WB_Extents_for_TBUM\WB_Extents_for_TBUM.gdb\NHDFlowline_Exported # NOT_USE_ALIAS "Permanent_Identifier "Permanent_Identifier" true true false 40 Text 0 0,First,#,NHDFlowline,Permanent_Identifier,0,39;FDate "FDate" true true false 8 Date 0 0,First,#,NHDFlowline,FDate,-1,-1;Resolution "Resolution" true true false 4 Long 0 0,First,#,NHDFlowline,Resolution,-1,-1;GNIS_ID "GNIS_ID" true true false 10 Text 0 0,First,#,NHDFlowline,GNIS_ID,0,9;GNIS_Name "GNIS_Name" true true false 65 Text 0 0,First,#,NHDFlowline,GNIS_Name,0,64;LengthKM "LengthKm" true true false 8 Double 0 0,First,#,NHDFlowline,LengthKM,-1,-1;ReachCode "ReachCode" true true false 14 Text 0 0,First,#,NHDFlowline,ReachCode,0,13;FlowDir "FlowDir" true true false 4 Long 0 0,First,#,NHDFlowline,FlowDir,-1,-1;WBArea_Permanent_Identifier "WBArea_Permanent_Identifier" true true false 40 Text 0 0,First,#,NHDFlowline,WBArea_Permanent_Identifier,0,39;FType "FType" true true false 4 Long 0 0,First,#,NHDFlowline,FType,-1,-1;FCode "FCode" true true false 4 Long 0 0,First,#,NHDFlowline,FCode,-1,-1;MainPath "MainPath" true true false 4 Long 0 0,First,#,NHDFlowline,MainPath,-1,-1;InNetwork "InNetwork" true true false 4 Long 0 0,First,#,NHDFlowline,InNetwork,-1,-1;VisibilityFilter "VisibilityFilter" true true false 4 Long 0 0,First,#,NHDFlowline,VisibilityFilter,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,NHDFlowline,Shape_Length,-1,-1" # Clip C:/GIS/ArcMap_Pro_Projects/Tribal_BU_Map/TBU_Map_Extents/WB_Extents_for_TBUM/WB_Extents_for_TBUM.gdb/NHDFlowline_Exported C:/GIS/ArcMap_Pro_Projects/Tribal_BU_Map/TBU_Map_Extents/WB_Extents_for_TBUM/WB_Extents_for_TBUM.gdb/WBGIS_State_Background C:\GIS\ArcMap_Pro_Projects\Tribal_BU_Map\TBU_Map_Extents\WB_Extents_for_TBUM\WB_Extents_for_TBUM.gdb\Clipped_NHDFlowline # ExportFeatures "Clipped_NHDFlowline selection" C:\GIS\ArcMap_Pro_Projects\Tribal_BU_Map\TBU_Map_Extents\WB_Extents_for_TBUM\WB_Extents_for_TBUM.gdb\NHDFlowline_Not_Assessed # NOT_USE_ALIAS "Permanent_Identifier "Permanent_Identifier" true true false 40 Text 0 0,First,#,Clipped_NHDFlowline selection,Permanent_Identifier,0,39;FDate "FDate" true true false 8 Date 0 0,First,#,Clipped_NHDFlowline selection,FDate,-1,-1;Resolution "Resolution" true true false 4 Long 0 0,First,#,Clipped_NHDFlowline selection,Resolution,-1,-1;GNIS_ID "GNIS_ID" true true false 10 Text 0 0,First,#,Clipped_NHDFlowline selection,GNIS_ID,0,9;GNIS_Name "GNIS_Name" true true false 65 Text 0 0,First,#,Clipped_NHDFlowline selection,GNIS_Name,0,64;LengthKM "LengthKm" true true false 8 Double 0 0,First,#,Clipped_NHDFlowline selection,LengthKM,-1,-1;ReachCode "ReachCode" true true false 14 Text 0 0,First,#,Clipped_NHDFlowline selection,ReachCode,0,13;FlowDir "FlowDir" true true false 4 Long 0 0,First,#,Clipped_NHDFlowline selection,FlowDir,-1,-1;WBArea_Permanent_Identifier "WBArea_Permanent_Identifier" true true false 40 Text 0 0,First,#,Clipped_NHDFlowline selection,WBArea_Permanent_Identifier,0,39;FType "FType" true true false 4 Long 0 0,First,#,Clipped_NHDFlowline selection,FType,-1,-1;FCode "FCode" true true false 4 Long 0 0,First,#,Clipped_NHDFlowline selection,FCode,-1,-1;MainPath "MainPath" true true false 4 Long 0 0,First,#,Clipped_NHDFlowline selection,MainPath,-1,-1;InNetwork "InNetwork" true true false 4 Long 0 0,First,#,Clipped_NHDFlowline selection,InNetwork,-1,-1;VisibilityFilter "VisibilityFilter" true true false 4 Long 0 0,First,#,Clipped_NHDFlowline selection,VisibilityFilter,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,Clipped_NHDFlowline selection,Shape_Length,-1,-1" # ExportFeatures NHDFlowline_Not_Assessed C:\GIS\ArcMap_Pro_Projects\Tribal_BU_Map\TBU_Map_Extents\WB_Extents_for_TBUM\WB_Extents_for_TBUM.gdb\NHDFlowline_Not_Assessed_Final # NOT_USE_ALIAS "Permanent_Identifier "Permanent_Identifier" true true false 40 Text 0 0,First,#,NHDFlowline_Not_Assessed,Permanent_Identifier,0,39;FDate "FDate" true true false 8 Date 0 0,First,#,NHDFlowline_Not_Assessed,FDate,-1,-1;Resolution "Resolution" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed,Resolution,-1,-1;GNIS_ID "GNIS_ID" true true false 10 Text 0 0,First,#,NHDFlowline_Not_Assessed,GNIS_ID,0,9;GNIS_Name "GNIS_Name" true true false 65 Text 0 0,First,#,NHDFlowline_Not_Assessed,GNIS_Name,0,64;LengthKM "LengthKm" true true false 8 Double 0 0,First,#,NHDFlowline_Not_Assessed,LengthKM,-1,-1;ReachCode "ReachCode" true true false 14 Text 0 0,First,#,NHDFlowline_Not_Assessed,ReachCode,0,13;FlowDir "FlowDir" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed,FlowDir,-1,-1;WBArea_Permanent_Identifier "WBArea_Permanent_Identifier" true true false 40 Text 0 0,First,#,NHDFlowline_Not_Assessed,WBArea_Permanent_Identifier,0,39;FType "FType" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed,FType,-1,-1;FCode "FCode" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed,FCode,-1,-1;MainPath "MainPath" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed,MainPath,-1,-1;InNetwork "InNetwork" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed,InNetwork,-1,-1;VisibilityFilter "VisibilityFilter" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed,VisibilityFilter,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,NHDFlowline_Not_Assessed,Shape_Length,-1,-1" # ExportFeatures "NHDFlowline_Not_Assessed_Final selection" C:\GIS\ArcMap_Pro_Projects\Tribal_BU_Map\TBU_Map_Extents\WB_Extents_for_TBUM\WB_Extents_for_TBUM.gdb\Not_Assessed_NHD # NOT_USE_ALIAS "Permanent_Identifier "Permanent_Identifier" true true false 40 Text 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,Permanent_Identifier,0,39;FDate "FDate" true true false 8 Date 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,FDate,-1,-1;Resolution "Resolution" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,Resolution,-1,-1;GNIS_ID "GNIS_ID" true true false 10 Text 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,GNIS_ID,0,9;GNIS_Name "GNIS_Name" true true false 65 Text 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,GNIS_Name,0,64;LengthKM "LengthKm" true true false 8 Double 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,LengthKM,-1,-1;ReachCode "ReachCode" true true false 14 Text 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,ReachCode,0,13;FlowDir "FlowDir" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,FlowDir,-1,-1;WBArea_Permanent_Identifier "WBArea_Permanent_Identifier" true true false 40 Text 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,WBArea_Permanent_Identifier,0,39;FType "FType" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,FType,-1,-1;FCode "FCode" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,FCode,-1,-1;MainPath "MainPath" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,MainPath,-1,-1;InNetwork "InNetwork" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,InNetwork,-1,-1;VisibilityFilter "VisibilityFilter" true true false 4 Long 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,VisibilityFilter,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,NHDFlowline_Not_Assessed_Final selection,Shape_Length,-1,-1" # ExportFeatures Not_Assessed_NHD C:\Users\nsandhar\Desktop\Refugio_Beach\Not_Assessed_NHD.shp # NOT_USE_ALIAS "Permanent_Identifier "Permanent_Identifier" true true false 40 Text 0 0,First,#,Not_Assessed_NHD,Permanent_Identifier,0,39;FDate "FDate" true true false 8 Date 0 0,First,#,Not_Assessed_NHD,FDate,-1,-1;Resolution "Resolution" true true false 4 Long 0 0,First,#,Not_Assessed_NHD,Resolution,-1,-1;GNIS_ID "GNIS_ID" true true false 10 Text 0 0,First,#,Not_Assessed_NHD,GNIS_ID,0,9;GNIS_Name "GNIS_Name" true true false 65 Text 0 0,First,#,Not_Assessed_NHD,GNIS_Name,0,64;LengthKM "LengthKm" true true false 8 Double 0 0,First,#,Not_Assessed_NHD,LengthKM,-1,-1;ReachCode "ReachCode" true true false 14 Text 0 0,First,#,Not_Assessed_NHD,ReachCode,0,13;FlowDir "FlowDir" true true false 4 Long 0 0,First,#,Not_Assessed_NHD,FlowDir,-1,-1;WBArea_Permanent_Identifier "WBArea_Permanent_Identifier" true true false 40 Text 0 0,First,#,Not_Assessed_NHD,WBArea_Permanent_Identifier,0,39;FType "FType" true true false 4 Long 0 0,First,#,Not_Assessed_NHD,FType,-1,-1;FCode "FCode" true true false 4 Long 0 0,First,#,Not_Assessed_NHD,FCode,-1,-1;MainPath "MainPath" true true false 4 Long 0 0,First,#,Not_Assessed_NHD,MainPath,-1,-1;InNetwork "InNetwork" true true false 4 Long 0 0,First,#,Not_Assessed_NHD,InNetwork,-1,-1;VisibilityFilter "VisibilityFilter" true true false 4 Long 0 0,First,#,Not_Assessed_NHD,VisibilityFilter,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,Not_Assessed_NHD,Shape_Length,-1,-1" # Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 2; ESRI ArcCatalog 9.3.1.1850 en The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. NHD data was originally developed at 1:100,000-scale and exists at that scale for the whole country. This high-resolution NHD, generally developed at 1:24,000/1:12,000 scale, adds detail to the original 1:100,000-scale NHD. (Data for Alaska, Puerto Rico and the Virgin Islands was developed at high-resolution, not 1:100,000 scale.) Local resolution NHD is being developed where partners and data exist. The NHD contains reach codes for networked features, flow direction, names, and centerline representations for areal water bodies. Reaches are also defined on waterbodies and the approximate shorelines of the Great Lakes, the Atlantic and Pacific Oceans and the Gulf of Mexico. The NHD also incorporates the National Spatial Data Infrastructure framework criteria established by the Federal Geographic Data Committee. The NHD is a national framework for assigning reach addresses to water-related entities, such as industrial discharges, drinking water supplies, fish habitat areas, wild and scenic rivers. Reach addresses establish the locations of these entities relative to one another within the NHD surface water drainage network, much like addresses on streets. Once linked to the NHD by their reach addresses, the upstream/downstream relationships of these water-related entities--and any associated information about them--can be analyzed using software tools ranging from spreadsheets to geographic information systems (GIS). GIS can also be used to combine NHD-based network analysis with other data layers, such as soils, land use and population, to help understand and display their respective effects upon one another. Furthermore, because the NHD provides a nationally consistent framework for addressing and analysis, water-related information linked to reach addresses by one organization (national, state, local) can be shared with other organizations and easily integrated into many different types of applications to the benefit of all. U.S. Geological Survey in cooperation with U.S. Environmental Protection Agency, USDA Forest Service, and other Federal, State and local partners (see dataset specific metadata under Data_Set_Credit for details). See dataset specific metadata. NHDFlowline vector digital data \\igskbthisusy01\nhdgeo\oracle_export\GDBExtractServer\Template\NHD_File_Template_High_92v210.gdb Unknown Reston, Virginia U.S. Geological Survey See dataset specific metadata. REQUIRED: The year (and optionally month, or month and day) for which the data set corresponds to the ground. In work Irregular -200 -56.8344239 143.165576 0 U.S. Department of the Interior, U.S. Geological Survey, 1999, Standards for National Hydrography Dataset (http://mapping.usgs.gov/standards/) FWHydrography Hydrography Stream / River Lake / Pond Canal / Ditch Reservoir Spring / Seep Swamp / Marsh Artificial Path Reach Code US U.S. Department of Commerce, 1977, Countries, dependencies, areas of special sovereignty, and their principal administrative divisions (Federal Information Processing Standards 10-3): Washington, D.C., National Institute of Standards and Technology. None. None. Acknowledgment of the originating agencies would be appreciated in products derived from these data. Personal GeoDatabase Feature Class Earth Science Information Center, U.S. Geological Survey 1 888 ASK USGS ask@usgs.gov 0800-1600 Eastern Time In addition to the address above there are other ESIC offices throughout the country. A full list of these offices is at URL: http://mapping.usgs.gov/esic/esic_index.html See dataset specific metadata. Microsoft Windows 10 Version 10.0 (Build 22631) ; Esri ArcGIS 13.3.0.52636 Not_Assessed_NHD en FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time REQUIRED: The person responsible for the metadata information. Earth Science Information Center, U.S. Geological Survey mailing address Reston VA 20192

507 National Center

USA 1 888 ASK USGS. nhd@usgs.gov In addition to the address above there are other ESIC offices throughout the country. A full list of these offices is at URL: http://mapping.usgs.gov/esic/esic_index.html 20100520 ISO 19115 Geographic Information - Metadata DIS_ESRI1.0 dataset Downloadable Data ArcGIS Geodatabase 8.3 tar and uncompress 002 file://\\igskbthisusy01\nhdgeo\oracle_export\GDBExtractServer\Template\NHD_File_Template_High_92v210.gdb Local Area Network Personal GeoDatabase Feature Class Shapefile 0.000 Vector Simple FALSE 0 FALSE TRUE GCS_North_American_1983 Decimal degrees 0.000000 0.000000 North American Datum of 1983 Geodetic Reference System 80 6378137.000000 298.257222 Explicit elevation coordinate included with horizontal coordinates 0.000025 National Geodetic Vertical Datum of 1929 meters GCS_North_American_1983 EPSG 6.5(3.0.1) 0 Not_Assessed_NHD Feature Class 0 Shape Shape Geometry 0 0 0 Feature geometry. ESRI Coordinates defining the features. FDate FDate Date 8 0 0 Resolution Resolution Integer 10 10 0 GNIS_ID GNIS_ID String 10 0 0 GNIS_Name GNIS_Name String 65 0 0 LengthKM LengthKM Double 19 0 0 ReachCode ReachCode String 14 0 0 FID FID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. FlowDir FlowDir Integer 10 10 0 Permanent_ Permanent_ String 40 0 0 FType FType Integer 10 10 0 FCode FCode Integer 10 10 0 ArtificialPath 558 Resolution 0 Resolution Coded Value Default value Duplicate Integer FlowDir HydroFlowDirections Coded Value Default value Duplicate Integer 0 FType 558 HydroFlowDirections Coded Value Default value Duplicate Integer FCode 55800 ArtificialPath FCode Coded Value Default value Duplicate Integer MainPath 0 MainPath Domain Coded Value Default value Duplicate Integer InNetwork NoYes Domain Coded Value Default value Default value Integer 1 VisibilityFilter 0 VisibilityFilter Domain Coded Value Default value Duplicate Integer CanalDitch 336 Resolution 0 Resolution Coded Value Default value Duplicate Integer FlowDir HydroFlowDirections Coded Value Default value Duplicate Integer 0 FType 336 HydroFlowDirections Coded Value Default value Duplicate Integer FCode 33600 CanalDitch FCode Coded Value Default value Duplicate Integer MainPath 0 MainPath Domain Coded Value Default value Duplicate Integer InNetwork NoYes Domain Coded Value Default value Default value Integer 1 VisibilityFilter 0 VisibilityFilter Domain Coded Value Default value Duplicate Integer Pipeline 428 Resolution 0 Resolution Coded Value Default value Duplicate Integer FlowDir HydroFlowDirections Coded Value Default value Duplicate Integer 0 FType 428 HydroFlowDirections Coded Value Default value Duplicate Integer FCode 42805 Pipeline FCode Coded Value Default value Duplicate Integer MainPath 0 MainPath Domain Coded Value Default value Duplicate Integer InNetwork NoYes Domain Coded Value Default value Default value Integer 1 VisibilityFilter 0 VisibilityFilter Domain Coded Value Default value Duplicate Integer Underground Conduit 420 Resolution 0 Resolution Coded Value Default value Duplicate Integer FlowDir HydroFlowDirections Coded Value Default value Duplicate Integer 0 FType 420 HydroFlowDirections Coded Value Default value Duplicate Integer FCode 42000 Underground Conduit FCode Coded Value Default value Duplicate Integer MainPath 0 MainPath Domain Coded Value Default value Duplicate Integer InNetwork NoYes Domain Coded Value Default value Default value Integer 1 VisibilityFilter 0 VisibilityFilter Domain Coded Value Default value Duplicate Integer StreamRiver 460 Resolution 0 Resolution Coded Value Default value Duplicate Integer FlowDir HydroFlowDirections Coded Value Default value Duplicate Integer 0 FType 460 HydroFlowDirections Coded Value Default value Duplicate Integer FCode 46006 StreamRiver FCode Coded Value Default value Duplicate Integer MainPath 0 MainPath Domain Coded Value Default value Duplicate Integer InNetwork NoYes Domain Coded Value Default value Default value Integer 1 VisibilityFilter 0 VisibilityFilter Domain Coded Value Default value Duplicate Integer WBArea_Per WBArea_Per String 40 0 0 Connector 334 Resolution 0 Resolution Coded Value Default value Duplicate Integer FlowDir HydroFlowDirections Coded Value Default value Duplicate Integer 0 FType 334 HydroFlowDirections Coded Value Default value Duplicate Integer FCode 33400 Connector FCode Coded Value Default value Duplicate Integer MainPath 0 MainPath Domain Coded Value Default value Duplicate Integer InNetwork NoYes Domain Coded Value Default value Default value Integer 1 VisibilityFilter 0 VisibilityFilter Domain Coded Value Default value Duplicate Integer MainPath MainPath Integer 10 10 0 InNetwork InNetwork Integer 10 10 0 Coastline 566 Resolution 0 Resolution Coded Value Default value Duplicate Integer FlowDir HydroFlowDirections Coded Value Default value Duplicate Integer 0 FType 566 HydroFlowDirections Coded Value Default value Duplicate Integer FCode 56600 Coastline FCode Coded Value Default value Duplicate Integer MainPath 0 MainPath Domain Coded Value Default value Duplicate Integer InNetwork NoYes Domain Coded Value Default value Default value Integer 1 VisibilityFilter 0 VisibilityFilter Domain Coded Value Default value Duplicate Integer Visibility Visibility Integer 10 10 0 Shape_Leng Shape_Leng Double 19 0 0 NHDFlowlineToMeta Relationship The National Hydrography Dataset is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of water, paths through which water flows, and related entities. The information encoded about features includes a feature date, classification by type, other characteristics, a unique common identifier, the feature length or area, and (rarely) elevation of the surface of water pools and a description of the stage of the elevation. For reaches, encoded information includes a reach code. Names and their identifiers in the Geographic Names Information System, are assigned to most feature types. The direction of flow is encoded for networked features. The data also contains relations that encode metadata, and information that supports the exchange of future updates and improvements to the data. The names and definitions of all feature types, characteristics, and values are in the Standards for National Hydrography Dataset: Reston, Virginia, U.S. Geological Survey, 1999. The document is available online through http://mapping.usgs.gov/standards/. The names and definitions of all feature types, characteristics, and values are in U.S. Geological Survey, 1999, Standards for National Hydrography Dataset High Resolution: Reston, Virginia, U.S. Geological Survey. The document is available online through