U.S. Forest Service Automated Lands Program (ALP) 2022-05-23T12:28:56 083515 S_USA.BasicOwnership vector digital data http://data.fs.usda.gov/geodata/edw/datasets.php An area depicted as surface ownership parcels dissolved on the same ownership classification. This data is intended for read-only use. Basic Ownership is a commonly used base layer used in a wide range of Forest Service business functions as well as those of other entities. 20151231 publication date Complete Weekly -150.007671 -64.734329 61.518990 17.738983 none Basic Ownership Owner Name NFS Lands Land Status USDA Forest Service ALP Land Dataset ISO 19115 Topic Categories boundaries planningCadastre None The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly. USFS Chief Information Office, Enterprise Data Warehouse physical Washington DC 20250 Please send an e-mail to the address below. data@fs.fed.us Microsoft Windows Server 2008 R2 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.3.1.4959 The Regional Land Status personnel are responsible for their local data stewardship and maintenance. The overall collection nationwide consists of 100% attribute accuracy based on currentness and completeness. Quality control measures taken: this feature class is populated by an automated translation process from the source feature class that is edited and maintained by the data stewards. Only stewards with the proper role grants can edit the data. The application used for editing has built in controls to only allow valid geometry and domains to control attribute integrity. This theme is current to date of publication. Generally the source information used to record spatial locations are from: 1) on-screen digitizing with a georeferenced topographic or image background; or 2) GPS field collected positions. This data was published using Feature Manipulation Engine Software. The spatial features were extracted from the transactional database, manipulated to meet the desired output format and published to the target feature class. This data was migrated from the CDW. The spatial features were projected and imported into the target feature class. 2016 Vector Simple FALSE 0 TRUE TRUE D North American 1983 GRS 1980 6378137.0 298.257222101 PartnerAgreement_PG_02 A collection of geographic features with the same geometry type (such as point, line, or polygon), the same attributes, and the same spatial reference. http://support.esri.com/en/knowledgebase/GISDictionary/term/feature%20class Feature Class 0 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. SHAPE Feature geometry. ESRI Geometry 0 0 0 Coordinates defining the features. Shape Feature Feature String 50 0 0 PlanningAr PlanningAr String 100 0 0 SHAPE_Leng SHAPE_Leng Double 8 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. SHAPE_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. USFS Chief Information Office, Enterprise Data Warehouse physical Washington DC 20250 Please send an e-mail to the address below. data@fs.fed.us The U.S. Forest Service makes no warranty, express or implied, nor assumes any liability or responsibility for the accuracy, reliability, completeness, or utility of these geospatial data or for the improper or incorrect use of those data. The data are dynamic and may change over time. The user is responsible for verifying the limitations of the geospatial data and for using the data accordingly. 