http://mapping.usgs.gov/standards/. Information about tables and fields in the data are available from the user documentation for the National Hydrography Dataset at http://nhd.usgs.gov. The National Map - Hydrography Fact Sheet is also available at: http://erg.usgs.gov/isb/pubs/factsheets/fs06002.html. 20240828 Statements of attribute accuracy are based on accuracy statements made for U.S. Geological Survey Digital Line Graph (DLG) data, which is estimated to be 98.5 percent. One or more of the following methods were used to test attribute accuracy: manual comparison of the source with hardcopy plots; symbolized display of the DLG on an interactive computer graphic system; selected attributes that could not be visually verified on plots or on screen were interactively queried and verified on screen. In addition, software validated feature types and characteristics against a master set of types and characteristics, checked that combinations of types and characteristics were valid, and that types and characteristics were valid for the delineation of the feature. Feature types, characteristics, and other attributes conform to the Standards for National Hydrography Dataset (USGS, 1999) as of the date they were loaded into the database. All names were validated against a current extract from the Geographic Names Information System (GNIS). The entry and identifier for the names match those in the GNIS. The association of each name to reaches has been interactively checked, however, operator error could in some cases apply a name to a wrong reach. This statement is generally true for the most common sources of NHD data. Other sources and methods may have been used to create or update NHD data. In some cases, additional information may be found in the NHDMetadata table. Points, nodes, lines, and areas conform to topological rules. Lines intersect only at nodes, and all nodes anchor the ends of lines. Lines do not overshoot or undershoot other lines where they are supposed to meet. There are no duplicate lines. Lines bound areas and lines identify the areas to the left and right of the lines. Gaps and overlaps among areas do not exist. All areas close. The completeness of the data reflects the content of the sources, which most often are the published USGS topographic quadrangle and/or the USDA Forest Service Primary Base Series (PBS) map. The USGS topographic quadrangle is usually supplemented by Digital Orthophoto Quadrangles (DOQs). Features found on the ground may have been eliminated or generalized on the source map because of scale and legibility constraints. In general, streams longer than one mile (approximately 1.6 kilometers) were collected. Most streams that flow from a lake were collected regardless of their length. Only definite channels were collected so not all swamp/marsh features have stream/rivers delineated through them. Lake/ponds having an area greater than 6 acres were collected. Note, however, that these general rules were applied unevenly among maps during compilation. Reaches codes are defined on all features of type stream/river, canal/ditch, artificial path, coastline, and connector. Waterbody reach codes are defined on all lake/pond and most reservoir features. Names were applied from the GNIS database. Detailed capture conditions are provided for every feature type in the Standards for National Hydrography Dataset available online through http://mapping.usgs.gov/standards/. This statement is generally true for the most common sources of NHD data. Other sources and methods may have been used to create or update NHD data. In some cases, additional information may be found in the NHDMetadata table. Statements of horizontal positional accuracy are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For horizontal accuracy, this standard is met if at least 90 percent of points tested are within 0.02 inch (at map scale) of the true position. Additional offsets to positions may have been introduced where feature density is high to improve the legibility of map symbols. In addition, the digitizing of maps is estimated to contain a horizontal positional error of less than or equal to 0.003 inch standard error (at map scale) in the two component directions relative to the source maps. Visual comparison between the map graphic (including digital scans of the graphic) and plots or digital displays of points, lines, and areas, is used as control to assess the positional accuracy of digital data. Digital map elements along the adjoining edges of data sets are aligned if they are within a 0.02 inch tolerance (at map scale). Features with like dimensionality (for example, features that all are delineated with lines), with or without like characteristics, that are within the tolerance are aligned by moving the features equally to a common point. Features outside the tolerance are not moved; instead, a feature of type connector is added to join the features. This statement is generally true for the most common sources of NHD data. Other sources and methods may have been used to create or update NHD data. In some cases, additional information may be found in the NHDMetadata table. Statements of vertical positional accuracy for elevation of water surfaces are based on accuracy statements made for U.S. Geological Survey topographic quadrangle maps. These maps were compiled to meet National Map Accuracy Standards. For vertical accuracy, this standard is met if at least 90 percent of well-defined points tested are within one-half contour interval of the correct value. Elevations of water surface printed on the published map meet this standard; the contour intervals of the maps vary. These elevations were transcribed into the digital data; the accuracy of this transcription was checked by visual comparison between the data and the map. This statement is generally true for the most common sources of NHD data. Other sources and methods may have been used to create or update NHD data. In some cases, additional information may be found in the NHDMetadata table. The processes used to create and maintain high-resolution NHD data can be found in the table called "NHDMetadata". Because NHD data can be downloaded using several user-defined areas, the process descriptions can vary for each download. The NHDMetadata table contains a list of all the process descriptions that apply to a particular download. These process descriptions are linked using the DuuID to the NHDFeatureToMetadata table which contains the com_ids of all the features within the download. In addition, another table, the NHDSourceCitation, can also be linked through the DuuID to determine the sources used to create or update NHD data. Unknown Dataset copied. \\F880\oracle_export\GDBExtractServer\Template\NHD_Template_High.mdb 20071130 14444000 Metadata imported. D:\Workspace\v107\Metadata\nhdflowline.xml 20100421 16520900 Dataset copied. \\IGSKBTHIWS531\D\ExtractTest\oracle_export\GDBExtractServer\Template\NHD_File_Template_High_92v200.gdb 20100520 16121900 Dataset copied. \\igskbthisusy01\nhdgeo\oracle_export\GDBExtractServer\Template\NHD_Template_High_92v210.mdb 20120221 13582500 iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJy0vVeTZNmVpbdda/cID61T69IKQKPR3SPaZmgz5Asf+EDj3+MD H2kcG7MZozVboBsNUUBVZVWlFpGhPSJca0H71rnH3SMyMisLwNyytKyMcL/33CP2WXvttfeJ1hun I3uHa2RDG44Gb//MaGShUEj/H7KQ2Shkg1FfP/M/f9fr+c6JhUMh21ydfafPt7t9e/j8yFqdnp4d i4b18+FwZNFI2K5fWrBUIvqWdtANoTPvcNEVsaj1Bh0LRyL2p1zdbs8q5ZpFo3E9ejQaWiwWtUIh ayO1hdbwDiEr11q2d1S1ZCJmuUxCbW13+rZzcGqxaNQur8/ZTC5l4bB759FwqL8b7Z7tH9dsrpC2 Qi5lx+WGZVJ8P2Qvd08sHA7ZxvKMJRNR9fVwOLR6o2HfPD60ezc2xs8aDgbW6/et1enboxfHdnhS s63VWVtdnLFoJKK5kU7GLRaN6J6Dft/+6ctnlkwm9PNrm/MWj0X1O/q31+2oj2kvb9rvD23/uKF7 jkYWzJdgVEZmvf7A9o4qtntYtl6nbY1Gw1q9kWUyWcul49Zode3O9TUrZJMWDplFIhGL0I7hyDrd vuZCPBbWOx8dV6zbG9j2Yd2Go5B9fHvFer2+hSNhW5rL6x14553Dsv3u/o5d3Vq0D2+uWSIeUWP4 Ofe5dXnZZgoZOzo6svtPS/bqsG5fvH/Jrm7Maxz9nKL9g+HAmq2e/dd//M46vb59dm/LTipuLN6/ uar+LVfb9mLvxHKZpC3N5cxGA3uxV7ZbV1bs8LhqB6WyxaMhW5xN24Pnx/bTT27Y/mHZHr04tGw6 bpVaww5PW/bZe1sWHvVs56hua0tFa3YGtjyfs2fbR7axUrSF2Yzm7qDfsxc7Jas2OmpHrz+0mXza Wp2BLRTzNpNNWL/f05xoNps2GPQtm81ZrVazL+8/tXw+Z5tLBXu2c2LLi0VbXijojVvNhrVbTSs3 etYaxOz65rLFo0M7PSlZKBS2SCxhsVjMYvGEPRnMWaUftZ3tPf1uZjZvL+5/betXr1hyULPs3ILG cH/30Ha39+3zj2+Y79k/+vILnL/9v90VstBobAfOfPZdLj+h3/Vi0mOYtlZmLZOKTz1nZJFw2BLx txkr1953ad/k/S7+2Tsb5pHZsG9WazasUa/b7OysFs3QnLHB6A5GI9s9qNjhSd3Wl2dtfiZjsUjI hqOhFnEuHdNCwHA9en5oFgpbsZCx1fmspVIxvTO/Hw7qdnBclwGazUe1KC+vFW17v2TPd49ta2XO 0smoximVTMiwHFcalk7FLBI2jUMiHrdoLGL3rq/YzmHC9kt1a7R6mlAYiY/urFkoxHQKacg/ur2h NvYHbHKT/hkMBhYOY+RkmTQ1otGIrS7k9XsM40mlaUendY3b+tKs2s1Czadj1u/3rVGvqs8LM0U7 rjQtWmnaYjEjI+XHkj/RaMgS8ZgMOIuPv2vNrgw/RrRS72jOzOayFomErVxt2tNXJzKuq4s5W11k 4bIROGM+Gg4slYhZPB6z7YOyhUIjSyVjdvvKohVncvaPXz7Vwr95eVF97Oawm8fZlFmxkLJOb2Cb K0VbWyxYtd6yX375VP1368qy3dha0DvTz3/4bl8L+7f3t62QTdjaQt4ePD+ypZmUJeMRq9Y7ls+l LRzBMA+t1uhaKhmX0T46bluvN7B/+vKFrS8V1KbFuYLNz2Y0Fr1OR/1Ra7Ts1UHDbl/N2Ew6avul ms3kM5bPJqzb7dp+qWrRaNhq9YYlEgmbLcYtm83a5lLWnu6cWDIWYnKobzCA8ThzJ2y9XscyyYgd HTSs0+1aKpG04vyCffdox3LpgRVnspr83VrFtg+a1mx2bH/nwNa31mzzzl3LZDMWsjnrBeu/3Dyw 6x99ZL1M6k8zWK8bqQs/NLZYPwZlDTEeI7d43+WKREIWj0YsnXQo5Lunh5pwDOC7Xu/SPqGEweR9 3/ruF1zjz4fM2p227e0eWKfT0fuup5cnnzOzg1JVi/fWlSVLJ+IOvQwdygVZzeSjlssMrZBLWn8w tHAobK8OyvZs98Qurc5aOhW3axtFe757KnTFImJy8fBkMmYrC3n7/tmhtTtdGSct81DI7l5btn/5 6qX6biaX0H1pTyQUtXhsYJfW5m1lfsa6va5FozEZ2liEBTp5x0w6bsPBUN/j+7zRYOA2BP60uz17 tlOyS6tFS8ajMhij4cjqjbY9eHZo966varHQLhYX906lEha2uIUGbRltjGy7E7N6I2LtzkAblcng u2eApHYOynZ4XNP36b8rm0s2k41buVK3ZGxkhWzckvGYPdk+tm5/ZHMzGVssZm2ukLJIKGRPd8tW a3bs1uVFyySjls8k7Or6vP3yDy9sbiZtxVzMijMpmy3k7J//8MIevzySsc+m4nb3+qoQJuik1+tZ QcYvbP/9n7+3T+5uWjwesXwmZZdWZ+y7pwf2xfuX1WetTstOqi3LZUZ28/KyPINOuykjn81mrFho 26PnB/bJ3Q27ujZnL/erQrvdbsf+5Q8v7PrmnA1GIfu3P7luyXjY4nHaMFI/tDpdO600LZeK2nAw sk/vbQndg/iW53I2m0/ZcNCzvaOyvJZMJGmDEeOQcgY4ErGZmRkrVhu2vX9q0XjGlhfC2iwxnBGh bGesV+Yy2kyTySVLxSO2tjRjL3aObfe4aeV61xJzK7awuGKhaNwSyYTFE3FLZTIW8p5CsBZApals xoah0B9vsH5woYYCM8XfP9Id5BoMhmajd0dYQiTDkRY+F7s7C+DPf725TT+IzoL2RCMxG4XCFo1E bWVlyd01EtbEPvP5EYYpYlm5ca7Pcd1CQhLuWVrUuFajkQ2HDnXVmz3To/Snp90P169ab1ul3pZb wOUMmFvicv34Ryhs2UzGPr69bl892NH3NleLcv1CgbvFogOZxLtmkWjMotGo22UHQ/UBLs5xuaWF z2Lw3QIiASFh5OKxmC0Vs/bL3z8Turq6uWCVWlvI6trWvM0WUjJ03Lfb7wsNVRod21jMWjzhXFWh hcHQvnmyb7/8w0u5xpfWiuqjcq2tNi7N5+zejVU9H8MHYuS9Y5G8ZZsNa7Wa9uxVSxtAKh7Sgstn kxaPR+UugVBAVRhRDOvl9VnL51MyyKAOUBD3+P9+99I+urNujWbX7l5dphvt28f79h7PHvWs1azb 7SsLeveXe6dWb7bt7/7u7+29G5v2ffmVFuWXX5atODtr3V7Pjo/2rdeblwHBUDWbQ+cppJKWz6bs tFaxRy9LFgkNrTiTtkazY8tzGdv96rmd1nP2kw+uqH8ePN2zcr1n2UzComGokogtz2Xt2auSft7s lywVj1oxH7d6o2mdXs82lmas2e5avdnRn0IuYzP5pOYRQ5nLF2xtuWv1zqHl8mnLZVKaF7F4XH2f zuSs3+/abCpmxzs16w9GcgHn5+dsOOzb45enojA2l+J2mEhYJxS3jUtr9vDbx7a4vKDNi2v7+Str NlpaBw/vP7ZYPPrjDdY7Iwp4Gc9l/REXk/jHGLpYjMU3Mg/KMA7/I8zVRe//tnbSDhZeJByzSDym jun2Otbuta3aHVql3nVuVThkkWrXoocN8SXL83kNPj/3z8Cl4a3gtkBFB6W6dnN4D1wM6JfjSstS iYRlMynxIN1uX/dPxByKwai5+2E4o+JbImF4G/8ctdpmC85oHZ7WhVZxV3Clpt1/DBW7ofsn7RsA p6zW6NjOYc0WilkL6d6u/aCMeqNltVZdblE+l7R7Vxds56hm/+Xvv7Obl5csm04I+eHeueeMLBqL 2XDYtqOTil1amdHP1Q/hiPgnXODP7i1YqVwXtwen8/6N1cDA0vfu3QZh3FCQVsTCyYg12m3bP6nJ nQMpwa1FYkkZJi5c8Uw6afeuLetdHr8sWbs7sMGwY51uz755tGcf3lyxaChsH99es1eHNX0XRLax PGvD0UkwB4YysqAIFnY+B6oqWibatwfff2sLCwuWy2ft5KRlp6en6qu5rNmzvSO9K4YWQ8fFHIeT W10s2LdPS5bNJO3y+rwM9OL8jN29Mm+doTO6Ryc1qzedq9hq9dSvuHul06otzs/avRtpOfC06aBU sf7QbGO+ELjyQzuttW1zFSMzsJ39Y1sq5uS+4/rlCgXbWGzZSb1rrXZX49Zs1K0MVxWOmoWjlo6G tGmc4bDDSdtcX7BEmIXatDmr2IHNMZls49K6vXqxY5lsykqHp7aytiQDpoEM6Jo/mcOavnyj/EQL 4NUbP/82zohOftfLIY/g/wMzBbQXUfrnvkTMTdp+UftlpMIRi4ZjFsLVkTvUs0GPHSpsnW7byvW2 Ndp9a3UdxwM8n59N2/VLi1pgDHTptKVdVUZLzzPtVq8OT2znoGLzs1m7vrUoQ8LnTit1m5/Jisdi j4IvebZX1Y48N5sWeS8uZuyWws04wp9LJLhcRtoP0kpYOpUQrMeViMccIe2+6riq49O6UAAbk0N+ Zu3eQCS3XNjBwBmYodn+UcUevzqxn3zI7o89HVomEbWtlaJVG13xSjzXIauB2hoKORcjmYxaIhYR EX15vajv93pD63QHNptP29XNeQUPXuyeaAHtHFbUh/RR6bRh5WpLHBLv6oH3+nLBNlfnLTRyriPu zuZKTkT9wxdHMtoEf3BlMDC8BBvAi92K3bi0qH5+8HRXpPXaYt6azZa9f2vDnrw8lvt379qKdTsN odP+KGaxUcgiFrbVhazoi7/9939jtVrV0qm0JdNp50KPcO0j1hv0bfD9rtpeLCRlVEZucqnvM+mU 9YcjufRcC7NZGZNCPmuvDupu84bHi8Xs0tqcAi/VWsNe7h1bNpsWZTDiGYO+ODsLRcxCA0unktbu 9Kxcg9+L2MpczvZLZev3IcxjQpSddsv6vZ5lUkkr1dsGQ8J4Vcsnoh7K7Yhd3VzSZ3PJmB0eV+Qa M08XF2aF1GqVE2u3ujYbr1srkrPKMGHZXEaoKpGM25XrW3IRGUNQZG/oUNe7G6wf8gBDIWu2unZc bmoiXHThE7favGg8mPxvu5/9SdfKQm6MTv6Uyy/uacM0bZjH/x8YqVgkbqFYRAaqP8A1G8o90H1G IRG7v77/XDsfBoSB/MWnVyyfjcudYLEVC2kFETA4LGAW5e7hqe0eVjQRF4o5++DWmiYaA+qfTySQ P+PNLBxWNAu3MRIKq//5vn8Hh5ZYJP5dfceHxt8PhYa2vlIMPuc+64MhvC+7OFzGB7fWZezg2GZy afv+2ZHdueo4OYxpdziw+0+P7K8/v6GNhM+C0CyVtOhgJDfl4XPHXcnAsQnp+Q5pZdNJu761JFcT Ynx9ccYebZfkChHFox9AmXBMuJC4cbwqfed5TTi9lbms7nlabVmt2bZMMmbJWFh9+uDFiZXr+7Z7 VBPaw3DBg2J0idQxd4mQbu+XbX25KEN569K8uLJff7Mtw0DU8spGUVwWY3RyUrFnBy1LJuLqByKh SzMJ3ZNAS0IkflJ98/HtTRHWLlAUs59+mLE/PNy1v/rsuiVHIVuYSdt3T4/s2nrBOr2hvBAif1fW i+LbQOQzuYzt7J/af/n7+7Y4lxeqAo3/4cGJxm5+Ni9KgAjyTDZp3V7Inu+dWrXZU4STZ7PZ3Lo8 Z3tHNRHxrc7QZgtpuc2ddtvabdy0kfUtYpFIVJsj0cHj05od14d2ZWtJ/dnrtGyuELMnuxVbnp9R EEh7b5jNLSzUGAmNbCHatEY/bsNhWIa5ODdryVTSYqGhXU83LR4e2veNtLWH4Xc3WG+zV37REo2o NdpmVnA/O/elfn8gn1j8R8wRc3+Oy98HHgD3h8v7wT/mehPiu7CdkiIAp6OSJohDg1ztd8YRMNAY vI1bgCCCgUhlOI69Us3uXFuyzeWCJi2oCvJXnA+RkVpLO921jUUhjWIha0vzBRdVizDYDu3IiAxH tquwf1U7OxHFdCpiMfFLztDwDmtLeTs6aVgm3XGoKBQSR4PBwc3AXZh4vKHx/SNhOCoTMY2b9OHN VSFg2rW1OmP/8tW2+CuUJCLhw+59nVF0rvqjFyW7c82R0AqXA7lk/CLWanfs4KRuy7xfYKB0v2gk +H8inQMZuG4wh357vG07h1W7e3nB+r2ujUZxBV4IQDii3xlkOE3QQDQ8Uqj/pNzQ3AORYGBs1Lde t2+1ZlNuDeOGrICo44udE8tn4pZLRcRvXd+as999uyMe00kXMBIje/wCGciaInGDXte6jYo9er6v zee4XLe52ZzG84v3Ny1iPeu2u+J44MDSqYyeCUfn3V8QCFKRRDxs+XTcDko1m59JyWv46tGB3bw0 Z9Zz0pCV+bzcfb9ZwCMRab3/5EAGGiIcvmhuJic3D07y4LgqI5vPJG37oG7t7khosNlq24vdY/08 Grj6rw4rtrEya3OFhD16vifEd2Vj0WZzaStXd/T+sXjMuqCmXtyuX563RfxZ0GinI5pguZi2+4+2 7fbVFbnrrVbDeQxhZ6BioYEtx3u204nbyvqyPX303G7euW7hWET3z0aGdjtdt6ftH4gSvgtfNb2Y fbjd/6xUbth3T/YtkaBDR9Zod6WTghi9c9WRzX/OCws+CW3/+OsHjZW4E7NYJOH0UxjhQde6vdZU hMH3mfubxco9WExwRWvLszYYdGxxLjMOeQdPCoysc6MVJTUTinIaLVylCc/k3LiRVWote7ZzLNkB E8K5h07HRGvLp1Vrt9qaHBiYk5NTi4RMhkMLt5gTknv08siuby6I+zjbD47Qx/WIR2P20a11C1tf CwTE0Gz3xaHJPoeRjpiih85Yue86wwdiCuYIrjF8RDQqtwaifWluxq6uFwPyvjd+V0j6AQGU0dBe 7Fbtv/3zA0krbl9ZFnp8tl2yR9sn9vHdXLDh+KikM1i8a3/UlTRgbjZr/T7arJ64JlzM0YjNM25r kYjNthr25FXZLq3O2/xszlB6fP/swPa7VVuczdrOac9uXll2bvn+qVzJaAj5SVgIMBoJWbfdt3Qm bdlUVNxXOp3UomVjG/ad3CCTLbioKO2NOIPOdx3vO5LRx8UC0VzbWrDf3n8lecZSMa0+5916A5OR JxLpuE0CVX2hSqQJf/HRVfvi/S2rNtpya3OZsN3Ympexgu+6vDYv0p5nX98s2t7hsZUqBBmKVsil FSSo1JrMSnlOX36/Z2tLs/bJvSXNyUa9rEhrPJW3XDajqOXm2qK4VwyuuCwCOLm8xRI9G1hIQR/m nOiSZNRibEbRpKVjUcuFOhazgWVnYhYLrdp33zy0tY0VexLK2Ye5hmWiI7uVqoPGe+9grCZCvjct 7GA9azD9ci3mU/bF+xsiYv3vEUCyQ55/FpOMF3RiyQvaoajj2eciZNVOfc6F5D78NxaAvcOFwPVC HBmgo2gEHVJM/+71u9bpNcY8zuQxZ+UO3q3x787HsEmjUcjCIKQAhUza7dwxvkffdbsDe/zy0K5t LpzpFSem7CvadFJp2SYaLemQvAuFoXQGDSPZ6fStUinbpUuX7faVhKJqhXxGxC3tW1ucEceRSDj9 mnP7Jm1mQRyd1O29G2syiL2u46W6vb7969fb9tMPL9vvvn2lzQjSu9Hq2L//6c1xJA/DjHjxH3/3 TGQ0kTj1TSRsvW5XLta1rSXtto7Pc4Tv7757pfajp6ItuGD/7qc3rVRuyrDCHSViYSGcf/jtY7k0 ClaEJ8EDoeBoVM/CaMTjIYuGh7ZXqooHQpsECozHQQSOOySAA3+Ty2YtkzplUls0BnLp2PFpUzwj jAZShDtXlmxloaCFSJ/X6k377nnJmt2RuB6QbDiS0JzsjoiQRrUZ8d79MJIDNr+wDftOn8YlVzgc lgA3GhoKmfUGI/v9dy/spNKWUBaEhHViBvJuLIMB854oXTJu20dl+/rhrgAEiBuU9eD5ob6LbIUo 4cMXJY3Hr+9vqy/ZAJw0ZCT+CcR9Uu3aYjFniVhMaIfNig2EP2i/NmYTkt/M5jM2m0vIWIGGFUnW uw6EFjPxkeXzCWv3eobFcWMSsVwsavEwFErX8r2qFRBCLyVtPrMpjVoiedWeRJK2luhYOjJ8HWE5 +zA69/9u0XrLIZwRRAGlXO65qAIiRaA8USIu7Wad3lgJwEDhUhC+hmPAfWPSexQyGobkVkrSEFwM DG4AEwKiUtKFQKzIvtIf9N2uEzJxQPjcdC6Nw9UiuoWe6G3uJzqoSrWshZLJZeSKdNodq1XrtrgA eRi3TqetTtVqCFy+N+FPh34cYhJ1NWX8MclCH2Pdx/nv+ggcLh0Ipm29Qc9iEZCWyc148upY0Byk +sHNVSEqp3SYRPC0C/dRqA/t5PTUHj54YPl8wQqFnF1Zn7OXeyeKMF5ZK0r8CLk+4YyGY67LI6SP 72yIiMZ18G4banb+/v2DHbt3bVWaJhaMqLBAzuDvg3sbQYTYaFsqHtZkZeP69TcvFYnzUeHhoC/E h8uMJADXTUYv0HKx8IundSms37u+Kr5lYylr4UjUDk5a1mz3FIjQvSQY7Wp+YqxAqXBHoLZqramo GMR5JOwkHYlkyrqDigST8HCR8MDm8zH79lnFZoq4o0RhK7a8WFDUUEJeiOVMSgEHDHO7N7T3b67b 1c2ezc/l9DzI+Ew2a/EkhitkrVZLbQhjqIZwQBHppljYPvABMgLpeKQdiYzs7pVF2z8q2+OXzjUv 11v2cr9sm8tFrUlPUWBWWCsEIpDEMA+gCzDCRE+RJ9NHaLfoG9x7xt95J84dZ/C2lvN2eS1myWRK 0d1hv2utBtIh1nZXkc/Hr0qWy+XsytqMpCD9UchOG02rd/sWHYUtOiLQNLJCZtae7VZlTOmrvaOS NVtOMvHe9WV5RyDKk5Mji8cSdrcwZ7lPN+2X3+/Zy2cDu3X7iqViYYv+6quXZxYMPq+bHE6VDC8U jzLYTp1MZAbBGy/FZMR/pkfFS0WJ5jidCQtSO3XISQ48pwThBxHIYnQ8R8LpYrC42iHC+rc+H7hg Y1MZKKO9FBVVuHeNJmbWpbS4aBypJEcyoBjGz9/b0s58kcEqHZWsWq1Zo97Uz6rVirXb8HFmc3NF SyST9vNf/OwH2LzAmAZGzRviSdsDQvuNCPXsvdn9MTjPXh0LZYFenr46tmg4Yj//+Kp2PL+IfdoL /4YrBLWw6JPhoQzxRx99pImF4YUPW1ueE3fFLpzLpuQiZNIO+XjOy2t+1Z8h5oP7QSQSs263bUtz Wdsr1e2nH1ySi4VLIiI90Dy5iKSJxyEk/tP3tuzvf/PY/s0XNyyJEtyc6wePxmegEKq1ttAiaUAE KVyqDPxgT21zhtxpwvgDD8Qc473CoZ5IdsENuaNu80M4i17s5qVFoR7aNWTZ+vEJhcT9xCxmH9xc 1wgzxxGoFYtz9kEyp35CgvLJvU3dnz6Gc+TZoCF5ByFTv8KpQfJL9mHOvXd96nivRDyliBp6Jr/p sxHzjtFwQmvu99/v2C8+vW6JRNKh2W7b4tGwRLt89urGnP3m2x178rKkTIV2u2tPX5WFPrPpmOYH GzbtBB1X6i378DaBkb4NByEZ2tJpXdFRjBX9NjeTFSepdTfAyEfUv7QdnjERResYsfaIkYva5jUi eUm5xox9dwR6DdtCvmCLedC7G6eD45p99XDfLq0UrNZoyKi+d21JsptffbMjLV0Uu0MkdGRWr5fV Fxszc/af3p+zr8sR++oPD+z9j+9a9LN7G+eW3BhaTZmBYKn53fOMcXjr+nXfgXx+bXG6D3g3yC1o Z7CmUYK/LkJIYcSS3ghMLXopcgnppuL2wc21MSJ8PdUn2FnjCet2erYwP2+rKxDMIzsqHVk+n7dG vaGoxQ+lCfmF7mH9JPJ2jsj/EeIwaYgiIWu2neuLa3Tj8rzFIk4PNXmuQ8D8XQrQB8jho1tr+v54 PJkU4XTAnZnI1PXlGZHXv77/wm5fXpKR/OrBrtwIJ1cY2Wm9JR4F5ABKgYFngV7ZmLP9Y5dC4zRP zliNd3ofYTWzf/l62/7io0v2k/e37O/+9ZH9h7+8o52fzY22orQmMopYE0J7a7UoQtkjJfFRQd8i VWBxaSF3OnZyWrGjSsuqjZ6tL6H4drs/z8XgsxmyKNFZgeBYrLi2IAJv6CV6DYeENkE//W5bPBLj PpNLKg2m1uqLS1qYRYLgZBf88bwp/8/nMVBxubduvYBQWNBHh0eWy+cUCWTO0UcuMMAsxnVyGx2o R8ZOY+wEwbQ9gXHWhhCS5unnH24owkhQ4aTasEqjbX/x0WWhIeQf9VbHanU2qIw4Y+4OqqSPn+3u y66j18MLgownOt3tdKWqb/cHFkukJGVA/hAa9qzeGlp2Jmuz+azFQvR9G/mUhcOg86QMebvdtFA0 Zr1e15LJtFXq5DXWHJ+XDFshE9Hmz2oHKIwGHQc+Bn2tHaQM5ZMDpzeLJyydHtpPFzL29OuaHbx4 gUG8yORMXAsm5h91BeSOyN9zj/Dk6Fmx4sTsBDqxH77GqMXfNwjOBShG/009xzfMTSwSZGNCepFw z+6+d0cT1rcFEZtv67tcmrjaId78eacaGFn4fIeMDU8QSWx2xAfhDqNrYacUH4VUJnCNnKsweXu+ Dy+Du33j0pL4Hj/ZJxIG9+6Yc2e8XKrF5vKMjMNXj3bFL6E7QoSJHAAjTGTs8/cuWQ7XWnyfExvC nczkU/ab+y9dBCwcmSxaPde1tT8c2mm1qTaglRL/olw/VNd5u3UFF475HhKRfP/RnpNyKI+ypugd 38VtxEhOSzK4MpmkLSzwc/debGMgPPryxd6pDMGVjZz1um0hr1qzJwRHfuWzVy7cjyofpXwiauKO CN9HY1F5HETweE8CDM5RCDbFQBTp3tlFPFmE04Gfaa3e/MK8NWpVGdlsDhEm7hFuas8y6YSdlJu2 OJ+zk2ozkKdwbwwjBiymfocaIGjhsgv6Nhr1rd7s28vdU/vk7rrmF4aY9uK2Qof4yHO313bo+6hq v/oZx43mAAAgAElEQVR229YXCpbvOylMc9C3w71jeSLVVsfK7b4tF7p2a7kgecHa8ow1+yHLpdOW hnLB3SdyS6QvGnbUTCRiyVTGCYhHzJ2RPd4+dBKQgnPt4e6CrVbvtzCTlGRndSFn2WzCEomUJZJp IWGkEmwuR6cl28iGrH268/Yo4Z9LdvBuz2Ca8aKD1zVOAfl7/kJgd0aZ8cbmBkYKxXkkJveVHQ8/ 3Ke5xIKo3/lrGOq/ZoS8YXwXY3W+D4WEppoKvGeiEukjGsPOj6Fgp0fsWG917Yr0Md6IuwXpvJ6I hIj8vFxr2uGxE46CCPS5sbTAGSsWs3PVHWJxG5N7Fwz3J7cx0iMl3PJMeIX/+o/fi5SnXYrcSUbh 3AWac3Nrwf7LP3xnn+Mqiez2CNm9ITKO3367a//5r++N4SUKd8hY3tfRCQ6NhCIhCTCX57P6HUbr 03ubrmJAuy2kyeckitQ8gVCPWHwUd2F9CF6QaCRq5WrDnmyfyOjc3EJoOrCX+y6dhbxHKi2Qpweh zDs1GjU7OipZMplU1YJ0JhsY3qGlUmFbmCMBPKbEY6VYTQWB/PtCoQwhypXRMJWh4BEnaUa9rjYb 5y67OclnPr+3ZX/3m0d2q7+sNKC//Yu74zWAARUaG/oAk9to1NeBy4naPR6N656MG7ovUI7mOHl+ A6ptdKRAJ7w0u1iwVDFr7eHI2NpOGkQwXWULOLl8LmwzybhFw1GLR0IWyyWsEGxEO4cnoicWZrIW y7g8U+X/QeegQaQPYnH77bevtDkitfEBFbg8+kn9M2rbTDZqB9WmAkDKcUV/FYur4gM5seXHpzZf LNgvPr2sihZvNFi+o/80ozW9NN++kN92vemjb7578HvtLHAulD6hs/uSIYxd0HepBnHOBtEn//rN