20161118 USFS Chief Information Office, Enterprise Data Warehouse physical Washington DC 20250 Please send an e-mail to the address below. data@fs.fed.us FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 PartnerAgreement_PG_02 619138.465212 741122.269874 4359231.974402 4463075.852700 1 file://\\AEI-MP02vm.ascent.local\GIS\Projects\2024\20240064_01_SIG_OPRMapping\Data\GreatBasinPlumasNF_20220061_01.gdb Local Area Network 002 0.000 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.8'><WKT>PROJCS[&quot;NAD_1983_UTM_Zone_10N&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,500000.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-123.0],PARAMETER[&quot;Scale_Factor&quot;,0.9996],PARAMETER[&quot;Latitude_Of_Origin&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,26910]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26910</WKID><LatestWKID>26910</LatestWKID></ProjectedCoordinateSystem> NAD_1983_UTM_Zone_10N Clip "ALP BasicOwnership" tmp_PlanningAreas T:\FS\NFS\Plumas\Project\SO\DixieFire_LandscapeAssessment\GIS\PostfireLargeLandscapeRecoveryConcept\Workspace\lyneecrawford\RecoverPlanningAreas.gdb\tmp_AmericanValley # CalculateField tmp_AmericanValley Feature "Greater American Valley Planning Area" VB # CalculateField CommunityProtectionConcept_PlanningAreas PartnerAgreement "GBI" VB # Identity CommunityProtectionConcept_PlanningAreas tmp_ClaremontUnits T:\FS\NFS\Plumas\Project\SO\DixieFire_LandscapeAssessment\GIS\CommunityProtectionConcept\MasterData_Current.gdb\CommunityProtectionConcept_PlanningAreas_w_Status NO_FID # NO_RELATIONSHIPS CalculateField CommunityProtectionConcept_PlanningAreas_w_Status PartnerAgreement "Covered Under Other NEPA" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Status PlanningArea "West Slope Communities" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Status PlanningArea "Greater American Valley" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Status PlanningArea "Eastside Communities" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Status PlanningArea "Greater Mohawk Valley" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Status PlanningArea "Greater American Valley" VB # CalculateField CommunityProtectionConcept_PlanningAreas PlanningArea "Greater American Valley" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Implementation Implementation "FY23" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Implementation Implementation "FY24" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Implementation Implementation "FY25" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Implementation Implementation "FY23" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Implementation Implementation "FY23" VB # CalculateField CommunityProtectionConcept_PlanningAreas_w_Implementation Feature "Blairsden Graeagle" VB # CalculateGeometryAttributes CommunityProtectionConcept_PlanningAreas_w_Implementation "Acres AREA" # "US Survey Acres" # "Same as input" Erase "Community