tn3x3ubYHWMwXFTufLsnrcPdQSVN2gwX5DnapK8e7Gkn/KvPr4oHmjZ6CBXhdXCd2OnlNAdVLNjd XXsQR/ak7AZVIdqdGAwnLfCBE9coz/EFiItdkITdclNygVwmrp2cnZP237y84EIFAaJxGqqR0lHY YUFMuGj/768e2c8+vOKSqIWQR/bqoKL0lf/0Vyw+R3bTHnb5/aOqffN4z/7m8xtjd9vxf67doKp8 1j2XKxmPWzbtchZ5LheLttNpWbVat2g8JUOFDosG4B7CzaFQpyLFoyAi9rc/uyVkN5nfLmqrxZQI 25cPduzy5pJd21wMaBCPUMP6Pu/A+zvqwo1J0NPimaJx9GCTVCe1M8j17A8Hlk5ntJirpyU7bndt dW1dY4jr/vMPL9mvvnklt1z6rRmX86nnib+LTuZVQHHwrNmZjOQh1R48n1km5lBso+ezMTCOzHe0 c30p7ReKGY0zv0/hCkdD1oWXjkQtBRcNjxwgZjg5JxGh8oXZy92ydXtwq6dyZxkyqkYwT4g0wlEr /Skctivr84o88lznQhOBJBodVtWIWCSstB/K6NC36slwyHZP+pbJpe3jmwXL5bhfyHLZhDNYTsE8 LXeeLM7J6nOQ9yIX8Swa8rxFEAUL/PA3LeQ/9+UjdCQY0152hP6gQ8x3PPH+1IvdJXjYOc4t+HHw OyYNMo7nO06Yyc5XrXWkfPfdc+PSgn3+/qadk2vqJkTWiO5QieDFDpNkoN3v1uUlGRaegZoegwN0 hvfBMDjUNFns3niNVeyBQSEgsX1YsWsb86oeQKUHl6A80GRmcoFSfvrBZeUpYqy4mHBOwe/68ucf X5FB/T//ny/t//ifP5N7RLvRMP3Hv7yj3f3Ji0Ol5RDdIgrHKKH2h5CFL9N0VxkXxw1xIeikggKi WESzOaFYF2QR0W0j6c9mCnkrVZrWaLesQJLuYKj7fvndjnZuBKJ//dk1iRYd2nCyDNrlKwtgRNKR qM0XqQ+VlPHBfeH+1HbKplNCvY6jD/Imx1FZZ8xd5Qq3RrxrzOWfFwr6rkcScThihULBuu22xSC2 caEDxAvHlEtDdruNhrEFtYTINw1mCPwmMoYqpBTarXDIMiQHq20IUCMyXC5BZ6r8UyAGpu8JSs0V nFHkwmmbVEpALhGx8Chs3W5L3gwC0chwaJfXCvbkFeg1Ls4QoS3RWvqdTejBswPlSxIs+vbJrrIS FH0MqBhc743loioz4Al8cG1k3z89sI/uOFohHk9ZL0RVjFlrNarjGmf//V+eWLSvVIA3X2NjxC5E VOoCWzOdEHvm37gt/wPS+cbPGbfRTXDcvXDYuQcsZBs4OOyNFG6IJ/ffGbG9bm/HHIUGNaiV5C84 gO+fHCoJmR0BIvOvP786+fIwpBpRuyWKstXts/c2JoENGRR2ISd/mEOCsBa2p9slFZe7vDan9BzE f14vg8u4MJeTOlluUrDzOh1VUD0BKcjAC3qdD8hkJUmXoATheX6+VyrbcblmxXxGhpZKCh/eWrdM KuYqSUwFLrxBxCg9fnGkGlF/9elVKZ6RlzBx/6dfYKzQrfXt4KRh//EvQVqujzDeaIKebh9KUHjn KsnKXivjI28jVTWQODVNiZSe+CQMHiJXlNC8G8X9qs2+uDt0UuijIO7/9//8mRCXkzc4194jPYkX JQFwF+LPl3uUVHEuFYueBchy53krC2GhSYc23XIQKR+4Z+rfKVmI3zidC+sQIZFKBQraVUukUtIK gpRPSseWnynIIPE10BViazYIIRUMoFzDQbBB6mbWHoys4NNdpjMUfPQ4PIWkeRdV43DAIxIN2f5u 2b5+tCt5AxIZtGWKr+uZkzlOJNDLQTDKi/NFJU+zob46OLVffXWoYogENxiPyxvzKpsDpQEXi7gV eQrjyX14jxDhMqKziaTNFfO2uVEQ8iUggd6R4EynhXfRs0Gjbb9//NTeu7Hy45TuP+SCnUdOHir/ MVUTfhCFjd0xBh3fHSRFMqdTUXuOxl9ewMaEcHIAv/Amn0EAR8eeSeu5oPGQuf4Np/sI1408t0wm YR/cXjvfXLdgBiPlsb3YPbUv3tsKAgPeqLrJHRRLHRPNqLRBUf/yh+eaQNTIgvvC3UGrk886fmqy 0P33J+jPJya7TXukHLXNldlxqRkm2s8+uCyS//7jffvq4a7dDMh7jHI/0DL5HZi2YXhJ9SnOZESO g4T+6ffPFJ2Ek3HF+Fq2vXeqKJ37nokP4yL0zzO+f0b+XtlW5nPjckS6/3AktxgC2aGKiASOmWRc LjDFGukPihry7tR74pm4SGi0hK5x4YIoozfeLDpXZWJkrVZHSvCvHu5JPQ9nBqeGC/Pds0NbmjeV qDk6rUnhjWTAVeCAc3N8ljNuA+Xz+eCJM+wTHsvRBm7joN9iyCqCtKfZuaL6uFat2d98cd2hTMSX ocB19Z5BKEjFYmMcmmUg/cebh+NSx0iKZ0nX5dogNzVwVdl8krGovXdjQ/1DXTKCE9c358f8oNxQ EB35sTEirt1xEMeT+IzpjUvLKgapDYB+DfoZhIt2knzKuXxaEiG5loFxD4NeKRYZClsqlZOQlHdA /0gOIro6JJzfv6hbONKWXOQPD95Cul+U9Dv9u9eM00UG5s/s+cnXD7mES8c7QFqTPzhdhnmKqA+e z8RwivggXUZ+90RV7ttORUciJsIuQZqEtF7BzuS+6+opwUFRnRNE5DimkXYTiO+P77gIo78Q1fLz p9vHIthBXq6eUjR40HR5l8Ap5EHBnMcVef/mmvgs0NbtK0taIPw/Sbp6dx9GD1w5oRXXE6+NJf9W CZVAa+WQjfsMfBRIie+hbMdAMMFlCIMoKgsO5ATZjjs4P5PWYvmn37+wVDIqw4V7yYRnUmPAPCKc 9LmbIERAeY5HquPqEcORqoMS+UQ/5PsHo0G/PdkuieeiAsPq8rwNDEHloa0sFlSldFxVQryfU46r suVxVWiQPnq1XxbSpH9/8v4liTX/4XdP1Pe4ZCDBlTCRrKw9en4k402SuquE4PRveBDICs6Ig4Vw nevpRK+u7UQpcaN8apVKxgTzTNkP4ZB4HbIgcJ9wH32NNAzOAHlDr2uROEX2nBv4eqaEM55jFCkj 4teD+72CCYo0DxWUgKDn3YmcgmjYYI5OqeKaU50yRN5+I/TvKfSnjeB1SghjT32tG5tFUQH3Ox2h eeZCOplUlJN3TaXidmOjKBlKv9G12WzChiNAx9AOUfR3QvbpvUv2dHvPXu6V7PM7a+8eJXTVBqaN xzuUE3Yz5kdpjy66AbsQEgTuhXEiReK7p/tK6KTypUMvZ8l5wugYBXzrEdHH6bQZDZbbwTzhyrtA iv/+u1dOxIcologQormOyz2DGGWhMmGJ5Hx0Z8Na7b79/a+fWoGibqm4jJWrhe4uJh6Jr2ibQAuI F/nDRPdug4+C+0U8XtCeJw8QGHxDvd5U+hMoxSV6e3fSIQb/3emwf3CXscwEmElEiAmv/L6p+wh1 tLsS2IK0PrmzoaglKRU8DxcJTRZZDRhgKjJQlZSd+BefXLXffbstBIleC+DTarn8USpfOp2WJ4LP ziH6HuNBZAgXkSwJmkwZFATJbAqutlXEluYKMioPnx/Y1sqMpeNhK51UpT0q5NM2m3diSz+FQAuU 9vn68Z4WJRIGLhdkIAvCVdrwRobvwiORS6ca+CEIX5cvyeYjZmQKwI83S1/maEyRIFwFVbmQv0da GBGMnCodeEQ8GlpSbmLETk6PLV8oBDow3CQqu0pvoecjRE+K5J5EgMfufsB/otsSKc/9I1N6M1ws RXm9lo+k+BmLliqSk9CYzZUZe+/GeoBMnXGSIFeylNi4/fwbZDQK8oc95+ZQGjmNSXsvt6KzFo6r HfvixobExrSP6GWz0bCj/Vf2aLdh7926Ys1Wy17tV22xmLJ6qWaff3DVfvfVA0ukZ+2LrbgdHp2c NVj+xS9GUGcH6J0So88ohd4RyQWEMbWkRJqLHO1at9+YNCQg4fx3MAgMpLLMoy6fCq5nbTlv0Wji 4ucG6KnRhFB1kxF09dHttUBd7a4hib5vCETwTBbttUvzSnfxv9dnAgP4ar8ixMFhGuRzrSrXzdVu P2uUJi3TvwOXZSLb9QvDGWCfszlp0ySn0ufRjfs1cCPcZ2UyxBe4STxRWlO2mDrtuJ9L83ml29Cf fOP7p4fW6AzFmbXbPfvJh5ft3/3shtuPpozkR7fXxfmQl5hPRyVKBV2SG+k+Fx5HTTHmMg71tn39 aE+LizImJO76BchixRhB8qL2J6LK+3ijw4EQmXTMjqtt+4uPr2gz8C4g98bFJQ2J2mMQ8GjOeCUW Fc9vobcikyPwwyVNGA1VdiadLIivxHBQUx1JBO/CWLuDO9znXcRZkvexwt6Vhw5I83h8iiDxVSSG E0kMuZXj9LShFeeKIvw77b4EsPSLFyZHYzEnRQgindOyINoiBEZlUink3QEY7sAUv4E59x4tGMJM UByGk1I0HD7hIpGuMiwXcxVxL1kTFF1EL8XYndY6ZqGuK04YC7tKI8FsBdFW6g0VBTw8admNy8v2 2d2Mffdk1+LRNUV7282mVcon9vDlic0vLgl9/u4pB1rMWT4/a5/cmVH/rq8u2spi0Y6PDu2rp2WL EnmS/0t0ot4OoPvEeLGrkdV+3r97l0ifQzJvMGxThFiIwmahmNuBg3yy3qBro75TH59b0eOFR8fh nhC1A1GxQ6Ox4h3gMnwC8EWXXxBffrctUST5VLgArzV3SrE+eXYAqwcDO6m27efXJrXYWQgYsl4Q usetId8PPuTutRVN5InbOtkZfc5d0Lqp/p5MSD4KnwPnclypSqXuRJi+gqhzRbzuzIe/pxMHROvL QDmdFvCb98aocrAEmhnqSyUTxKMcN8bnIYyXckn7ifgKp8B3i2yygbnIWEgkLptNvVZRvuH/+rcf q0/c0wd63sMgZYrnU7YGEh31OlHT6egm90Fxf31rXlwLqFkuClU5C0lrt9P2bOdUPBp5an5uEHVD hPrNo30VMPzivUtCB7wPixpXi+8936tId8U9WZCgxWajaw9eloSIichS3x0BJlkh//z753ZcScpd Yox1UlA0bO1GU0UG3RxwJ0w51AYRzRpzJDibBfMcnVEylR6PERswHKwyJVDKxxN2cnKseZGiuJ/c wZ4l0lkbdblfoJIfG2c7Y7gwRhg9iH2NIUp6p1wWid5s1tUPVKpwejCVuTgTACJaDLKiyipzbX3R HRTy9FVJB2i4ktgYRRfRHruFFD4oZGxlad6ub0UdJXJSV9ll/pBLynfKzaGVGmEbnjRsMAwLUWH4 9A5BHX+MlXSCyYz9h1+8b9Fff7MjMRwTH/0H1RSZ8xgDf6niwh/h1vllNxU/nNqRgavsUk6AiN/b 7bfPfHGcDhP4+dMXC+Pl/qkiTUxEfHAWAnwEuyW1qf0udqZNQYTMJ1GzKYqnUiK1dx2n3cezlzdW 3oBNJwowgGiP+IORJ9xLCPfwpGGFbPos4hz7y0G605gfmOyaZ11y9/lcJm39QUlVQPlhWQS8OyJs balgxUDh7ksDu+PZJi4mLgr8Ekmx5KZRBRQ3DM3Px7c31JfAfRlQqlTEwkJd8HuLc7jguaCSq1to ri6XTaJh8HGBAWNnJyWDQxdAav4YMH4HeqO0DTf5N18Mx6r0L797peOyzo+ZR6ffPNxVIjaBE6Yo idKkooDoqAgRAHBVezg84QCPlUDu4ZCvK8HiJAfMQVxauCn6S5s1JxUdVW19cVaVH6QmxygEqnai qg9fHKqyKf+GL6NSrPJvA3mQS9HyOrlgnmjOeALc6ckcnzTlHgfrwLlrZjMzlCLqW6vZVMpKj6BS t29HpZrFinnNdcePTZ1cJU/azSHkENwUw8SFoeJdqB47GLrKFJ1uxxXSG5ckchvaabUtw8SmQhWM 1YWCdftDVeJwR4fNqGaY5qg2rfDY2PpMDAwVc+c3919J+/XzD7f0u2a7Y893y0ba7r/9yS0FMvge hDv1yigDRBVWfkYQjUbB317ZWLLoLz6+/EaDwwIE0qtUy+v1+N7h8kuUwUQO4HYcD4kZDHduoZsM GLCLLingzz2dHde3kahZIReXwfUI0UdHLgoeEPY+Kbdk9e9dX3bnxrXbFo+HrdXtWG/gI2GTfphO YUrEvaaLSNnEKPL/e4c1+9mHW24Cmak6AS4SrpJ2O0kNXAXQi9r2OnI9+28mPgsJwnlr1ZUF5iKH EOgOEY9hAAGATDDevgoDi4TaU+yYcHLAfBYeixaDj1xiNsdRVH3V2aIv4YRIfiei+d2zfUkIQLP0 NQnTk93dbUJykZSmQpJvUhVEae/DlyVF3yjHgus9rhpEuD7I48PIk1OoiFtQG8xTESwoeLXTasOe 757YlbU5OyxV7IgSwrMFVdD0AQfGAdIYY+qNld+IHMHtUAFuNehceYVRF3FjNOmfGY2vI8xHgeKd fgThgZgxUDwH4w/3c+vygiWTznhzth+bH/2RVoUGosNOga8gTa8jV09RwyHoNThEZIqSkQEjShcK KqeSiB+OWbnesZ2dE9s/qMiIYKQZYzxaUIl0YIH7J6MYaAURtLoKrEhMakJOlKQm15I//WCT8+PB vCBFTKcaBaWnSWXiBB82YcrJTAIlzi3m+QwWSLDaYJzK3FUeUzLKQRpNjV2p3LGrW0tKl8KA3n+4 Yx1VZEGE7PJH/Tvw3vxNMvjGysLbSXdeAALuIvfobS6hHkfUI+LI8mgQpZgozYNPBRUp3/W66Lns hvBEnAbDAoQgZpLhcjCYvrLm9MViZ6LCl1COBH7GRUgG+n+5hhgmVUVFce6QG4ucHf2Dm8uBmtkV DfQXE9jXkaetTAQ4DxG7k+USZPC/XRk/TahOdz6DR/tpE+k4izFXCproHn+4QMvPd45dGBhUM67m wPl0IKSoEl65DyVIWHT0HygGI857YvRQ9GNcQOBobMj6ByVw7t6vv34h2K+oHaWaxcM4YpZx5shZ 6X3M1VXnD+T7P/z2mf3VZ9fGjIDL5aQeVF/9znFauJveEHpRMwuDsSUnDQTLQZ+uzHHPUomhfXJn XWWF2h2n0yIqBcKdhPldWgypQpVG145OmjJUiFZpv0tAduQ/xpE2+AXvDaGrPuK9BDYeJy3xrhJt Zsxxg4kyMrdWlwrSkIFmKF/M/ADBki9Xr5Qtg4o7gmzDFTT00gSkBU6ESiQ1bt1IxKqVqi1ms7by 8RX1M3X9ORgD9EJ/uDa4drhIcZC+hZQAPu8Ug3Gs+be8kJdWEK4Xd47DLNYWCpZNgZKG9tGtVY0X rh+Gi+DDp3dnJ3X9NS5BSpWqyrr+JWCDhg85y7WtRaHoZy/3JOOpNHqWyaSU+4kMhnxVKJLLqzM6 +QdMQLCDMUjGcYHbyiestXpWa/bt/uO9P+4QiouMlXd1iHIAaS0SSA76XVVrmBgonyry4zUPFwUE 4N1IiFX0YeqCk5AA8Fz0kIudhT9vvyZtnEZC09En3FFXJocqlq6kizus0l1wAOQ/3b66INSS1GC7 3KszT3oNaZ197rQ0gYvgAvWwQFSumgBpKS7aRP9iRBBRclCCv880OSs31CPDsNlVAgaBloffA8vh 3n7ywSXJBtghWbvpFOcAOj4DFPTNwz2hrRuXl0SCs/tiuNAjTY8ZC0aRLh2sUbc/PNhVhJI6Z7ii IAUqUcAhubLIvi84oNNVTNDPCIWj4ZKObE9lSdAArS/mpOlptNqqD0UEk7pdbDL+nen/Wr1jj7dP VHETzRU6NN829W8kogWpQECtqZxMDDdzzCGewK2Fb0J5HtSGc5ye0xExH8iHxAh/em9DPCZIDmTI qdmgb/glwABpRfFkSucGutOFnBvjXLMJLdAbDlXSZbE4a4MeHokDEyAdDDGldXySKuWfSJOhHykK aKTlWEj9/koltNNS/FNayB2eQfXTkMowvzo4kfHQydnBvEGKwKYFMsPYc5q3RMk6Uq+nfpDKvd9T VHW31NBBGB/e5pQljHPXTso1O6UEdIjUqbTmK5sdfKx6kKTuGFRE31qtskoo3dqaF89GVdMXpb79 L3/zvko+/yiD9bqzEnQqZgojFfjgnX4rON0j7JBWUBbELbw/PTVnevGqdtYFFScIqwtyA4n/KEHY xS6l/5ud9P4j0glWx7wQL7cRHEPFRdY8uX1fP9wXsXsZFw6jdVEq07Sx8i7MVGj2DNoKmZKT52bb MlocjIminr5gUDFYXntz3pUeG/DAxfe1z/zY8AwmNJomOAMSapWQM+rZTCZhT8oujwxDQUoPvNNX j/bswfMDpWDQTqdDm7yjqxARlLRZnrHP722MjRC7LFFJPkp4HSGrQzROXuDb7LgeODxKHWeEdDlI tJBJ6f64OaANdnQqanpxKu0AuRGo4MiySytF++zezDifcLpv5VKFw9rMEM7CC1KfnPLQRHl5tst3 nOTzieqgltu4QoXJxf7VVy+ETOB5SKjm+vXXz8fPqlerSrCGXPft9GOrZwQSkD4yk8FQaUMR+iAW s2bT1ZSi3IzLjCDiSlZAR6cPcRNSY7QGg1OMOFCCaDhGhYAU2je87qfbR6qpRcPZiLaDo8pAxNsU eSw3LE2wwkKKtLKeMMq8B2gTw7yykLVypapsg5uXVuS6I1E4bjSt0ajb3jEVYtOKhsJlsnF99eCl XdtcEtBQtFV5piPVsP/+yZ4d5ZPyehrdhPI/OZOQZ767wQrQkeOjnFtDpzrpwcB6g85UFYCzsIYs evgbr8h1k9gZE68Mnj5F520u55tkF+cv54/bn3S9STxL2zES+PZ0PrwL/2ZHnTamTDAGBNR1eNyw b5/s28e31s68P5MNbseR+T70fPYIsQnf4xN13cVOBYrcO6zKcOGSgioo2cvpMYrQBhYqNK6vRXST hNa+JkFwZy0XpaIEQQVQ14u9Ewk7c8Gp0LP5ka2005rI17cWhC42ljjBpS/F+5WNBftvv/xeYkM4 lXic8LirLqGSuSSwZhKqlImmjPcDmVFfajoy6mQBQTZBcOq0kseFGNxCwSDl0kkJHeE5cHFZKBgb 77Z4e43BwgUBUVAD7GzfTvpaWq/RSCiONCj4Mchexo9ghvL30GmpIKfjdZ3syq0NxyE5zhB0i1aP hOnZAqg3LPEvmibqSEnTlHT3PN8WCYZJJ+J0cESs5PD5ZOsQ5XQocNiz0jFHkyFc7ctYcGCEjEho aM92cG2jOq261R3acQXEmNZZkzkQeRja5EC8FG4xVRbYMJCJnLRaeh+qWsBjlsotbST+ZKcCm8YM usOkUO/Tl4fW65utLxZUlfT5TlX0wUm1o3H65N5VrRXyF4kgM2fn8lH7zf1da3dmVcBRR8Kpdv/I PrmzZv/3Pz6zf/ezu/beEhHnSRT6rdUapieRD9F6tISR6g97rgDXBVEttwwmE9CvM5/HBxnd7LiS yuwOpFn8kPEAyXjtjl+EIJ0LNWGjN/9OUcLguefJeZ7hDoxwtZvOJ0vzMSby1w/3FObe3q/obL4P z6XiTF/ci3w8wWj0Tp2undSaeib8gU73paQzu4i4DPLWfH31s3KH84JLFpcvP8OJwfAnJJ3CrXAf /20mMrwKpDGTDiOL9oYJOQr6ih2ad4ckL87mVHiNY8lSCVw2l9sGQqLS5Wg0706rHg7sBmcCxiK2 e1i2n3ywZf/61XPxg6ALKmBiKEAlGEEMFjXmzyreJxUlcKNx7RTRpIS28s5C4kYof41BdhHdoeYP R3R1g7bjCsJrudOHJnNFJWIScbVjOinci2uFjJQw7w784DtLQV2qo8OaAhgqXBjILGRMgyoduHJ+ nHytei4kGp/ciSlVC5719qV51QWLhQMFuypsTmcbTHRSXmZE9YQ87mKQdjPQO1PymVpeNY0hho2z Lcm3/Ozepn4O70RFUgwBJ+GAvOkjii1ipBBcg6Lhr6jSwfmTmVhcVVVBnmQuJGIhOzpuiRfmPTFa lGkGbXHxTr3eqTYUXGb43u39ntxbUO6NK7mxwSbSyJrhBHHQP6JWqIVrm3N2cNqxrbWE3GyODx9u UwMAACAASURBVAM59kcQ+wtKrPabBH93iWiOl4IvIRBwHE6F6xas01owsH0RYc4OTSJlP0QeO/sR lIkNFg8TDgHiRdf5e9IiSOFqnVLHQeZ7YLCArCz414yEFtPkzL3pS/Wwq67+t6pOksPURXPCycRd W5rPiihn0KddKle3vmu/ub+t3UcnycQiQlZvukA5LCQimZwaBLo4rbTt6Y47SZfTc/aPa+ondD9M SshwBnpygs05cUjws4kUwo0ZxDikNQQnOxvEqncPmeTwXiwgIliv9sq2vV8V2QmZzedZZPSlxKIj s1tXlpUQTJuA/ogWQTJe8sLiHYScABRJxa+/eaXJS9VLDD//D1cEGnByi6EmIe4WAlDaO3H73N+g NTgMPYO8w3hM7h9oiqPgdw9Og0MTnDCSsxYxrPcfHyplh++7nErnrvCuGDuMDsZ2WtHvjZly21SQ kMBBoLwdOfeVip3UHocbIjqsAoFBfStv/JycwKVT+aJ+npdBV6aE727XfvvVjiQbvW5TRktaU2+4 z7nQzUHIsuJH0RqOrNFsC6GQbAwi5zzCO1dXlBwOJ0hU98GzfQUcOPGHd6FfOE+R4BM5stc25qzV alupwtmOx+rD1YUZGTgQOuOxMJMR4t07KltvOLKP722pHprOluy27dvHu6q+urU6J7Gn5kDgklIv jLXN5vHg+b7eDaPvDjnJuDp0w75t7+zZs726O+B3hqBRkOoTDlup2rbD0459fGdTaz0hca47iq1a PqUahUtJcH8Hya0Ksbo6zT4ZdWyg/CEM78ALXfwpXIRJ/SMlgAYRtzdd7LqPX5RkhFQPnhrxATLC kF3EYZHO8SbRKhPRTd7pZwzt2ycH8uNRQ8t1gj8QCnRGASPHLg9RSR0fzhV86/uPRtpdfFVLCGYg ONUQ8Ms9sYwLN+0WEFkkjAxEx5CAojws5j8Z7SGIjDHzT3MGjMnpati7fL942rmt8BKgqS2En6GQ /S6yPXYTNpYLQj7uGVNHxEfCMtp+ATJPjsoNkbBTNaBd6DwSEbr67//8IIjQZZXO4tJyQDxuRmAM qa4JwnZVUScXzwEFqay1R7/+NKVABU6f8N1/+v1L1YefzSVF/H7+/paMoacY3AEePZ2wDW+D++xq ojm3is3JFawDWblIqiup4p6HoXCRsXXN+UkZIZc8PZqqU+V0R65agyorkDysMw8cRULf8AzqxDe7 A5VocVHiQCHvbub9S1dNAxTXdWlhBBeQkyRiUfvk7tbU6Ugji0dDqs3WbFJLvm/LxZR99/TQHj4b qVAifY2mCqnFcjGjzfBSlpOyyUF1ixRdFs9RpDIcEnJDjvDBzU3NCx8lxTjR/3jmIF9KOCnQQPmb IKm70uzI61hbAk0nhbyI3FbrDfUHlUS/e1ayuzc27cnLQ1tdwmA21I+Ua37w4tQ+e++SDPijFweS L5UOXlmbyg0EbuIJBFouokdJlpD3z0UfvF6G5YerL0wn43gdFrxDEP3x/3bbi46y4hjSty16/hAZ YwGwIKcv1Sh6w1mE75A9NL6A0sB+OBmHzpyBAsGxizuZwsA+e29TSM8LB8+7nD4cj9spBflhdayX CYdc2ZLJiTmjC9CTqbgaQ/Bk+0gGyx0jxSEPbqLjpikHjKqRUld7tOX6nNOFqVzAoZiQp/BZvv1E fViIIB+qnDLJMMK4Al4p7sfu9X50RzdBKruSJm6RKbk4+Dzo6ldfb9v87BW1EwOH20sJZgwmfxCN urpdQQG8qcoGGHDXP4Hb7wGPkAaLaqQAxqW1WZGy3JuDRZcX4Docf6TzFysNRW1JUMcVVa12hIzN tvX6LlcQ5ITbSsBiwhueOVBtgsaCSLdLcwly9ZCLKO3GGUmdkhQcU+YSfB0qVXkbhf3hK5EcTOcx BArz4FRtZ7PCFhp2bfugYl8/2BUnSAJ4FMMaiJbHbm0wfygMCDe2thCRFODhTt0ub8wJ3XBvUDyR X0Sak0BLyDo9ZAhlOzptaUOdE9lNnqNz/UBujmt28W0yQhBCx5odpVv52QsdgcaPU7Ndja2RuE7K +xyWyto8fMoPTBSi1GbHpa7xTgCRbMaJWZHk+Og3YKTVqFu9XlG11ChWa3L0+A8Vt5voY87+dPK7 qWEYR7z8KTbTkSMNpvQhLqn2jU8MwuJvOsk5wH76f1CFV3hjxICRTlH8dgTHBCAfkYXuj+ZiEZO1 zjFhVNH0Km0WPUSsENj42Hd3H5cq5MSIuIBqU9chqOkGOxdgum7+WRea5+DCLMzmdBQXEUhNctJv wmG5cRjByUk50wEC0GVYSFHHZR1Vbb80sY1E99h1iRTx/csrQepDkEvn3XyPRM6OvWkBaAEHJVBA v7gCwhlDl5RNH1FwEPfk1tVlEc4gZPrw7jQqBZz5jJCpzcmr1XxFDSEYcvwk4HUTGWNNcT/0Qr7W 13RJF87MS6eSOjzUuYXU0mpLhoEwlL7lLERldQZ5fOMczInO9IyS280lL7foI/Of4uGmqmIEhlNU ikoejRSU4IBTNoXmoOOCHjG3kbh2u/IxfgzTsYgtrxRFXrta7ZNo7mRc3DM5JxLuiPtwwANatdX2 QHMId42ySRghjnTDaEeizhXm/0snDev2EGIvyuVFhgGvxcZEoIILVOYigqY0JRA8h2h4LlkZF7WW ap4xvyROLZE6Nqs8zmKBqg8pueZs4qUKXlHEPlsrCoW5sedMx5q8hg9ubcgjoGw19om8yFKpZC3T idQ/tgInsHfK2ZtSLF90TZJuJyHq8WQdC/Kmcg7Hf7EofD6i61w6AmPgP6vwcLMjqA3S2DmoCsKy i2PRz+bnvf1Ck4MkgEMcmNjUR/rZh5ekQobfQnPFoFFADv3R7SuL2lEwUhDZ/M2g0Z+NhhOlpuIx u7qxcKZgoBMdnuuj15LOPSlsKq7nCuy93r8eUfnVNc4dDH5JSsW1zbPRNy4WOMJa4D2Eq3jF8Flp w0So6tEN6C4Q0wYejHbRg6rK4PqFRJ9T/gYe7S8/uTZ2e1H6T6qJunbgfsKf4GqkEu7oOHLNHP8T lcvockZZ9BhY14+4RPx/q92Sa4fxTAYiS6did4GTZNgZFLg0SGK+s7E061xav8mBnok+jY1PcO6m R8vTx95LxU+OHVRJkIoSRFe9vnC8IQeuJfl8GMkHz0uq6spnjisdyyVHMi46U9NDK6WKuUBJdxgy NMju9zLZNp1t4fsFpAhy2liOB/KKiM0VZzRPCX7wXujjEIDTB2y+6SQpMwRemjJk9DMb2DHZH8cN tQEuE9deEdN1TmqikCEkfUNzQQGd4EBfxmz3qG5rS0V5KRzQCqLmnUDu3J+1wkaP8p8kdlC+q1UW nOHAWYycV5pMBuh9aNsvnsuf44iycHLOBr2gRPK7XAot94hGdM9k/p/RpQS8lA/RaxAVrSEqFD6j p2k0O4roYHBYNMgCnPbNpUMw6di9tTBCLocJ14zH+HQYPo/i+7TCwZT4+VWr1uMikRlIuWHvYJBp r/fVyU98+Kxks4WU7uddLR0EGgk7F+TygtqHu0eZYYSrQlQjqhWs2eWV+akcu9f7kclnowmieZN8 4qyGapoR9D+fOmBi2gr+gJ4DA0wfswHgttFW+BGGi5w+cSMxDjrtjpGrO4w0LBnCdJdSU4pyt3Ap cuHC7pxBgga+b71RdeVbJupxghCkSTndT0bPECcZCStg4L83fr/xHunelcUklK6804nhxgjiEuK+ wP3sHNbcwludk0xjUorHBYEm/TVxs3wKj6sD5oyR6lfh1tggOEkHI+kU7xN05wwaHA+GQjl1FBXk BOiw2UkZt6lqNzcdteE3F3/Sk1KGiFzifgXGaxJBDAtpMwcxNK7OWkMoxUVxnSQGxLu8OGulyoEd n3J4KfXxk6IH6BtEoqw9kLCSuHsDqebpF6qFqhKGDD2FJk/sycsjRbBxD1n/GJxsKqYNmjlCcUMX xevZt49Lmk8nOkClowKUzLdyvWt3rlIJJSzOjPHhQFkqROicybDjEiMhF2BAjjEzU7Cnz7et0onZ rRsb9sXq/LsbLOA40TXOP/MROjqPyezFYE564Px1omj+MFQgeZBLq885V9DxDHyfweTefu5Mu38u zO+qPjof3i1SVSYIdDwuvcNxNy4VZXrB+hpRFy3i14WsnIzLnzOfegMZxgRh8Dnm3Qno8poA8HVv us4yVm+Oqr45c/PN4tuzzZwcWXY+wgifQ4kUyjRjIODHcFVAJS4xfKjkaFwCJbUGpXcWeE+NjSNh 6Bf6n0oPlB1RPl7gurCo4I8mLtOkkSzublA2BkRw59qKjnqiHSQ2y5AEXI0/5kpGLjgBms0IBLey mLeeSqpQcpnCekMhcCKb8CzFPDXpj/VYCHnU3RxMwXxzaVdOmuDz9tS8gPyWUyok59JckFqwIIls UczskcpW54JTilzpHEUPAw6NKOyl9TkZksW5gh0cN+yrBzt6LhUhyLPUs6ZQLbor4jscS19IxKyu MxqDw22HISs3Wlov5H3yh1QkxKDUrPc5qlo/0Yiib3/5Scb2Dk8VLfTrk/GixhgI1vVXb/w9qAei wGy+/BsZDLo1ziTAcOEaMsd5Fgewkr8JUmL+g57YfJg/ZFlQ3QIqgH0bdHl9c0njyNig+sf4AiwW 5/yBKiGbLWTstFpTrbvbW7PKFa33EvbpB9dsfpbAlL27wcKak7u2tYLfmXjDgrkAKcjdmxwwOr3w gIr4tT+UJsP3hUreeLHQenIDR0OOjpqqvCl47gSLTGZ2FdCDy3S/WNv02t3fUP+L3ZPB5Tkgq3e5 gh4at/vHXWc5M/3kTLtGZ1m9c2HaaY6RCUXRQX4mt6LeUT8TNeRjuDHXNhZkEEBfVIc8E0wRp+O0 NP/wu2eqH4Uq3Lv6KOA5QcX3LTsxbh9ENxU//cnckNAsTJJphYzrbZeMHMPdQEIRRK+CU5QxLO5k 8JCqtz58fihDQk14dnQiYnQJhg/kATIHzXs3ElSADm6JVKJkcE9/FFpQSdRxV25z5AJBwGeywEmm VuQuQCX5TDooieRONgrHKXAX0YJmsSvVx0yb6f/1376x/+0/fmQvdo+0wGPRjor2ObV82CKphCVI 8o6zoXNIR0dpTmjZuP++5C9u82BTRTvnz450mxh92pMRYhNHR7i+Mq+o/P2nB5I2sCmQFoM0gUh6 PEZZp7Cqf+Du0WdIERjzRtr1Gzo/NuI0dfUpm1SCeoEfdDWrkPlgyDGGIGvWBRVa2btASmyGoKrj w7o4LIzsyuKMzWRBnZPoOP8Vs1H76sEzy8YHdlQb2gd3r+mkcq23twlH3U2cSpgJ4hc0k2y6oub0 daERu+An/j8mPMJDAPDbrzegjVFIkwe3kMHljyJFEt4NFQ4GeTEwfA6ykIlGDhMQ12XJ+wX49hZc ZLREWq9TV32iA/uhgoXT9/PfmH7H1w3nBJOd57guuOuka8Y/cVaLvuFCQKnToN0NhSKogcUfbs14 008IC+EwSJ3BlUDjJD5lkgGv/2dxMB9cLTN3lBrX0UnNrqwvaMEyzkcnVe3qtKdTadnl1aLOH/yn P2yPsxxoFYEChKvIFULGWXrURjNbVGK3e3/aQ9nlB885wIL3GomTo7II40rZaCdjgBuLCQX5iwgs RDZGC5dNBirgj9z25sj76eADUSs0bKB8jAYbFAYRo897EyE7xVvoDm2JYIgOj+UMgQkvyQJ3LmzI luey9mzHRTDDdadFzGQTtpJJWiwoqoiXQPQS3RzvSfRuc6UoDsp5Mq7ihp8XRCDxWFifGC3mOMEV pVplkra+kFd6EeNFPXx4IVxmjAnPQyDKuOM1sC7wZghOcLQ948Z3+Q7iYE4wmp9JKRLKQSr0GRQJ id6UwCENiDGlrw+PKxaNhVTqmrzUSm2ok5+yQclsJU1zuCpUT4/ikE0LDbq2d9q1T+9dlrESLxmU in6rwRKCqDZlALDmiPJ+hFJgsnLGRK43V+5UEaGmgGD7MRcThgWIWrbZ7Ama4qNDcOO/6xw2cxoW 54KGVdaXTp+bce6bH2j/99sQIxcQHDdpmvjkPggDv3m4r3MF/W79tnuKH9FhAtNlbad+P4ZGrzXm zelIozcr30j0hXcAufBrJi/IFsoJniXJYZnRiPgJ3A0QL4QsZCq7sT9XbiJS9WPg0mTQcsG7ELn0 3JTC1PM5e7V/qpA8/16cTdvXjw9U9fP4tCGDxe1YdHcQqO6fqJQu6nuQMoGdfDoidLRz1Ah4lYkB oOoEPzutNe3bx/uap7i5IoAPy9qoMHwuKdyn3gyF5qg+Abryp1OP5dK+cui5ucEfjIc7X29kG2uz ylzQ2X8IkFuUU27JQM0Xc6pLjpof5JeIOakI0V50UWwWLEKMPNEv3zYqgLIyVE00oETof6pp0GaS khvIAA7cu0HD5NIpBXd4L0oDEd0jkEKEGMPo3wHDlc9llCqzMp+xXJqSNSFVQSid1iTpoQ2+FJBE zDpirmwjlQmKql+398iXDckYUdMK/pPI4KW1eQmgj46rMnw8f/eQe45U5qc3aKgSLO3k3XlGp9O1 o0ZLGxNHeYECq7W61eo9my8W7da1lWATDcSzyERYy5NEtTNrI5jkHVlV7UjdvlTeOmBz6qj0ca3o QOjnIlWT3zsVsIua+N3MIStcTNIGwj/aUDGhUSB32NGKecF0Fh2LEiU+lR/LtYaMDDtzJO3cFfRI 08bqorzEi1w/JA5wPVc34mcSqfmadk3VUvKlckI/EDUN8vCnqj74e73NRTxviiaIL3Bjpu4zFW3W YQ2MIwI8dm1gPwtAeiAOo0hwyGxECAH3j37ESLGop9NYzi9gz3ug3UEoSN/nMy6diD8Ic3/5+5cy WHyeEim4ReiKrmwuqrom6Any+tVhWW28e21VxlS19Id9nbSiRN5A8T86J99gw2I3J0T+yZ1V6X/Y VP140XLQARdGE3RRa7QCpJOycMy9g0dUPiv8zGYSUAsYglXKyCgyBmKsW4X0shZGiT5D6xVXG6mX h3HCHcUwETyiAOIvPr0WiFThYAOiPtjQhZhiMSv3B5YJPBpFOCG6W0S8h6qiQVQT94tnl05b0qQh 2UBsfO/Gqt5Np2AjWwl0W5yVQjukxWp0LZPi4ImYZTNpucYLMyk7Kjf1HPpOivPTmsphI3KGSqFI Iu8DAmMOcUI7yebJRELrrN1pix5BAY/rz/yiDBBGik0I5IeAGGOFPS6dVu3Zzol9eHNFhr9UaVil 2rBYPGnXriwpCOPBgd9I2u2uRX1YcXo10Dk0EKvNYBTzCSuVB9aJmL3cO1Zj3em3jvzm/xlEX6LX 1WF3ZVddJUIEdB7MObjMANEed6z6GxbplFFh14cHgW9h10WHQ85SaBRWLXKMGFE9RUkSEXEwHKqJ 5AGilgU0bUTO5pNNCfHOLVAuiod9endD7zd9+UjhysLM+DTld7rOJTX7Ag3nuanpRTPNH03a5+sf O+KWyYQbDNmJEXLpVCO7sl4U6czFhIF8rlP/qpBRvzHhiOwh8ps+fn26PRNhqgtBe8MEvJ9XRLVi uQzljT3x7oItvp2qG17M2+pC1UUgGy3bO64L8eHSUz5aei7pikB47KhRG4XcgRhenwaXo1OMwkhM SHMi9QMXMqW1DyrBdULdTigdo4g2jl2a360ha8gmXFVVZTGfH5NJMrQ3GvBEzGmMlGrfi5huCXlw CAYbIep7Di8VVxaJSNIiPRJHj/UGVshlXBsDFTzqcOeJuudJPY9r1+2QwqD/B71yEAhCXe67NE8J n4Sr1VaJiVdj7rsa+hjhsNBetd7U+FMhQSdGDYfiKwejoZVOmzYYpayIjCPsKYGExurZ7qnWF6iX seD9HEHuT+IZiBhfKmZUzeOlFO2zun+tOVC0mBxEkBkuN3MPuRAuunM9yfns2fEpRphj6uP2cudQ 6zmeTNrSEkLXWW2irj5ZkAqlkslkuxxY1J3jd95QmIzUXGFhjGxm8wl7vlMWkbexnB+ni7yd++H3 wckgUyfKcojCmyJv/sLg4eoRtWCSeOuOK6BTXLrU3+FE2vCY+CaCCVyOdSI6GBJ1vGef/YHiF7lb b8qH9G1ksvg6V7TL82bsDAzAR7chl38cd3U2QBEcVzBloCfXWOh2sRbL3UzvxwQnMILrIkGeEBQ6 HKdaZlPhHixonTQcnBTj76TiccGjpoWKZ4ykNo+OZdLoZdzPs5m4dfoTdO27QpqrQHgWCruidLhW 958e2tYqhG3E/s3n14NDPwJOUweewj1GLMqZeNGo+CP6Px0khGuB1Luq2U7oHY0Q1VenewcUwh8d 4BD8jDmjwyGCcwNZBLL5EZfLN8mPdQbXjweRMYIIpFVJr5d0OYL5tDsCjXmwW6rZVjxmmRQ6NaKg A7lo3JkqB2jTnDfiqmVMn5UovVLMked9jryC/xqaPXrh8iPhEhXdTbj3F0kfDru8y5clIVTGFLEm rrxI95ir0sA7wNURGQW9Mk/QbWEgHS/kIqQQ8sMR5PyhNjHcSH7O0WgYXj7HuxMRJHBRbfaUe8r8 InqIfAEgc//RjmpfMW53r67KZXWCSpdk/mT70ELaPEKWjIXs6auK9UcRe28ZOoe6YC4hnLHp9zj0 pCNeEwnE/klLJ1v/4EVHu13ODSKZ1xDZNBZO6O0L9GxYy2lcXjcc3FfQs9l1MoghRfGI6jnFtTq8 kNYu4vQ6PduulQN9EHwFGfVohCBlc9rhJg3gb4dCXC7jDzNx0wbFyyxoHxoaFhPaEtpImslZGcW7 XX6iOtX768bqjAF84/0nJ+LgKoMq+RHue7VR0b2A4cB/JhmiWP+cmWzSiUbH955Wtk8nVrvx9xID qcUrLanIffkaduKjMtVI3TFXjseC8KbgX8+ioaHKC0GuvjqsyaW4cWleFSUcKU8lAgr1oWHqafH6 U5Ewthga3AsOqrDggFVkMCTsMkd00P0YFfkKDY7AdygJisMFZXDbFnimkBq5g2dRtze604FcjOWj l0faPDmBe7HoDo9wB4qYyrqASHSsWdvJAjilrNXo2Ee3qdkV0yY3ChgYENj4vEGdwuwONGFe5pJJ a1NmZWjqZ9xoqipMty8UZCaApvjbITDmZE+aKxKjQS2sUy8j8rorRMi48SC8Xpcj3ahdR511qq+M 9H64nrj4jDWoeyUPQIkqkFFpdHSCUTyK0V60SHgkF7PX7yrR+vvnJQUecPupySV+jiPBgvaXqw25 oMiBZmdy9tG9q0J10DudXlsIjvnARlSuUbIqJK8BO8A9XyPd/eYOknBHPLmLXZAkWc5+w6JSdaB7 OvhBgzU99pPlELiNQ3fiDe4ez6ND+bdTOuOKph1ReS5XED6KP+QhsauwW6A2X0q745QckXoekfgi +0zq12vEn23z5HcSqY5whcu6R7na1Qm5GHDPh/2Y66z7GYhvA57PN/diXdaZu8gF4XcI+OAWicKw GJWYHQ2roB1hfyJZcFMcR0aomuoULCr4gHTTVb70g47Uwx/QQZfzfowDRo8JC8JgIlM10iu+qUIJ l8SiInIHavOnsLAwSPVYX8rJtaDNCAg5iWZ5LiM+iSJ0RCaJKlIrCUOlDUB1r3BXkra5XFBlCS7m CMgFd/f9G2vWaLZ0X1JAnDs60alNH4UG9wM9AOrW0V0qIxSo1c908TQ/6wwJN4Sjol1UIsXYEBmW dk1lfeFKnUgZXoaIHQEgkK5U5N2Ovdwp2c2rq+pTZ2g4bqunrDHpvSJhpeskyawgOj8cBd5EXIYB VJRXNHqyoSEPoCwTUVMfPXb9g74RbRpcFVUlRnIboV/c2nKRQVczHte6YUfltk7xAUUhbcGlm5/t CVERKMGd5qJEjZ67yglDSet2WpKSUDUCtTugFbIcbRxF/NgU4CubzbbeAeQJ+U9eYFoH4XL/WQEP Do5JRN3KffSiZKlUStkaeAsYsW8enTv52YUPqd5Yd/Wzp8q2MMh0PpOWiAC3RYJ/8aqc/IV1rbda wSGck7mBsaKwH36xP6oKYhCkNF0n/W3X2lJefr3KUKhDx1Lo19b5NHLxSuYLmz71OepGsfAxTs+2 y4p0vH9jJjiK6I+7zhL85392scs6+Z3/IrKBujN0czkRrogIETK6iTWy5bm8/nBRHlcnHCdi2iVB NpDsuBo+9K6SJm2nnvbHd7lkYvdceA2SqVmInFnIIuC4dHZHkAtokwmJnsq5GWGbzSXshQ7GzIj8 h8fhEAr0SeVyWQp0qnHybM+H6GBOjzqDvlDCL6WbKZRYbYm7gmCHl2z//7y96XNcWZLl57EjsO8E QBJck2TumZVV1VXd0zPdmumR2Zg2k8n0UZ/1f0lm+iiTzcikMfXY9DbdtWR1ZeVG5sJ9wUJiBwKx h+x3/N73XgQCIJidM6+MWSQQ8Zb77vXrfvz48UZV5MiNAChHrayxkYoWPNk8nkH9CINSposmps1Q nHo1SDCO7eE9jF6en5Jx4vpgpYwVnCMSBDC/qXhgzRC+/uTd1URnjINrcH83rnTpI6Hxgpe0MFWV 8QPfdVFAMlIUQeStWs7Z+7dWBF5zboibH9xJO4p7l5ucffHduv35z98KSQj3RAnZiYBYR6MI+DV8 E1IGMLD7MSLgZd4o2Fn0iPRh5DEic9PzCs9jiRufQ6gAGAagX7ah65sHm9D4aNWuX16UhwZTfe3l ju3uu96/MrSttpQzuAc2CWAEPDKECdWJW5hIV9ll/o0HSCYXDJ0xer6xrY1BloHP4n5Gur+Lzp9c lNQJYVAePN0OaWYn2CWrKAsihyWm8I1QJHoPiWeBO+6FlbidsXlpmoXqtzj9P/Nd1LM+nonJeoNn Hb4YAkZxSlgq/WpNKu+0y0uojbWl+XRerOp8x5AMZYbE2o9npf8fcSYMC4uH0Ofm6rQwjr6XEP4O D2l0ZEcGKtZkLs6M2ZIKqFOAHEoD53BddZqYeimWSjCO0QmblNcUMa5Y7wevCGOlcpUJ0eamDgAA IABJREFUeuh5xpgQ/t7j7YRhjr5W1JPiGpAKSdMjrZw/xWiz6zI3yWA9eoEOeVmF38w/QlRCSjJ4 Swt5qTOAezIfJMSoYvWumkC4smfAUYO8C2GU+FeZygFCkGzoJcG+UAOJRwHpkvF48Hxb3hqLG0PF PCSlT6G7Z77RcSfz5j0QKUNyb70tfAjKx/FxQ/jYSNjA9V4Dj7BZb1m1lHcjLHpRaCQcDi/5QaOL ZrUojSIT44knwj6SGWB7OCAkJvC4GItKwpx3/E4ChBLN88wn75vONd49m4zgofCopYUJEWgJMR0L M0VZqDxcXJoJjW0Z76rKjxgDmlzgjXEhvCQ2Pbzqbx++1MaJJ8b7AsIAaIfi4F5v3j66c8l+84fv VKrDJuwy1QtWVIp2t2Yvtw5FSmPiEPJkJYvdMHkszA66Td/745YDaskRJVOSPFMSZsB/ikJy/cs1 6gINoZeeiukgT0yKld5qXb00QqG+4xw2xcPSwE6mZTuM4p1aMFQtSctgBBE441mhR/xwY+XmexiF IlkoSQFzWmMYv5utx4t3T+gUdbx5LyNB5qT/mv5ZdiYmHdpD7LyEDExyMkuEKIR7ALiMAcBnJNPG 86u7DN5PkHCONaF+XWSXXTrIlVN9N6ajCgAq3h1z6RcfXtMzdcR697ISFgX6R1RPYMDwXrzLkZdq qIL/qKGOy8yfqM8Vi5GZ2GQUCaXGJyiR8SQLHiQHixesS7VqAd9K6gTRYhNuF7lz2SqCbGLEQy0M ime8vUciRoHSJf6Nx6cQEQnmpemEaA0W5JlSPIcpNfOgvyEJC8T0Hq2haIH32xXRE6vDM5WBILYP rBQ2DQzhQgZ66YWef4T6P3131Z5vAleYNNoI1eA4kYWNlA6ego0kmWeCRLzNPAXHh8eeSd2veQUA pFDCVR+nth3VgG1gCtBOrypZGRpLQCnhWRBX9K45beFmkhNamLIbl1kz7tTE+Tw1UbDZ6ZqNjhTs +SYNWlYkeQNNibmWkNJ7HZsYyakEC+mglUXXcSuiXwOmQbEvbnO6oEPr7YHwinCIDAlxuIo7RYsY WIiZZePSMCD/wxZy5L1ELfiBZX4ik+g3Q8gqL2F23JYWkHM9XwjJc7IjeZhDp5BDa6rDrBusz+69 kDwsBpAdBbcQcH1spCzP4sc4+g1xP+eHn4jnFSPbvqLm9EXExSrJFJoKdHraqaP3k70WBoPmCzSn ZJERYmCANpEcqbdkhMAr8L7oqDI96bAAC53QIiqgRn803HXIGEZFV2fSi70chOn4pBQu8nm7ujKX UEJgR0NAvHWFCej1oJwLwT96Kv70PRQN/CHwkvB4KWMhi8V9UA7DgeGlXMg9Bb8r8E68TcKyKH6I ARTOGhtbhLkqzzIYp2SMY0F0Rkk0Ddv9s5GGABiOUB5FvuBn0F6clR1VK0wZLvGzKhQmdyReZ91K spG/99ayPXr2yrYgJU/5hgjsxj2yzh4/3pRHyXtD0yuXzAvHlFFtZUxuX72Q9CGMuBu3jUNHqIUo X+wXELs1ezlRTnplhHXq1LwAVWhMyRGSH9wP+u0vXh3a8/U97wXQBq90favx8apgCOoJwekoR2q0 usK8XFvNw3hCTmAVOJx7UC7wCjf29L0KXDiEMuuomT63ybHrwk2Pjo7UmXthcclurnr3J+ZokdTy 1RXPAvRn8yTBEKZo8ITC2yN6mwx90OKn+xfl8N8MozLEKvVhfJ+4OImbxdQOn2PXWQmD+7oDwwYg rB2p1dFEwWjxb3CFmSnKFzzbwwJDP4nsGbvo6EjKS3rTo59X1c/xyj6bfzajwRT0lhJj1c8sTQ7A aEBvwo5mvalFHdu4x3MCeL/aq2lSs3DdQzJNJsDVeGommjhcAmwPZchY+JyLHRv3Xiqm7Y68GO4E kJyUNx4EWVruQ56GlEvdOPFvmlWgixQZ/Hgq8KNuXZlTZo2uyWuv9uTpHTd9kcR5EikkvDMAeYpx 8c4wZOzmfF7EzTK79pTC2ckxwFvHRFnULFjCHMIRzeSuK9xGKWNwGs9QQkfo352z85VnaiMcxSYc ej0qayaysmvCpx6ZV28QkoE9ce8HB0fqCEOn5VIlcg9zwvN2YMVDSA3wBhslNYV6b1MjdhnPOBZp 59zLw6DhSfZ56XED0QYcCbH+HBgbjyZCxJR3z5uwjTCM+cG78LfknbPb8X2rB+KOsDYvSkeMgLDR N0g2Aug04JnQK/C6kaJxLfdDGW/vyI5HDqm7JiknWPwUzKN5NTkaW/Ll7ODg0L59uG6Tk5O6PgmD mK0vXl1xLSPHTyIvJGPKc04ae92BAYCbxHmIV6Pcrry0M9a8g+Cu3hD378EyEFxRMkHwajgVoSig XZxUHhpipZuKh70LeD5kHWlMUNM94Smpy23Ha5diT7a6iIodcbf4g4V/IyLo0GMI8n/GGCRE0KR6 P+JtqccVjTl/vJi7KQwFLEq1Xw0H1jnY2bzjCxnVCZVRvNppJoqxTMbI/cJrAPPgwECwqNFPwrBx b6TL6fjDGEKShArAeIEvYTxybYqpq3bvwYb9/P3VxGsi7HtB2UXGqxT/SQ0YCpbvel9CegwSsoof lnRScnlqsDGyijQlgOCIgJwMTddVQ7d3N+3gqCPDyMFOHmcOBgVuGuJ5kDZjxtcToyrYC6Sz+L40 ygP0Dn+PzCmAapcn9s2dUNe5bf7ZyOMSTaPdthuXZsUGJykA0/0vfvm2ddtwBv359a08izgnpvfR 7pF1ZsbktdBcg+oExhuj+Hx3T+EkoTFhJ+srKsRmcd8+PE61nm1RBEhM8Y6gIDD+B/s13Ru/pyQH g8UmAObG9VhHMNZ5JpwZqAWlck6AO5guxpQDY4WEDeoY0IkwVo+fv7Lnm4d6dxgZPETwMaRkVhbH peYC/geIH+sh68fHQYGFDOFLAfm3ri0p4wqLfnIcrfkxoxrVeVEJXymjHKoVwr/dEA07eGGwfqkd 4iGxvNOT40EbPtIaHDc4vVzFP4PRAqDHMnPwUpgg4En0okMWo+974Z4Q7uM+tKMmHXppdsluCu6x 4OGQNL2dlc9k435+9/XTEPLA1CWt7l2r43j03/ObGaHTjqFjGQiBvkGGEDG53OC5HMMgY8vC9T5w SPKmQD3eIx4MXhcsdEI2jIIqE0IHFtetN5uZGNUmoKYNtLoKnZfjtcBIkFzGU8DgA6IvzU2oVq6T 93CexUWhLhyk2IGalDiFw/QdxKD4Ynbsy4Ffl1EFU0MkDiPMuTG67Mxw8vgcmSUZopDNxEMik4Si FIZIIn6xjjGDSfF8qEgcN+AOknLvemgvJdCOslyu4hCMR5LoiBiZe91qJ4/uFfMR1QgB8Q7mk0mW dEvmvUdJnEKxZG9dXRT1BuMCraKT85bx7UTU0ec4HpVVS/LIMEoYBt4nfCoMC41ve7mccCn4YHRV jht7Grb6Jo3BofwqJnBEZQj9O/ksmxlQEOOMp4YnjOeq9nX7SMvkJVnD++t2WjYx2lT94dLidBBr TA9qIPHkq6Ou1rC1TZkVhsp5mur+0+6IG8Z3X+3saT1zH2SqScSQsVViolaT8gMh6tUVOv40bWpy VBuutPG6bSvGphOnrzwHzXo9jJb/CENAXRITQJIWkDeLJZsoVyQDq+4jwUV1Ox/qCAcWXZb+wMFu vXeA1nZT+ASLsZvvamfAIidSyIGvFbW34Bgx8AuSN+mFTBeD4NkvJjQgMwaRXR8iIM/CRALAZxGO j9HmvGXfP4EUBxGuKw8sdgIJ9mTgvtPJwqQg/Iw7H787i6c1nF3vKrkxxR537fTzfjGMAt4TBnhp mjRxzhp53/35Gq4+3X+Kxa68CxYXRgTD5CRYDxGiDlE2Azks20qWCcAe7tv37H7ofEfpnmDbMRzs gHjD0WDB+YJD9Nsvnir1r3q4/Zo2H3Usbrbt4Yt9x6MqRfXEA7MhBPDmIgVlpbke7wNvgzS9ehVq U8orw9xuF5PC63R6ueeN18AmyFwFePbi+J71YNQHzGewLCs9BQ1BUB4o2tQ4IU0pNDj1xp+MFdgb mwOUD9EIqoR0KSbGwgUbgtBJwqFT8HrDsLTkx5cLebs4N2E9G9fPwB1RySAxoHrLg7rUFmrNlsaD lu1IvqSF+K4DpjIgGOI0HyF8o99nGf2tamiG6pSKJ2t7cig+vLVs+0dO0JTRzadCllL5zOGxEsZ2 lAkFoxTHLrQ2AyuDwgDuxhoFKiJBwPpfmh8Lm6Yb39WlWZ3j7v1D703QQV2iFkQ628LJ5mcnrdly QVA2hvk5VwHGxhzsb9nExJQV3fOJwzd0aaXaQOEjANUb256pwzAQZy4vTokKgedy3PQW7lkYnoxc fIl9kyLz8hApIxSD7YrEqmu9pyBpfD+vJA9C+YHL6gJ2MtExNDJinXC9DP7jXj9V6E31T4su9JWL M9KCYnHw79px2wqjvoMCVpfyBRnFLHlVOy4vuOtF31Euthnal7u3l5eR9SLO/LmMVQwDXckiw7zO HITGGCvuAc+DyahSiSPXK4+NXVngI5WuMr/whRif/qOfrDp44PUQgvMcTGIWKx7V909f2fWLczL8 JCZ6HYqN95Xh4zvVakdlLPjUeHTcC9gIJSM8CwYATwXJFKXc953XwyGKxMKkFTf35M0xl9RTr9kW 4LpRb+pe0GaK1AgSBaq/C4/CIoB5HlVUMVqcn9BZ6XjRQTKZ6SCxE0tyYljlmbiOxpQdXiU90Vh1 XNq3mEc+eE5e7Fffb4TCX8d5XAlCPdE984cXHzols5bkUWXmgktHu1Q3zyAKSs8THswjDEMNoLvq OOW3jylvAi9y1Qg8SLA6NkvK6Cibiax/DkI6jBoGhUQBTUiYt4yJt9pyxwVhxT0JB7TkGGBQdmGi t6lzbIkAOjpa9Sx1KO3xzcGTHRvbwC/8vh3qDies3mopo0r7MMJ8IhnoLK4+2rJKgWihJqE+nvXh 002FhLw3he+hFRubWDEujmCaAjsh3dmTBR/4VgxwpZJXZ9w6cjNhQMBTQPoFbAaghc8SowJej4y4 zAuTdTh3242SshsdxzocPzi5yF0E3zlAHFL5DClhJjgGg09zvcHmFQDKLHgmI4OpCvvYddm8h6A3 NHXXWazvTuDlxHtVWt//nykcM2Bq8ilspa7P400w+Sg8xQBDHcA4SloEEPgEUdFfjqtanDRW3AsL HI/v+upcwl0TOF13OeN8jjCwoonOgsWzUF3mMbIxLsiG1pXkR0LrMu5FCy1zPSgBruSQl7GjTRSL F3yFsB8DgBHf3D2wJhsErPcayguULnmpFN4N4483AHH01pVFZftYWJTVkNlk8ZGhwlBhfDkIHdKk Q89y4zRWGJVBBLdiQ4pt2iLBNXqkTGpCCjJVjM88RccyVGmYrS4wsatHhiIR2eL+ua6tqeSmaNVy XgtubmbKJoqu1Omf9/fOPHo4Qr9AQmqX8fbQNX1vsNenaPcVMtR+772+BI0EA/IFYUFkAOO9cKsP n74UF+nD2ysC25lbFD9zMO5w1GgAcePyZGik4pu9VFH2YZl7xpf3QPKCbHgsQ+I+MD4xpIbaslAZ 8eRUG7FCipubMmAYGIB6jDJAOZlYPEfeNeorsxjKrm+sUCDgj2FQmYcTVcfg2MRfvNxVhpDoDHY7 6x9bQYQ1MT4qDbRaDXCeBhhmmzs129w/xMNKtaj0ygN+AxCeNRbRMGlnK1A5DotaylZ6ubj3LIjY 6FQ3GVjsrfaxbe3jfaSlKIxVDJncwPmLJERzTXcHSL2du4dXYlmQLq5BUKxq4IcdEcgbdmBUBnsS JiGB5fo8EdQgsmHGeXlYCL0xYVk8gI3oP7mAnhs9MCXCJQ41giCMSGQNM5S2zKHq/d2aOGGEIdFY cTDuYDwoMqgHYJSwyeXs/pNX2n094dgTVwcAXtrqYbFGDaTkWl3X0CddDy6B8QLYx5MCi8LAEL6h 8IAXNTlWsFdbO5qUrudO+IhWOIqi3h/ys2+eCzxHK4k5ATufzC9yJoRMk2PeGCK2Y4/EWHZuvF8m OudEO76uol6eu247u/uStUG+hjmDseT6ZKAAdUWAbXc13jJSyphFTpVn+1JD5YbGpVwONd6MNQsL UuzkhNc7xlZikde1tnWg0MU9bad1UC7G+SmxwbMaLRXFlA8jnKFueOQRW5QpYZFgYb423dOry2AQ 0i4vkj0c1fxi3fEzEhKA62BArBcoAyRFmA+SZTpuJmqkP7lzUfgSHhvXdwkcki1EBnhsXYWKs1Ng o03b3q9rrRHwoH/FIpTSaZfYzSMfZZZRkKV35R7lOxXNM+oTgVbmqhW9H+ZLVB8BnyvmeurbOTM1 IRy8gUZbmQziBWs2avby1Y4d1OGKtmxsDNB9cGG4r3NiEfazrpOfBuY6GEQ+WSxRD4vBwFuiGe9R 3ctz1Dw1Kf2I6diQaqU8YNbj+NhcNWax4otEIgPgFC/hv8SRpR6cIH5mmEmDfiOTj50dF9fF+gG9 CzKIay/dW/GM0548j3DCJFQZjNY4B9gG5xxsQIqhkL5RNOCBMS9M8NALnvFgIkPZxQ/dEyDzx+RL GrX2ugrpGGPeE/rafI9FI5LkwbFqFME40Idi4XiL+7wWNk1Qn6zvioMENoWxYCHPBZnbRL6IpiKN tnpNItHDxCbcodTKtc77mGfJfzknBovF57ImzdC5aFT0AmUO93yuRX3/KAsMWTFK43hxdfD4E6Iq ofChno0QENoM3yEk1ez0ym7xCnu9VvKCuH+oGw6D+P8wsi0qJ8BUGZtMzabPqziJoAz5vGJOUJUQ 6Qu6V/TvG03BE9cvz8lD4h0xZ9DRV6+ELmRZVwRVgwkK3Q8Btnu2tVNLsoXMD7pFM1cA9/EAJqrU iZJh9q7jpfGyjC9RCM7DQa0uL2h+piwi7FG9rUwtBixnHUU7PC9jXK97gw3mBM/Cz3AQOKBBPV3z PplsKnj8PN+LjW3JDKF7z7tgvs6sjOkee52C3X3wwq6tXrSbV5cVIp4wWF44fNJgZY1VXwFvtqw9 1xMJzIF694p6BUTu8jYxXu5r/DjM9PE/kQVb1Dl5/RNHbP+kcgu9eADzA1s3NK5DVlBs9XDf4Zbw JtiVz1ubeNaREAkz1IPoFUWjPQwQ4n7VoDIQTzkHYSgvFA8jlssQomXx76wzF7212HQjGnpCTABx jBmYRRLOCBTuavKwiCCNqkaLmrXYIQikNAouJlywnu0g5FZvBaJmWUoJ7MYkNrjvdvBWCLkc6Ob9 IqE7q903duLB7acRCcA/hjrR5RaZ9UghzC8/vCaj9+j5trwDhqBe9+vFMScj59kuV71FugTPid9h aPG08ViVvQv1dKif4mEw6Rkq1D4Zl9GRqRQbDDxD0VcyvTZ9czSbmKgISCZL1ugVpCCRdn8OHlEu rxIb3jG8uNhHMY5pHo8CGgdqCIwb0kcJhSJQIBK1DrKvuw5eh7DT01U+hyhyPlJ5T8eNjQD1ogBx srpgUtTeUZEBUE/dHhtcr3vkGOchxqehxAkJM/BBjBX4m1NNkJ1pWaGISm/BmmTY1eWop7nA3ylW ZoMh9APTInMKx3F83NVfCYchHGMYMbzMH7xpXA0JRPKdgoeBgD+HrPFezu5cXxEerW7gKtlxbiS6 Xq0uiY1Je/RiW9/vW8n++lJjdRqV4bTQKEsC9Zfg8bH/Jhti9ovXpd93HhC7ODhUzLTxUaV+S4UE 4MZ7S/sTRoPVf1+EG8TRP4bBitLOsVA2y+ePfKbzhowyItOuqMgEfPT8lV4yHgbPKHXW0IuOAwPA QmbnEudMmk4usQJ2Ba4k7S9zygbjB/+IA7oASRHnyUHMdDC8n27n3VMwVGBLeAtM9vHROe3k3zzc 0GSHJ0X4hhopE/Xeg3XtmBincqkskJWQhB6Eq6HNV/bgfZECf7qxq+JlD2tzoQkJ4arjeBgmKU1M jMjo+D2CLzaFuZFyl/Htwi0aUSkKWCFZKfC7n9xY8tAjvB2nHWQbnkb4KlUZje8TFYvjY0KgUjBK HjVoo8x8FEPx4uWOxlpqBmGORSOkOYs8ToG2Xc44b8i7A4aPyST4fkGYUFnXnn11nzGdkCgitbtc j5APEcbN7X0tZuaJroOQX5mKjX0144BDyLPCqeN6QAGE4FcvzcoTAh/CW6aGEwghUntUdqfav5qK p/FkwBapECBZUtU87dnU2EjAS1vyXtE4g8o01qWsy2TYqLcFSqGUy/WvmNsjtvFqT94Z41SdQyK6 bKOjIyqYFu7V66oTOYZta3vfnrfa4ndNjI36OcZcHQNJRy0Ml/hNO+cOGqsfUkeXTZgP/ua00zGI kXODixgNET/H8meP0wxqPJjALsrvgKI7Rc5h4gYiABq74HKIuxMwpXCV1Ks6S5JG0+dkaHjawcRC PocQB/cbnIhJonA4UAtc5sX1tXkG7o1FS9aSzwHAY4xny2TjatqhuROXFSnp/IR8jLW6/AqXOVIC QK3J8ApzXuDK+0VCh1qwsTFkb+mi0xPZFgCdcijCdSYh8iDPNna0IwLAYrRY3NBJnFjoPfeyB8+C gSN8ZBEhG4KHovQ7+vs0N6lyr3nbOTyWUZudynYicohBCRU5o2BDaYlK147VhIKsYTRWseSLTct5 X1G5NfVw4jyKIDVh7XEBiWA812aiHoIho96NzQYjhQFgkZOBjQkIDubSsZJGGC4zbE7MSba6Pauo yXO6MggvGVOoAGCQvFPwQ9rH03VcJOwCMsclVXfARbq8WLE8qhbhacarRb0v+G7Mq+mJMXnDzC3C OxRZ0XDHKKqLj3A6T0wxX2GeM/94h4wlsAUSQhgIMoP8jvcPFiWKSDCujAN1kEhOvdo71rtkvJbm aeR6LO0rvGBqD8E8IadCByFZMDZaVeNVrsncZVNFcujo4MC+frBhN68s2MUL86p35Z2D9SIJVCwG hb8gkJNmwpLuzj6w2YUozlGjYfV6wyanTk7O5EjJS/2L+wxvhMnxY3hEHGo0ifb2IeUcHpooGxPA zEg3cLa8v0woEx/eoeEj+2A6kV9ngrWD99fjDD2yz40BwjjzvDGBQKIilo1EXaZowDFevhD85+xc TBomFJNLLHRKOsY8S5jlgREe46Lz2SjnAw7EI4En8Lz8m00iStsS/pH94dwQMOFgsYsyVrSsJ7ME S50R2a/VRSf48PYlPQ8GFjfeuWz+bzzet29ckJfm9+abxd7+oWobAWFZmIQsGFU4REnxu+YGmxaq DDvCYkgQuXRvO0keQDPwLF2KOXqCMJwnAbVT/hUHGuaioow716vW6NizjX2FxFyTzK+ahYrA6NUc eMlRJCB6VY0gDU6TD7YVgG/mBXIpNJcg7I2ho+6HcVDWsRA8G4raPaNO6IckD4kM3k0h8Oa4FlfF y+H52TAIJQkD8YQQK6QwmvcN9IAh5GrU/x7WejIgyuYD+OccHyUEvHYRZj31mU6SFb8O/LLtCTW8 ajr9cD8HhzWtrfm5Kf3s4bNXUgkdG5lRwfSDpy/1LvGkIRTT7ATvkGoIph+GEfIq94jXPFpZkASy k6Gh0kBEnRAeuTQ/Zc1G3b64vwnTPTKsWXDEzX3sqTBZ+vWjcBO3t3eTlz4xmQKqw4/zM8Tf5Bie CEh/xyJk4arbCdnNWFuV3FPfN7Rjgqdki46TIvCok5pJAiQlHUkp4Jt4Wa5BJOoHjGNARk+h9mFL r/N2eT48MF58NdTLDePVgXPQB07S1oRewesh84e3RDjoveYWbW4G7ytnv/7iibyHiwuTmqT/eO+F wGpCD3Z1JjJNMpmEpNnhBWE0uR8KmTknAn8iU1pPXhVeQnxvnlbvuk7X5KhUPeF+IbfLhO7DTQOd hep9DAU0A56HBQ/2Aiue6zMO/r3Q1Vm64J4tVEecULoyWMHAs5Clgr3OtSmkXqBRMIq3hNarIw5J FApWKdIEtGxA8Ud0W86ZPXzySoaWn49Xivb2tQsKnQkAoXwUIVxqIwqzKqFZILPk8yvqj3mDiFnV 7xEGuhR4T6EnOlkxnBUlKaiNjIyUbKFUVDaQDejx860g+BfC1A4JCmez8075WbMDsZgi95YUM9QQ lmij27Ot7UPVDuKJs0nhsREugo+Bt+7VWjY9NSHuGc/JHzwnsr8YNiwG3vTv7z4X3PDujaWAdc5p Pkg5uN0RoZvNaX1zy8htXFyak7FCKwtjpSqUXlWeHvda7FMEyPCe+hbKwPpjwMrlsoTknz9ft7nG jI2PjVm1GjXU+49Bx+N1ZSs/JPwcdh6MCq5mtm/g667DZKVbMJPAVSqLCSlUWVBYutYTF0a8Kz2Q hyjhr+e4N8osQhie+UZsARYnclZq5jTDDIAeM6Yp9aR/vLPvkXCN0LCG2N6UZ1sViuaQJpkTOM9u ev/5lrCKqYujaqBJ4gS8iO/jDbKL4iUxeTEieHVMeq771XdrWjRQC7JduqMcUVr3RkEuoLFL3IBd YdBid+HBZ8cYgHeB0RCeSVmzCU+obcuLM95qLCFhukxz3/P7CZNGGdGwcfBsnbbXLqLiMQ7RFJwt cOx0xlj8H9uBdRExdFwKT+T7Rxt2eX5KPRjxZKG3YOS6qvzIvr8sjpaZE9Q5AnsEg4Qnyvi2277h FAtkN50v556wG0vfPLlPr+qIPEDan/1ZEPdTFKEC6DRaACckowg2GcNmiNUkMVBdQBJHszKfkyHH QxI+ultTVcPs9JgoRHh5s5Mj9uh5zx6v70nDCnVib4hbEE2COQWmhlEkwiFZhAuAd1dljHodURm4 hrBYVErrbdFLdvYOtNG8d+uig+6nguin/JxBnZqeEPcFQBBXcG1tQ/9eWJiXfERajxjd8fMZoSyu cGrt4ZDfDfNI+BH4UCMYnqjCmO0tOHgoG3PsJMxYbxdDRiZvMmkDYJzNHrze0HoX7Ej9UFY1DcIT k+fPN5CNPcVopT+L3zk5BtkxYlEThXTaXnZCwwN2MrwrdsT7TxvaKdHuBjwH/wAfQ0vnAAAgAElE QVSo36/Tqt1Dg+8f10Iq3o3C5989tT/72U15SEqr76N3RPh5YO+9xc7aLwYZn4/xxWtibFEcpVGD 41+hNZwkYEK5ds5UV0bHYh7NG4Eg9YxqZkeZpFiapGyxFrK/r2ytYIKfDijPjoxUbGmhZFONtjAV WOyjaMvnI53Gi+sdVsi7Lw22Wsip+enswpQ10PdXr8oLujcMOXV/eKcoGzDv1tc2bXJq0hp1Z+cz jmTfxPrf3rGZ2RnL5x1fwiDR6ELyTDSPONiX55X0v6QwXRpU9AKk/XzeSoWSNRqHAr3x+MgOMqYu CYT6hZfYsTlgnMH7oHw4s79t61v7mv8YMeZEnIMYJUJ29K/wtpgfZDOlCgEjAILwpVn76v6md+Fp 92yvWbNbqwsaW8aUigT4aXyWcV1/uScIRO8VhZTJUXnD9KfErmLsyBpikEVapbLGfuCB0RobH1XR I1kaTaLjur16ta3C1KkpaqOc/KfFHWgAPLj6i6nduJf88OCDR7pATwPoTy7I7Hc5AOpYYApNAn0A l1h6PRD9ApMvaxhiCDnMcKZGIHcqqfb0Au/YPDZb70a7Kufn6Luh5tLXU5pqH3bdIU+djMcgBSX9 edpR2N+Lu+UIsOEtSutc5L459RrElYc8KspBAbXZSceRqt4kgqdiFySlzkZAKMAO/Mm7q/KqdsNu zILNen+8c4wUm8nmqwPVKUJEhqTpkZIXGbs6aSA2R65ewKR4R5SCddpl31gC9paMhqLrON4+j3QP EZv11G5SUC0DF8QMxQIPnXxismZt3Z8NHSwMTBzTasFJQOBBGPd7DzdEy+AcpO/xeOBQoYVOSLy9 syut8r29fWmDceHj2og1mk2rHR3b4SH1dW1JR7NWiGRmZ2esVjuWRtTs3Exoe0XbsQMlPVRfGbBW tagvF5U4okEthcg+nzzjLsJw0Kni/sCt4gBLMugYAzsTopI0dOcPoeNxC22rqk2NVLVWMISMm9q4 zU/pnKikTk9U7MXGjnDLKxcr8haRkeGcFHATZs5NV1V7SjjPWuU+f/3lY9vZq8tjZ33OX8PYmm28 2Nam9E9Gtz1+Ltv8wqx2jYODmrR/qDlSxXqhqBvkJai+a2TE9nZdhA0gcnaWmrFsVi7jcZyyPrMg avysQM+kxZR/kawEExsX1GsMaTu+rTqmWIeXpLf7zp977d9PO9Jwp9/Qeag37PPUPIbsbMD0IxEk Lpj0s91zeXOnkXxTLyyMT8AyMneT3G9s0MmBkcKTxmuCLxMzt3z3wbMtYVp8lsVsvZmkkgBbDGeH 8xGGgv88W9+1d24uh0LzV9LJh5IxPekaTh4WUQN4dqOQeLCo6RsA3uI8vEweMIwn75+/xmRG//i7 fAnyKMg4j0EulWWMYVxOIH+riRROVT0ffZG6t+b0NdeLw8MhnCVbOXNjyT0UOi8fOFeO+r+jY7PV YtFmZqe8zRhUHpEoe7ZXN7t9dS6pEMEIN1uQcuGFjVl1dEQbzIvQeBZDQQUCCZFO1+tYsbMYTDwS DDpY4v2nVQfemRehPpfx9+SBG1+eA2PFRuS1nWmCSZ5ukb6SY1JJ5d94bfx4Zw+ByCN1oQYkB4/a O9zUtkvI+PD5rsB5xArh3yFqwHd5NhIF4FWPnu+IVBo3bWgbJHygNND0g++TBAKu+UEGa9CTEMCN hG2xYKVyyerHI7a7uyeMC4PkBZ90SPbPjI55Vw1vOulSxeks61s7p0eSmd+Ly5KwliPB0wFJBMKY fPF+tct0HegdjredjaGdFo4O82r6PpORrEmNreMWJ67Wl5lMnzMSV2XMeicX31n3lJzEL3Aq1vhk fccWpseS0ifxiQIGFT+UlQpChQEBQNYvmcNsuM1ODB54twOJdc/WNj1DyXti4cFMZwcmC5olZUZv NFvbFx6q7/mi4XYjDEfO8ZasZ+qLwDPGeZEtCU9TEjCGkWfDA+dcYyNj1oFuEdRQkWnBGCNPBB6a iuJluFyZDQQs697Dl8Fr820HigAZXegDx5OjWiPVQlmZL0IkopR2e8yebL+w+fk5bb67ZE63a3Zl eVG0j0qlKhz1MUkhOE+zE96CPqgr4L2kXY6K4jNNTZQ9871zKFyKDCJEUQjLJElcuSIYXHWw8jpB ZVgpcyrmRQjFI+f9EA6rPrXt5FU2IafRlOzo2Ls2IXuNcrHey1hZmUCMJyx5MMdVSnwojQoJJ2Aa 5tdf/+auPM7Rcs5mJ8qqJ3z6cM2e5SEdj9rWxpHV9kZ+mME6C/MCx8JzqogVDXaEbC67W/pSq9VK 4r47FjRkJ03m6WluVvrX3kAGLxq+2HWatxJfCjvKsCzaac/2Oq7XaZ85OUYBYI94XryHfkcxeZ5+ nDhiLQN8sHMYrVPu+ATgz4FwGiFFLBj3xg0D2OCAwWYhM+nYBMAJ+Q0TE0IhAD4fRXOMrBmfZdLD 1VFouBwwpoxxZV54HzuXSIle4anPSDgCRhVCu6TaIXinVEgAgHNPwACry3Pa2b0dmCc+2EjRMkfR AMY3HCeVTREFlAuiZijj1ydF0/9uxaeiA05Q7wTMhkMUybHMcwi2eA5s0mjRw73CwFaKvpmLJ4bm lgqBSwLv71y/4KGUukK31P/xozuXjX0YJwFqiZcCebPiojkJ9FDkVxY+SacRSRI7iRp9MG/AgWGJ GzC4IxlGvEI+RzjG5sPGzn3BuYNvxcxhTB06qSjLvLVLpcWYjCLRy+ULk6FrUNfevXFB9JB7D9Hl R9xvy9Y26YqDo+Keer3ZsdtXl6zdrNnTxw+snJ+xbvPQes1DyxdLdnxQt0phyh4+ePhPDwlPDxNx Nd36e8PKc3S1ObnGz33ERZylI/jCD91BxCgmbIhtrdrBU+hn9gPixskOjnAW8K/rZATjUsytv3lG Px6WfbCBKufEkThJagxl5pmPDqdQnIV3ne099pTCZlHHHnRDj2xqKxzeZDe9RkzNe4OMvP3pJzeE 6fCzSGVQ4XEsfqfmtN2W1hQk1q/vb6opA4sbXhReAy3LTjQb0XdRm/VWWSzoXKEXVCpgou+HfnxV Mf7x6vEG8TCWF8BG0kwkz6AGvpTPJKoKfi7vNJMpks8kRNJ3Gn/fk2rCV/c35KF69i39rmo21aHI e/NNjGLkvVemk2IDjigFjYIya2Tg1Cxm51BgOWTeqK4geWfY8zKMblAh8BJZ0LyD8YOnRYIFUurP 3lsITUDQqQp1i3C06l50LLmcatnXiYBALwZ/+GLb6q2OLc56Tao3C8kpvANQp+8kGCaGe2mO7Kb3 uJyZmrSRyoi02ODlsVlBn4JREHtY4kjA32q3m8L5RqoO9qMt//2DZwqxL1xesI+Xl9/MYGWzUOf+ TvKf/zLHIECevREGimyPZ6A82yNToNbgXTV+bNFsL4QMnU7Nxsf7deMHjVH/tdIEwbCQbNBbOWE8 MtFP9sjoOAz83CkWXk51Miw9jcsVw1DPVqbnI43vNmR4iBsXZCRmDvdGe9p970IQbHXs1pULNjVB GIBnEfWkfMw9fMxsGDRfqHhHYXAzVf8X8Baadh+sbMUzV9kRKMqYFFUBAKdnX8KFBWUR+RmYisTj qs6YnhhrypC9eNmzJTo4B4yGqABAvh4SE8mWkuhjxQ476YuK7ebx6lEeFccN+R5hcqO6H/AdDBjZ OAxwbIYBDeHx8x1lUaOXybkJ+5iVPDdG9u7DdfvozkXb2qb06Mjef2tFeJlUHnQvgV+WmXskUEik bO3V7a2rF4RxEdrde/QyFCU774tkGZ4U64DzQZ0AwBdrP2ZR82ZtFFdakIhd+YJ7w3NknAk58V4j E58xaHVa9sV3z4Ns0JS8vEqJsPtYeBQe+cz0uE1obfXUnIMkDF7i8spyMq/u3X9h0/PLduXaNZuZ Gte538hgvYmxGrZgfgx+1dnX42+50z2MgYwRu1q8r3wB1/dY9V2fffaZ/fSnP7Vm6zgR7Hepm6Cg moAkKcA7eAws5b6fvC7M7ONmhV0iwa8GQHJ5izLGrxcJHLx2Vi/ev5M+zamGPwDNp52TrA8qp0jm zC6NibxIZx88GGEXkr0mS+gZZEqDFMpAFei59zA5DnXBd3ZuSt1yNvckt0xz0XgfHHhXLLxypWJl CpQLbWWgMByk5wll2NnJDE+OkQm1pDOSizD6Ds8GJhHH7sn31e/t9nOndg5ggO+qcevl5TTEIgFB oufu/XV5M5Tw8HyOtVL+NWKvdl8EUqdXN+B94AkB3DPl8AyvLE/bZ3ef2eFxx3723mV5Ni6B0/Hs er6o8Hv91a6SKHgy0qYK1R0xOQIAPjm2r43Esbicff1gXZ/lNYBfrcQKhCRioACZpqj7ygK/c+OC fk/lyLNNSqfGRPXgGtR3wr8CAwVEJ6lFhp5yLPA2FB5ouCGVBsurkqDXPRA8BI63s3NgD568tNs3 CWpJ0tQE8P/svSvKaNJRW6G1veHxOn7UiZ/Zf/7jNMLk8MMXaeqxBDPWiyUeJaWdJT/SzoZnvtD6 xA31Xk+vi4z3JHA9psgHpXwTLzTiWYOAeL93Ndy787S8gP1TaCBnkU8H7/e05xnkhWXPHX/PDvyP Xz+1f/aTG2odB9j95f11+5OPrlu315LWvrDFIKsibRAWCewOGloEgccI9nOQ9WIxI3vzJfLAClsg r7rBch2nokp51GiVlvehYJcFhbflGUgEEL0PoNeLuu5a3HbAlKgV8DKbiIuG/wxJAiG/8vzlnrJj GGQvN3KYgcYS/Pv2tUU1oMBg8qzqTUiHoJClcz6VnxjDLG1+jLeMaF4eIp/7w7cbMhCdjmv3Q/sA +6HshXMR+n33aFNAPJ4lz08jEWgpJDrwrAjZuE+6mbNZYGT444YdTTVKdsL4B+MMlYN7RI1D8kUU cdOsol7Vd7whKsYXgmdNniUZQXnHyBzPjHhT5qDdj9dHjS80FoQRr66U5OXhBQIhfPHtc93j+ksv lSJZQ3kPBeFkmd/Qwzp9wvPQUQExnclONSKrQMEuN+3eZv+KwB3kM/xUGkaZTBMgOXFy7BAyuHDY IdhJwF1wac/HWcreY7rYSBTs7R7YhQsLtre3Y5NT3rAg9ajCf1x4PexC/owRFo8vO3vueD/+J2gm RW8wrE41LggNLrMbfITZB8PFwXcRheOiMmw/N+wk1pbFVc43TOfzlgHWyerQ5ukerZomqpp8qDjQ MBMRv6hDxeKl+YfTLDzEguLSapPKD1VjgaBKSIc0M5MdagqdXgiI2d0Bn5NQPBSWKwEEqZMymmrA zqwrxYFH+ztqLSZ+WMzmhdpGSJBJdpHmuruHmntSZM14pOBBhKl4De7RRUMeqxM8tUGGkEyqvMq2 nxND9ruvntida4teWhNuXg5nAingZzimBbaIUciJaOxPiVoEXocEKZdnRGqemfRMIc8P8M7P2EAw yhScM/aE2oSm4iSi3R602vgceB8eKSGsvE+wrQaif7GqweeWMv2UIAXRQsqvCIkX57xjNM+K6sfW zqGyg3F+8pw0o4C8jNdWLuJdFa3VrOsPmPHt60vCUaFhSJW3i8w3Et3O23xDDOv0CQ4wifZUmNLp L7QYYzjjtVKJ3Ef0doKGNkdao+cHaVw4J8TgGCbSsVj2qPcdReXAPRKWdCbs46UyaOwkSs+ewnLn 2RiwwlxQhED+OHbOzdIMEk8oY8DiFXNng1ER4ATMZIfzr0cDyyTzOjhhHBkGuzN/+kPF9Maz9xKv 6z9cX1uz/f0D579VUIzsSXbWDYNnc5kE1Iaq02/wesbHx8Wpu3TpklWUPInYVcA1ksL4/suzoFgQ b13xd8GipmHCB7dWtKOygCJXyjv8lNKsY0ib40Fkkw5xiPDMRqtkGMeD2FxHoRQbneM5qG+EXoMi v3r2mVQ5YLqn8Mlil+zS4pSknJ9t9Gx5blyLJnZ5So2G3wMZRcffvWsN6Xi8FhY5YR86ZKmxShMu eHcFGOsi6o4l8EN8PwDXGIPovav11lEjmcPu7bsRp54RQ/37u89CD0Wn5kDGxLtjYfO5mNTwZIZL EClzm6WHIFzQomHFoRQe8JCQwsbDYW0R7sGPQ06IecF9gqXh5WapJvxfqQhPjCL3HXlfMOEJj0UP qVa05vQewOZQG8lTrUC7rnGFiRDIYb9DpaAV2qULk9LzEu1IvSHaqlPutOlc5DSlHy1LyKJQu+1k 