Protection Planning Areas" "N Quincy & Claremont Projects" C:\Workspace\Plumas_NF_Dixie_Fire\Plumas_NF_Dixie_Data\Plumas_NF_Dixie_Data.gdb\CommunityProtectionPlanningArea_Erase_NQuincy_Claremont # CalculateGeometryAttributes CommunityProtectionPlanningArea_Erase_NQuincy_Claremont "Acres AREA" # "US Survey Acres" # "Same as input" Dissolve CommunityProtectionPlanningArea_Erase_NQuincy_Claremont C:\Workspace\Plumas_NF_Dixie_Fire\Plumas_NF_Dixie_Data\Plumas_NF_Dixie_Data.gdb\CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont Feature;PlanningArea # MULTI_PART DISSOLVE_LINES # ExportFeatures CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont C:\Workspace\Plumas_NF_Dixie_Fire\Exports\20221121\CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont.shp # NOT_USE_ALIAS "Feature "Feature" true true false 50 Text 0 0,First,#,CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont,Feature,0,50;PlanningArea "PlanningArea" true true false 100 Text 0 0,First,#,CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont,PlanningArea,0,100;SHAPE_Length "SHAPE_Length" false true true 8 Double 0 0,First,#,CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont,SHAPE_Length,-1,-1;SHAPE_Area "SHAPE_Area" false true true 8 Double 0 0,First,#,CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont,SHAPE_Area,-1,-1" # FeatureClassToFeatureClass CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont T:\Projects\2022\20220061_01_GreatBasin_PlumasNF\Shapefiles\_Data.gdb\Base01 PartnerAgreement_PG_02 # "Feature "Feature" true true false 50 Text 0 0 ,First,#,CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont,Feature,-1,-1;PlanningAr "PlanningAr" true true false 100 Text 0 0 ,First,#,CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont,PlanningAr,-1,-1;SHAPE_Leng "SHAPE_Leng" true true false 19 Double 0 0 ,First,#,CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont,SHAPE_Leng,-1,-1;SHAPE_Area "SHAPE_Area" true true false 19 Double 0 0 ,First,#,CommunityProtectionPlanningArea_w_Implementation_Erase_NQuincyClaremont,SHAPE_Area,-1,-1" # 20221121 13585200 20221121 13585200 1.0 150000000 5000 FGDC 20241107 15540300 North American Profile of ISO19115 2003 FALSE USFS Chief Information Office, Enterprise Data Warehouse Please send an e-mail to the address below. Washington DC 20250 data@fs.fed.us 20221121 ArcGIS Metadata 1.0 USFS Chief Information Office, Enterprise Data Warehouse Please send an e-mail to the address below. Washington DC 20250 data@fs.fed.us http://data.fs.usda.gov/geodata/edw/datasets.php 0.000 File Geodatabase Feature Class Ascent Plumas Great Basin Project Area 2022-05-23T12:28:56 U.S. Forest Service Automated Lands Program (ALP) vector digital data <div style='text-align:Left;'><div><p><span>An area depicted as surface ownership parcels dissolved on the same ownership classification.