8fQvVL3Q4O4PA65PO2huQRzNwDAxKIwtLnk6OHpraF33OxwpcZOJpa4lckujHegndWbDHNEwBo7s /Z70LvpDsH4A/hQcLXuviScFJ6gd2NzhGRIHPWY9hx/JfMxchc/Djq7Xj+3lyy2xpC9dvii852B/ X2FvqYR4W87q9bp+j1FjgWM8x+gDt7gQDFYo8E4EDP0a6X/7rw3ugtdDKIDuEcRLJvLtqwviPTFE MiqxTi9QXNL34F2tCSE4wDBurC54qyy4fgW8lZafIxhdnhftfDSWUowJg9WWzhLkZhYeOJUaNUxU 7fC4ZfUW2WD/vhIwOaSMY9MSvLVsg1Q/MQW+6D65eqarR/AzmNh8lvIWwitKVbhf7gdBRZ//uWRe f/90y95apfsNIXLP0C0EqwOTwkCBNZFp5Pz/7ONrYn87W9/nQyTyxiNVjXUJ6NMAGYqIH+EdrsyG sh2nHWGUYssySJox2ytNsoTbFt86BqQnbxe9NtjqUBuoR3UFC9drw+DzfZ5hdWVGtYFUUfD8qj98 umH/8PkTddt6+8ZFazbrdvfhS3v7xrIUH65cXBD22EZuu/SGoPvrjoRcOLBOB43EmxxRZjiGNril g14S+AYcEP5wKYwbuy1uLS8VFzTqvGeB+aGY26kZwOFHNr0djzd7zoHP9jlwDnwm10pp8PEHGezq 5HFh+YJd6C7a9MKiHdUbNjY+LtkT67TVSbiJRpL1bP3pU5uYnLCFBW9Giq63yI3VTNH4GzySGtGi 2U+YMjWqCczk/c2XT5Jlj77Sf/Mv3k0eJA23vATk20cbCg3Y8fHU8IDgDY1WAsE00gTgP/W8CxLv mCJtb1Lq/QFJ9+Odg4UAWcDCh1JwcFSzg+NOwuqWV5Qr2pGNWBlPMd+Q2mg20RGTEki3eJ8/sKim yo9YrHQCIospvKcKt8obBOcCv8p5Vn7/45W87e4dqd4QDwwKw2gFffhj6Vr9i5/dtL/59L6avRzV kCWG3lFKsDanP6TVHTHsRzPKp0m6wcY5GjOas1NVO6x5MxBC5ngo07dICY1DOCQL8L4iDzD1EMkw tqTyQRclwklaqKlhCSq1dZpiuDQO2vB/87vvBdmsvdq3RqMtY4Rnh2dIAmRmvCyngg0kXyirxI9e BOtbR3br2rIrSLSb9vWDl/95eFiDh+gc/ZDO0GMYNkI8LGLgGQccHQzbIPgeMbGorDj03t4ggTDs s1nv7CwqwVlGLBqiwY8MozNkPbR4Ti2KIecnAwNLY74yYhcCftjG6wDzC11fONVIlVA5b9VySYW8 LET0yBv0xaORQ+bqbEqjLNZzvMt4j4QLTFhCAU32prcCQ1WAxUGIBdUBDx28BOVLsDDq3Noh7CMD yHvsdry5KmEyoRy/a6EVlc8phEApCjlmPhMFHJfmXL6XFlfURfIdQsNbV+H8VKyTw7DkbadNV+uC jRea0ptizjo/zPGTGFa5d9a03cNXYpFfvTgvnAnDY722qDDddksTkfKbA+nXd6TrFDegw6NDu3v/ hdQ2wfcuzI1JHoiEAfgcBvCTdy4Z1TuUL9FstAudod2yQi/WcvZ7/u6V+yGtKyReDg/t1asty+WL dqxKq7zVj4/sxcauHTV7avIwNzMh5U8cATZ9xAvxtMCWyfZh5HkPeLpELISuAPmA4z9//2ro3RnE Abqw4HeEadNpCRgHuWTWJ8x5DCqJBIyVxhZ4RFjfiLxqEgKv9hrW7OTsk3cuy6jTemx9c9seb9T+ yxis04KH7MQ+97mGGDWAP/Cf837/dec7fzh48rPnPbz8JBikDNk1/X3631Pvy3pqscUfvjoCPybj fSJ9gmZ2pViUtjhHCVwj39WCF26DVFBxTBpI/DkWVagnCRUafMZ2lHETYFevaaKhUhAYYHhTQ7KG 2QNjE8XuigXPkAG8wo1ikaqcZL+mhYCRQfm01VpTGOHYo3eqEYUp7EYYXBjT6hre7dje/rEmOsoI /JvCYzUVLZdslvCtkLPPvlmz0bExu0mKvjJqe52SlXo5a4G9U99WaFupB0bm7PI03o7cPG8A2t2r qb3X29eWFP4p7Cs2hLUxNt0kKYT6wCt758aSwxi9gu3tbtunX6/Zf/vnHwpcJlQmcnAJGcdmiegI YckJxGKQXg+uVEndlgnnXcfer0MoD17JOAEFgA1dvXLFjmt1e/5iw4ojU/bdw+d29fKSPKvj45ot TlWsYjV79HDLjo5pTV/UxkKYikHnfaC+Ic18JGaoOwyifowxWVmoDBhPzxC37ctv1kRHkLSMYKJR hZfewixIMe/XrFR0Y3r30St779aqehby3Cs2YddWZjySYn7nTOP3j3df2L/65btW9AYIqfLmD1l8 rz+GeyvDrieQMfQxi6Fk/BhWOaqG/tAjXpdGBoCertKZ/m7wvt7UwA0efJvUOrsOLxvQWGS7vSNl qbIEi9eea+C+6tLmylkVnfugdtns5mS4+AneFIYkn3NhxihLovR7hj2hz1DfmqhxBg59Nv8RMnbq bJ3LS7yuJTUFf0YA16mR0gkpmaFhtv9DBa38jFBCnlu1LKKh+FchrIlAejhRYrjwEDZ36/bWZfg/ WJuC1VueTBBvjawrkijHLf2hPdj+cdcmFldsbnHRmuWqtToA9WYla1sp17ZyrmOFTtvawhKdyIiX gHY7noUvupySQGTdKNnhniXbcgxnj/6DeWt06CRDJvFAzTvuXFuwEYy1MLWWPXi+beXKiPovsoA5 x8lBc+NlBbw055oVSxi1op7nD58/VaILT+ziwrjt7u7a4aFjfozc5OSEDOT4xISNT8/bi5dHduXS BXv75kVtVHWRpL3b0dJizsan5lytNnjDwq/KLuAXFW7dMHntpYeneHLevo/PgCVPT43Zn19eCFk9 L437/d2nGj/CTRrw8v+FXEfCj7dvXJLMzeO1PWVNHzzbFC0DTIvaVBj/85MV++Tda/b2jSUr/uoP jzTpKhXv0RbmksAybw5w+sI5z8LF+CCSD+jGQ0WJF7Alf6C4Q3QENgp3qpSUro3nZ6JwTdxwFjlS FIMNJ7L3Niw8G/zM59+90AtRx5mZMbtxad71xRM1x/QZs4YC3XR2HQBQXGVXRBx+LX5GuQgp/mIp l6gyJvQLGaw0o/hDOG4Mn5eRYHjy0g0/JnNGyJQrWBlC5ElUPqO+lYa0bvbOrhX167ikSilQAETo GynZb754Yn/00TUbGdLuPvsM7I8Ayv/+7+7aT965LGAbDINJLpRGIW7sZhMZ5fGJ/WDXbnbMvn28 YW9fnbetPfhVHbt2CYPnWUPCmdb6rsLPS5eWbOLCJSv1ijIeja7LGI/mGlbsNaxgnpmF6MmcAOzG +L7cPdIC411n5yOL8/NvX2jOco+SPqYfQOAq8agT4xXJbY+qDjGn8JEEwMarmv35H92WsTrt4JxQ DL747oX4So39TTViwNA9eLFv5VzTSqUx++u//9Y+uLVkI6W8TU1N2sSEt/46bubsV394HDCsov3z n9/R+KZNPaaUcdS9Cxf2bF4q3+zZRs888nmvx7WkmUyaNQePZH3jeZEUS7seUXh9IJD/5uU52z84 tqll7yaOsXy5U7P84y2t57euzAbqhwsh1GpH9tefvrI/+mBV9zQ/OyaHpUicGCe+P4jfb7Y1O0aG wYu7oUh7Q/r0DR5gBeAICMS9/9ayXFgmH/EtL50b8AajXh6Bp0ftVSxTGMRtIMjB7+D/6coSBz+7 GAYXVzwQxSf2xkgBjpJy9d3DbG+/JrLjB7dXZEiHkSPZDfaOXGKWUgnORbEwICu8FScI9+NX0ZuB 1Hh81EhavGMsUWw8baJGcJQQre+pwrth2lDloS69wT1UES+JBrqsJKUVmUTIOY7zeo5quYY0CcJz QbMKr/Gn716yY3okUvqRufFBo894/MnH15T9dS39/q7TMTXvdJeg5BFCWIVbIVPWzhXssFO0ojK7 7tVgDNsBd+K8F5fn7OFmzR6+atoiKpgyUk0teAnPyUd14i3hIyC/SkrmJ/WcKzRwnaExQ2h2Gx7j /VvL+vvn3zwXM515y9zkc+oipEggZ3/7u/sydmh/gcMx7winaM4QD4Ts2AihBcGpYm38/WcPRYJ9 7+aybW7t2q9+s2ZLFzzLdvv6RbNWXetnbGzUbt28Klmn0fFJhb5kV7+8+0RA+FtX5mWQED6MI5zy 2/IOhDeRBprVhpfOg1AcPkA74ncY6W63pfH97jF9El3+GvXaqNUfN364XXiY9Ep4FkqVfvHBqhjw 79xaFf4VG5wQaiOjc3EUfKspwP83Xzy1nd1Dm5txue1ibHR42i6OsXr4bMv1qislAW9YRDIvZAeI ez3TcvKgYh32Kzcstz8Qz+QCh8UX5YtjGJLNAA7eD4sC8tvjtW2VGECmY9AwXOxWapvVdvYvVh6j RhwOVoLnBpCLtb999YJKHCKTulKe0L2wuzbabb1o/rAgKQdh4nKfGCruW6leddsdUXU6kwvDz+Kl JREG1ZteFEWniCUiGG06mizOeJ+1D25dTCZFym/wiYL30AC/0GaXUSYNhdw058RAxbYhfZmsU+wO UimlDJY0eBCmUlYDrjR4sPGo+6+6ClM+40KHJDXgcDHZKbiFKX7Q7NikpKVPS1z4OSQxHZ5n8DPQ EQBgHz17pd0fowDvKakWoIKyhCLIgX33cN26hYp1yuN2lBu3hjICYHAda+VytrAyI4+KHwP3kUao 5B2UTjYIdY12qWPmLJlmSQfPexlLuDN9h8JjDB1pduYyYD60BhYd8w0hPCxyKhoAACAASURBVIwJ xkBAfC4n9jdzhvFXQ9tgxOGU/d3vH9q//uM7Mmp//ZtvFSoTYv/yw6vyisrFGfs3//LnVuR5W8e2 MDere6CcLF+etK8f7jhcUjuQtI2TqPMynHRCclXSQ3trdcG75oT3glIp65nx/91Xz2QsUdhgS/Ty n+iQ5DIe4rbmETWPrH/m9rWVWTueIKMKH9PXYzR+jOPzzZo86Pemx8W2//vPHnlpVu5Q64vNQe3N psBSO3b/8brOyxr97tGa/fFPbtm1lSklV4p4CpD9nq7tCuB0F7wn4TW8LAYMy8diiyEUYZ6aNKrt OrK5604EDCJpLvMBqQw1y0rQRU/T81lyKPyP045BagG7bqWcD6nepgwJ9yptbxjvqELkc+qCy6LD eOABvXtzWS+Kl4ixVYfezI7ORIWANzNFP7euzn1w2NIzktkC9HX2cPqyI0eFglx+j9fEZLy24tXu 4lWpAWxLjxoXJ2OBQueNy3OJggQeAw0ByMp5oUhOWbypctrFKBmTdHDeuKYcQw93iM0ma9fiM1EW go4SXaIHsSiAV6ROWHSO9cWSFtqSuYSvJE66XXWK6Q5gjWI6K9sbm0/ERh5pSBwPb2KxpXf48dur gfbg45n1tubnZ2ynWbI/fPPQpudG7MN3V+y4VyS4k6E/6rrqAl8jSsFYMd16uYKt77Vsc2NTHlXE YBhRAH/4Y8zzxdlWokqQ4qmk2FtBL6pod64uJmRT1gu1gHxX2vRzdP7xORLhBh8vpzhglFVU3Oxo AyM7OD81Yl/dX9M7IuvGdwDAV1cuJO3BsnOXuY0nHm0q98+6E0cLIm6vKwPDhoOB8iYg/s6ZmxyU D7GGeMeHdAqXImlNz6wWeaEvI8x2qCVS5whjgoPAeViLZHf5uziTmvNlu/tgU2x/wnVCZOgteHOs W94nxgps6tnajpcALc3Y8mzVXmxuS0sN20Qx+eTkuG1sblnx/rNXourjLZBe5UGYrCx0Tgp/h3Sz awiZLYadM5L9YpmHQpXws7S9FAPpi+7NcoH9R9yN4m7IiyANqvZXsTwm3kdsnNkz75eXMH/9DmKC YfDAAHkmjRDO22+ZTRpt0KInNuxQ19+Jqv3k7cuBJ5YaQ+5BGEDWAwqNVEtFdLlyUo+o02mT7kMZ WZcBwv+PcmDQz8rK4sWAscF7wwvIHiIAlmN3H5mEjGpDGkrAe5q0nG0eHdsicyZ9oszC9wfsqyAI NXx4N6iYLgXJZMIofkfWC0ORL41YO1+2lhWtZiWbhwqxsmCT00iaFIXh0WG5BekTxc7gpXajsUJZ s52ztY1dmygXxcLXxhwIk/whosATuPtwQ547XCEHzFGCwKsMHY4k9xt05IPFALPyx+rao2ebtrnr XgwbFsYCziAL9cvv1m33sGZzUxNqFEElAHMV4bpP3r0aKPehSiQoGZiG2R0Cra3ANSSpEhUb1J4u g+Pi6eD542FhSIk2+B0eHGtcIWi3pw0bPJYIhGf58PbFPj20+K6cZkRpFSU+JDN6Nj7GBpgX/UB3 mEdpo6k/UEegn/AdhaajZfvm8UvBIwuzwCJQKfY17pBmi4WuOFgf31kWP+s/fvpIfRZIoMDALxIj K/ujiuvZOLX6xDGTjTDxjrjpNwDfM1rbP8aREuH8blMmcnp4qj1raM4u/k2JcWHhxahJ5fvpeeJE OGh1kgaZ4nshK3ICRA1eROa+swc7Y13tzJ1CcNoovkmS46yDUOOsno9MRuROfGcrerFrqBNVp1+V 5HgCJCpvRjA86q8DtLJoJjst22u2bJSi5NAQdxD3PMG5C3rzhJuSYQ78c5oj4G01ilN21Bqx8UrB jjtmzVrNHj1es5Ey4WjB/u5XXyhLtbxywRrHx5bjJUpYsKRd/riF9HDbdnf2rFFv2+U57+cXBllh Fi/h2rI3iahUikqwlItFNVZgIeoZJe6Xhomuq6X4QgZWyZZG3a5cnLNrq2xYKBwcyWvEc7n7YF2b wy8+uOaFzHjvsdt3j6bBJb+X0EAjff/5ZNyQ68F7wni6ZBLYnmfwRFANDVP4FWOK0oPKwXqmEhyI n3hVZOTw4AhN8QLZJPCwwVrj+3U6h9d8Jl17IhG16yPBM5R6vmjckJaVZHL1B+f88ZmVCzMijX73 eFNwCp/FsfjZ+1eUaW01GjY/VbavHmza1eVxm52h3rNj95+9tGebh55gcvZtN9NMPks3GM74fJNF 5Iv6hy+21wHq2Z+dlQg4KwOXDVlTbygsmcw5ycARuo3Roy6x6t7Vd7tBY9IQGodEBl5bJRijhM9F bN/pGVG/sKjXjOF5DdXrkiBeQHu24WbXxeCQDMHTZpIBJqvcRkmTXqZNVtRdj2Qt92bZDUuFooww nK12Pi+yaQRwzzr4PuFw9plkHIvOet/c27NLVy5amXUwWrU7d64KT2rlKvbhOwX7/smm7e7s2tzc jO1s73movbVn9x+1BHSDO+Gd31lZsqlKBPc9uSHWfFBJaNK6anRcdaowz6ExkKSh5AhPgsghbkZ6 JLHY06hDcuC5Ytq7s1qyj+9cVJbwlx9ds0fPX8mziE6Ce02p5LMynZLdCaTr4ET0gnyxMnqB8uHP 0FULOu67XMa44okFNVJqboPqLl4O/ClCPeAgwkHgEjalr+9v2Fffr0u2GqOCJA4YrGdp8xnpGQ/x XZY69ZCFIbe8qa0iKxKPwavma2BeSCvz91vXLshIYwAFJxFp1DqSvOFaS3Oj9r//u8/t1vVl+9/+ 7acqIP+jD66wcZYCKxY3b9giSNj4fuPeqPbMMOnHOM7LND/r56ecefh1mACI0wY1hWEH5Qo0zpyD ctF3A6Z2TzMF72EYncpu4CrtNp1oKW6UiwNoUY4PaYrwTzkGz4VxIaPjIejpbP/B74JVffrVEwHK hIdgSlTMu4flCyXrLcU5EvXU2d3Z/NiVR2m62e7aKFwxSfHk3mjj8wXsjTpz3bod1tsyVuBS+g7q nY2GjU+NwCOwi4sNeTHgLROrS879DkXNTFm8kelC08byruMUQ53Ua+jZ4xcs2DFbmIXlPWfbe4cC 0FnMZJJnJjycj961njmzHLx0KPWIOKjTJHuJoie/XJwZs3sPNu2vfvu9/dnP3kobo0aaSDHSetJW ZL3kvB52sQ6FF8sLy1mv4BQQySbnvdekO8CxfMe9NcI+sCR4YDFbGYmh1BbyBzwLtQ2IrRQqx+dN BAijJ5WncJya3brCaAwhPDWqGNDPgubAxWkK+/3jLWVC4Y9h/GICgHtEFhtPuAXRt9i1v/39Y/uf /uufqn0Z5z4QGbZjRaj+g52G4+BEa4/b+OvPHylEIHxBe/mj926KzEZDiR+XZPpPO84ugfHuJlne UzwK0mnqz57FRXkMm1w4gtlMwKROuUCy6/J68ZxK+YJVcanjRJTa44+PTw3zrgijNrb2FfYQFsRD k4+dOjhGfO5vf/dALZpITYPnAJ6SEQJUJoxKPUTPqEUvS6Mq7yB60R6e4K3guSMbQo86S/g/JxuY xJ9n/z14iJtfIXMLsL1vc7OTwqSOxXYvKqOKnMzoxIQWzD98ek98N2gGbBLW8/KeWxcnbXzWDU4/ z8ulf7gNT5o4hYfkwtw0ZTejdnXFew0ioYxeOl5BVp7IEwuRP+Ydp9VTMJdT9kuZyNAolf9/58ai CqD/w6+/tX/1i1sZTC9my73IO33HFnou+njzfFIxCLwvDFep7D+DbKrQNaEZ+H1GQb7NV/va0Lz3 X0UbwvT4iCoM2KSgKUC1+Pr+uk1uuDggHi4NbJUBLzmWHcm00BPAPcdH3TMjS49SB7iTK5HkVXZF UoLNkw467711wZ6t7drTjT0Vii/OjtqVpUl7uV2z1YsXxPSXTE4pLwAfHFBMd9z3wQOgDqYtA0HW gcJEUpPdVtPmp+dE+b/3zfc2MTFuq1cuScN9qHRLAMLf9DiNCT9s0v+QI3uOGBJk4xUBkzDuqYqH jVx6fVA7uPj0s8gr+pGN+uACHzYensXx9PSJ3wXuO+dhDkCOhLkt3CrYnd9++UTNUcnwwEbO5ynA zQc5sKDdlWl51T8WMauXt8lyznYaTasWi2Lj81NCYRj5530+QqMLkxU7apq9fLUrZQQAdXDDeo8w klIkU1Z69PqK3bi2bBOFpvWaNcv1vFiZxfZqe8s2eqNBxiWOXb+ni2clAwZOS+Y2tIPHmL9z84JC fenQd7putAyvJsX1PBtKoOrCjcc1Snb892rMooJiDE9H3aH/8lffKrt8/TLelxst90YDrio6BpBN lPROAX8MKu9PQHhGugcvCFAcg0kyIiY5kECep11ZGe31Cbv3YE28sFtX5kVpALv8/ulL29odk9Ga nazas7WX9ujJpq1eWrD337poRzU2oY6yd545dyXVWAlBcoJx+OjOpeRdxnvTOIehxhgDvB9ACF+a sdrRkQqeC8WKvb06p+e/93DN/t1ffWV3ri1ZdaRoxf/n7+7axERVHBrGhjQpoCeWdv3lvrIFZMw+ vrNiv/3qmf0P/9X7GlAqspeWfPf95h6Gi1b1VRV+jo1VEy2pMH1/kEuRNVrDjNd5DNeJzwyRGnZ3 N9vAFFC9bZViwcbP6BJ92vWy93iez8dr/hAjfPb3egI2IbjCLGeiR6QOLSJ2LXAEPCskQqBxAIBC hCUb+NN3L2uXZPcEewGf+OS9Ve+kEpoHFDO4VvQQ/HcBz4LcCobSbou7M4aMMTt9p2tV0vsZDCQ7 SQYzwwDbOSO0dnyQzOpoMWe7Ry3Lt+tm5VErBbyHQGiq3LFyr22FETA1LxAfrxasMzWiVHn0DFNP 0Q+HOrzTsUM0cf6FTGDwyOJt83lVEnVbynJ6+YrfvwDxTts+u0dpinP5kC6G1kKoxblho/+v//Of 2F/99jtbXpxUiMb3vaenQxSoS9x7tGGfvHtJRhLOV63RViUKhOi79zfsFx9eTUJIUUyExwUPSB4Z Xq8bZr0vxBZnxqxSumDPNw/s4fMdeTkoOUxPXlbiBbljsKOb5YKtvfpO3pF3hHbiuBvoNNQHM5MR 15jGWDlibSFZIMqTRzKtbkdYWaOxoZCdhPDTjQO7sVqV8uj/8X9/Konk/+W//7n4bBIRpBL85pWF pCV7PGD3Eo/+5T98K2AQ6v1/92fvJpk5PKpLl5f1skD3odRTy7S+vqnvoysF8IkOUaw7+iGL8ayf n4aHZCd9/wdOvxYu+37La+8wXhAfSz/QK3oTY5X9/x9yjeyiZrI8Wd+Vu025C+lq1+JeCh5FejTg y7RdiUGLK9R9EUL+7qun+g50lg9uX0qMB7hWesRwsN/QZMMarz9zY1CmRTmNDsQob0typd31LkbI tRy1vfvLdMUX/LBxLFvH5sZLtn0wYg8fPLFrN1Ztulq2VtuLtBX5BfrCbqtgM/DDWPgCdSGa5pS+ H9wI8VLSZ3B5Yg+pckl3H/fCPfZSF6gQbjn/MGe5UgzPXCGV81E3yPP//INr1mgcW72hmM5++8VT URw4B1LSeCl/+sl1+w+/+sZ+8s5q0gZNhkVZRM+8fnV/3a4sz9l3Txy41xjJayqJQ6eyoIBdusH0 NmnJewmFn+oviIRzoaRyn1LxQO+Axd0NoSTjSTGzJKTzpvnz7ZNtlSO9Iz6eh4SqLQxJEgwXv8f7 hZaCK64EQd6NmFR1Q42w6+lTzwuPq23Hx0fq9rO0MG2fvHtFoSrYHl2OPv3yqd26esHeurJgRZQ6 ncPR79E4AXNWocKz9R0VJsaQz0l2lsTR4+OOjyCeRl9CBnh7Z89evtpW+ID0MHVO+/v7Njc/KwN2 mvLnsIU56F2dxxsZFiolS2nIdw/bXZupFOV2D1ss2WPw+mel6s9zj29qsE67HuQ9lB0ldTI9qh3p wbNX2ng6fT37XLOqjOzvwP1C6uP73z55abfKiwm1YVB1UKFPAIod+0s5VWkWMXhe4X9xnikT2GnZ dr2pNDV/psola0PaBaA/LVTsdW2y3LWZkYL9p7vrtrd7JNG+xblxG5+mAQWZWyR0yM7mJBdT5Vrd lpVyHUxRstNHlntabpPFcYM88s6RCpUJiSFiEjaRYdw7akiji+LckUrQqC+49lWC51GdoAweRc9e p0jkwmcJgza3D0QhIMzkehiRv/jj23b3/kuRRqMR4GBx8052Do7s6wdrInFHlVGkgvCyysTEYW7w 3tWM9eBYXjNcK4Bu31sCNqaaXp8TFy/MqiUYrcnuXF2QYQHTom+gGh6rML0qVY1avSFG/sVF2HY+ brD74U5xvRur83q+SH2MZfdRn8ySLCjSzT2x/P/44+uq5fz062fqCv4Pnz2Q0b16aV7qtRfnR3Vv n1MAHifRaQf8FrIJcTDQrLn3aFPFjFj07GIjDKRlPcf0zKTCjuPasW4W6QtXvqwrZFxeXkiMx5ss 8v6d8XxZw5MLPNwzZEAyf11LWMXpr853/h/iHb3ufn9IqBk5NyMjJYGnseSJan7UJWH9i7xHJi/U 3N25vnSCIMp5eK8f3b6YbA4Sd0gaaKT1ZdHFx0NxafRUtz45X98zpiqqJCOmKOtpNuzgsG0H3Z52 8RZM8iBvM/gONFWVos7ZnZsrmkO7Wzv27YMXZoUt/X5lecEur8wJz4L/VeuWrZkri+XOXVV6Hav0 GlbNOc6SGtZUtjre87ONPbuyMq8ehngDMdxiYyDEc0WRoCiaKSSmUoKCa7yCgpr7Ol8qAvTQSzhH 9E0jxojxePetJRkTJ22618IYYHA+u/fC3r5+QUIF0TBGw+Z66z5ewDRPXuzY+taewk/GBUIwyhM3 V+dUSDxWb6shB7AAxujdmysSKYARvzQ3JrwPJj9wQKvVUDMJDCPrn/pIEhJ4QdQJQ/mgNA2uG28Y z4zGqXhhaIDhzcnJyRS0Qxehwe7Hb3tT2P/rP961tZf0XTT76XtXBPxHZVUwv/dvLen3xUyi41wL C/SfWPeL79a0c0ciIufhIhSFxs8iIEdI6MDluHAu2tdDVONANpZ35X3SQjutARwj+/+DxmEY8Pwm dAgsfL1rNimeiu/gsRnleY4fi9B5nmtkj2HXixnd8K/k5wDp/Ml+jnP+7svHIg+e5/07LsFu655C zBZmExX99xRCwoR3lZa2cGgB07W427MXrw7s2csDL3GBooCWeKVkY+WSPK/Bp8dTWpkqWas7YTtb e3bl0qIMFEqVtVbHiobEDh4WGImHh9mA7xgDk694kbihtBCybIE9HktO+ILKsSQZloa9PBMCdNTs IZOMBLSePZT28He4S3hQkCRnS6PCk6RC4AlUkVFvXFkMWE5qIqn5o6aPjNy7NyB0B8RRm0hZAD2f JJGi34XrenLM76/epBnMtpJkv/zwmgztk7Ute/7yUEZFuCMJhGrJ7j/bVngJjoS3h3eUC+93cX5S 6igHtbqNlLy57DvXl+ybx6+0KeoZVuft52FDZD75q3ZmPTphqLF+du+ZknYkFDBeUXL6Hz5/bL/4 4KrG9+//8NhuXrlgk+Nj9sHti8LIOAfhI01A5mbGZWcWZzpWdNfU8Y3zhlqkyf/4o2t9i2nvgFbW O0ONinZppDcA5ENjUj61uXMojs+NwE3x9xN5MS4u97pjeHbsbCA6HnJXBz+XabBw1vFGxNmBjOSb fO+Nj4w8bvY68Vwu5t9Txpe0tcsYj4XwJdtA1H36NCnQFQeJzcZ/5heL2Z/wrcBoz2JZAxtJ8EL4 LNX3TzcPhN/goRwcNuybhxsC+w/pjIyoXfDaqApw+WiH30eKZkdq49UwazWsOFG2MQiR3YKMFVQG leIkd+aGi58ddagrLVlZ2FUIC5NncZ4StA5xt+TpFITDkP1qN5F9aappA0Raf1any8jbDMkGQkiX RfJxiuMBPwnFgp99gGebMf7drv3688f2yburNsbDBe8JIx7pA9u7R5IYBsthTPBS/tNnD2Ww/u4f 76vuESMxNz1hH9+5oCzc1s6BCKK0jM+76JDliwV7ubUvD/Hn763azCTUD54PZoAptOMFU4pFlFQp OMzDWFBVUCyMSEiAsBgVE5p6fHh7WcYI4+zvN5nEAfsLNBLriuN1KYg2/s2n30tiCKNUO27Y59+u 2a0rC/b7u89FLyHcZEyoDFBFAO2G/s0/d23tN81W9U3E4BaTXUx7vTneRRwMpueTwnddAF+KMlW5 HkG74OYmZTThZXsqdAhl4AzQPb2vfjpCkpPivoKIXX8SMW09ftox9DpvgHudFdad9fvXZkQz/x32 Xc6/tbUjzxZS9sRI0T794qFVRkakTnHr6kIGsxr8rou7ZUNyLbU+SMHT8VmvIfvsEdPCEEAkhEGP ioGuIU3xggqGv/p+w969vqQiYc0lvJYS4ayTX6kqyE0UbXp60QrdljWsZJW8q1u8zljxO3CuVjdn DbysDBmWudqoN50A2e5qI8UIRK4WZ/p/yaqPjdjP3ltV5hVwXtoRgPMDIQ+SxzEbCcMew/b1dxuO 2QQgP9YEYpCBJVA78PsJWdKQvYbE+y9/cdP+6rf3dX8A7Wz2jOe/+efvqNfiy+19KxXHleklO0nD D2GXedfBAl/mirSARwQQwzI/MyqMenOnpgipkPfnnJ2esMUFzoPBdNCc26XX4fdPt21nv6ksJdAD od363QO7fWVeXYS8LjQmCf18TmjtqaaRxM5bKhrvaiwfrdF2bV/46erSlP3lr76xm6uLok6grEIS QhUIYJTQFt5kUWQnYPbz8F+4IB1DuFHqkrw+ynd0Ynh4I9niY7TYHXQM186WZPQZr4A3tVuiU6it U8hDVUerapgQJ2b2QJdc6ejwOxQ6G4QjmrheFgNDvX/JxdrB4cZwKJj/Bp7QaeHtaWHeeQ4tKPhU ba/8T1UNTh5qaZUzu3f3nppOfHxr2SamJuzbx68GZGUGjfLJcDuCrmn4F0ucUgZ83KAc9Pd2XpSQ MKF/QalFoeCaWoENvrpStLHdmn1277m9fxuFkIJ2/IMj12ziFBilmSIYUNuOA7bU67alDYYhcgGQ gNUR0gaWezRWAuXDeZKNtWuif6DNdPnCjFQ98DYwSKh+qn62UJCEDDItXhwfytoCTytk8UUTET8J fhYLLSn6ztlBvRlIvKk5dZywoELhX//hof3pT2/6PYVWZvxO8s0To/bJOyv2h2/XVQ8IrkX4xHtj n6AGUN/pdkKxOFm4tkK7SFjlRiBwYjzAN59v7KnlGRvNk/0dm5ty/FNlNmRzxSEMNIS2K4+gad9q 1zTf+DcF5P/f339jn371wn4qj63qyg+1prheGOTffPlYHhJ9A26sztmz9V37hz88lJf60duX1W7t d18+sbeuLui5kBKCHxaTJE6aLVqRF/NjHMpkhCaa/QvTDRau4vnFgGN9Y4aj0zM7Oqx5eUHXQUd2 ima+aGWyNBYaZzLQva54Ol5AayAVjpUVclYxGix0bYxSlVOunW2vdeJ3QzzQQc7Qacdp342/+6EH Z2DXpeUSXXK96WwmgzBwrUa9LsPV0KSuOqWhQLeaptcPMvZ+V55epwUVHkLYSLzFWgTX0xLwJCvI Apb6QWo4AXTJMsW5QgV+LEXxSeneE9eGrNhdMXtGO6gFyI0bMnSEBd5fEDqBz61ir2WlVsMmqihf FKxOVYKVrFsc0T22MWAZY4XxEi5Fr7yuSdCPewf7IRVPgokManyfhWLMaLunNDZSVs8+vE1XF40s +TQT9vTFtgwbXszG1pFNTVRUHE/JEJYFwTzvVgOTnTFyD2Zjbc2ev9iyg4Nl3QM6Y2oBlu9a7bBh 67tHqve7srpko6NlafUvVUq23yLUyykk5l164+KePr8tT2jRky2BDU+ZVaHocjKEYbD38YyurEyH sXHVX4cJ/HwqgKfAuYi8d03Ph3fGuMCzu7Q4qeypeHuVotRFgZoePHeZILHhcWJKeXUDYo2tLEwL WgKzY6z/5OOr9tk3L+zmlUX7t3/1pd25ekHjgOc/WilKU+5Hb0JxcvGmzVJ/eD1KOAe7Y7ttW6+2 xXGZmZm2SYnpFVX6ctzuyosCVMQgZVVTORxrQJHz7DrIuIgGSZ1nGZXsc8d/D/vM4OcH/539DNkj cIZ4yEhooQYsKuPB1Ost0VDorBue4sR9x3PXG8e2skK2qZJwi25fQU97S2UbgKQilEpZsivxxj/7 2S2dM7aGQicsNk6IO2CU0ZUxCPpk6uidy0kXaWVxJjFu/lbTOrns+KmzcLWk646Njqi28f6Tbfv0 yyf2y4+uy1i5R+PqCP6ae1bK46k1rNw7tkKuZY1cxWr5iryuaKy8ntCN1VgGapGK7kj2/WVrAf1+ 8bbevj5vT9b37a8/vW9/9OFVmxoHdE/1tOqh/RWvjfIXHIL7j/d1v2QPp8cr9ukXT5T6p5EpE5LQ DsPw60//YBeXFuzu11+q0w31dZOTU7r8wf6Bau2q3Y795PoHSXbQQ+Su5j6ZVeYMZWTdYsWWLozY 3FzPZqoejvJkHiK6AaZb0ezUhP3Rh9dkiKfHS+qIzeekHx+cBu5ze78uh6RaLaosJ/YFiImKq8uT 6ie4sjJrE+Mjmj8YKKlRBOIonifzCS24dqvrfR1DxIUhZS79/P1Vz8C2OyKte0Y7Z0/Xtuz7p7s/ jsHK2qKY7va/Z8IKQaVvTl+I5+clgFEgP8FPVlZWNKiSNVG4YTaWkXf5p2XuhulGnW20XmfMTr1S WKQYJgkQhs8y8QAcqZyPnDVwCEKAepAGwSVnB6LWk92bhT3IGB88Zmam9IewLKq+xeciZc7fv/j2 hbwZ2MXcDiU6Tze2bbxaEeZIOhsDRMaY4tbYGITEC2ucLjJoSqFgyqRl4V+/DDUma5wyyQH9PaoV BAKPMnce5lKfdvXijK29PBAPaHx0JAlDaT9FTauY3ZJJyqszdR5CY69luR7cLDY0b3MWGgy5ZlOX LkMBcUu4hVmdrsDRCu/WgWdEGmfsxea+Fr/mJN5+rWalXN4ePN+xKE/uDAAAIABJREFUmakJYTRs pPK+hrwHws/bV6eVoeOACjBRONAm/PjxU5uanrbnz5/byvKylSslGcta7diVF7KNOTIa+/uhyB7v eaqAFhjcNx9gtWyju7fySj07OG7bxCjilhekjbW9e2AjpUmbHKvaq71j9VqEZIumFaqlhKN47xxv rcLJdLjHPc+O5iYVEvQOxLOEAgErHjY9URdzhnvjc7OT8LSyihz9G0SsO1TtreolUXF4af/6T975 pxmsaLHBBLDukBZZPGrpVC4mbNgT3xvihQwus/gtPCIGm0eZGqvaQbtlxakxa7Xr1mr3rFSi264p eyIcpEyWon+KJPiJX/RUYDoeygr1hns95zGEr8tccnVStt6QoytFBbSvd/aOFUoRw0utdawid5hn 4vvsPBSvkj0hpU4WhwPJDlLeGBkBsWExu3zHyU5AZ90rnwNMxTV/72ZR9WIYgg+uL/d1dwGngNtF rSGV/2CY4Dq4/62W38+f/uRGsoHxR9LCoSVUNhscQ0d/M3EmuDeHYgAGG28PAieFzW6w/IjvFVxT zRQk1OaroJyHWd+0Y7hduSKFPYF/D76JqmvJmr2gVEs4Cp+MmZbDyFHP49WAcSz5Jp49tXR4EcfI DFnOxgs5e3rYsMfrcK8W5X3W2GDbHdVLSg9swHDdvBK4jVFYsliwjz7+SH9fvHjJ9mvHtnjlmi3P oFaadqlpZXBG3+g6XtaC4SJEBphWuZAbWw99oXr0bHqkrPt4uVezvVpLLgSy4EAIl5embHKiqhb2 nuWkrAhKxK5YAVEGxz1oN1I+5tHIFFWDeWG/oQSOKxL3xPOKKg6QXDnX9Utzmlcx4RXnZ8wuViuV sC5arqUfug3R0KV4nqxgZpNJG3kC9IKHsFGj315v2nePNu3zr59qx33/1ooaQSYLI8zDZKomyUUH jIPATSL1CnlQ/fYs02+vWLHREe9OzEFtGiFirdkQ03Zvvy7B/4W5cWnNR7kTXkK08q81VmFSB12O H+SpDY5p9KLQAwIQx4DiZnuLb5IIPcnH/vHH12So8KCoTGccs8fsVDGR7M0eLOitnSPVepHsiC2W WDhgDYRwKWcqeHCKK/27qS33v3iNIQamp0wuu93gqPE9imNPjI9WySAlIparRPKppJ60qByLSrWe onwKRhqjx+K5oAYF3h9AJR9+oYQuMzIyEkplfIJ5sTJF2h0r5bpWsoY1rGiN3KjVg4QyI1vrFK3V q1gLlVmAbfr+gXvRyzEYMu5nJN/R71g0bMhfPtq1mblZhavx8Wn7vrwyK+5Xrdu18QBJAFHA3mcO e+ZSNG/HVwfGjndSb7Vt/7hl4yMjgK/2d79/YO/eWFI7um6PNvP7YtizeZDJRBOdeRU12GluAvhe xzsF/hCW6DhevBoqrT9556LmIMhkdCygKaD6GVvWQ3k6brRtad4bWOAFstEe1WrWRKV4Yswx47ar UHAPtJ8/qrfE0SL7yFx+5wbMfMfsHjx9pT9AF3hbpaKrpDLWGGOXIi8qGwkwD/jOBv7hrSX7wzfP 3MMaZrSUlgzTVFiEMlFpvZZPWlMZBS+5WqzY1J2LCkvITHC6g5bHzeRL+JwmZmCXR0pBxLf8ZSLD 4udWC6ain/u048UGXTj207WS69nv7znxDkavFnc+Zw+fv7JKBQAv3ZkHjzgGKW7Rnxk7r2c1yLnC i8Lr4aVu7R4qdCOMwx1nQd4aW+xr95RtOHreg12V8gsWc/wuOxqNOmqNphp+pjfp/6GQmUfDUzjZ Gdu5dmSi1jb3Ja8SW5qntIa+J0/HUft2pAqkhNG05jBLNohFxbFWj++G2kOqJqbGVBtJCzYMOdnC bEMIvtNsNEWbQTVEtkAbguNm0achfS7vSSFM18oKJfmZWStXsmqhZ4gu93ptK5tHDC0r27HB1crb XrdnI7m2rW8f2frGni1evmKTk6M2Wji2ar5nR42GdWjCIaFC5mym/TuJHhj3nZ7VOl2rN5rCchbZ QIM3GNcZxo26uu/vr2vDYJ4g+rcVVEpnp8fUoowyFbhqHUK8bk+hGM/LO8eAkTUvVV3THQoIQxaV MaLHC4UC7hUZQqgcbKS7ezXV8zGX6CzFbfF3PGdoGt41qquNA7hgbsYjAd4358TQgF0yVzA8eJtf fLcuWRo2Tgw4emDcI12veer5mQnRFoA+dveP9Tm8OUi3v/n8kXhl3pVozP79339nRTdMoWgiTkbL SamRKJJfxnqvMjeV1mX0L1YmWSFvs9Wy/mSPuHAbwX3FRZ6gbXWiAX9+w5ANbXAZscQ8pCZmtyfg +OGzbfv6/qZ25vnZUe+q85re6j7BU4XRuPzOcwwjy3I+7odSBzInly7M2NLChN1YXfjRpWYiiTN7 H3goGEpwMMcDBg5ChMmqPLuBs+m/7JAA8MipYLyytZ9nJhSkAxWyhCkVLpTuZDHO+CcLEaQaW3hk 8LC8CsIXXTSa/h0H9+E3xUJkP4mD39HLwkhFHAmjpGaphkfQsVoHQmjJKp26dVsNnb8b53uubdVC yWpdstCU+BRsenHJphaWzLptmynURTwVtUYdm04TSPRM2xilP3mz4926PXuxawvvr9pBs+0Do/mf s3FkqSeLtvCT63Z8XNf9AD4vzl1Q56kcmcbtXdEa2h06FXVVISCuIQ1uR0hAzMsgYNymp0aDFJBZ M6njdI8Gz2tlZtzmJsfkcWL4Xr7as+NjZIS8aQoYFhsHfDmMCXQHNjfmMHMCjxNW/ez0uM0CT9CK r94WCdQZ7V27dnHavnn4UvQUl77O243VxYSiArMfbtbFhSmx7dmg1GDXegLg0eP6P//yczWe4ftF rP6gXBJrm2aYY6cRHH3GnD9ckgdFrN+fnYuG6iwgezC06kTsJ4RY2a96mDKX7DgA00/X9k4oCgw/ nG8yLHM37L5OfLuvPCiQ5UJlP0xewrOzjvMa7GG/ZxIQvjG5s5rtXJP0OzvY4AFfRwJvQ6/nmA4l PafRME59jkBJSSVnUl6WW6t+D2vw+bPXGRupqI8ff+c5VpeLAxnckPkN7zca7hgeitQZ5Ipd7K5g x92SvCVCvkatJm8H0BlRwMVpWr/h3bHwXQWBhcncreDB2IgdtbpW6dSsYR2j5QIgP5F7JHdHkqmH 2j6+CZ2k2RDf7fb1CzZaKNh4Oe8beaPhzR2kq+W5EDZZ7l9NJcCJwf+KLlfMO+b9kBlvt5tWKJat 2/ZCaBb1rWuLwp42tzfVdZxQazbUjFJWQ2kRxgfDTKt5DmgQy4twz3LWbXW0dkgsgCMynrwHvCok