</span></p></div></div> This data is intended for read-only use. Basic Ownership is a commonly used base layer used in a wide range of Forest Service business functions as well as those of other entities. USFS Chief Information Office, Enterprise Data Warehouse Please send an e-mail to the address below. Washington DC 20250 data@fs.fed.us ISO 19115 Topic Categories planningCadastre boundaries Land Status NFS Lands Owner Name ALP Land Dataset Basic Ownership USDA Forest Service Land Status NFS Lands Owner Name ALP Land Dataset Basic Ownership planningCadastre USDA Forest Service boundaries ascent PC558 Great Basin Plumas The U.S. Forest Service makes no warranty, express or implied, nor assumes any liability or responsibility for the accuracy, reliability, completeness, or utility of these geospatial data or for the improper or incorrect use of those data. The data are dynamic and may change over time. The user is responsible for verifying the limitations of the geospatial data and for using the data accordingly. <div style='text-align:Left;'><div><p><span>The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly.</span></p></div></div> Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388 -150.007671 -64.734329 17.738983 61.51899 0.000000 0.000000 publication date 2015-12-31 0.000000 0.000000 1 -121.616845 -120.163651 40.309708 39.348915 0.000000 0.000000 The Forest Service has multiple types of boundaries represented by different feature classes (layers): Administrative, Ownership and Proclaimed. 1) ADMINISTRATIVE boundaries (e.g. AdministrativeForest and RangerDistrict feature classes) encompass National Forest System lands managed by an administrative unit. These are dynamic layers that should not be considered "legal" boundaries as they are simply intended to identify the specific organizational units that administer areas. As lands are acquired and disposed, the administrative boundaries are adjusted to expand or shrink accordingly. Please note that ranger districts are sub units of National Forests. An administrative forest boundary can contain one or more Proclaimed National Forests, National Grasslands, Purchase Units, Research and Experimental Areas, Land Utilization Projects and various "Other" Areas. If needed, OWNERSHIP boundaries (e.g. BasicOwnership and SurfaceOwnership feature classes) should be reviewed along with these datasets to determine parcels that are federally managed within the administrative boundaries. 2) OWNERSHIP boundaries (e.g. BasicOwnership and SurfaceOwnership feature classes) represent parcels that are tied to legal transactions of ownership. These are parcels of Federal land managed by the USDA Forest Service. Please note that the BasicOwnership layer is simply a dissolved version of the SurfaceOwnership layer. 3) PROCLAIMED boundaries (e.g. ProclaimedForest and ProclaimedForest_Grassland) encompass areas of National Forest System land that is set aside and reserved from public domain by executive order or proclamation. Please note that the ProclaimedForest layer contains only proclaimed forests while ProclaimedForest_Grassland layer contains both proclaimed forests and proclaimed grasslands. For boundaries that reflect current National Forest System lands managed by an administrative unit, see the ADMINISTRATIVE boundaries (AdministrativeForest and RangerDistrict feature classes). For a visual comparison of the different kinds of USFS boundary datasets maintained by the USFS, see the Forest Service Boundary Comparison map at