ZBhvNsPNrT1VBMyHzYL5ro5LNEnWnOw4NJPLyTvm5+Bxzjvz73zy7uUkiQA84u36TIXnMeL5H//i A/vqu3X704+vWpF0uLN9+3sCHreGGyUnhZ4MW96EIT84MYdN2Ozvsr+HD0K1OK4ovIy5mdBEIHPE 53CuyJi4LkhBI2lC2OgnH/hOxo1/XVbvrGdIvQfnGy0vIiPS/xxneSin/f6s8VXPR7WzegOe24Ak THruk9nR/sHq/5x7kpFsm343tpTP/iz2DohhYjaEjn/S2kNvLVWVZ4zR8SYGMXOXklmDdHdIpsSF EIuRo9eGVgOsazyso07Rnm23bG1jR91f5uanrVvp2v0XW3Z1adJ2/n/m3uvJsSxJ83PoAELryEit K0t2V8uZWc7srCQfaDSjkY/ky/4FfOK/QyPfli8kd4e0Xdvlzkz3TMvq0iKrUusMLYAAApL2+/wc 3AsEIjKyqnqWt606MyOAK849x4/7559/vr+vYmFklinyJzuGx1Ep1NXc4tHajhasF5NnbXGmbAtz k/qMMLQgOR61teLYMhwYT/BUlfIwL5GAUSNYoBekcLLiF8LqLhSL3gYO8imCfC0KtqFy+M8zGaRg 8uqi3Gj27MHzLfXtLId6X0IxkjTAEYD8OncLSemmipjT3dULSs50lSiAeU5z4TPzk7a6BMzgdZ/U FeLV4bXDL8OYXlx1zyeSucHaYuNlNdsdL9vb11bsszsv9PzQPFyPzN9hrd7oN3mBY6cO25ZREufD r57az9+7ovd289KC3Xm4bvmnT+F7eMjQ351hJocwDsArmdhuRUllD+srnbTI+9HCK2rqTmPw4Oes FskM9uzS2RnLq9No/w5HegTQH5D4ULDQC5M+7Mb9z41gcp+Gd3Uityp4kccZo9c18sd9XhOqA5Df 6EvHxMwiYTM77DCA7+7Jqx3Po9F/OlwOYnD9sUg/uRsQB9ZThdkp7k7yLCE/GIyQ/3j4nP69JAUe PNosvfc6SqOrTlEhj0tAS3M8Dxcoa9le2yrWtEY3Z7vVrn15+6EwvzffOC9A/Y2lvGW6U31Fi5/c Omsffv3MfvnRA7G1mfOI7oGLgunFY3evbp/deWY7tUMtNvW/TMkvR68PI4ZeOeRZ5zeZDE26K04h X7BmsxE4SUmGXf9GDPCwoQJptY4DokEnvtPWf2TlyNa+e+OcPDI4YLTtw5gwF2Ym+dP7LeJ9IdQH PuXaWM6rgtxKzRbYKqD9s+2aQHf1BjhsiSgKQL+168kteVwh6ul22koCUI+IMYeCgkd1ZaykMXn3 +op9eueFKltwIkSDqdbVj7DWcAnui+fmbHGG33kigMy/NkTC4jnCzCylOauv7RmdjpWdtPUenOxJ 6PRaXKWQX8T19uarr+nNxV1Oey0ZofAcQcIifbpXca3S4d/RywwaMF42jUXx8tQONFUUjFsfRde+ y3gzIaR8sLZnL7P7IvihY8ZkpMCZxTs/O67LYsy0mGRo4rAkRoKD8Mk9ztNQUqJ3hec0aJz9vIFT pQapTakW6DMKpTx1FY1ErJ9LwHn+i+2v/P6iSigvEC9hY2tPi9VCQ1qkW2BdY7TifQrTCqz6XKdp Bzs79tb5Kbu0OmOlTK2vQJtJGXVu8dLKjBMusjn77eePpByA7C/XiDgkoRU0EPTvHz7dsolxlwqn Ls+7W5M961mn2/aGoJPO6uagLMXHO6/QTi2zNC4Y2VwojYneY0bhK+/41jWy764v1m11rdHq2rMN PJ68vKBSwXtrXlidsxsXFuTFvFjfVWZvvDwmPS0aO3zzYF2sdEJEipl5aO4dnJpweJMkR7NtN1Zn bbpSEv0GGgRzlrCZ+j9uDQ+02aKv4L5oJ+COl8/NqbSGD1CAjTrEezdWrd6kK3rHGs2OsC36Md66 ippI0PEi2xlkrCL1IRa9YyCPzRKetHhO81mfZHTJdWKnzwJ3iQequU86R7+SPnQTeW1v4OihxRp7 67HQYhPWuDjDCQg94YCkzzc6VPM7VEpeO/5guhov9enLPU8JB8na+HPO9wM13jy+MPo02BaGiUUz /BmyLQCaSN3uHRx6CD1d0U5LRolIFb4c3/PmtzwHP8vJ6MWmnCNGOuVFJUYmHQ6nDxYHE5QQBS5V vE08Q++gnVfWSp15KDGpFF12WP0EHIcCr2Tnjtfm3zQoRU1AHtDKXP9+pWzZr0VN+EosAnZ18Cnw PY8oouEOzyKD6POAmrkL6iBOqDij8qSna7xL0vdlcae4HcDppfkpUR5qjaYSLS83qjJsZKwJLTln uey0Gtdc71kuJAx818z1uWp4WqpBlAEPKhBS7OxKoZPzxWdk8TfbhGtNjdedxxvCqzBanPfF9oHN T41JVbg8FgxA0ORC9RSBR1Q98bgiTDBVBoMKRdwHTXu2VZUUEZnCetMVSUluMe8R8iPMZIwYB7TX wbmo+eW911T6s6PNAX5WCfgiY7a5XdUcIxlFuN9qNoMGvr8viMnXLiwHOMW9TTzS/PfvWcUJbUo3 b2/v6k8uWxorqWJ8amrydAB2X0fJxfaTM/e+s0GV4QqibQLbu67QSHYLwuZX99fsh7fOyb1HnoOf jboWjGDOFeuluGFaGcWDhYKhoGAWz5DP8jGwBTgvr3vfxz3zcQegMV1MAN4henJQLwjQzHORKfQs qvOhWCh3Hm3JO0iHkQnWlOLkpcpYhrEtDI0roHbkmQDOAtw6sxvuTtu295N26PfXdrXLYwTgd8XM spp94kntVEWcJSzDMJDqZ9HBO6K4V1yxEBI6Huu8IDYewFxq2zDaMO/BUWYnx6KcQD+LKC+srwrv WUsMEVmv2BIMZU68DLwXZFU8++weIZ4H/8FFIlT93acP7KPbT6SLzoZAowVKYKhb7AU6imgc0Cta LS1gSMuE8c6lc7lokil4lNV6W6ES98m84qg3u5q31FyyZ1Ji9c3Dl/JOIGgy96g6AM9dlrMQEy3g R4cK+WToOz3LqK9DT++OjP/Z2YptVxv26y+eSTNuYaqiTZxQGqoD7xCJIIihGCOUX3l/0CTgPlYb lCnt6n3Cfs/nmwbMB1t/cbaibCchsjxKeH+SZ4a/llN4+/6bF0M22Ccd5Fn3sCIJb1RjwmMWxais TvK7JBwiFKpV6/KsZmbmlI49aaGNChWT1qRBbDcVIn7XI8qjdDs9e/xyR5McfI5i3Xr9UC8eWgIi /8MHYdhHt5/aueXpfpMCXl7aYHk9YEdeg3+nK/1tFhjxfvqZRxmt16F5jDo8FPLrUGsYPUDCSIiC cFwwTukD/lX63MN/JmF98vf0wWSjwJcdmTCE63pRvC8U8YDyZIxcRx5nCC8JgUDC0TgOTH48lMPm nl41oQue0fjZooiyH99+Ko9kcaZiG1v7yoBxHQ+13ODRhAM+2sZWza5eXLSfvr3sbbyiTpuUCGK2 Oq1ykZCHHXMiUujY9QvztrVzYB989VTGb2UeY+aDkcY1+c77b5yVF7mxcyCtL7AjeEhwsdgk5ClS X6f78MuppVo2o+eMJFvxm5od8Z9uXV6WGihGjcwwHWcIz+DaIcbHPCNR8Gx9z56hO7U8a1PjXrBN FtFZ6l15ZcAFeITw3Lh/ro3Xit4XONPEeFF8serZect3uzZTcqY8XireE+/YM4gL2oiSKgbz0rGe b46SmKYFGM0rOk15seiqsWnjzPRK/g6cmtJV6CvdM7rxwPqQ/HSYE7FXnxeiHidXfHJYclxWi0Ou YbVq4+Pj1kAlIKiLnnS+448g+B+lTORCDkqpnC5cHQT/+SuD/d4b51S9Ti+1/VpdZSG4udTEDRAm wyXU1y2fMxp5cIjcGBb7wPVSf2fiUSWPd8Pu55P123lWp3luzg03BsJq5L3xUSYLE25UCzAV0Kqt e8CbwsHiAvRNh6kKp2JYGBp4/O7Th/b29VWpSOIRDAL1yZg7YdRxE8pDeqXoPyc0CCY8eAjcnK29 msJbMBM8LbwF2NTb+4DXtIyacJmdTkdeFXe+MDNhs5P78rTwvgjn/B6S29K9pzK8ozaN2LQUj5vw 6cnGnkpxkKOm/VRUYo3hpbre5HPy0lHnpQYTfId7w2vD08J4NFtO09nZP1CWj3HAqCXhtU84sKbr F+fl0WMAPSFWsLMryLCUbXNrr1+3idIvdXxgTJRtnVuZsqW5cc1xIIlava3CcoqYVxZKktRRguaw LW9NnXMmxnTl5emKNYL6w6X5KatQuyqqRFeZPGVGgzcacWs2csjjGB4IrihBeDa3Yy1JSrtBpy7U y9O8kYWUWTst29s/kJKrwvOQfNBcIVvcVbvxiBc5wBldxjTJL53pe9UiSeMxhWJexbYzM8Sq3OzJ 4dyrzj1wnZTX9TrH0XMn/wZHQaYVTIgsC7pMgI0YMXZmwpdymRDKuU+A2PFg4UWpjIHrDBE6CdFY UOyChJJRtO270EKOO3DdMVaPX9AA08eKhYvB4nejhCvAivgOz5oeGwwsBsuNnHvkkaUfN4FOUDOF GHjSIQXNvbqeHRE3layES/WvGPBBTfAcxmdcQwkrmvMTmpC5er62K++FTUChm/XswbMtMc5vXV2W sYAECxCehPaA1kH6YkQla9R6jwRU4U5B/vf6xQUtxq+fbNq1c/MyWEmGOLVeQqIAkcJPv36uMIj5 hXLow9qmxhnjhVGFFU6tnDon79d1Pow1XonXBXIvvtHMTo3Z+TOu0uscPF/DOB5sQniuGATqTWkJ 9vDppt2CeJrLK7wmg0dpDxgn75OxIdSVsTw7Z9ORTIw0czFv8xNl++LJpsKxm6uA6TFLOjjP8dDw qverdRXAAwFMlPMKd9WJR7hlkJSWHt6E5r96o4bWYCjB0qSW3g9aG4gOBs8XHG0Aw5JyYl+U//gs WDpEOGnBIIextDQfWvs4XlAqjb0ym3hqDEpfZNJ5u6rvckRuT9TCGisV1YKJCUBI8fvPHmrCw8RF sAwmMQeuO4vUd2mzi2fmXJCul9JDF2bj9xhDx+idwCD2EMXDxTAkvoS+u+Ol0IOMYXpNsgCevoCD hNSMl+hwxGwpC3+ifNinLETpZMJItLnT2FbEtKIq5fDPjzsUrr3Y1rnAdsDa0sx3zyTGdxPpAZ7d RKYFLh7wEaERYD7cHgwqmmBUFGCcN/b2FV7BDSLE8S4yNXli8V77m0uffuJGKnK+/KpO5xH4Hdp6 oYz54Nm2VA4IuVynKxjyIKcSM5OM3zvXV+yDL56Il8dm+HJj1x4+33HqSy6jebCzV5MSL94LSQjm GIYlnmOsVLQbl5fVINXD2GSe8Z4xnISBaI1xfTZVPJVWK7T/6mHwDvVUGBPulX6kzD+IuUAhhNQx iYQBAuNqHTatXT+0+/t1mx8v2/ykN9Fgc4j3xbXoY4qaKON49fyiMqiE0btglZms3jFOC9gX3lOU kQZvdDytI+8OY4uhA7KgExflfBjlvf0aJXuhk0nYmYZxilHHaT0BXhyFqZoYYVdOq4p+2/OmP+8t NqVFEsRkX30MG1oGbXf/UN11dV55EwFoz2Ts3JlZhYb3n2wIC+AlY8hwiclwgXcxocGmpKAaUvUc DhDX5E1F5jsjwaJDOxx+C4aQn5FR9a8F4mS/3xs1lp5xZTJHIbXjDmcnuyZ36qnjqGnn2qvWNUlo Ix+pFdE4Ea7gOSrFnYv0A5IPjaCV5XIy6fFMk0GTMR7sdZk+uH/CRsLjO4/W7f1b50dkSpPwP/5d LO+s2d1Ha64O0XKvgmvLez0zo5Axl616VpBESiYjkBxFDIwM9XJ81zWikuYRysR1XAMsm00IrQpn VGFBkwwAcDDIppWlhkrr96q8GQD4dMZRHb7CRsjPbl5ctDt4KjmysBXNKfoBvtio2vZuQ4W+Kq8J mFnclP0/56C4V5u6LxU9dzUPV+Ym7PHLPdseH5MXxu9FrSgSPud0LSmXhmfnWXkmKBB8n0x2NNFA IxQ/k+igWzeZw2fr++qYNTdR0jzG4DCnuQbLG9yKUBQKTSIBbXrHtAKERBpDQ8Z8batmszNTMkzb O/tmmby8O+71zatL9umdl+KEsbb5Dp5XXh5Vf6eJpRPfvhPxyKM/Z0edL93t5dsdqgFUOJLQJ+KF RyUHhkFumAbOzE3wMADdd26cHRABpHTh/MqedgnUIcbLBWVNAOZZ4HTgBcSG3Ora1ngAbb10YSrh upIqCYsPUJbdLTK53UAMGiNJ+LTJNh7a9n5dnyflftxBl2bOPaokJx6buwX75PYz3R9hihZuaN4J u9lli5EHcQVSjpcbLm9DqJKM4fEbTfSM+thZ/634wbPi+WBIMKKMRfIC4/wbfH88O/gVmBQhDedo iRzbsmKpLJD97pNNfZZzg6FFGgEa7RhcaAd4NTSSiPcZw8+oqZV+NhY34dvmLmBzU54HXWPogs2m 9fHtZ9KjxwDFw9PxoWSl49rrtIlfnh23R8+27OaVpcB3y6geFoMYS6ViiEfywpMIvkFksYAh87y7 iwa79zSUwaU+d7xsqwtdbUaEbRhdNddRJUTWMh1XTJXIQJuCfMessjmnleBtc25CUrKyGGUaKo9V xpT1azVa9mJ7X7WKP7q5qto/QliSNKiWIsinZELgzWFkhNXW23ZmGe6aU064F2gurCPm0/aed4AG KtmvHtjkRDmURZXUwBleHV4ldI+8pGmT/Jv9MY6E4/Qa33lNPIuT1w4cA6Cg1+n/7ErdV2QkPWMW 9X7ioTZG5+f7izUeeESry9OSz2HiYYjYYYrBQEjruwc/hR03q9+zuOiknD6Y9ExIrk+W8TQHO1oE qGPB96iDqnokbk/6DIaYSRI9KTJDLCAmnOrUAl6CcXDJZRdWe/x8x6VRgpRLLDuKmmNMRjxGx7YS HJTxB7OicUNavE1yO/3uMoOeYAwr0++fSc49H+56Ol4bUKjbY5wxLOAwhDeD5WMK7HQtsmN4Xry3 ARz0GB5frBjA2F1YnVXaHimfGCbzrtd3akrtO56VNJiQd0yICU0hT3juyQLA9lLBx0s0CsntuEwL 38Frf7Hl1I34nH4QHvXktdQbZXkzSmxwvVzXZmcqNp+N/DJ1u+0PKWM3N+1S1xgsqAY7VaICFCZ6 6qbTarZtfXtfmVYMPPdab3VdRTSfs/HJsj2nq1ATY0S2My88kWiEsBbpGMJYxhZPH4OlhrNFJJ+j tnxWWvKL81P6rhd6uwY+NZ1UBEyM5ZTt/MWHD1Vl0O5kbKeakkj2rIx970d/93oFbeLId77F7wiX cC+ZuICVLEj1bHPJvH7IO8xGH66r45C3NeJShE+cH3LelQuLom08W9+RO4zHRWBN1mXi2ZY+K62g EWFwDL/IGr7OwYIjPX3SgTchvauTjoxJtA2mMYJ47JCENItzk31VhA+/fNL3jhgXMIj73S2lvn14 PEua5qHxrBhpsnrpg9vBs6EYl4kv4mSODGZL+M+gVlk6FLRX9GD07CxeAaIUXJ+Nw0UcY/IoYGDB wHppSPC0w8/7WvWBbe3fSbKHsLZpn8WHK4FYy3Pweby+j755roVJOYp0rToA9OCWWau1i5bt5W2+ hIxxTxuJqzskHn/E1FwYr6uO0+/cOKfSuD6ptedF9WBGF8/M2L0nWxKxJJSMvyPTlq4USHPn0rQD 6CZb+w1ZaDKQ2w2HQPgMzxFJtRA8t/caUm+ZEKdvxnJlQHFGPDNHAAAgAElEQVTXmK8QIdSdpsHm 9osP7lm1fqhnJIxlHhD+Us3JpTE6OBZ49owhkQ3YHZsccMosGdgX3ptgdrJoS3MV9+7kDQ4RR9OA epyk30tYyIvpfT+e1fA9pg8yRuzgkNUAV8GPZuB/sJOmJGwGnmsoQTSY7Tl6EAI449qPXD4rMTIy Y6SQcZd5M3/44rEIhywgwiovTHYXnYUuSeROTzwYFq1rgvvtyOCEiv+0sWPH4toqc2m0jhmf0Aa8 44JokQ8XDY8MmVLY6D95i3SMhcBZag4LWRkhDiYtha6Mo38XedyFVOjmnhpjhf54myxkr2e/+fSh lwBxjkJei5gnI0Hx8PmWrok3xvnxhPFWBx9lVFlXxMocB4xhUvw5k/6w49geWk5sVjC5o/Ehha+Q j25JeJEyGImahJ8n5PiCcH6cBhIeCqA83yeDqnRPDPGzWYHNAqh7GdtpZW2rjbICPkPW9pGxaYEH 1m0q6+Me55onNhKjCh8Qrwbtd4D5mUtLI4x3T5shdA8SQpMV5585Fyxoi8Wgpo8LJhsxPC7CcMJb 1gf4balYFD0CfIzCaigsbDyPXuzqOSGm7tRb1qlm1HRiN5QfnYW4u99Qez9C1FtXluQ0YJDgZwGR gDKjv7ZTRUF2TeN0+dyCxhHv/dLqvLwywj6A+mq1ofE8qJdUSgSrnndGh+n8t2Oyn/7oG4C44Z1w vDatYYCs6t9l1yO8wwuCxIlrvV8uuggdvZ0GuEDH8c68XpGQLa20wEHIibHBWxi+dybRn//4mvSD WJhgEVSYAxy+3HCpFoU/4Tt4KmAIGFQH2d0bjBI6GCu8HQkAwrspIpDmaWAA0ShPawHE5xy8eGER bRpWJpK68oSCOiTGDnwCtz22XWPcGLN0MTM0As4V9bSY7Nu7PWX1wOnS/LFmnQnu94BBIzxgrNF5 Z1ISUqnD8NykfN1iPh+EAUPofkShdDS3jxCDrGC6BpPJTPq7tkcLrXGVm5DQ4MDYcg08AAy+1FxL BRX+ossmXhKlQy1vx4WXocLxOMdSooO6NkJ2+/WA1/jywejeuLhk+422detZW2uPqch6eDU9OyxY vtS28ZC0SFrZDc7JqOZK4TVa+KT8h8eBg1AQ0iy4HThqLHj3IzaGjUdCPWDOwavqhX/D+4phJVgp nLD9KkKDbVFO2GimJoq2fm/N1rYO7MK5OTszXfa7zmYFkQCF0HyDd42HpgqFOl2ot4Xvobv/cqum +4hZa0itGNuYaJJT0UbRYVaGCyySwmgSK9SLkhnO/zGNVfpwAkLSJeXI71/j+id5WfFgMdIhF8OC l4DePItsZro00BvxuPOTSUoD5cMHkzd19yEcdQlfBM5wjz+789y+aq2JU/LJ7SfyuJTBCsB6zPQx 0cTiPabGEilbFtvyPE0CxrwOMcXSl4ehbr0esrLbuj6Wl7bwvC6V7J1QWPCAq4R/hBccAq8ltZvs /izqeH7/08NEjCVeGaFkbKKgan/pnvfs3etnxEfDu/n7jx6oIBdDj7Hl84TrsLYphq6UijY3Uwlh omfG0hjXgLE6OFQ5EwYRwxQXoaRkujTlpDfmrM1Mjdn6ZlULhvfEnGPHhx3PuyIhAtOaekAPSbzT MdfmGngarmnuBFoWMRk2NkCkmsHHCDujp4mXOT9dtucHWSvWi9ZLvUfucDLf9nA0qRHoc9lclcFp Ia5sQdjWteJYSaU/EDwvrMz0s7CdDi23wE1JlFDMnrdaoyZMCMrJYMJicPz4ES3nmaMYcPhXGHCX SHb6DfMMJj/3tTBTUZjGHBGRuNmxMjhYuSj8jQ2M7DWqphislc60NuFer6X3zx2QJKrWevZ0fUdJ CaRmKmPU6Dq3zSkOqKdEkrKXzJFVfPNK1v7T7+4L8yL8hdv1vbf5Gn30y+1Pdbyud3XSEbklvFBS 0LUG9XNjCu3662LEqeCy4AGc9jrsRr/9hK62+3pc9OaZVP/oh1cUbnF9VakftsSvQS6DUBEPKNEp H30Qv5cOcqr7O9q6LFQUNNuajKTX0wflFXho4AXsfhhVvLZKqRy6uvjnjjOW6Q2CCXbz8lJohlHX eZnIPAs7MZPb6VIxpOrZ7PS4ym4wAoDdfIeM1NLqrDyDjUbNDg5bCh1RtcDwwZty7NE7HjOgaMvD 3Ibbd3l1boDwKuxJzQf932BtSFDHdA/JAww6Xub05Jju98nLPeEzPBNGVN2SpRC7p442DCubQyQG 44kVQh0iBE+M38yUe3zEyo9f7FlrfsYOob2U3JCI8Jrp2VKhaXnrGhUoRaMbs4edsftjoMdatZ21 WjcvEBrjvXOYsXq7bqsLU0HvrCuDQGE1cwePkHnHmEGd4RkiMdb5TemMuPPkeB4SIkADSM/wztL9 ISlVWlmc1ZxtNw+1NqJy7m71UJsx40Xdn4ynurrnrZPNykhxfbxbbfbKXJas3erI+Mbndmik05dD jwqxUfDQf+a1rdQWskHjBTJ/B0D3P6qXdcqF/20ws1fddyGGiQdNWfq1zZrt7TdUrClFxBHfAZh9 nQNWNbs+u7oKelseSvHvi2fn7NzKnIiSZHfQrWLiDbdrOu7w0MvJp7ng9g9/D5rDKM+EZ4fdHD0n V2lgIo3J04sKF4DUTng9OeEBwOwkQxpD1OzrB+sh9T5o/d0hIDxE97utxUP6HuLi07UdGVhCS84J nsLOLpA6KDRE7C6758aPMQOcv7Q6O8jOpziYZhkHLRUHozzgCQcHm6N0TfSqub4IjLms7R40BArj ucbwmmQKUAA6VxhjPDY8QDYDYW/ZrPAyrsMzSDYoV7DczIJV2z07rB5Yo+6eeTRYVmipEegY/La8 y88wSijgTNPml6Yk7YLdX6/aZj2UPsFabxTswmRGqX3ur03JUe1QzS/wDDHyYKfnz+RsfXNPfQah M0TvTVpV3a5CYIzU9IQ3YpEXCw5GR5pAEvUEQFbZwLjZUMMH1YLSLniEqInGjDZZT8JKdMAmkWsK ah8c8/MTtrQw5ZSF3QNb265qs91T27q9fmSBh82mSfEzhtOVSj35sr29Z9883pRRhNuFl4d3ewR0 jxPz+z0CPTVgWUdKV76loRp1nZMOCkNRTWAXpS4NqZBspiZwNqbzv+3BhHjjylKq8UFPYejXD9fl XYFjQUAlK8dkhywJZoQrjfY8nkgEldnp3VPxc7HDROyBUIWDl+7yJj6WhIJ8+mibesdpohop3hz3 cFA9sL3dPSloVCplnS+WgAx8+5iNjJ9jqLgfdlNS+kH6IPkMInOFfB9H4zt4OOWxRbv7ZEMhFoYP +kikL3CvhBF4orE3owx/gzKWCeFHHHGc+HN7t6bQd3Zm0o1IbFQQhjDikNrtQyZZ4LuwtbaTgQso e1IsvSuM5Z3rq3pv/AxQPVILuB6hCe8WQ4mB2OhVbLpVtmKbWtGW1et1UR/iTTxumOVq6Nw3B+Y6 3uPKZF7nv/NiXwXS8+MFW5kpWDFfsLF8xXLtujWruy4HbujwV7SAFQbH5roYoPlJGVqwwjg/vDWa u52Fds7Gy90Qxg4mnQQthK5FZCmd3pGR+CHzeXN3Tx4j7yrpjeDlXU9f7Nn51YJNVcbU1AJvDVpo hyYy4/SxLKtQmuQAY0ctJBAIHjQ2DkyzkPeWXrlcvT/vXzxfsxfr+5qvM5WCre+CG45bntbeKg/I uu768JL9Xgmkx2R/7Dte83U/y45K+hTDsbnD4mjLzVU6PHg9hB+EMqPOzS4xHMaxk1HjBieHRbG2 vS9DSF/BL+68sHvoBc1PamcnrCGziOsMwMkOSiaEhUWcH115wHF2eTJ3GDe8NUo3OD8vj51z6OG0 wJikuP7lYkGCaZxndioxZNSyIfVbrx3YDJ1eKnTqRfJjfCADmBxJaczwgefa6We6Bjc78BiytmmD xcEuf+PCoj1d9351eHvDzPkoQVzp64OjK7YjvIkxjIC3lFZRAynkFa4Q6ifnccKt+vbJO3LsaHuv JnY55yIpgAfBgXHkftQibQZ5YMpvNs029pXtSsYGHAzROgDqQ9vs5axZHJNHMlYu6b/0ASkU2WNC vcPGYV93ixq7/WpWGbSN9S27cu2iXZkv2OqYKxqIL9Uds95EWRLGEzmXfY7hefSOuR9CRN5FrDBw nAxWvl+LDfQovSZ0gYzYUfD25Kl7VkAJEtQZMNJLc1N+X+qReSjWOx7RHEXQbEyoLIiRn1W4p8qA btfOrsxok2D+4ikzlsAKKF9IuTiTlScGHSLWu05MTtg7s5MK2z/8/KFl8Pbouxj5OiQs3DYHAp26 4BztnfZdjjRb4Pszgq9/cG0mH/VUS3NtAbm42vfBeuB/TJXt0bNtYR3DbcZ4WRifYYOFESEjgsGK AC0Gi2uxWKbGvGCa0In/pidmBMxDg2Dn+ubhRmD91oWdkWmRltZBQx1DcN/xsrhXdiO8qyNcS4H/ HaWLCdtwt8GLDoK0dTwAzeESQXYtlwkN3UVn8owCa4cNlfO8vFlJLCs6zhsDjxpWQNDuncvahZVZ eY8D50bn+4CejXWNpbKv5aIyluCC7kW07dwsOkqewqdkg4JbxhyvD68n6lSli9P7rekg3gbCJV4r XpvKpmiisDCltfr45baKkjGmgNAi2QYqhUKuXk80lt1a08ZnEeObtLakao4e6p1YHrOpStEKsM/D +6jW6gpR6SY1PTNpB7UDe9Ds2cFs2YrFonUzyKoAQmes2O7Z1XLdCpmoVT9Yr6nmvwEr9lI7L43T O1ThcaxgiQqmA2+5v+79xK4HFvsyxuas/kkP4cHwMPRnFsfF4+JATTZGG2riS3v6dsfKZa+BRLb5 4BFSyxM2M+myOlwgJoUWbVwGC+b8y8O2Pd86kBxzeWLcpioFKxezli+r0WLsO5jk8LCssUkqhut1 zUs67EsKZE+mEowKFf9Yhwun0Qa9JHkYMBRCRFKn7Cj8O1ILho/hRXYkZBrKMbBoiP9Z3OkDw4Lh IY1L1f765r4MEsaPsJUwgPtjR4oHGwjidZRYMKGkrCkMyrEa/s118A7wwrg3eEmDoWJGvJlmo277 TTqplPpgPud0ueJIZPRmp3wnkj65lnNz0EBPz41YmZq6UibjRN4BKegkkzVcExmLac2S7GZ6YWK8 UBvAsMR7RjBvvzpm1Yan5Nn9+ZUbIQqDYxdyD8MI/wkDd6p1KRtMT07IiGHo+CzeHd4v78ATKB2F pN7sg8XIM7WUwTuzMG2FyQmrqjXryUchAPClrDP7u2M5q89O2kZr1nbrHdva2LbdQ7PqBqGjY6Ec pTEyqRO2VSjYUiHRN0sItkmZlGc73btMdMuGOYhJBUHkgCkcDJnCWPniVQROjI3kYM5L2AwJHBEA 1gubvbhtJEoCVcOJ4nTfylmVTKSY7y2VfTEfSCSgqEFfQi+I7khm2nHVnq5BCH/t4pL01AiB8czV ZpBblJzYUHcXWsQ7a/f0hms0/pVwWV5ljI7j35zmu6/9Hbmv/lcmLKRIGSykYINaIiDvsNFKE/nS BjiC1rEmLf6el5BuMT50o/qDhbu6PKOwkXtAg5secXhddMDF+8HwOZ7lXCyME5/lcME3b6aJhzc8 nunXgiFrN5u2v9uSG18oJGXjzsMKLne/I46PE1k9DGEl7yVCw+PtkUViXeJCIX0OqAq3BoPM5MaL hDoyLE2BIcQw4EXJqLY7wVPVVWRswM0gBnsjFF9Yqq+cLUkBk2ww7yISZkm20B1KYWbO1QnwxqB3 AKoDJEdBvTgXyLZSL/rl/TV9h9KSWFROiMf1wdkY95eFceu0Xj03m72seiFWcl2byLXFegfvKWfz VskWrVxaEpBdqx4odBTpFW2pWt0aB3WrlTJ2eTZnixMFG897I9gw+uEdwCXz3pousezwRiSSppdC HM94jUiQjfWbsT6Rn2PsMTI8L5wzhBQp/8KzAk4hlMa4xCJ510XzQ2VcvY6tbdctX4IqMW6377yQ sgOeGPfF93kfahlGt/LZcW3m4IgSF9jck+eFsetruieTLrHKdK0VeCzGLp1pXWwOwt0orGv4GDQW idF6HSLo6HOdfJwmaXAcTsaASmIDDWlpVW8IV4p8I47orQx8fwjjSQyaG6NXlT3F+2G3wXtgIRDX 436vb+2razSAKwuRjEv0uljYTBRq3DjACcDSBs/txjSmujl3pUiX4q7Nzk7azCxp81eXTYEh4fGg AhE1vwGe4xG9peHwj2QHlAbCXcILjDfNFLhvxpXJnoYe5HnJuxqX0eK+MSBcE2MHn059BOV9uVGF z1MaQ+/K/4uYm/CwhncOwiPC+GPwMezwwda3aurOQtIiVhuoHVbbsSxS/3i8APTiPrGRw+midnCK xqJZq2RaVsvmRpJF0wcs+LVWUU1ZwaPGs20Znvl8y8ZzXau08tbsZq1bKlqnV7J2L2PVTs4ODhq2 t7tve02zz9daNrl1aHNjWTu/OGGThQ6K58kaDi88KTkb5GUNvuc+r8DL5sK67qu3BO5XnJ94T7TL g9rReLKhTCrGn7GFNMrnqX0kseI0mZANzZqtrW/bwryXLtWaLfv07gvVKkIIJdvM54l0yFJi7nhn UCl4tyr1mZ3Q5pN/lWfC/9NqW6zY6HG13XCVUt2Uh/GLI8Yg2KvTAurfd1iId8DEY+GyG6sW7Jhu 0DwbOtzsqGQqaOQg6YwVF8xP81vSB17Pw+fbMnTsRmAcGBQW53il0CebRr0sMk0IwY16XhbLgrKH FamY3nm8LryLZ2BDZNfzItq2VcbK/QWvLj14J1uobPr1vIbPS3kwxkol50mzl0LJ0unG0Gu/Dm13 r5Fk30INKs+kQuBl+soNHuzI7OKMDzQCwk6KhxkbPBXGl7ILDCGf4d+ROwaVAYE+ah0xWqTyBcTn PFlBhb8wuCGvLnoU/Nu5XM76x1Ng3J20CLcqJxIpuzuhjQwVEiyTZTu37GE8YSYHYWR0LJFjhhvE dxetafSXeN4siUel8qrUmMaEf/yPUh0MUSmbt3K7a5Vs2ybyXTtbpD0rhSxefN7smq23SrYwnbex 2SmFRc93Dm2jhlxyx17W9uziypRl6jWrZNq2MD0mVrk0uQLwnsytYSwyGjJvXBpxRq3P1O+9PtEB dMYmk/HwEEii1mgJf+VzkRiMHhcb1/SkmxaB+JmsLU5XbGNz3z36XNaunJ+TKsNmDSHJsl1YnhnA G/HAmdts4ITd/JtwNB91qoZ5Ukc8nBGGC4xrlLf1/8cD5UUoBJJxCQJrrwodWRiwhwm7CM3I5LG7 4ykgFMehSnyyWGpmEXg/xYyq0L20hr5vxPbOdYrhlfhDJDWGQqvhA6MEQ57FLYZ5Pid3+Vkox8AA uV56qiJ/pqLFGB8JY8Zz8914udjgg8X+qnuIB8+EIZYOeaRAhK92ulnX8W53FWYNe1kYsv495hz/ YswAvQG1IWtOlEsK0xh3DBH3zY6NJ8YOjnfk5MiiwkFCzbuP26q7o41U+nqjvGy15BKh08fp7qN1 6Y07qJwLnlnPDg489AMLo8sQ4aLKWfBQwyu8cm5BVBTGj6U5lj20rVrD1g+YAznL5gqKSuBvNQ7r anjKNQChWbD8t9doWHNi1nYsb+Odjs2Pt6wo2hm0eCoV2lYsdL3eM+BeM/mcvZiZsGf7XdtY27S9 x1WbKJitFHtWr/ucmB6HOoIEUPrpo7fFEepa+0OUrIe0RwXXSwZ/rGibdpCSl/YsLs+gZiVh42fz 450wZ2MNZzzfysK0/fqzL0ToZWyXIer2wB/LKiyH16XsI0X0Zra0DAxAHS5kZGApiLcZxtrjVcde ToExBcOFnWthtDo9ddgYqFo65hz/OQ0bC4SFnW7lflq+mcLEKa/ZImZnp2WnllRK18FulgteGdSI 9PMzySGnsoMLh4LbEn6NIVzbeiH5ZQ41YCBbS2aFluKLU0mYRbHpRFnSKdWQRWNHw4Dwb56Lz4Lv RK5WPPCKyHymybDqaae0v0seuzE9+cAzc4320QfPSQgH5waPKSYZhvETXV+lSBmNLZ9jbDH+GGVC cJ4BrwpMj0WBd0uoS4jcbFZU6M7C4GeEm5VSzs4s04U4SWykaxM5VJo0ju6TC/vheQLw4xmCp7EZ qXazgd4+ulee7e1n26xn01MV3S+GKj6TEzUz1jms2sHeoU0jaJcpWK3VUc0kRb1NGpGUxmyremAL U+OWLxSs2TiwsclZm861bSaPBxzrKQOhF2WIHAY1AOuZrk3nu9bLHNpeedzGVuete7Bvy5Nlmy+2 bXOtYbfvv7RzSzPC/tjkYhPYFEw4AFckKq/+hGpD33CJbCoQ9H6QTBZHLooJdlWLOjPpNBhv0OHq Jsn8D+TVUG7lBNSW3by0ond67/G6EhtvXlrytmBt2PddYXgUV+PBHTQa1j7saKywUvWeeiaGGw5F r2kd7ZMO9bSjSh8p1U6372kdb6xIz9of/RgMS5OfM0jfhaLhTO1ZhVk/evO8jBQv9PLqvOXyzu8h vKHwmZ2I3/MyMVJM7lq9Ji9vKaXTpDHvOS+JI2ZIAM0xQiysaLCo4ncMClwF3Gesb7igAeABxlA3 bZTjOIwKOcchjBaGd+Ljw/b0z0ey7ZVlK8iIoCcGsEo45ob6+Cwaz48hxkCAUSF9Ity/R3PYHXlG LBwAf/AOCIosahjrhIw06kQhE+4c4SRemBtLD0MxTmrZrsJz5yPxfpwXl5enBH8rlqjwdzwB7kMb g7JjPq8iT4+D8QeD4X0Tqs6OFez6Aqz/oq23i9ZpusJusWyWV3hTsIlMQWn+XiZv5UlwMxOedaZ4 GCgJGt0jSaqoKpGBAJtr26WxhuUqZmOzFStl2tajQLjXc09xoiR+Gc9NsgGsj6YqiOaB1fF8bIrM VzYJeInMVQkTBviAceV9Ms/wcFk7Lvk8PK/oau2Z6piAkrHFHuDUoPNebYi2wzhD/qXioVaDC7cr 9Yb3bi5bpojSedvKMN3bTStQ3wSZudW0XqdluULR9moH1t/uNTCpjsDRcMXfjXKz+RyZQ7pVYbgK gfJ/srE7yus56RheJOmXOOqzg0fyueEavG974B4DDlK7xSL45tG6QGO8Fzwl7gECHwYa6RgoBV4p 5u2z0qJ6EV+Bj5VWO8UjUu3WfsMbdwT8hRBKrZpCmOf1eyVlwaBiMNEIVfkZ93OyN+nKlpAZhWUh D6yd8mh5upownGL4eB7vcjMf+glSbtOz2/fXpD6gjNGIwvMYrGC4MEqR+kWqm5IQwgxAV37P+LHT xwOPbwmJk1LWmh06sbSEj3F9ziniLeFwwT1Q6T8V81IbxZA+WduVwXfFDD8nuzznYKzhkfV1zgN/ yt9FW2PN++OZ8cTeuLxkO82W7dUPxX1iE2+GLOtEIWtdQQZO/Wi2mjY2PmUtdNY7/o7jGEZiqSuQ pt9dxsPZXseWS80+uM6flHjjXVLQzv1S4M3mQabz6wdrMiCqJX2+IzIxnp+HxlnN26iCGz352EjX 131X45/0NPT3zLtVWzJtAoluV/QUwR4pRUNPi9/dvLQgAwpsgK5W4/DQfvnRY+FTNy/jraEnl7HD TkvGi3cGY77Vamp8CLKTGd03XElqug++6UX57j4K28JoNdFfwmih4ZT5bt2ZhxfB91kuNIqOMOpg sdx+uB64Tf4dGYAgAhebgoKrUE/3q48eeGFzaEHFdQgbca05FyEP8XjsMuPnc6/jD18+6aeFuScy fYSL4CZ4cdyl6gF7Xfvq3kthSHye0JTrQCxlofM9767cVjhFWEmKOIzkkXHdqx4IP9rcb8rTUjJg yGC5+ih6UwdqWUWaeTib2wdrUxubWp/buMISrkGGTk0NGq4Ky1WipHBs7R6xuHh6Jix4DN4azxbl mtM2T1nCHnVpHTs4RC+MGs6Wxhr8awKBuXH3KmKyBE+VsRW432ipIkBNX1s0Bj0MBeI5XY/x5B3G rBvgc8yOKmxfmNS8gBEP5nNw6HSgsULPsiQaMJjZrPomrq4u2fZBzTrZieAQBE+tnbdqN2dTOa8j FHUCZnqetlwkZZK12Y11kig3hGYZykTjzYub5hA/85Z3T6cZavkwZIz30/aO/n1moaSf0Z8A9jlj SIiOzLKUWPvsFA9RyYhGEjG/w/ta266JqY+UcWpGaN4DCzAuGL+piUpoZ9+SvlYs5bpxcdEePt9V UgoFVqgvzHGghdUFXC6vZ8x1C1YokGjJD9IaBmZLv99cUuntRZlHLY6MFqlgGjQSg7KTDluA/gj8 cQqsvwsNYuSRyWiXBZeKBzs1l/ny/kuFKSwwsBoWSGw2wQIFkFSLplAozOJAaoa/I57Gd+WNQAic rohABxcodlvhOnRFjtIwXBMDNT89qYUfM50sfDyxb9rrMli8cLyQqKfFfT14um3PN/ZDoevg0W61 1JYe76JQLIR3PWjb+CsG61cf37czS1PCksC70vSXo0OXGfCA6BKjbjCttiaxZ1C35XXFWrbhMDYe GAXqMCHLrhS8tGn4YNy8OYWLBZIFpBs03tXqonee4ZrwszAqhHDwqihRktxyi0zuTmhaytjXpdZB YTFVBRi1MCX6ygIYDs80Z/sJiRebVZubR7KnoIwnG12j1bL7T7ZsvmjW2tmyNxamrF0cs3qXguGu HXYz1upl7dFh2eZyTfGzKsj+pbLqsWV9JrDZ0WpzflyY9/1MX+BdUUSurK3TXcg0Mz7IN3v1gEMC cYMAqE+/xkjy9hA5ySI6X8u7ApHhY57FZriRToE3jBQ2nvFbV1ckzscYcz8SjaQMh/rQpmc1f/r2 efvs7rr05/EASW7K+yOR1SabG/ToQ8Ivn/Y4Bhe9h4j6WF+Un3CENIb+FVi1SeaBkJAm3HTZgEE/ eASGbff1agVfhwaRvv/jvnfa68bONLzgdBaN8xJ3M/j+uZxdvbAgw4UXBQ3iP/32G7uwMudEN3XY YaEWvOxjKLZSiji0/46Hg+m0JUd21msTnaDnRcGR/V0H8zgAACAASURBVE42kHvjZxgq9xLonuz9 88i6YfzwpO489Humqwzn5S4q5TEbr1BbOWnFoIt13HHt/ILCC2kpjaB1nDSuSS9AP7gPtOHhQKl9 b4Aj2OEZJzxUKvnZefkVIRhGA2MzfPA+8tKjGhMmBV6Ip7QXPCPCcMYCj9UXWN7Gy57dImTn/bFw ndHvmvaQT70VvONZKj8Kc8uNR5JhA1Pj/a0uzqgDUbPRtM31XamokkV7UavZ82cb9pc/vS5Fic21 Lbt8uSz9dRYpa2WjPSZC6Xq3KFpEpdOR4ZrOOvnTx9eNUfq/CJJHVkcYxkCr8FCU8aThKh2y+SzP R0cdqjqgheCFMm94BryhCKjjWcYCb0JjPGY+63QJ2P4mQxgHAoNEp2cUFWhqQnjMxkCXorPLU/Ka