https://usfs.maps.arcgis.com/apps/CompareAnalysis/index.html?appid=fe7b9f56217949a291356f08cfccb119. USFS boundaries are often referenced in national datasets maintained by other federal agencies. Please note that variations may be found between USFS data and other boundary datasets due to differing update frequencies. PAD-US (Protected Areas Database of the United States), maintained by the U.S. Geological Survey, is a "best available" inventory of protected areas including data provided by managing agencies and organizations including the Forest Service. For more information see https://gapanalysis.usgs.gov/padus/data/metadata/. SMA (Surface Management Agency), maintained by the Bureau of Land Management, depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. It uses data provided by the Forest Service and other agencies, combined with National Regional Offices collection efforts. For more information see https://landscape.blm.gov/geoportal/catalog/search/resource/details.page?uuid=%7B2A8B8906-7711-4AF7-9510-C6C7FD991177%7D. Quality control measures taken: this feature class is populated by an automated translation process from the source feature class that is edited and maintained by the data stewards. Only stewards with the proper role grants can edit the data. The application used for editing has built in controls to only allow valid geometry and domains to control attribute integrity. Quality control measures taken: this feature class is populated by an automated translation process from the source feature class that is edited and maintained by the data stewards. Only stewards with the proper role grants can edit the data. The application used for editing has built in controls to only allow valid geometry and domains to control attribute integrity. This theme is current to date of publication. The Regional Land Status personnel are responsible for their local data stewardship and maintenance. The overall collection nationwide consists of 100% attribute accuracy based on currentness and completeness. Generally the source information used to record spatial locations are from: 1) on-screen digitizing with a georeferenced topographic or image background; or 2) GPS field collected positions. This data was published using Feature Manipulation Engine Software. The spatial features were extracted from the transactional database, manipulated to meet the desired output format and published to the target feature class. This data was migrated from the CDW. The spatial features were projected and imported into the target feature class. 2016-01-01 original metadata PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0idXRmLTgiPz4NCjxtZXRhZGF0YT4NCiAgPGlk aW5mbz4NCiAgICA8Y2l0YXRpb24+DQogICAgICA8Y2l0ZWluZm8+DQogICAgICAgIDxvcmlnaW4+ VS5TLiBGb3Jlc3QgU2VydmljZTwvb3JpZ2luPg0KICAgICAgICA8b3JpZ2luPkF1dG9tYXRlZCBM YW5kcyBQcm9ncmFtIChBTFApPC9vcmlnaW4+DQogICAgICAgIDxwdWJkYXRlPjIwMTUxMjMxPC9w dWJkYXRlPg0KICAgICAgICA8cHVidGltZT4wODM1MTU8L3B1YnRpbWU+DQogICAgICAgIDx0aXRs ZT5TX1VTQS5CYXNpY093bmVyc2hpcDwvdGl0bGU+DQogICAgICAgIDxnZW9mb3JtPnZlY3RvciBk aWdpdGFsIGRhdGE8L2dlb2Zvcm0+DQogICAgICAgIDxvbmxpbms+aHR0cDovL2RhdGEuZnMudXNk YS5nb3YvZ2VvZGF0YS9lZHcvZGF0YXNldHMucGhwPC9vbmxpbms+DQogICAgICA8L2NpdGVpbmZv Pg0KICAgIDwvY2l0YXRpb24+DQogICAgPGRlc2NyaXB0Pg0KICAgICAgPGFic3RyYWN0PkFuIGFy ZWEgZGVwaWN0ZWQgYXMgc3VyZmFjZSBvd25lcnNoaXAgcGFyY2VscyBkaXNzb2x2ZWQgb24gdGhl IHNhbWUgb3duZXJzaGlwIGNsYXNzaWZpY2F0aW9uLjwvYWJzdHJhY3Q+DQogICAgICA8cHVycG9z ZT5UaGlzIGRhdGEgaXMgaW50ZW5kZWQgZm9yIHJlYWQtb25seSB1c2UuIEJhc2ljIE93bmVyc2hp cCBpcyBhIGNvbW1vbmx5IHVzZWQgYmFzZSBsYXllciB1c2VkIGluIGEgd2lkZSByYW5nZSBvZiBG b3Jlc3QgU2VydmljZSBidXNpbmVzcyBmdW5jdGlvbnMgYXMgd2VsbCBhcyB0aG9zZSBvZiBvdGhl ciBlbnRpdGllcy48L3B1cnBvc2U+DQogICAgPC9kZXNjcmlwdD4NCiAgICA8dGltZXBlcmQ+DQog ICAgICA8dGltZWluZm8+DQogICAgICAgIDxzbmdkYXRlPg0KICAgICAgICAgIDxjYWxkYXRlPjIw MTUxMjMxPC9jYWxkYXRlPg0KICAgICAgICA8L3NuZ2RhdGU+DQogICAgICA8L3RpbWVpbmZvPg0K ICAgICAgPGN1cnJlbnQ+cHVibGljYXRpb24gZGF0ZTwvY3VycmVudD4NCiAgICA8L3RpbWVwZXJk Pg0KICAgIDxzdGF0dXM+DQogICAgICA8cHJvZ3Jlc3M+Q29tcGxldGU8L3Byb2dyZXNzPg0KICAg ICAgPHVwZGF0ZT5XZWVrbHk8L3VwZGF0ZT4NCiAgICA8L3N0YXR1cz4NCiAgICA8c3Bkb20+DQog ICAgICA8Ym91bmRpbmc+DQogICAgICAgIDx3ZXN0YmM+LTE1MC4wMDc2NzE8L3dlc3RiYz4NCiAg ICAgICAgPGVhc3RiYz4tNjQuNzM0MzI5PC9lYXN0YmM+DQogICAgICAgIDxub3J0aGJjPjYxLjUx ODk5MDwvbm9ydGhiYz4NCiAgICAgICAgPHNvdXRoYmM+MTcuNzM4OTgzPC9zb3V0aGJjPg0KICAg ICAgPC9ib3VuZGluZz4NCiAgICA8L3NwZG9tPg0KICAgIDxrZXl3b3Jkcz4NCiAgICAgIDx0aGVt ZT4NCiAgICAgICAgPHRoZW1la3Q+bm9uZTwvdGhlbWVrdD4NCiAgICAgICAgPHRoZW1la2V5PkJh c2ljIE93bmVyc2hpcDwvdGhlbWVrZXk+DQogICAgICAgIDx0aGVtZWtleT5Pd25lciBOYW1lPC90 aGVtZWtleT4NCiAgICAgICAgPHRoZW1la2V5Pk5GUyBMYW5kczwvdGhlbWVrZXk+DQogICAgICAg IDx0aGVtZWtleT5MYW5kIFN0YXR1czwvdGhlbWVrZXk+DQogICAgICAgIDx0aGVtZWtleT5VU0RB IEZvcmVzdCBTZXJ2aWNlPC90aGVtZWtleT4NCiAgICAgICAgPHRoZW1la2V5PkFMUCBMYW5kIERh dGFzZXQ8L3RoZW1la2V5Pg0KICAgICAgPC90aGVtZT4NCiAgICAgIDx0aGVtZT4NCiAgICAgICAg PHRoZW1la3Q+SVNPIDE5MTE1IFRvcGljIENhdGVnb3JpZXM8L3RoZW1la3Q+DQogICAgICAgIDx0 aGVtZWtleT5ib3VuZGFyaWVzPC90aGVtZWtleT4NCiAgICAgICAgPHRoZW1la2V5PnBsYW5uaW5n Q2FkYXN0cmU8L3RoZW1la2V5Pg0KICAgICAgPC90aGVtZT4NCiAgICA8L2tleXdvcmRzPg0KICAg IDxhY2Njb25zdD5Ob25lPC9hY2Njb25zdD4NCiAgICA8dXNlY29uc3Q+VGhlIFVTREEgRm9yZXN0 IFNlcnZpY2UgbWFrZXMgbm8gd2FycmFudHksIGV4cHJlc3NlZCBvciBpbXBsaWVkLCBpbmNsdWRp bmcgdGhlIHdhcnJhbnRpZXMgb2YgbWVyY2hhbnRhYmlsaXR5IGFuZCBmaXRuZXNzIGZvciBhIHBh cnRpY3VsYXIgcHVycG9zZSwgbm9yIGFzc3VtZXMgYW55IGxlZ2FsIGxpYWJpbGl0eSBvciByZXNw b25zaWJpbGl0eSBmb3IgdGhlIGFjY3VyYWN5LCByZWxpYWJpbGl0eSwgY29tcGxldGVuZXNzIG9y IHV0aWxpdHkgb2YgdGhlc2UgZ2Vvc3BhdGlhbCBkYXRhLCBvciBmb3IgdGhlIGltcHJvcGVyIG9y IGluY29ycmVjdCB1c2Ugb2YgdGhlc2UgZ2Vvc3BhdGlhbCBkYXRhLiAgVGhlc2UgZ2Vvc3BhdGlh bCBkYXRhIGFuZCByZWxhdGVkIG1hcHMgb3IgZ3JhcGhpY3MgYXJlIG5vdCBsZWdhbCBkb2N1bWVu dHMgYW5kIGFyZSBub3QgaW50ZW5kZWQgdG8gYmUgdXNlZCBhcyBzdWNoLiAgVGhlIGRhdGEgYW5k IG1hcHMgbWF5IG5vdCBiZSB1c2VkIHRvIGRldGVybWluZSB0aXRsZSwgb3duZXJzaGlwLCBsZWdh bCBkZXNjcmlwdGlvbnMgb3IgYm91bmRhcmllcywgbGVnYWwganVyaXNkaWN0aW9uLCBvciByZXN0 cmljdGlvbnMgdGhhdCBtYXkgYmUgaW4gcGxhY2Ugb24gZWl0aGVyIHB1YmxpYyBvciBwcml2YXRl IGxhbmQuICBOYXR1cmFsIGhhemFyZHMgbWF5IG9yIG1heSBub3QgYmUgZGVwaWN0ZWQgb24gdGhl IGRhdGEgYW5kIG1hcHMsIGFuZCBsYW5kIHVzZXJzIHNob3VsZCBleGVyY2lzZSBkdWUgY2F1dGlv bi4gIFRoZSBkYXRhIGFyZSBkeW5hbWljIGFuZCBtYXkgY2hhbmdlIG92ZXIgdGltZS4gIFRoZSB1 c2VyIGlzIHJlc3BvbnNpYmxlIHRvIHZlcmlmeSB0aGUgbGltaXRhdGlvbnMgb2YgdGhlIGdlb3Nw