ymMlWx1jAz8Q1stmBmeLZyFEnJv2Olon/HYEH/D8NBjBWOYLpVMI+PULolUbHryuwH7u41yJq8ge UO+gNFmzJ8+2hPjz6ag7NEe5iGN0wc1OMv2EH4QeSHZIjTLWL71mOPh9cbikhjDiwAjoZaWIofwH tkUNIPQHYvfP7z6XOoTvbt4UIs3hwhNjskADSB/OxvZFziLkBeLB4WoDpBIScqhVOhwn9NYnXUFA zSCyWVX+Yxz5Pl4H3uLzjV1lZvDGMHilUklFua/Ufw9eFuFWLOkYPk7k4B0Z16x0tWIjC+/1FxVN XZI5Gg8lJEjnT/ridIlnnzPyMDf21eEFsbn3KoQzLvkM8M5zY3gI/Qip6RnJe3CvqGer3WmFq6jS IkYYVUQJV+AcSTL6mDmA8WOD4h4QpON+Y9kJ9/9kbUd47pMXu/IweT+zU95+/uWzl9I4Q7O9k2mL lrB94AXYlTzqDWSdY39EV9GIWFYmgtpRcyx0PvffhXrBWBoTy6vUtzOpZsAw8X08eOZEbNmFJ8o1 JcNNGdOYe+zFTLaPC+KNzYZmG1Fs0P/LqIib+4SqQMYVbJW1QEYXgxWjNuwAQP3YWN5yGQ97lT2P lI7Q25E5R7b22dq26CeUZJ0o4DfopaSF/zOJ4Uql/pSBCQz5qirUO6oZinQJbpqXkabuD0wCrhfb aUtxYBBi49xoCIm5rdrHfr15/34BOgvZ78doMdFGemkBdEzuLcFw8CbeuX5GRbqEemg/cbAQyDh5 KEh7MDSsveEAWZz+GIYaLC7L7yJmw4SHBcwESreX5+eK9bMJQTLiYzE7CBgrcb2s2c4uVfOH4j0d HhzIM0nf/0ksd+R6jyPbpsfiVQfPBM/KO9Uk1yWMxSskfFTB+MTYyGRJtI0kGiDnUkKFobh8bjEY ev8Oxo2FhlHBsJOkSOu3q6CZrjCHMNcPBPriWdABh+YPw3I78vIODkMH7I5LFM85hkX1LeFRsUCX m3l5MFyEzHJU6WAR4uFu7VCnWLVPvn7mKilSanVi6ns3z1oxNItI0w/StYG9aLDEUHdPyxn/brT4 u0p0AmAeFRhipMDYKptcyCnkxYtCVJL5BpMdD957FbrBYr7DNkdhQTjpfl2fhRCMGKa3H/MEiTd0 hR7iSh3gaOh0dTrTNjtNjwOfa6ilYISQX+Lzv/vssTx9NnWoLerAFBIktXrbHj3btE++efntFEcH 8IsIHjLxwrtld8BwUEUv/WaNsg/6Ea5XqgSAP2bHS9YpeyuiPv8lKkogjKdkgDPtfe2kVRWdG0Z4 z/W/a2IQj2VUVhNqA6Ail8UI+QvODXwy1hWyOAlH8AJYjIQfhG3eeMEziZ98/bzvqREOybiMoCLw zID6aVg8NoEYPgh9qKgHM2MREvqwgLmPWH3/7MWWANOdelea6GALGGL+87Cip7KVW1eWpfUFHpFW Jh02cqPA+OM/Gwo3Uj/j+fFcXw0D+PPjAdDinUlO9gnvEcNFY1UvsyHcLtriymQISwe9QDZAB4Ux fg2NDZsqi4zvSZFVPCs6I+15ke8YPy8InCZEcnnr1H3JMynY2aUp3UOFMqaA+TH/mQ8YMDy6XSof +FngMSIj9PvPHyvDSxiKke3zmFIM/qy89Gh4Ux6XeX1pzMYqgSIPNmG9xyweN0rJFMKPGCKX7nZP 188fP+vzazZIYsfwvFZv2NrWnm3uVoX1sZGxPuGYqb28pG1QAPHidWgNb11LGtiyyXBdPDZoFR9+ 9cTX035dtBjwL4wl+Bc8MCSowc1eqTh68uTxWC7SxIKuafziCC8qYGKDZxjUWiLVGhpGJvfgfzIg vs+49e3jH6nPZWGQkzVSNsdPjmEDXxtUFnj1QZwd5UbSB4PIpGJHI50NsAlQmD70Yg9b0sO60pm3 T795Lg8C/It7BluIPQtXguIluxghorpHH3P4LvnqpyANzaLj/YF9lSpeeMqEZtEtIp1S8uatogwU vaCYCRXJl4zf53e47469de2MFmoazxueF/0C6IFN5FU1poNHuiZu1KfSmKvryntSg3vs1DvKZjF+ bBiEGdGovOpgSYN94XVIdz6oS8RQiDGjVEpNb6WM4R6L34+HmOku6t7BOWfdqAXmN90P7fAq8IgJ hzzs62hh0rYL4cDiOVeWZc7gBfLeGocOQovHFTlRjPlQfWBkyAxv+m7M8N78txHQx7OjZtYBey9f 4yNkFV2N1Y1ilEaKTU4xOF6SlZeniNfMvBZnK7xjPs+oeAuxiIP7+uAalN1IMWOiLByY37FxktmN xGPGiI16ZipgWN82fBpFEdAYqm7MdxsfpFQ11TE78quuoUmFCzygrXQU+EV+Iis1yuTX3VhOpNIK QtZBXtFxRvk4hQU8ARY5bjEFyTMTZU0iQo+oiBnVMDFAeAIoK9JMFdwDNxiMS51bcMtR10SNUXrd Trjku+nOMK97sCD4jwMPD1wGlxssB88Bg9uoeqpYnK1SUfdGqJAu9H4YpEVggo96XYMF8/r/kfdD CM+7i+M+il8HJwlGeLquLV1NIiOF3HFmkPcFm3u64j0hlxacpCoPK4QVx91v+nAczw2Jy0o35QV0 wzvG81Oyon//bhUcZ0oIk309udD9Rsszchz714448KDYAN4rJT/MB7zjRqOp2tR/8adv6L39+pOH 8oTevXlWgH3aqkfSaxT2i+8jJuf7CS/RVpJsfXwm5jrzA3yRv+OZU2DO3FFpUOhMzkGEgJcF5gcR NGKClXKkvKR6QYprWLK52SkbK+SV0IDgS9h37cJSvx8lWUMwWf6NY+H0DH+4mCmcGh//fppQDKs8 RE4DljEz7G29Hm904DjOCxz4TNjvoicQJ5JgR9xnJQV8BwFrw8AdF7qAMeH18EJi92MOhO/iuWcm xsRMh8n8ye2nYvMqvMt5uQeZGIiU6qwyM64dmrCQXRtCH3VYSzOur95pNW23Bjg8o1DFJU++++Gy If535HjVE7HXtYUFmjkgtRwKVUcMbSJxfJoXNziO1VB75skVPBDkhoPKA14GOuWQD4O8CSEa+E3f RiV8ybDITVy/HlUE4UPe23DC2pNjMh5RFfQ47YnjScfevAJshcUE7YLLkzSRkGM/6x0zhH4/icep 4NGNQfCihDWm6EHxOyQWHj7bVDjLYo4AOZIweHjQPQhvVXM3P6kwkbXU7ZHly9tn3zwTfsez/KP3 r/QNX5q4mRjF1EYSnHN5QIF8izdNU487jzc0V99741zoS5nRPXDNSF7m/GT+fBOOm6GH0XiLIqv2 vdlYgJ61GWFXhKjoinnDVv6jXCy+Dp4Loxz5cUQfojn0m8y6RlufhzXgJZ2Q8Rm1Q42aBOKKqMV3 W5MUiQwGHVZ1WR1NXu84ifdz/HeSP4VGhJSvR/umOsh6j6LKrAivw2cGFITnhOW/cCYxWDcvOTeL 7NaZ0JIebwsPCyKh8JHQMQT3llCM7CdXBwxHdQDiHee982jNnq61bWWuZMVM1xZnUDwtKQWc6eNo fi2FtKcIp4Y/w7jHVlhsXNKK6nTUK25nZ8+WlxckkyxzHmRE4oFBJaPF9715wmCSJazOlDcUAW/n glU02X1H9wayPpEJ02stNJ0ypnaR4b2kELKjzyejxzlcrquUbnkf7pEwMLk3x3j6kEUYGzhdjCu0 EDyMOL4MG3QLPoOnw3OzeHivhJocLM7YjCJ9Zz6jIhwSxyGGt6FJbog4AHu9Q0/VLp11HS74S4Sv 5ZyHuXhb9FfE5kHR4Hjz6orm1Me3n+keAfSPrtWkv2Pa443vJwlO/PeEmzRAXZyt2NO1fbWav7g6 L08uf8mJshheEiFUGOCB8R1C5KhbxoYG9eb+k81AB+F9dG15YSJ0Eg/lZaHsiRCYRIe6KMF811xs KeoA56VygWoPPDiZquAlymC9Kh19Gh5U+hyxcQBxOBaTl8Ik29nZV5r38oUV53JF4baBY/g6CS4Q Rcb8U68wWjF7OLBDJweLJccAiCXtoWKS9E28OHYLupFgKJ6HbB+HSIphcsTrNVptNUP44s5zhSm8 BMaBFwkHCsP3+88eykipvCNoMrFg9w+a9tU3D7WTvfXGFfv63pq0ncTKDsZDWZNgVDEE3tXZKQLO jTn6sPFv7MY0ApCs7WEzgKRocLdT7ZVyWrwPn6It7x1a+I/FghaXXPfAEv/RmxflyaSHdXiKCMeh JGZIZ0u+bezU00vC/JHHkXP659Vuts9hTr83jdSorw5oFVBYS6YPGWzGAiPAWKxv1pUkAhTHg2Cc p2uHwngYO94bGxSYSzRIaa807RFGLaq7T9YF6OvOKNcJ2vKEm7TNEhcsdAdHIz3BQv1k1FgiIsm5 piYgC3uTiHNnkNiOLd2icYrFxiO02wcoEUjGhI1F/LOsRBLJ4iFL9PUDL15fmHMKktZIgDg052Cf B49zEvglEpWbLuanygSa9Tbb0s4H82UNqb9ji6qPXbt8fl6bOBsD4SbPwvzn3C+3dpTt9XkdQ13H 3vIa2D5YerrQaxSrPP0zgDfCntiaiEXK1r67R31ZyyoVGksOdaY9wQYNhJP9HevkLFL/tzF1OeKc mvx4gv3LD57z1o0zCkFYeGmJ4WFPQxNFKex5nY/nBofAEL1zY1nG5uJZMmxedKv9GJyv3bbNrT17 Aonu7IxNzcza6tKkOCx0sumzAPu3FhZJF0wo6SAtZdAw/oS4w1SAs90ZY9+L+vQsxog7RDCWU9OO DHzC6+ZSkzSGE2GXVBv6oTWhUOfgUKoVgN4vtmq2NDfeB65RGk0D9lGPHVAXHCR9ntRjDeAxEYvB ZwMTI5Rk71ZCJdS9HVmrQy+da7IRkeigcJmUu7JxKgNxHSySFUlTik5fkM4zZE0ZnajvHkNlFiNJ GpIoGDXCywdPNuz2g/VQcuL8a2EzZGu3q/bzdy9JtfPzOy/sR2fPebIj8qdC1ph7lXZXp6uaP2gF hGQ0NkE6OGaT+/hZH1fz8YhZw+PwR5XxMC/zeSuVaMuWFX+Kd8bzn1+eFTSxV6uL2uJS0e5hYuQ5 d2wSwsHz0NXHKw8S1jwJDbxfSKDb+w29dxpM0PkZ40Ti4MMvHwtTffR8x84u0RQ2Jgr8OV5u7Hqk pFZGGVLZr5fRGf5cBP1cpsObP+JFsGMV8hnJviIZkbGJmNceCCOOPfep7uD17nl4AYw6CM/AWlBa naJb82vwJJhYvGhcYj+S3Tjen8ad2sJMxhanz0pGI0epSDdj24dthY2SRAlZznh9tIG0WEd0OYpg s/6uywZDpvIpQGvP2nCgNDoxMRGKn13vHDvpX3t12/gooS2kstezj796Incegb/d+qEtz3jrL2ly K/vk4w25NnowgLq0XHvj8vLIAu2YVRvkASZdlIVHqsU5YUnrZMZ+3LyC0ZKCRzYj0TnKdtSrsFp3 asdYQVmqjWZNjHuIzBAX8XII3XifGPdHL7ZFd8CruHl52cuIdmqu3TXjXb4ZV0p3PFvp90AGGQMI XsY5uR44jnOpIm7jYDqZQ7J4Y0Uv2AZS4HoA8pQQxc8NzK9+CV2y4/Fs8M2QSkqIzzFOjJsZzUt4 /qJ4Yr/79JEwWyRqeAZ0rWJ04d2SHFuKMALz2cm5STaSErDqQU+t5wmzcWYm6S4UemxyfP4NYW5O 3aQgmn5174W93NrXRiDIRb0KAq2hHz6l2LSvg46nMTBexFPkcEO2jDo1icdjvA4P1d2kD0T6xUNs /S2R+O9wDF7yaEglfXF+kjM7VOmBZxhPd/JhXpKPM5SLw3YEmc0mJis2XnZCKAceXbfdtSws4ftr yuCR+YJ/VvdoQP/HeCaKr+F9hddIp5UEYw0YhjA7MCPfVTF4nWxO2U1PWx9t5cXPROYNoRs4LeOA ycOQg/txH8U44VEUXZ61+kzL/u6j+7adRe9qwn776SMteCY8Hkps9SSib8E1u/EyKOcYpRU/+t0F grAykKY0ekwejDp6YWwB+fkW9RdqcjE7oU1hZ6/hPfQwPrYnwUE2HIwaC2ft7r5UOCLJF6UGyMHw 5lhIUEfAuTBy4DCA02zcRBdfP1wTRsWz4M2hGcVx58mGlCL+8ifX+2tIGGOqa7NUNLqUGh3a8sUp m5kEpKfeLmv3n27L2yOMjUaKx4u1fxx4RHi3eH7eph4OmGef+/XB/RHyA+9scjxrNy8uiv+ER8Tm whnJmKogvhOiJMQKQ9iPF6UQM5Oxje2omJGxlQU2RS8zA1THU3vwlMDejR1t16j9vHXljDqV01SE ecX7jIA/7iljKT0svuS1R/FBkzTtcUDucQceFfIV1y8uCv+Iaf5yuWSL87OWDYWNOmesyYrX+c9k uPw4/rrKJNIqHDYyVeVwS/rp5ORF8zdsEWuu1ekJ9+ClkR1kIjXUIDVj5byPLUFdu5e1DsB2LMrH KFLvxsQqF5Wp+ebegZqwpsXp0hQBv49oJJMG6MNPRNIOjwRagLAlNQgwO0A6+pgtyp+lI2/OZbG9 GBtj5U08k+9Aor3/dMPevHZGKgs/vHVW/DNsPHw1Qi2MFsZJ9xeaRxTyM1r8H371VJ1YMN6DTO/R 7yYbjRbeXhu1kK71+hngBBnD6OKV6r5DKCrjC8cpg3571xbnJ+RFcE6MESUlFHqDP0lhouUaZZBU +R33zRznT7hqJGII/fCoVMkgZRPvH1nIL3lHmZ6pEB3jBVxAKdfvPn+kND9VFX2jJdvjPf7AuSAp Q4at1RFidO+OuUD93TN5fa7iibghXp0Y/RlkihoCttHHgpUOmRTPNlEgSQD5OMRufJyPhRdGOKza VsqgtmpKmuBFgunC28O4aS73PENLKLw8P665z6nwKgllnQJBD8KMGqx8ce+FjOkblxeUREArDMMe tbeUeScZVsBl6FkhlxcUkYcTxA3PT1VsXlIkvRHu+GhW86jdL3YqwW2WsiOysdtVyWww4N1ew9rt ed8NU0Q6F8FOmkSdJjv5D3kIqA8kVNL1xZSHE70XFgE7A/pgHWrLzs1bvWu213SAnEXkCz94s/Rk k3ZQelwjMZZqeldepID3zoN1fe/6xSWB4I9f7miM45i0Wi6ZEsMKXHMMROTMsENiCNAgVylIMAhw yJaXpsTIHjBYmUGFWf+7e1S//uTBgEotk5JFwCTb2DqwDz57rHtlbsGSxwsAXH70bMs++uqp7v9X Hz9wPTU6FLccjAUzwfv6Jz+9PjC/hr2/YUMmbK7btdph28p5L22qdjtH5ihGmvcWEyvdYOyqVAKU 8paDIpHPuSz2dk0LiMJhDAtjR/QQ5YScrV5SE1cAa0J/D4NSiqEkM7IUf48JY9O96jNdO7cyrdCM civkbRKFBH9OAGlIxqwTPE814C2geuAbO4YFbwfyJvwsvEPGgc0AL1DAeD4r2s2ZeS/C97rNQHIN zPsk/Ey4Wfq9Giu78YgNbcHzCCnB3/Amr12kVMtrAfkm96qkQa8rwUCRbWfHLWMVeWm0KuM+2ZS8 18GO3X+yLZUNNjlVDfQ5bjHbTFaYDDc6ZF3Lz+Jidnv2u08f2NkzrkPOC0pLiMRjeKIcnVRugHhI fgyYVikVvQByZlxeR1/XPHU4dyucK7gKadXT9DXS1/+HPOI18bZoOEB4sUuXgPA0pP/LKm3wULeU LdgNhPwCKBnHZSCzFhfbMY/D5yWvUphUOpjd8u8/uqchwlNJF00zNnCH2OXABggDKBxlvDFa7P58 x3vMJaElrwNXO9Z4jRpb7jEdOsC4fvv6mRBKHWhicp+k2fGy4ia4r06+XQHchFNTlZKHb5FMLI01 J3lyYLTAdD65/UylQOnC4z4kM/T+YygE7sLn8wW6DhP6uRcoOZiQpMHYJll93zhY8NXGoVW6Ldvd dOoF+lXFTM/OozIQwnXeIaUsbALRo+FnkFb5d3KvySbsuYxAp5E9cPG/L+4+73uajKNwtLVdfQ9j QINSynSgMRASeQgXoxGy2j3xAx+/2A2UB4qs8XiqIhvfurLikIN6CmRDEb/3HcxC80jRGyLuHP+e xgsd3wpzUV3JMTjeuUmbn8qS3JNM1irzzUuQ8KSYX+s7B0o6OWbVkZGezrB5t+3//uVd+8ufXRNk 0O/ZE7T4YiQGP01/QquYHnceyk/fvmCFUlHhHCoDWMFRbORRC3mAjQ5XIu8ZFXZ7DBXdixemy7a3 vYvST4qEN7h6+9dSVXM87+gGGf+QRmv4Wkx8D0eSF+Ve0cCXLB9Axe96r+yuLArCBl4sIQLZLXYv 783nB7vgi03aZ7kRwDAA2OLZKuPVamvys+gAvr0Y24X04jshQ0N2L01aHQh7g2bUF3dfaIFcv7Ak zgznZiFRvvKzdy7a335w137+3iX79ccPFI4A0FI3Fg8XGdwSeTJ9HQwrHvln37xQSJk+TtqwwFRQ CygVi950Q2vNPy8UJGwWw+9DyqLtrpofjI+VrNNsWKdAxsxrKtNF7ixCjR8GJALcfUZJ9Kyi7jne m0MJ0Rtl0dNAg6oDsLzlxSn729/fVYXD+7fOKkmysjjtHisVGaWE1MtizeLFtjveMm2/IUrAymLX FSc29+yn71zQ2ktDB+n8d7JhpikZKd31YHzg6AkLCxUhER4S4120HP+8WPOZRALHz+fYIN+HAH37 4YZdv7hsMxPey5LnEEZXyNnm9oF9ce+lvXX9jLKGvLtoT9RXMdgT1EzB+n772UNRQHSIoS09orz9 4fPHMljp47SLznGNuKt79gMlSEmFlAoijJ18Ln/JA95WZAynvvfBF48lIUyGxbt0eNYGjCLK8EYZ FhYY+MPb11ZtbtrF8057HI+fhF5u3/L73+bg3RCKEGKQQif2B8egXlFMYil9TghjiCUpYvY3mire jT0XSYtj8FDDqFYp3h5TJohQR6qeQxsKIRs7ajzn+2+ckwH67acP5Dkxvow/P0MU7/aDl9rxKz8r avL+3Yf37UdveRF1PLhXcKu0wWKsoMSgpw7OE3/2Kq6g/5zwK+FgxRCyb+RGfB9DxX8YVJJBhM6N ql93enbGCpWKFbreVy99L777p5ITIZhO424aeQejUtf1Fu6Xz82JOqBmJo2m/cWPrwj7Yfx4fo9w u5LfBsxnnhFuN6S1DnA+bVcvLIoxz3sEGmAD2Ksd2o2LjGe8txhKR9a5UzEkShO6ZfWNbGwCjFJu A0WGhk1NkkQI5WFxUIPyqjzIoI+XUCr8uhgmNp7Nvbo4V5/fXbOblxftjStnzLpkCSfsi7uPBA2Q pPjFB/ft3MqsnVnA0KIu4eF8oibZs7/+/R37+XuXjxY/M6Ds2pAgIZINH68EQtV8wXkZer7wYqOl zGSS+ryTvI+YbpW2dXQWUyALC5SQKN3GfYhsPcDhAUhFSqPThVPzDxtSftdQNj1OGA08JLwtVAXw tsBR6JLL2ANMslFEkikH4D3gP0aH7+I1RMngT2/X++RUvCTVk6UUGTjI6mAsyXCpTCnwlKAifPrN MzXlKIc2W3DKaONO6h0MCC8Lo0B6+jefPNTYg72QhRvFEhHNJOcNPEZBD8PjGf/unv3RLOFxWCt4 FFQBwmHmEBzB7b19YblTU3iEXhkAkM+iZsqcFGUc/btDH0/Xd8UfitlJDJF6IRbpr1iwP//RFb0f Gfs9RAZdEgcPmQ0GRv6P3rqgubxbdSUD5LnJyFEWw+/wxs4uoZ5QFUUD0clkrFJFtX2J5aivFXCi rldCEJ6zrtTludmymUzSPi6czQ1d6G6eZtbHa6lHpJm4WEtzh1KtoOzng8+fal4gs430OFlBnKTq wVNvUhuoNdFPYW5u71Tt8/sbuubNyyvSPMujWcXU3mvQLdgrv8vFvO0hpNdC/oEed+4VUb6R3Hrq vYS/+O7jOtaPn2/ZfnXMdqoNXXBv/8AePl2zsSBMdxyYP2I29OkW/doalbigHFkcqPE76ZBnUW8F zZ/Eg/g2IRsv/fefPdKuxoFHInLsqFR6aCvfC9gPoCMHE46DhSnMD23vkNXBIPzZD68EFdLR4xQ1 jd5/87xaOwG8EgqwIPBOKGDGaETjxb9jmBfF8Tgni+fOI5q0bkm/i6wuYxqbLQCK450xi9AMl3SJ sjguecsiIvyTPHM+L5zj0rk5L78J0se8/8++eR6yTXgO3hgB/Oivf3tHTPP0G+DceMQffP7YM68d B+UHjtAdOoosqu3UxJi9fWMwjPSPDr5fjDcy13QxYlzIBAIAX1iesmUkoLWxmhVLYG6hVCno7Y82 WolHM3xdOFyXz0KRICTyDK7jmZyv11di+OWH94UB8h085lhihCS2Y1hOSCYTqIL5ZlPlL1AonB4C 1EKGc1slLtRA8k7SOljRg4rep5pFBMOMocll8zLU29ARoLyMFQYoFjGb7/hfDH+TkiT+3ul4RcaY mt2aTU4g3gfJlMQPKhYlm7tQtn/7N58rS/j+m+fsp2+fFT7oY+ZyyHC38Dbpv0k1AsYbDzH/B8D2 pWmXr2g0dOLc2JQ92diypdkx29zYlDIlu9fEREWLlFTq5bPUMR2dFGPFolzW9W2aDjhLeGHalRbf unHRKiMUCF7laTnlIXGbcEPZ8V7HzBBGUUPG8thZkQAAIABJREFUTnaa68bfp58tHixY9KyScGM0 kzjcrjwY8CKuH+sQo3Jmkv3qKQPDfTJRAJ4JqzhEmpsoSTEzLdLHfWG0AW5/8+kj+/uP7iuUR9wf 4wOpEaMHcRPPaViemeONS8v2zaM129x1+gkifTQPjfcuIDhU7KfVK+IuOD1e1qQjLGQcEpA3OVhI b1xxYij/kRoPYqP9ustR4zaQpe7/ItqHwQQGYL3rtR+vEspBAohGHnyZjQteEsXpeDsYToi00XOQ tyev3T0jfo4Xw5/gd3C2yG4lvKboscRFnLFbV5dsDN3zXNbuPdlWzR5NGfQoGIteT3QOAHY2IB48 Niqp15GS3rbtKyvygL68v6bf3328rrni/QaS7B6h4ZtXl+Uk0NgEw4w3BhXDWfHBI+orNoQi9dqh PXyxK4yxUsrbXq1pK4tTnkkOz6PSmCMGObyHwKiPz53JuBopITCedbdNz0VqcJdsa7cqUvX0JOTV rP3s7bO2vOD1uFFsMGKAcLf+2c+v27/56y/szBJ8t5LlG92MLS/PWC5bUJyMRaYDCV1wLl32RZmN LaBU1Oyp2o9uP7P3bq4eWdCUN8D7qGAx+2S4UEfUbtmnX720KxdX7MLqnJ32GDAYwYCxC8Oc1u43 QnFh+Hv8HdkWiizZ9WM7pG8bHkrk7pQGjwPjjcb4KDA7nqNYPNTvwXXohCMDE56V76orcspgxQMv DRym8oPLyg7+h199bT9557z94I2zwjW+uv+yL4s8fOBhgUOdW/F7AVAebvTwFz+55qDsiGf8zacP U7LDyXMNjwtjPvy8r7thjHqv8WckdRr1hnA9jBCbcPpzJB2gW+xU6xoXkg6EhXjGvEt4QniXhEMu Muff82Smb5L8kDl0dmVGigrQSJ682FaxMGOQ0BIiZtSVAeDvZHCpJ0UNArVXsCiuB+ZHun9pzr1X 1hmZP1jsu/sHYuD/n//vp/YDlEgLLhdNucy55VkXjQzaVfwCI0GiaxFv/3LPnm3sK4vpHcNh8Tds ZX5CWB3eMp7vg6eb9uuPH6okiRIpvF7uC6mhz77JW+2gJcOB1tXV83MhQxq4WkHShpCSelzuHZ7Z xnbds8GdtjXqddvZq9nMzKTUST/+Gl5eVvpqSB/TVyD9fvkf9iZbcA8O3a3FOTruUJe4Y/nNnbqk Rwv5gnZqdJFy+bY9ernrJRfJ1NBOw26iUotOV4PK34cPbmDYEHBPXBSDgZXF02Fne9UxalJr8WhX TmnLSyg+LdA/eFBl/+O3z/fBeWJ9whIGj135Z+9eHCn0Nrw4RuMVo+87feAlMV7vBiM/6vN8hfCH xZ82ADnEziTgltQzDh9MdjJ0aKXDcfrg8ycKKyKdgBCInY10emTVJ15xIagVpFuWp8fueJkbQsbh MU9Cj9OPz/DnRxknwkRAaEKn4XMwXDCqV/NFhWEsQrr8YLgIkT/88onCVTTIAJSnJ1ADgHfo52fz +u2nD2XEYsKpj6GRBOp2FZ4RsmMAMHDcB2HNx7efaJMhLCOcjiFU+hmQTMbTIXxnM4KTxub06MWO /en7V1NUiJ5wSbhX3eVpu3J+0T79+pldWJ3RvKWPImKLMbsX62aBcqK4o5pw1Bp6Nyx4MMj//d99 pHuliSk0k8/vvtT1mBOMyQ/fOCuDhsHmHrivG5dW1GCFA+P55b0XdnZpVlADhxpFqGdlFq1T4W+7 1aZdWJ0XT6vTbtlhoy6j9eHt51pnyOdcOrsoGgcF+F8/2rBbl+ZtolLuz0EM+rnlOctlKF2j7nPC /uqvP7V/9me3LP/G5UV5TJVSyf7qb7+0//afv6eM0X/1j24NSWh4txMANKw4pDfcTowFi+JVR4fC 0XpD/BLIkBDHTprIw4Dr8OSX1jkFnmEyBUTResfoufMzSiji7gefJF7ro6+eHAuoDp/j2xzKfqlv XEJBGHX0E6NDByEVYVbEzEYdzgvyDeXPf3zN7j/ZsF9+cFdZpLeunpFqBN4XADjJiljg6wvWtfkd SI275/EGJ/07FQGPeN5R4zlq44nnGz5v+rM8N2EprH8Y38OyKrqPYlFZz2yuYFcvFO18q6PmEv/P L78UcP329VUpHzBGLGayV/Tn41x4FGRdRfMI8xyPAo+DeYYRo9iY5fCnP7ik8JEMH4bQazdJ6mzq HdFF5/1b5+VxEZKxQePNsVAxuJAv/+4P97R5wZT/p39yQ2F0GFlNAPHJ8jldpzLmKqr8/dnanroX xcYPOA0gHF6InWi4E+LhkQNwi87S7tp//1++L0YaHiLhP98DF2STZpMkk4tBOQwh9a3Ly1rXKobv 9WyqkrOsESW19cz8DKxPOl7ttqhLdx9v2fLitE1PlqzTcn7YQb1hX93ftNXlBWWj1eKr9dL+ix9d 0RykSuC3nz2RAohL+HTt6cs96fMzFiKl9rz7Dt5oXoBn1uz+4x1ZTm6cXRqS15jkHlKaQwxQiOXB pn767kUVYdKzDu+L3QWLzOdUApDDe/HvUN82MTlpjXZGHJfabt0+/fq5eEUDiyGVHmWRAVgPgple UI0EBpmu57PjAh9JvavVuwqKc/LgmGzy9MLc53y8AO6fUEjaPT2zl1tVezd1iYQE++2zicPfZQJf fYVHSScS3/WHzkVShC7TD9ZV8tBPnIdw0dnIro/EweJgMYCJ/Pu//0qsbUB8dnhwMQB2Puva8d7H TuRKPbP/bHgsRj0bvwPLG8mrS31/1HgMn/u433PwvuFmAZBPjs8oFKPlmHSYul39/MLypBp1jo3R 0QX+lGcZCYnAcZhnkfoRa/4A/wnTJgPZkp8R8hA6e3IB3GlT1wY/jOfgTr3JAooa3Gio3cxkZJQI wb2Nfc3eurpsv/rkgVjrUSAQnJC1sx8MC9lKsmTv3Dijd40HjGGWxHUosmbDu3FpUeuxdtBQqM/i J9P31rWVvofmLeJaWou8FrwlspCEyfCrZmh6mnFsCe7WF/fWbXx8zP7kvXP2xZ1n9sX9lzY+O6HG sNBTyOiSDb60MmHP1vbts7ubdnF1S54Zz4H9YD7xLEQPhJtPX2zZ3GTRnm9Ubf+gZW9dP68yHwz4 wtyk/fDWeeltYYh+8MY5+8MXTyQeiCyyhQ4/3uAGr7pu/+u/+YP9j//Nz/U8eUo8omXmYrxEBip2 xyVUiqAiJ4oyEnyHgahIr2dOaVB2cNw5jIwMjbgaLpfBIgILoKaKOBfXXnrrpLCL+aSlVyrn4ruX Gx7XjfbfkA3ihTIIFK8OzXKdRJXkLMJQmxTvv8/iDQzkyBuLQO1pPK1XHaN4Q5w/Nq4c/l38PIC7 d3Y5ei4mxs0rS/3GrgPXSD1LPBgzMit0YSFrxLskQ4l3xUJX04Bu27IZb54RjUeSRXr18/H5GF4O H8MG6FXh9EkenToRXTsTDKr/7L03QjYwfA/iKHOTiU/DA56RscKgqplE+trKuLnAogzYZLlfhB3D cYwB0jA0aXj72hltwOn3JYMmhbckvY8hwCiRueUzLES8lBuX8sJ4fvLuZY0789iFFP3+GU04Vb/5 +IHWBB4f6xABPFwh3h9ZxIyyjjt6LowuOufeYdvXJcYJ2sP6dk1hLcvFG+u2pXNF+y1t4kgRFwt2 NpeR8etS4o9xx1DnsnbY6npvSEnJ5G1huqJkw8bugY1X3ICBR0EyBjNkQ/nRmxdseW5c3LxzK3M2 PjFh1UebdvHMgqAKuID/+t99ZH/5sxv25MWWffLVE/vZe5c17i4NPQ/oJUVSjB8RWTbTs//l//hA sk3vv3lW95L/2dvnw4s3y+TJBuZk6TFwuLfgPFSK/+OfXnMGMWnutd1+N5woBDaeKyqVmmQfEmJU X08JWxK6xx6gOPh8W3gABzeNAQJzYNGGfMbAJEvPZ9x5JmKUaj0aXriFFljqof0rF1X82WkwmNMc x3kmx312ADGU0mRdY00YAfnWkwSno2TE3+HyExLigcIqvnJuzjvv6BkHGyQIF+k0LZNJWmUNnbWf FRp1rVE/O80YnuYzw17cMEZKh2JJqOx7wT0kVTqvjCox82sCC5Tt/tMthYMsOowcuCqyKoRL1y8s aE66vvjQ/YbMmLyq2qFqZvE6Yk8/NnCAazwsVBKwTSqBkn2PHXQYI68txPvFI9aygYQb5i+vAa6V oNpuz3pvnu8L4nkT1cBOF8ZWVYj1z//kZp/KQGZtZX5chsy10qns89b2UWUVZgAkTrKneG5gaxvb TmK9eWnKdnb3pVgBroQj8je/vyNDQ+YacUEwKZyadvvQ5qZKMp7QTPD+eE/cCyEwOB9eFqG5E8gZ Rq/EECyRydhnXz+VcSQU/MVH91Te9db1s1oQGLB8nAjqrEpdF5wMVfKbBhE3jdCNgwfBuuLe4vKm WcpxEkR+RprBORBiwP2g2nx8TG74zfBimCx4Xbjg0PA5BSELOxR40/B5Yp83eXMUI/MSU5Pa06rB gIUyCVekGO4ycvxxGuB4c5Oea0m6X228JydEBTntMSoEEw+omJeMLwc7/qg27f1nHDhPggmJwJtF k2pWaW84V6tLLVuZ47yxB+IQMRPv9BVUg1EGatTz/DHJtOnvw9vZ3Ka5QVXQhoeqJ3eoJmxiZ8c4 sRH/4oO7IrdSWsQ8V0++TEaywSxeMK00ZUIqJ11vWfXw+ZaoGx5OeqEx/SnhHTFw42N5LVYyXr5Q QxNZeYdOZRBPizmKl9dN6mkpr/ry7gt79yZeJtd02eL43vg7qg6sU2AFDC5Oh3MOvbfAzq4XnkPk /JP3LlmeInE4l6WCrW1ueX/ErAlzUxbv6rKtLoy7am63Z1cuLEvVAgwMPPHW1RV7+9pKgF3ydnBQ s9999kih+KMXa/arj+7JqfndF4+VZCASois0iT36FTL29EDg3OCBf/vBfRkt2Pzggf/xN7ftm0db 9j/9D//U6oeHSoioqL8/Aajyy2ZUNvAff31bD0mWhVBOLb93D6Qm6LyfFcWtv/jDXfuzH1zWgw+7 +8PMZP998JtCp1h3q2MVO5wY2rlHYDqjltbwiagrA3OBHe0Tpqf7IPbX4qILcItWVCsamMjG9R3E vTuFsrLSfh/pgs3h49SLiKxeq2eTkzPWbB5asege6s7Oli2vHK9bf1x6fthLxIMszU1q1CS/8uVT gY/j5YJdpo4s1BEO3m/0gkLWURiihyt4aD9845wkX3b2qnbpzLS0431hJIB/t9sESuh7EnFhRUMo gDf36gYZeIdMRuYKCgx4BunnSx/cI3OM8iD9W3wt9JU8cyogOpA306GvcLx2RyEv3g3vHwyLxg3q Ytxo6edRg9wrLpxmo78HPX5OSfXAX/z46pHmHyix/uqjByJtEgGgahINF+eAW4e38fD5jjhs3jwh vlP/k2qAX374wOZnr/XJoi6e6Uoe/s6iPlXw8FOETzyue082RX6meJg6vUjkBGZxhVGKp2tqKvFX f/O5znftwrxdXJlWiNfLYKCAX2hC4R7NyuKMkge376/Z9UtLoirpMwXadWVtqVi05std1/MKDYTJ YC7PYbyhQnVVJXDn3jM7vzprj57t2NpmTaHq7PSkCshZp0imv//WhX5HJpwhMq3cA+8K45fPhsxn r2m/+viR/flPbqh+EAoJdmb/oG55hOOpR/MU6aEtTBVt/p1z1umhxLinVj9kAf63/+u33nMMPKqI 7o03N/wPv7otT0uZjGMKZuPhu0p8GaFINGb4+iFglD/OWLmQsxvn55WZoDnA1/efW+PgwEiiTkyM q5kF94Mw4IuXe7a1uWXTk+MiwB4gb1EZs8lJWhfl7Iuv7tj83KzY+vWDus3Nzohd62qGfl3Svvyd F+qZFzTVewrJWFCUrqj0KO/Sz9z/7l7dtrYwIkWr1g50Pfz+ifGn2rHSaT/+qiQEGRYB/yzAUJFO E4vQ6tvZ74PeFE0Ailmzeu3Aavtd29jY8c+EFk2c18fYF5HCh27X9uve4SRmBb0vXMYev9yzj8aL 9ufvX7WVxUnDIU0bLV9EoQzjyKuMxusEw57JyDBCFmQjicYqzoPh+SFaxuy4kyeTERucT6mwOaky 8z/BeSgnQ/UzlofEz319f03g/JtXlkdsRsGTCffMnxg4wkrmOTgXXgq8IYip1Pd9/PVTjf3q8rQW ExsLhgxM96OvwHTcS2HusLbgL6GsQJYTAJ+NJuJgapIRbinhcQW2TpCqAUTH85scH7P/+h+/pWJn sMdOr2P7tQP7/M666kNRH71+aVHPgLOBkcH7w7hFAT7wKCKMqIwAJgWl4Z1rLRsrV4L4qG/0MoT5 nKgwF1Y9K8iBsefn3CqUi4myF0QXgqQN6gu0tQMr43zYBkLfdATE+T++/VS1rPDFUKr99cf37Orq pLTh/ud/9S+kFXbr6rI4huygFYrB/+1ff27/8k+uyfJls/WU55GxqVLGpsYqdmGhYj+4tmC1Rqu/ cNnpD6od6TOtrW/Z3QdNWVsOjB8u8I3A4Rh1xF5jw+UMzrtzdzUdlpxdmrCzixP28Mmabew07N6D p7pPso+bO3uqXJ8fnzTrNmxuPGuVXM4a9X2bKuGCd+36uRmbmqRdU84e1bZsYWbFxifGNanYNWII ObxQPvryqf3pDy/11ybubx/EV0i4a93uRXv06JHNzJyz2ZkZ61rbzqz44jjeW0vA7UFPK67EhISY LK3UuUaEf/HfEb8L/0rKJwYKBgBoq2qMcWV31jWUaE8+VlIWd7i/nf+Zs2wOpzw2MzjeaPFTcfZO oLyMoqwMDtdRkL7/+Rg6h9+z7xFaDY85f8M7x9D88g/3FRZjaGKyRudLD34mowxk7NyN0J4XCgfZ pFAnxyJm3vQvReZ8qmJ/9oOLDosYXbZrqp/D6GDQzi5NWlGKBIlQnuuex4078WATOIWETcYTCNdX JUlDSBf7GiDfBL8wCt/FMJK/LwewmwiF8IzrYERckyvML85Pd2pJ83hiweWhkpDTNdUTfXU2H9Yd SQWSEjMTOdvbr8mwUrgO/wvDFecQayu+E87xq48fetJsEtZ/yZ5vIoWMjHLdHr/s2fQUPLEXel6U QyjrA8uaG89b/l/9dz9XycBn9zeNCBHMhDIOeCjpBTW8I777JviI16KpM1qqMhmwHhdw5cwgxhUn hXtYg2HkabGjuflIGtT/63OEEvceb2px4JLHMHA4xIrP8t57b4w8d/r64W82NeUtsofvhwlNfdxn X92zt64s2+VLnrXKZDs2PzPTL6846fzHgcHxL9HjOSl0HA7FyfypTXifbR0SKqnEQzwnRMtLZxdU GkH6utVs2u7untRhx8crIdRPCwx2rNP2XV8GPiWxO/wsSXmKvVa28FVHxH7S4xgrLPIBcxq+J6oD aD6KJwoBEm4apU94nnhIhCfpA+xqdmpy4OdprhheC0RUzhdLargSGzn3Vio4JYK5uDAb5zny1LE6 QncXn0gvxAX7Xko7Cufhz3542a/XdSoOv6ugO6YoJhg4kmDyYpzwq+5PwC1hDMBA6RXIxnTvyZaq SzC2/TGj3AatfcnJdNXrUUonYX4k4+vhKvOB7kvorUNZQBKGlnTWbSmZo9KjeXhYwCEJBJSeryQ5 MGQ/unVOahA0sui0D+33n9y1ifKYPd+s2c2pGRnY+0/X7dOvnygi+fMfXZLKbp5Q4Z3ry9a7hmhf 2Q7brlP0N7+/az9+61w/lHDpkAO1/omTgZAGy0tGBPeT+JmDWjYExgABMSKDrdeTdl3HGaZXZdP8 z2ThacJkMqJUsFDYPdMh1euAwOnv8CPCg/Rn+BmuPdgalI83r6xI7vWrJ/saZOQ9JKccVCaGNcqH r3mc8TlNBvBVCz/ZcEb//Ouv79iHH92z7XOLduHsojqW7O9XlUhAsSAanUKhaDMzswqt45jHXTe5 Jz8vE5s0ujyM9S17/Mh5XdrV0x8Ox8DPU88Sw93k3/4P7ygTCxGTRqYH1QOrHxzY3t6+2NF95aeA w2F4+Tus/3eurmhRp+sO0+8fbyY9Ziyqra0deQGcAx/zwkJJHjrMcxIZ3A8LC1oDUipEwBgEiolV WIxnqlKytvUy7pnF2jnu41//+4/FB/snP7+hSgXWFM+MdyTc+NoZ0Yeq9UY/iw2twrOHbqQUkXTd u4teDWEkxei8Sm8XlrT7UnYxSKN3Wm1rGDAKaymp64sJKk8I9EQZmRwvK1lDhn97qqAs45O1qp1Z nlPJT7O+b71OR8Xj0Tnh+yTraJv3/9V2Zk9yXNl5P7V1bV3V+4bGRoAAySE5MxqNbI0dUmjsGMsv tp/0h9pPdijCdkhhT8Qs0khchuRwAwEQS3ejt6quvcrx+869mVnVVd0gNb6MJoCurMybdzn3LN/5 zr3bW/bBH57aD9+6ZcX80N65v2efP3phu7vrdnYxFHynA6lipWx/9h5sFHn76tET+/Crk+nKzyiU SPC37u6I9pUUASYUTAd2K3zdXzw5VGQFpPvZRdc+/pxQ+YaEBacVgosQKBESQpf4MZgczANURe5P