YXRpYWwgZGF0YSBhbmQgdG8gdXNlIHRoZSBkYXRhIGFjY29yZGluZ2x5LjwvdXNlY29uc3Q+DQog ICAgPHB0Y29udGFjPg0KICAgICAgPGNudGluZm8+DQogICAgICAgIDxjbnRvcmdwPg0KICAgICAg ICAgIDxjbnRvcmc+VVNGUyBDaGllZiBJbmZvcm1hdGlvbiBPZmZpY2UsIEVudGVycHJpc2UgRGF0 YSBXYXJlaG91c2U8L2NudG9yZz4NCiAgICAgICAgPC9jbnRvcmdwPg0KICAgICAgICA8Y250YWRk cj4NCiAgICAgICAgICA8YWRkcnR5cGU+cGh5c2ljYWw8L2FkZHJ0eXBlPg0KICAgICAgICAgIDxj aXR5Pldhc2hpbmd0b248L2NpdHk+DQogICAgICAgICAgPHN0YXRlPkRDPC9zdGF0ZT4NCiAgICAg ICAgICA8cG9zdGFsPjIwMjUwPC9wb3N0YWw+DQogICAgICAgIDwvY250YWRkcj4NCiAgICAgICAg PGNudHZvaWNlPlBsZWFzZSBzZW5kIGFuIGUtbWFpbCB0byB0aGUgYWRkcmVzcyBiZWxvdy48L2Nu dHZvaWNlPg0KICAgICAgICA8Y250ZW1haWw+ZGF0YUBmcy5mZWQudXM8L2NudGVtYWlsPg0KICAg ICAgPC9jbnRpbmZvPg0KICAgIDwvcHRjb250YWM+DQogICAgPG5hdGl2ZT5NaWNyb3NvZnQgV2lu ZG93cyBTZXJ2ZXIgMjAwOCBSMiBWZXJzaW9uIDYuMSAoQnVpbGQgNzYwMSkgU2VydmljZSBQYWNr IDE7IEVzcmkgQXJjR0lTIDEwLjMuMS40OTU5PC9uYXRpdmU+DQogIDwvaWRpbmZvPg0KICA8ZGF0 YXF1YWw+DQogICAgPGF0dHJhY2M+DQogICAgICA8YXR0cmFjY3I+VGhlIFJlZ2lvbmFsIExhbmQg U3RhdHVzIHBlcnNvbm5lbCBhcmUgcmVzcG9uc2libGUgZm9yIHRoZWlyIGxvY2FsIGRhdGEgc3Rl d2FyZHNoaXAgYW5kIG1haW50ZW5hbmNlLiBUaGUgb3ZlcmFsbCBjb2xsZWN0aW9uIG5hdGlvbndp ZGUgY29uc2lzdHMgb2YgMTAwJSBhdHRyaWJ1dGUgYWNjdXJhY3kgYmFzZWQgb24gY3VycmVudG5l c3MgYW5kIGNvbXBsZXRlbmVzcy48L2F0dHJhY2NyPg0KICAgIDwvYXR0cmFjYz4NCiAgICA8bG9n aWM+UXVhbGl0eSBjb250cm9sIG1lYXN1cmVzIHRha2VuOiB0aGlzIGZlYXR1cmUgY2xhc3MgaXMg cG9wdWxhdGVkIGJ5IGFuIGF1dG9tYXRlZCB0cmFuc2xhdGlvbiBwcm9jZXNzIGZyb20gdGhlIHNv dXJjZSBmZWF0dXJlIGNsYXNzIHRoYXQgaXMgZWRpdGVkIGFuZCBtYWludGFpbmVkIGJ5IHRoZSBk YXRhIHN0ZXdhcmRzLiBPbmx5IHN0ZXdhcmRzIHdpdGggdGhlIHByb3BlciByb2xlIGdyYW50cyBj YW4gZWRpdCB0aGUgZGF0YS4gIFRoZSBhcHBsaWNhdGlvbiB1c2VkIGZvciBlZGl0aW5nIGhhcyBi dWlsdCBpbiBjb250cm9scyB0byBvbmx5IGFsbG93IHZhbGlkIGdlb21ldHJ5IGFuZCBkb21haW5z IHRvIGNvbnRyb2wgYXR0cmlidXRlIGludGVncml0eS48L2xvZ2ljPg0KICAgIDxjb21wbGV0ZT5U aGlzIHRoZW1lIGlzIGN1cnJlbnQgdG8gZGF0ZSBvZiBwdWJsaWNhdGlvbi48L2NvbXBsZXRlPg0K ICAgIDxwb3NhY2M+DQogICAgICA8aG9yaXpwYT4NCiAgICAgICAgPGhvcml6cGFyPkdlbmVyYWxs eSB0aGUgc291cmNlIGluZm9ybWF0aW9uIHVzZWQgdG8gcmVjb3JkIHNwYXRpYWwgbG9jYXRpb25z IGFyZSBmcm9tOiAxKSBvbi1zY3JlZW4gZGlnaXRpemluZyB3aXRoIGEgZ2VvcmVmZXJlbmNlZCB0 b3BvZ3JhcGhpYyBvciBpbWFnZSBiYWNrZ3JvdW5kOyBvciAyKSBHUFMgZmllbGQgY29sbGVjdGVk IHBvc2l0aW9ucy48L2hvcml6cGFyPg0KICAgICAgPC9ob3JpenBhPg0KICAgIDwvcG9zYWNjPg0K ICAgIDxsaW5lYWdlPg0KICAgICAgPHByb2NzdGVwPg0KICAgICAgICA8cHJvY2Rlc2M+VGhpcyBk YXRhIHdhcyBwdWJsaXNoZWQgdXNpbmcgRmVhdHVyZSBNYW5pcHVsYXRpb24gRW5naW5lIFNvZnR3 YXJlLiBUaGUgc3BhdGlhbCBmZWF0dXJlcyB3ZXJlIGV4dHJhY3RlZCBmcm9tIHRoZSB0cmFuc2Fj dGlvbmFsIGRhdGFiYXNlLCBtYW5pcHVsYXRlZCB0byBtZWV0IHRoZSBkZXNpcmVkIG91dHB1dCBm b3JtYXQgYW5kIHB1Ymxpc2hlZCB0byB0aGUgdGFyZ2V0IGZlYXR1cmUgY2xhc3MuIFRoaXMgZGF0 YSB3YXMgbWlncmF0ZWQgZnJvbSB0aGUgQ0RXLiBUaGUgc3BhdGlhbCBmZWF0dXJlcyB3ZXJlIHBy b2plY3RlZCBhbmQgaW1wb3J0ZWQgaW50byB0aGUgdGFyZ2V0IGZlYXR1cmUgY2xhc3MuPC9wcm9j ZGVzYz4NCiAgICAgICAgPHByb2NkYXRlPjIwMTY8L3Byb2NkYXRlPg0KICAgICAgPC9wcm9jc3Rl cD4NCiAgICA8L2xpbmVhZ2U+DQogIDwvZGF0YXF1YWw+DQogIDxzcGRvaW5mbz4NCiAgICA8ZGly ZWN0PlZlY3RvcjwvZGlyZWN0Pg0KICA8L3NwZG9pbmZvPg0KICA8c3ByZWY+DQogICAgPGhvcml6 c3lzPg0KICAgICAgPGdlb2dyYXBoPg0KICAgICAgICA8bGF0cmVzPjguOTkwMDAwMDAwMDAwMDAw