pATH5nURuEUbcV7DoQywjtQHvsPpeG39wjnPTM8UN6EIOiCsyY7/5AsP+wIg/Ffv39F1aJhgnVis CDKcs1FgccLi34vO4tk2T+B8/+hZ1HAzqlQi3KYR9PHWTimSt68fPbbT4wO7c/umffbZFwmuCYGF iUhA4f7921ar1ROTML33dD///rdfKqTd7g4tly/brds3k89YQz6209/BuR59SNl+Z6OvLjxDoYXg sI7X8W/+fIEm8fhIc8+aJeoMNAQONLF6BFxgtIVigdlomjlFTUlspQg9la0vlazT7VqttqyqT2dn Z9qAtVpNfkLgE0AE5gcSIKHLC7CJP2g8cQqXdJ6dUwqEPZFNfsW7ALH4219+pr0C4JeUGLBJW+vL Vmn7+CNEj85aMjVZa35Ax+IjHCYuKEkXqpQK9vIV1DUOmnZ++Ti+RCiLYmSJZnBy0EV+saDtiyCh N9DBMBj0FfX8YDCSO+bdhzcFExG+r0iqF8nbbZUPc208Z3sbFdtdLSg38bGN7LR1YRtN90PvbMLr ti0/OSb5n7xzQxr/f/+7D+zezW374NPH1hkklZ9nlnzOS1gDgAOHRakfUK0/ffe2NI6vnrwS4yST RcQAocTpSx4StumHnz+3j794Ice8uI+2VxIJjepLeJX8JTnTMupxDLG/brh89t/AH5hU6p0hEDmZ EmqMmXtmf0e/n72Es+hyrt4Xj4+s0wchTCb8bialZbrJZ7DRSBhAcaIT2fvl774S0trHwOsHRvM5 MmLGBTHvvV5XcEUNh8XhRSd9Y47H4ILA63j58fT6kT18+MBGhYbeiVp6jP/9+/e82ETFTUR3tfii jv4wN0Hmm7z4LtYry7a7VUgEVGyzLA7pd66nCJqngWbHpzvMW7lybqVy2Xa212xtbcWGVrRxrmhr a/CvL8mnhNlEdMo1q5TVNm7gmKSM1sO/8QG1Wm3b3tiw5fLYJoOuvTrr2HFrYOjQWBDMLRHIiKnS 7AbcFONWr4UAEdWJiNgWYiFYf6d//sO3Ejj3bm/Y//3d1zIJ4cnCUU5Zeqrv0P+SKIUwUx3RjtuF tJ/Y91iLMLpLAF8K/d7rKafv8NWRjQtLViiVkpSXaqlkVSLb7YF1+mO7USibGKCi4FNH3fw8fNWy fq9rh8enttJs2C/+7bu2s+FReWee8Lmh0AxC2ool6xEc0LYaW7FctmretTOizEsUY1EqFOX/hnKq Ey3kwPunjx9Zv09e4rrl82P7T//+J3q/jIblOXnUeIuLAM2ATYqQwl8DzABgHZ77i+6aJD8vxWmG P8AjQbsC0rHRpVlVHboP7IDJurHdVF4XSaTffPtIQsJTeZZUbRbnLxGWqOrP27BXaSFUOkFtBYuC LwLnKI5B/BvZcHi2cV0E7WUbJ8p//vn7CYfVd2kO0yBDvWqffvlCY4iAxmymqISX9/YFBVwD7XSR ibjofbOO0Xn/lp9w4jAQ+I2mwuZgf0pesJUcL0LUxSJpU/HeI6tWq4K7RKc98zeeEMmk8OY08js+ l/DzvD7+sdtln9lE/lc0AMCTRPeUigNtzykVrz1gxLoDXAqEwSmAXSN1Mzdvy/Wqnbb7dnezodA8 67DdurDDV+cSHhetc5vkCvb+g1u2u9O0Tx4dW625Gq718Y04K0Eu+kP7w9ff2hgNxvL25p1dUSxF KBDXkHZFhPrvfvu5QL6YmPiE2GsoDayTXs8J+5wXKpdoWbFAKZF8mkrLSzvm2bwzxVFGloPrv7Fq dRLdAyqfH4qnsCJu7lXt2xen9k+fPJWQIl+4uVxV5DVGTOX8bnfs4Rs3tIedL2skamopBvmCXQxG 9tmjI1tfbygNqKJMFV+Pw8nY2tDNWM7ug8SfjO3zp6/s6FXbdrbW7dcfPJKmx71I81lfbSZCOKym GZNwwQZBNYWSAyEEgAvtRZS4QyKGA4VqAZihUrJIOCHefROhNpCvB2GFUEJwbK8t6+Uf3Nl0f0AI daqe4YsTkbaxgQkHf5cFG/sNxkYk/Ejufl+majRXETylOYKLPsTCkn/sDcbYAbLDvP5v//tD+9mP 3rA3b0FH4tofarUI8jLvcF1bZF7O+y4mXPad4mJXxetARUv5+tG4bMWAiUvuxxbLlwJ3t4e1sw7j eb60f6lT/fs0Rb+KzreO/5LiGzjF0T44IBEIR922DgkOjBdHLSXfU9aLeQe2ELuJxoCww4+LaYJ5 78Urxra+1rCHb95QdKtRWxJE5tbAw/Os17s3NmTuZN8YWvBKDWbY57JUfvr2kf27f/Ou8G8utPL2 Z+/dsf/6vz5Uegvvwf7B3wMUollfsu3Npt3aXbdf/uNX9td/8Y4om5m/7Y26tEEwVrwAviS0qbOz ll0Mcsrj64/Hoo96Z3tDsBgbDRw+JKmaV1GKEX7HSV77jh8Rbra6YlUBl8lhzv59dnQm83d7lQK0 mPgIxmEgIcirlBr0PefnQG/a9lzvUrG+MTVqAAAgAElEQVRbO85TTzFgIp7RB8fz8a/t39y09QrZ LdMHbnb9RP64YnaNT4V4ZxrqKAC5/oAqvl79Rqk6Gf+MVNOxl+GGlAytCWwIkprriB5Cc4Jvi5MQ vxPaGdqIc11v6rSYdubOT75drGW5BsGEIFhBPKNaE2VB4AKkcwiHa3Gx/68jKOZtlOs2JNcwWYTW 0TQhNqSaCE9TQcpAmZt9l1nQ7ey7z/v7dZ8l9xNK2s0B7xvZDdn+xu+H/8nOpJCDB1jk2J2hC87O xfcZx9dpVwUgYsfRRLZ2V+3P3r+t4q2fP3beKXjwAdASxYuFJFgDVK9hbuBHp8KTkPFCwJcS/nme S1YHG1Y+LRz6mffHBYEQ/M1HT/TnT35wWyZcohNMJvLxguFCgJJH9+Hvv7IfPLxt9bprcDtbDeUN /pefv6daBX/5k3vKMEE5YN3gG/3yuC2cWkx+hvEWd8vNnQ0JKZDmsKOOi2UbVpt21mtZY61u642y NUkE9zrgydzJXAxOIHx2o2LJlqmaHWQZ7pxG3YGh572B7o3vFjaHl+dOYkiNSggS0OIuxEo8saXc 2LZXq4IjMI7KBw58cHEKyVU8OHLUP6SBncHQOoOB1ZY82dsDAZGf383n3mgkbZCqVXMpTeJgz26C WS6l2YaGA8sl0QKkNMDU0bcnqsMGLkRsljlnXCB5EpRrvC8TQprELNL4aqGVwilcK8j0LfyJsAXT waIlogeGjE84XW/iuwnVQXTiZUPYgcPacygXwzAujVug0xFAVGhqB6Li70BTjQ1BetGh4sxo7rvN CgWuzwrzec0jctRPvGyuxXeKwiqgP9yMkG+qlAEVRt9ayigZiw/8/9Sa5kdrX4+RFiZTtPpatawA DBoVFYHw9WAKMtbMMS4NTHVYAyhiir8V5zTuAx1myXt7f/AfzcJL4rNxeRDJwnXym4++kTlHrhxQ ipisz5xx7//xfz4Rkhw/LvARzKlGAxNvItA1woi0IJ4JQh+hhT8Y9P3OaceW66DPQ9pWsWA7azUb 9Do2BMayRMGXmheQnYxsv7nkEJfoy8xow77Oo0nZFzC7N87ZRblqjTJU1wUV1u2FGqMV1v4YEsm2 2D5abWenhe+egEmxtGSvTjoSMTjNf/hwV/sZVAHWw+EJpeDou5cf5V1v7a1qjAhyLBcKdnDelsYl UxZ2F/PK0jFiBIi8QSFVH/g4AX5SxehAdtNMmxTTPpNLiyeIEEB6bFBSGkAi828xNlAvDRT73S39 8A2nu2hpcSHJ0cBQ1SOeaZHQyi70BKITXnT2O9wrli9DE8QEReM7b/Xk/yC/0U2kgafdjEbWHw4V XgUtLMaIGbTuvI2GYCEfCqFMonEsy84GyvaJBS2Ghjlm+Ky2QooLaH9Oe+6PtgCHOr6GuCkUpi8V lLsVS6pnxy46+5Pfw41fLiifS6etWARSSEC2JXluYLLC9dcFM6Zb+uxZlX/ROppeczN3m8Nxz7yp 0nShIN8OPkMEED/k+eGjYeNiJtLYRASXmNd+f2CP0ICrS86E0KwlhI5XK43+XgQu/vJP72uTYiKi TeHDZL2gIa2tVOxv/sMPXbMOzKKvDo7tsNeztfVVpcLFdwXfCN31wze27f37e9rowjuZQxhwM/zo nX2lMX394sxu7K3bzZW6kWI9HvbSjJHEXE/N9vTgMiXUE9WH1ZR8xSFQiaWS3dhZtY1GRYWCMeNI P4O8EAzb7d0VW1tx5gw09U7nQmBYQBZPnp3YSasnskK4uxC4QDy6nz63h3e9RF2qeRJscVOcYMV6 rWq98ciGaItnlLh3nCeBCg7L6saaoo8yCafWw8zCcYZOd+LJER58GIn5uEBFiyBtD4f6iQEVBZrH UtkrsBBRi0VGOV1IzCS9AZqaX3/4WP4EImzR/Fy0eLO/T2NvswjwaWFA+NWLkWLijqXOR67rYtHJ +0m5oNH3X3/02B7e3rKVpp/As5S/2X7xTlAwU3TiyYtj4bPiqTjP7Fu08bO/R5iS4qL+9AbKvmfh zlYN+sOjlxL28+7hY8LphaPV0fBs5vUVIoCuZeVnFsS0YHCsjxDPgTY79x3MtqixXKU1XSWk5l2X DThwID68symgL0m6mCGxcThwqs82SP6Ya8y22zfWxEziuYXT/YiH9/xIZdonDj5An7gfiP6h6VIr kkIL/b7j1LAgIBzc2Fqzs9O2Hbw8koaXWgauqeDv5cDkzEY4LJWroQ+kx5XsrTf35MAuA+jtttBJ JCCzxJt0ESxYrMgupHrRS3MRTYae+c7+ptLRaEBBYJl4/oRK4whWP4CxkAThCGs49qNSDu4VKGJg a4k5ksLiOZ5OBTIymntK65RGaommFkARtNu2trpuL168sKNXgEyLVm80rfP4W1tfX7MiJzUv4ORm lhRRJDeNmyKsPvn6pVgbqfyBqhermDA4XhMQkJl3hM8jmJQ/Y/FFIh469Scg4S9EwQp/NKWqYoSR PoCS5YRDSJDsSRVhJDM0vmCiknQdmBZRERdgnOa1RZuE50Y4wqwJRWNTc1rCj0QQAUFx77bnkM1j UOARfKdd9LQOzBSEl5DQl65dvGkX9ZtnlhY8F+jAlF8xKcPklXuSiF8mtUULXPggnOuLMwTjPSNL gYQWjvsr2C/mCatFjbFicyzi2Jpz9+RvsZqPAgrC9bhWe+W3tVFg9vR1TYucZbOR13nfZT618YPJ nKQTEPndbtqNrYZddLt2+0bTjk/O7eUxFC8FObK3NpyjC65zCohKeQ1VaBSNHY/s1x9+LUECKzC5 s0NwY2jqRP5UL3FiVaVHSVKF/NbUkkrZWi9EfUNqHU5wCsjwOcEFfmKqlUzUellso+xr0RsdnFm9 VlGAgn0cxz3mQabpdSElCPhLcC/4OAX8nQSko/LTLA5nE3EXBW4UOOB7Vq0s28npmT17caSE8nff vm8/fveObWysW/GjkGeEoABD1cfTf9ZR5A8bkzJgqM0/fdd5s9h48skEhHIacIxOdy9OCfcPwipb ogmThZNunbL147F9/eQowUyRrIkW4QLOSwxhLiLcGGxKMqE58DmZ6+Ro4dC/uQMGJtVctHlCpZMs uFCffQffyzzzkxOGe8F9/c+fPBUMgzAzd3eaDYCHqbDwnCyTicBfCDYsuv+803uRthETa0chbJ3V pLx6yYwfKDKLBexP9p6IsSge/LORo6bnUANlWxrCz79GHnS81/zxjX9nfjmkSDSe99jL2lm68PMJ +t5hMu7vc+oh5cuR35b3Ar/RZyp/X2BvuKT5Rh63THNslsMACPHDo8VzEHoIGBzFMceS8YERg7VK 4dCtNXCNgGidKWI46CmCy0+lCnjyzC4uOvKngqh//+GmdUcTWyov2aRQtLM+bgqS5s1y45GVUA4U AY4ukCC0M4cH5i8KB3sQptM7+5HtJB27mM3AH1STdhbTiVD33JZK1LGK0tSKygZnElPf7xfpiXg3 EP4kWI8DHou83oiyV1QTmYNTH0aOkMv48vDYznoF6+Xq9lc/uyvHfGSjKNZKIITP5HxEKtI5Ehix +WeJy2iibZ3jGNXg9L0Gn+rWDZ2qlc0NhD/6tPDZMGj93lDhUtFeUIDz+Yl8CPyOHKXIbyXciVDr aWoMDVBmrPmn6iHXnN5XCYjv6kjmPf78x3cVUPjw82fSSBHQCGKKPUpYB6FL+g6NAMSnX79c2Ier /HOzjXHhnaFUwafFmGZNwClhIHHlwQSlp0D4ZuB2MBtT5HlWo5C5yHdexywLi54nKJUjRhZf4z0u jUPO/YbgfpaWYhpQNOHTwhyzgp0DErYCxoKPuv2RsG4crkKvB0wcsBYEIt8GuCzLAh9JOOn93sGH pmo0CBdPncGsAjhJCS0+u+gN7L0H+4rUJcnmuZygNDizSS3pkiFwe0uWhVJyQhpM5HBHORoM8B8N bblZt6PDV1YBewSzJtVvAIiHPiFQxlgsJZzpAaAqTKcHUCK0INvYhygb2SpAXJuNwvnv/F61CtQz nnrHmOH2iIdApCyanc4YYc7eX1q7IWCI+Jvd2GzY0+fHYhQtcWj0IfcjncgzC4B9LC9XJG8Y77// 7ef29JBSght23h9bqWYKTvCdYn9ctGpxZGtrTaUfSErDdBC0gXhax44mvqzQOfl6ykWpnqRF4F9x 29evww4nQifNhLJFZxfa4HwGMj2WrYJHHu0MDiU2NuFoNC6vF+e1+mLkRpORp5gnJ95seD0rTC+D Kmc3ymy7ysGbvZ53JOeMn7hpoOcFYAuSGt8SCzOq0Xw/S/6W7ddVz17Ud1I5VP3n5Znd3PVKyUm1 5Myl0xpVRmfIj208mijC1O32rUToO6zhhG7lmj4ktwomIjlfShP5DqXTsvfF7KdoJhopJrXWUGC5 xXUAhGC2HxxYwGgg0Ds7d65zxp/oL8JktnEPnO8UlcD1wJygVSiiN8kJklCrUlAUM35kB0dwwbX1 HGrjganjO46hkhc8xpOVMcEeYO8owPP2vqKIXBfkYdJEvIvWhmkJxUy+YEtwdmGWZXJvY4Q2CqVJ JKHMpFap9N6UEE99bkKhh4OefoG5KwbK8cwsJH/zCteeSN3p9DP9uGIOM3+J85PPQ6jWVx+PT07t 4qJro2HdGis1W0Eow0L6/NieH7Ss1Xll7zGupaISyylbjwz68TvkMqPpucCUCb+9CTbkxJ5/8dLG k5cCw4F+jhs0Upk6N7TnbcWqwc4NXtDm4dSnthmMgn5KT3OM01hALrVdvWOwswmoXI/GxQ+DS+lu fEYsXhZyFAARPxUXfJzYOFlRRc7+frZ9F+1qnvky2+gb4FRwM0Rv+MEfgLntNM4hjy3gSub147tq ejBg4iDFtwZgEj9cdK7OG5updwoZ+O12x549e2k39ndsZdWLiKoq8YzIuq5fElo47UHTh/Lulwtv XjZ5s7/TAbfuCPPs9bOPzo4T64D3Zl1B84uFsLF2uTpR/A735hqiYxyyziLqkTyEHYGe1UbJqhWn Ai8WSqomDdDXMUHR5+IVayJEBD8lAGWsgxgdzD47+hLlTcSvM3Gznv6vlqlcM7bRct2OX50ICR85 veK6yCLjLWE8CSZgGB/2J26dqDGTD4rv2X2oAztp9a07cI6uXVWQSg8x9Sz4DbIQCNfQ08h/WMGJ lMoFrjbcNowR8yAz3Tuv9zjtTOy9t+8k5H2x3d5dFyuM6iAigw7P7enLE/ubv/6xfOCkSbkbxoGy Yhy9tbcudCuny8nJiZ2fn9vG5proRa6P+uTUUTF/ombvripJM34NIceAMmgM7sujc5lRaExMKJ+j rmIGxohcbGhU+5VVW23UBHVA60IAUG0jalsI3kv+msAJdI1bZer6RYv7qnef910+Q/hSfZcFiDAB sApBWvTxXRZWvgxisBWtCSGeLXqwqC+Y5xDkIdzxp/DDwkQ7vc5vp1QdmfHOQOCbIdun6bF4PcEe Ns/YRKJIE2tFeLla/bLGc/kebvJe5ezO9oumA0xmlmOxXufQaXf7itricOeHdciGgRCvVBxZsVTX 4aggFOjwUS7wrCdbVgIarYo5gxARnOH2Ovsm5FxmNPw4pmCbQJVXC3mrF90pftrBfeLJx4Csz0Lh Ue9zdHCn5pbWdqjqE7UhTFrYSKHOQXshv1Eke7mitft9u+iNxaZwZx+Cv3h4+pzRX6emSWmfLo+9 X8/aRABiSWHCwdgCSeRvPvpWEKb7t6j14OscqnMVUW3UNJZpMCBl/OU/LCmKo5DrSYk0QXeGYyuV vbQdChJBOP6UlAC4iD9oqVK19VLRjl85sBJnYJa9cd7kIzwIt+OoJ5RLGgMqKo43NC5OLwpGNKpl 2fa3d1cV/mTAeHEKSp63uqKhzdLgZjclzncaqj9RCz7FlIQKJ54Gs0N7nbC6agNer5WlKuqiyY0n P74rctcUUZ3LARY3oP/rtNURrAPwIYv3dYQuJjmRJ7RRvsszttepObc42iZ+owLmT80mq2blkCoE u0BWu/ouGl/ynXzeDg6ObHV1w548fWYEibj3gwd3piKA183BvM9nNdLs71PYzfUtOulj4xAFAd/t duz4vK0CKWw4wvkEUPujYSpQmXMExdDs8bdem/DNmxuirgZRPg6Ofi8w6jAb+cnGYyVNN6kxmRta BwLIkwtBakB9o11WywU7PDwVGwL4prjOkoPDvBOuSXuCNgoBfiH26tZGQ1xVq6t1pSgdnJwroPbw zoYQ7bhlEAJoYpHdwSOspJEtiaNKzA/RvZK1XKAMOm4rYwNfHkIOQY8VgUAhQLbebCc7kAMbLZLi NLFYDO+BnzKCammk88CyApECyebIEnI9kUnck+9Sio9IZZENRdktLmzUl+z+rS156w+PDm15sCyh BVf5vHWV3aygxn8SipMymEhJTnwAZ/hzxN9sYwkg8UQpMXpJ3wMzg0rIZ5RKdyGcc07zjObFPfih z8Ad0GJuuCz7zu37bERvs7HRxfeh/0QyQT9jl0fHbnKnOTguNEgmCk2USSMxOfvs7CmVvQ/CnoVB wASQLpWtoanlVFrEySVntqqn5K3bRfgzL64ZXH5rf1cluSbn/MwoBN4q3AZEmwejnH3x6JmNbMk2 NlYFICZgAaNptkX0tvwtSd+8klKi0civnRXu/veoYDNmRMRabdZVb0qwyXSbolt2LBuHSuK8DpVn jk7ONXb4ut7YX1Vlhj6fB82Nu5KTJ5dXPmdvvrGVRBndX+RXyccUHNxD8vW0L8wODs7tcEhxiLzS XjZWq/bW7VWV3SqVcPIPNT6np22r1Qbae2JeGI2TSBl/531FfjcaWrVaETsFZhMgUMcI5hRJV3n6 zYai/gfHF/byVUcmGEoKJhxCmfEBl8gBi99oE9fAjC/Y+4CAbUtIEcmFagofXayLSfDOMyJ8bd0V DVV1KoEZUw+BpLzeEN1H4JKdAGU5+5tCGGhbuFXevLOpvE7YRNhHRZJEcXgDuEs2WrVie3t7dnpy KjK35fqyMs0T8rQw66k1Nm1+4IDmxaiwi+RlE+Lg9GjKtMqO7wVBhWnJ4DKw8T4IOk6dqY1DFdrl iqqCQHPDaZENBMThjfXeFkEFrmvzr40CI3vqXP5eNlWIU1vsiUSnZm43ry/iBtpwMCjpJAg8D0yE e17TXzFENKoyDSitxMZDSGQd/lPPA9j48pXllypWrYXTdU6LtDig68VKmREeHkVyKVMmAkyS8UnH vn76OTyb9lc/e89arZaEGO4DRdbiGATXAX1PCueixVCOCg6rQNWDNo7G6GZEgMAG2AJjJh/NWUfr QDUpw9hGiEOWBZ6oHH62crOi0DrXD4Z9pZkctTq2Q6GJ1Zo0ElwllSQB2oVSZwTMNjMbQy9dNzWn QXChry5hOskqztmP7m9PjXG73bbf//4zCR18x+KcIghSKttXXx3bzs62tKgezvJi0ba2/N9o7MvL JPMXk3XJHDm3vwtQxov3/9UHj70egXjo1+yde3vy3eldegOZtWR9ABo9Pu04a28oe5+4CCZoZx2N N4KN8mHQMyNM0ILgkofMkuRvDwpkLQ+/B/ufwssXAQ8WT19A5L/9+Ilwlqxdcm2/fnYis5bMAXzD FHbd313zXMIImswufKTi+sa6fByHh6/sm+enOolhEVSCMtGNTOl0RcEAkcrRlk8SSPH6s+EIwUsT wHavEoL173HSqOJuvTLVj6nJn/M7Px0n4iaKgsG52XN/FH/VfMG2mLdq9ndRe2Is8NFxYmDSSsWt lhQRW9Q4KRkLoqAU1ERo8Wz8BXxvtkZfNJ/iM1moVH7GaQzPF4cGBwNVj2Z7TAmlbw/b9vD+qgIb iyh4EELSEGc+j5kQqfD2jbK7vWZLeTBKuzbod4R23t/ckFoPkDH6UOJ33LHM5nbBysalNHn0N/Ee 5OsJwhIDKnpX8H4U6jVr1ppWWVqyosY28r47Bgsfl0CM4AQHgwCyLQkdPkS7K3ge5c39dY+ojTyH jtSUVD/zTVgrZsfAU1SiY3z++osapMNLsg3s1cpKU/7jb755IoDo6empra9v6LOTkzNFSXnuycmp /eIXu7ay4qXCvKVRfDQg5gLti/3GfCGYlkodQSvAVI1D/UaEOEoFJh7CjEo5YBpjubGsJhuhKqSH MfZwnqExQrjH83DZ4AdXkrIYeh3nFmuWZhtCCaVEvueMbOd6irsgzJSSF/xwwry1O+rnD+7vWfGn 792+chOjqu7tbYuw6+z8TKhceJIAtE1VJwnfUfWXPmFdz+diQRHudyT9WIA00gqAAOHAw2yKG/C7 aD9sLDYlgw7OiyiP0zGXr8RbJUso49C+zkGN5ocWOA/VvsgJn/pgfDKo2PLssCb7n/QNfCYyK2Kp pgDE5Icx4z3qlSWdeORmxd8TeMDMQzjD2Z2cYXPeEc0OPxi+BOaEBYDPMduGQz9E0Hpmq05nW7aW zXUt9e0FkyxowP4OJdvbbExFt65rCHkuJQI7KxD8/nDNO0BSLJuYUVPIRtdABuOR2AacTtgrH7Gn ygL6R9NxNtCRjbjGik7x1g5tIMUEXJtrmgHuEL7qm32x62Bzc8Pa7Qt78OBN29w8tuXl5aSYBhFc OK2aK3X5s9rttsrKL9omfviX7fDVhX3+zaGinrsby/Yn7+zL5Dtr9+3bg5Y0tUqpKNMTSyX6k+Rz SoIW8XBOoUKMP344pTMBvg3paQgYXEBoagQP+JozW7gJi2/MGYYdVoLl4PLKn8v64BpqC4hOnQBN tSTqHH545t7mikz1Imr3PDzSLKixvlyTqXh+di5Jj/parlTk70LgxGs5iQGh8hJ4/iM6PIY56SkY C04AJC2pENOlneLzU3+Po9Yvz1J0bPMDAypCi98pZ2/mXa56v+uaErcbVQFChYehWGodPqNUSOBY 5/TO5jwiVDyi6SkzRFEJm6P5PHl+rDESU8J44hEpBSL68gsQyMCeF7FgiCJTUoy8NP7N85k7TjH+ jL6+WcHFAkCwU9WX8ZbjMkTUuIZ0Ky/8OT+69n3atMkcF34qwBJhHg21K+bBNST8mdD8+vwy7mjw vLNy1lQNpiQmTdZX1AhidJI92J+MwfBbtQiTxeU1MQvBSH4/FdaNpk7sW1rZCLBnGgWOQjLVfhYN r3w9d29rDjY2NpwcUTUfJ3K8uzpJz8e2uekFWBbcSf8Ht/SD+9t2eNq2wiF1BprJwYjZzF7d31qx zx8fWq7VzRACxtQoT+/JTkncixx6JJSjJBAcigcsguoYsG+xoHXphV270rZ4bfYn1gGCUdHFKC/C M5hT3BbRh8kY3Lu1lT1vND8U0pjGEswM5GwT1mp1ReFp1NZOp2cjSj/lC85rHSaYMC8OVjhxhF8J fgeZAeG+bKTjs7yiJJcEFqemFqIPFBPoiZKLGyovbA/KEsexHzJG0pSNrMPaJxA1uAoNSFjgixqc 1QQQjvoXOkUB3hEsUBIp9xp7NRAmherZDvLLy4lIUQKEMteRksEJBGCW32uRBA3E1WcqALVVIRet IvKPR6c82GuEGJorJ0/02eDzQhBmtUX5nDKQj8gaEF0AkYMrlpm6hrXmX9RmNU9Za67OqM1jfog+ J/qGcLqxvaqTGa2cKzlAKNLJfJBIzLW9XtfZa4uRZcFzWqlYXCzlxNUUdeTsOkg7dzkdZ+oAUOKg pyPFfya9nRLO4e8ZbXDeoUmLxSK8bh9Cj6jfRSaoQSAjJtpP0o7O+bvfx8kMYZugniYuGTRaNByC Va3O0PqjkXxF+JiJ4GPlcLBiRaBIsAY9wu/ZBvGQQSghhLguHtgvrS0yRJh+KdlFw3NQOG5bc8/d NE4UGXOOvdLWwSuPXsKEgnZGah7r+ujY3UxEXCNRaJwD9vdcgXXtiVcqKhGx1bqwR08O7Pj8Qr6t pdJSIrjQGNC08E1lJw10tTL+VfOtJ+GGxEb6MmiOwJ1Mq+MZ5PUi842NTGoMTkBCoKKnQLgoZcHz t3yB5BJKWv7OCYTmhJaCqkyLNK3ZvCylOISsfyYI57FCy4HjnElHZeZ33It/oxEAhFNCLZunN9Cg K98t1HhTTiAJvzjFcx69ktqNKhywMfFEig5kvsdph4aBWk7ppehr8Al2f0bqbHY8FL4sfAFc44vO 80fxYWB64K/0hPbXSz6OJu/r2nbT2orjmHBLTwdIpnFW8U+PTDlbBQtcGRMqtBASajMVeJwuxzUC Nh/c4ZtLMFpebtJ+MkDIK1s04e2yFpW9H9oF65g1kGpjWSuVtVXIHMZUGupbr4fP7tKoSYg5X/ww M5bpfV1QRvPU/yyX83Znb12aEM700RhfIFgvUvHOJRw4PBEc7BH8zPQXbQmhtbu5on3BQRqFBwct igjrOhI/sreo5oMCgoCMeD4O+Hsw68oUDL67CeuupCwEqnKxX5QbDNzjrCMtK7K3ACeJjCgOmi0o oDCXIvnSkM3hK9Iiai7bD96qWeu8ZZ1ux8rlslUqhK2XJIjYdJzqND/BYYV0wJhHNEgtyOkaHKsr 9SW7c2M1mFqXC0Jc1UcL2hT5Rw4oHU0hdbMqKEUwEJYvj+Co7mqQGFhPvoRgDEGAo7aYfJ8J5h7O RuFsDGhYYrYIbIoIAyIxHuEqJflrsd9OB9PwMHDIB7z8OtOO/UUNvyBCCb/drAqfnbdossRrmHSY MtpHLW3og4NXtr2xYoX82Dq9rsjYKiQEzxFEl8woBiIbnc18Z/7BEuYhbPpUQM1jKk35u7JFXWn4 95gjonq4F+K9lc86HNso7+SJrW7XOAdW645Sv6otMgkvX8chkpq3sf/Z13x2cC4GURzMqSkctSk3 x1X2S/sBRg9fW1ntLD4tPlMlvQyB7JVusmMdBSDCw2V3GNeC2cZayTbWVvSbvW1YGpzllsMvQlQQ Yg57aHnE1kx8bqpyBfSoWZMFw/p9Q6XGerIAEG43NpqaD+6JoAO8inamPZzROlMZAj4TwZRTpPAf Pn5qP//XD4QSwH0kM1/FO1wj87WMzUIAABA3SURBVMhsgHRgPs6LMmXV4PnAyLSx8ZorDVUFQXCB lB8MXGghQWdhBQmTQsxbC8+gcAB+HYpQNpbLMuu+b4sWniYwwzwQWzQr/uNfvK2oGxqGJ1P7CQb2 iYiJJ38LF5zgjOaORWatM7jU9iN3irE5PT03W2kGkziU8w6cRZi80xWnpxsChcyBqAFEjY7vslgi M+tsl5J5DP/zTCX/HYsQTnmSzzkt8UNur6FhluSIbfWIBOVUGorcwMXNnd2UTJ8fuEg1EBdSsSr4 xM5bHSUPI9zRqjEvsmym86Ov0wJz2owMNLoDB0Q2FYwYW6WGhpOpzrzoTV7Df5ftE3xieUXb5h+g bG6c32nlYy/NFQUW49bvE92e3W/T2Q/ZNoI7Pe8pcVPmotYoAQxfq/NM3cQXHf6tIi+ifu5KK4qV rfBvwsrKXnDHt7tzgMig0UI1TeOQd078FVlQngbkEBMoaZiDbtdrNDC/MTUtClkEJJxluILee7Ar 0xRMWjShI9d95I2fiJ+MNd9NNSwiCpgsUuEwzwJla3ZSLwmfzCAQxVhbX7Nut2et83Mhb6lph8aF yjl1giX6cbo4EVDn5ZKQ7KvdqtX2MxEhCdNAxpao5PMjLz4m7lvKXWHGIDRQeRlQfjhFaAz67z59 qv6Cyk/ocqdKQsVnZTZMeCLoXwSW6tbZxJ4/e6G9quKiwDowFVQOvqyin82Vpt4TAT/bMC0Q4oBp 46KI+WeYHHGxZN891pabKkQqf0oMVTtAMpef2OZ6zXrdvD1/dmCF4qowNMXJwEbDvF2MXANEmyAC VykjVGK5ME+81aLSc/IZjThqRf672D31M0dkbmiffvXcsyggd5PaTxBhyWv4vUYGwjxtzAXoRHzn 7XY3KauOr/Gqw+8qzWqelhiDBXLAT/0+1TC9sK9vOjdpConZhzbl95z3ftl3S5kR4q/GE1wVaCCu Zfl34vjPDyQtOswI7pDyRvpOWoAF14TZ/mbdGtWCLCQsJbi8EG6xZB4sunf3qW6Vk/DCjSHereO2 3dpd0RpnHf7j75/KTVOrkK4T38qxcVyPW4bA3K8+fOwBpHB4uzDt6d5aZ0pyJ9czCCxeggohMRRJ R0TtInK9pStNwzii8TMAcEAhCNVeKCw71KIUQZ+iYrCPOm6F58k/E/idUBGxhbVRX1ChI28rMDZU SYVwgTW7VrOo59gdKr1cpeELA7LgVEUVJSeKMmH0EVAb/fRKI87eqGfNMzJUby0nXE0J6MZkYrdu 7SuCRKGAmLIkwF6na4cHR9LqGK/t7c3LEhaQbL0qxPvsc+Lsu2bsQkhAysHAS5ULC8O4Xy5YKwGq tBE2zyQcLJymJsgK1xNQ6Y7A2+RUoqpQKtqg17VliqkG/14UiqmZ58I8+v6ymrs0oH7fnh+eyoz7 4cN9zfnx6YUdHLdDlMhxXougItnfeWTTN1m8nIAHMI1WB/qSicwMlOblm44Wfx2hNWVdBHdA2p/g K/ILXeMONDxu6mUP4Rg5j2ZfWoThsgk/+87pdZf6Ool7LYJFfUNHzeyS2T7HXYAv8/nBucaQKCFa UWRnEe3Q2HNZ7+2vyfeLe4DyZwA3Qc8zMsoquOjpuwg1QKUcNvii4K9C+yKqh2ZGJ9Ci2dv0Bewk 6151IsdjoeHfurcr6IWbYC6PkAv6HXjLEyy3kRXBXnBSIxGJHpHFziQdvGrLt4TDGH8Oiz8SeV0H B0AwNZsNCS/MRIRX1GosV7RWd6wXXrqAecEXOBKcmmeORHZ+dxqRRgQZgpSXjrlos5OZ7dJVYWSa MCDBj5ZdCP5lZWPY+w93ROmMOUi/I11MaiWl/iH/muNtEEqNZsqnzhh4i4ymvslALu/u7egEUZHS ORWLPF/MNaapNhWd8gRmr+KLwCIjn3LoYKvSAraxCdUdnNyghrm214MWmNB5MRSzNTEGxP4WijUZ xRdtuOT7Cq4obSbpzESnIb4NBwQW5MAFb8Y7obkfvjrzrP7u0N6+t+frRBpQ1WEWwYTP5mjG95u3 3lQwNpdXFJD8ONbH2sqyPbjr98aU+OLxgXLe8FfWKYIwB9SZHRsvQhuwbbN++LjztadyU0IiNWMd zY1w8gK2mDLTt8i+U/rorEBMr7387pMQNVa9Ll+DzFsO5giCQWNp44vAv7HJ19TrC2aDVoTgcZYF D07hbthaxTVTVcSavlRKOTs4PLWzDni3VNNmf0aeMQQh8qP9zYHcFTAx4LTnQEI43b2xpj2M5gY1 OYIKGSP/dhDESnyXT40KRLekzcEldnRctU++PrSiUzucKoEWAKbjedAsGpKasCTAda3F0RtIcDmq 3F9wVm2WCqkIjm82UPHLjYpAbxSDJF+qUSnacKkQkq77+i4lhVoXHb0Y9jQnrig3RmOZqyxuVEhe CPApwLKFE7PACZ0sTHFv16US4y9zk8k/Y7HFSNzORl0Z/DhRmdT7tzYuJe8mLXE7uL29qMVIDoKM Hwc+BsqSjJHJAdLuUBG3N4VJm5XGfNYf9hOwniJKg5GqDWNmxkuJnMF9lVDPDMH4jBPz1AW4E/FN gyN5Bqds0RrLdQnH9hABsCQgIjmoghT0+/IhuRPX0eWYHRJY/b58GuSLvfvmdgIi5ZmixV5GqKe4 KTcfZ3b6nAlF+LL5ONxiOlP62VhCs7tU1AYhzE/J+nSyUnwRsAHVXAym21w/UtKvzIQHzTZWUZ4F m87Oe0yfUf2AkNIUC5Qo+HTcDqlGfpguq+JzFgidS3R7PytT3RBBc3qOxoPp5qa1rJhyST6qLKmA Dl4zOzp20DVWFNAd9j7+JyLt0tvyJWv33A3RHYys1RkJ3MkagiBxf2fNVhtlyQXMYMYZAYWJyM/u lrMIL9dMQFZXOpZUaBmK8e21unIZWZsRJ8IfL4/bUpLwnZHSR1tp1uxnP7prRZIYKV5Kp/kwW20F LYgyXHA8I3VJUO4VYVMEfu8mHXmCgCJ5EAIFR26kQlZVWIHRara5tmatdtdeHJ5YbjyU1kRh1XI5 5chBs8EJiLBM2SX9Mwbg8PhCLyvB10JdJPeoklSOSdZW9u+B0jgi1Zk01F3699WTQ1UIAZQYSefY tOKrV3ku30wIad4Zfh4KwMb7ev9mzK3MCYrgo3IukavoX4qbNJYQo+FLa/CcYl5aCiBUPscRSfZ8 lkkyq3m4djXUIEX6DoRUaamcQBVAM0vI9PrCIFJkokxqBZAAzP9iwba3101+4cDtNAVN0r4c2Zia c4WilWpVO7voqpbci4NjbXIELabFbYqSBhWNhUg0UmYmHPhvbmZSPq4DKntAIjG/Fow3whKT0jn3 m5e0l831ZeG3vvjmpTMJrFRVZAK/3HLdMzU4iF2zcnI8iPvmtqTLoUxWCIK5bzUKq4x2GPqblbUI E6rKoKHwqw6a8ZgiGH4B2ifvzDoFwAnc5937sT7inM4k4+X1DdiPn3x1oH3rWSYl5eE1lz1iGA8F MIAoAuOQXnN23pGDXDCZUkFCkmAPP5iCmHDHraHtbq1KiwXIu7vVcNE5JkXPKZEIsuG456BAcRkO xmIPgVMPWUDl6mcHpA117f2H+xr/o9OOXDCCN+Cvyuft069eKpdTUVYFmRhzChLvuA/rTwNf+2xj MiMSlpeANpmBICHxKGzE/sBvyEQ5ZfFI1CgeniRf6UIheLQuBjCX90xyMFrHZ23b21lzhgaxM5Rk SyMc/dRNG4ueyB3POTq9sFNVNxl4HbqKp/co0lUu2ck5pck95I1bhIWN5Adb4iDEFSHjIR5kksGR UMo+jcBEJ3o8hX1h/M9ffZEIrEuCKvg8PCncK4YwVs8PT5SzhoCM4XDne3K2TEchT6w+WrJRzqRV YV4xfhweBAPmOZt1/pPPSRQlVLyOviIWDxS9XgG1IA1nPOxrIcl0nJSkVTkUYCT/1WgyTDiRwIQT /Zt+PzQJsGsFa1bL1hmObWWFcDeVjzJaZ+gbcxqLkS7Y+XMFlwsbD2dfjpVdvtaJJccJCp68M5zs lC+D74vxxeQU8+UZdN0tW2nUbaXBnPgBNg7vJt8Y752FDFyBMUs1Mb8G85Q0pyiAWMesT/YOwgfQ JuP34M62Nj3aDH4eP8DMbt/YSHzGaEz/8PE3Ehpg0NhLp62udeG12oJ5NfbBUpT6cCyTq1yqyfzm viDfnZI5cq5N5FOmSIfj2TraKxzIAJ15X69NEIpyrNb1XDQl0ZlnAk+sM+6BxYLWyHeQF9DEAKRG FgjBv1KTwoHmBpCcPShXVLsyxZYa/YUEAfgeEKXoD4za8EKkuz4s5pXWkW1Iwp1NKtU25OlHDez1 /WZoMZiPkQtenV2ta+LAdbz/1g3baNZE4P/05VDRnC+/OdBJuLG6LGHFJo7fn2f/8wIMCpS5DDQ2 M8JLJkhnID9I+2IQcso87M8JjMDkWgQB0psGeeEnXz63mztrMlWzA5eTiTadGrS6jE8majtRqKVO 2WCKS0A6ZQe+r4YihoMhEdiy2A5mW/w+mwp/AEJg1veUbpD02V4lF8b26fvI1Ftynw114zAh6kTl GFcNSSqUY3RT2y6jARG6jwMfwYh8R4DX3Niq4GJWlmWy8l5e7j13PYYJQjqBIOe/W4DuJAEFh5Kk ayD7PYQitMWPnh7Z0xfPFeVkHtGWCdj00SqDJkqBBRJ/VxsNhee9cMRQBR8kqF4jmyI21r3TJDtQ l43JhkWrgC4Gx7S43p5RB5HrBxImCKTNNbSXrnwzRF7femNHQE76iBZI0EA4pWJB13/0xQs/qAXH mcyts+B9Gqiq+NYqSc5NmWkUKvb0Ny8PNg0LcfcNZjvvgaBDmOBEx0zEjERrY+86Dipl6Ih3QPhz j2iVae2zh8cT+cMBj5IH+7Mf35UmjGaHUKePyAPuifD25O4Ul0cN0L/95WcKNnlB4AChwQl/3eRc tQjZ/DjPrmrK+6qS2NiU+Si0a21JnUE9RxUlYvH8sKXFiQpPwu7s2RYz9NWnMHT1StHu3ihpIukm C6F90bfNtaatNd2Ui9iOjTXn3eJEQI3lM/qv0t/dvv6eMF26B9irf4hM36NAb+xvTvmnQB5HX0Qs ZQRyuTsYWLXiqQ31atV6A7fpca7PE1hxtgUoTaJ6Kd4mxedYhvqWaKDZ+XlHpjRO5dic291Hqt8P KnUmGTmbSRBz42ZTVCSyAvjWtcDU/AAThNMXZoUhfE9DGAKgf5lOiM+8XKK5JU/NhOJnW8QqRfbL 7H1mGxrE7b11jS+b79aNLSsVinZy2pFm2ayPdJD2h8ANoF+Gsw3fqbs1kj7M9IO1FNeI58ZR8MM3 N2vsxnZDB2UhN7Zur6/Ni6/nyUs/QJXQWylrM//+yxe6J5sbtwJ9ffuNHV3DQeoMvO5CODk/tveW 9yTE8N1e9EbWHzl2anPN08H+8OhQwjrOB/3HzMLXSo2BdPVQZSedX6+wFLQtUZZX9cPaADKA5YSF wl5F80IwIzxROpReFtdO+IPv0C/GHYGNcMMi4H0Qku/WK+oX6UHg+v78R3e80tBwZM1RRYKRufHk ayczhHSQMYahZAqjGObo/wEOEIyMsDvBggAAAABJRU5ErkJggg==