NGUtMDA4PC9sYXRyZXM+DQogICAgICAgIDxsb25ncmVzPjguOTkwMDAwMDAwMDAwMDAwNGUtMDA4 PC9sb25ncmVzPg0KICAgICAgICA8Z2VvZ3VuaXQ+RGVjaW1hbCBEZWdyZWVzPC9nZW9ndW5pdD4N CiAgICAgIDwvZ2VvZ3JhcGg+DQogICAgICA8Z2VvZGV0aWM+DQogICAgICAgIDxob3JpemRuPkQg Tm9ydGggQW1lcmljYW4gMTk4MzwvaG9yaXpkbj4NCiAgICAgICAgPGVsbGlwcz5HUlMgMTk4MDwv ZWxsaXBzPg0KICAgICAgICA8c2VtaWF4aXM+NjM3ODEzNy4wPC9zZW1pYXhpcz4NCiAgICAgICAg PGRlbmZsYXQ+Mjk4LjI1NzIyMjEwMTwvZGVuZmxhdD4NCiAgICAgIDwvZ2VvZGV0aWM+DQogICAg PC9ob3JpenN5cz4NCiAgPC9zcHJlZj4NCiAgPGVhaW5mbz4NCiAgICA8ZGV0YWlsZWQgTmFtZT0i U19VU0EuQmFzaWNPd25lcnNoaXAiPg0KICAgICAgPGVudHR5cD4NCiAgICAgICAgPGVudHR5cGw+ U19VU0EuQmFzaWNPd25lcnNoaXA8L2VudHR5cGw+DQogICAgICAgIDxlbnR0eXBkPkEgY29sbGVj dGlvbiBvZiBnZW9ncmFwaGljIGZlYXR1cmVzIHdpdGggdGhlIHNhbWUgZ2VvbWV0cnkgdHlwZSAo c3VjaCBhcyBwb2ludCwgbGluZSwgb3IgcG9seWdvbiksIHRoZSBzYW1lIGF0dHJpYnV0ZXMsIGFu ZCB0aGUgc2FtZSBzcGF0aWFsIHJlZmVyZW5jZS48L2VudHR5cGQ+DQogICAgICAgIDxlbnR0eXBk cz5odHRwOi8vc3VwcG9ydC5lc3JpLmNvbS9lbi9rbm93bGVkZ2ViYXNlL0dJU0RpY3Rpb25hcnkv dGVybS9mZWF0dXJlJTIwY2xhc3M8L2VudHR5cGRzPg0KICAgICAgICA8ZW50dHlwdCBTeW5jPSJU UlVFIj5GZWF0dXJlIENsYXNzPC9lbnR0eXB0Pg0KICAgICAgICA8ZW50dHlwYyBTeW5jPSJUUlVF Ij4zMTI8L2VudHR5cGM+DQogICAgICA8L2VudHR5cD4NCiAgICAgIDxhdHRyPg0KICAgICAgICA8 YXR0cmxhYmw+T0JKRUNUSUQ8L2F0dHJsYWJsPg0KICAgICAgICA8YXR0cmRlZj5JbnRlcm5hbCBm ZWF0dXJlIG51bWJlci48L2F0dHJkZWY+DQogICAgICAgIDxhdHRyZGVmcz5FU1JJPC9hdHRyZGVm cz4NCiAgICAgICAgPGF0dHJ0eXBlIFN5bmM9IlRSVUUiPk9JRDwvYXR0cnR5cGU+DQogICAgICAg IDxhdHR3aWR0aCBTeW5jPSJUUlVFIj40PC9hdHR3aWR0aD4NCiAgICAgICAgPGF0cHJlY2lzIFN5 bmM9IlRSVUUiPjEwPC9hdHByZWNpcz4NCiAgICAgICAgPGF0dHNjYWxlIFN5bmM9IlRSVUUiPjA8 L2F0dHNjYWxlPg0KICAgICAgICA8YXR0cmRvbXY+DQogICAgICAgICAgPHVkb20+U2VxdWVudGlh bCB1bmlxdWUgd2hvbGUgbnVtYmVycyB0aGF0IGFyZSBhdXRvbWF0aWNhbGx5IGdlbmVyYXRlZC48 L3Vkb20+DQogICAgICAgIDwvYXR0cmRvbXY+DQogICAgICAgIDxhdHRhbGlhcyBTeW5jPSJUUlVF Ij5PQkpFQ1RJRDwvYXR0YWxpYXM+DQogICAgICA8L2F0dHI+DQogICAgICA8YXR0cj4NCiAgICAg ICAgPGF0dHJsYWJsPkJBU0lDT1dORVJTSElQSUQ8L2F0dHJsYWJsPg0KICAgICAgICA8YXR0cmRl Zj5VbmlxdWUgaWRlbnRpZmllciBnZW5lcmF0ZWQgYnkgT3JhY2xlIHNlcXVlbmNlIG9yIFNZU19H VUlEKCkgZnVuY3Rpb24uPC9hdHRyZGVmPg0KICAgICAgICA8YXR0cmRlZnM+QUxQPC9hdHRyZGVm cz4NCiAgICAgICAgPGF0dHJ0eXBlIFN5bmM9IlRSVUUiPlN0cmluZzwvYXR0cnR5cGU+DQogICAg ICAgIDxhdHR3aWR0aCBTeW5jPSJUUlVFIj40MDwvYXR0d2lkdGg+DQogICAgICAgIDxhdHByZWNp cyBTeW5jPSJUUlVFIj4wPC9hdHByZWNpcz4NCiAgICAgICAgPGF0dHNjYWxlIFN5bmM9IlRSVUUi PjA8L2F0dHNjYWxlPg0KICAgICAgICA8YXR0cmRvbXY+DQogICAgICAgICAgPHVkb20+VW5pcXVl IElkZW50aWZpZXI8L3Vkb20+DQogICAgICAgIDwvYXR0cmRvbXY+DQogICAgICAgIDxhdHRhbGlh cyBTeW5jPSJUUlVFIj5CQVNJQ09XTkVSU0hJUElEPC9hdHRhbGlhcz4NCiAgICAgIDwvYXR0cj4N CiAgICAgIDxhdHRyPg0KICAgICAgICA8YXR0cmxhYmw+T1dORVJDTEFTU0lGSUNBVElPTjwvYXR0 cmxhYmw+DQogICAgICAgIDxhdHRyZGVmPkNsYXNzaWZpY2F0aW9uIGRlc2lnbmF0aW9uIGFzc2ln bmVkIHRvIGVhY2ggQmFzaWMgT3duZXJzaGlwIFR5cGU8L2F0dHJkZWY+DQogICAgICAgIDxhdHRy ZGVmcz5BTFA8L2F0dHJkZWZzPg0KICAgICAgICA8YXR0cnR5cGUgU3luYz0iVFJVRSI+U3RyaW5n PC9hdHRydHlwZT4NCiAgICAgICAgPGF0dHdpZHRoIFN5bmM9IlRSVUUiPjUwPC9hdHR3aWR0aD4N CiAgICAgICAgPGF0cHJlY2lzIFN5bmM9IlRSVUUiPjA8L2F0cHJlY2lzPg0KICAgICAgICA8YXR0 c2NhbGUgU3luYz0iVFJVRSI+MDwvYXR0c2NhbGU+DQogICAgICAgIDxhdHRyZG9tdj4NCiAgICAg ICAgICA8ZWRvbT4NCiAgICAgICAgICAgIDxlZG9tdj5OT04tRlM8L2Vkb212Pg0KICAgICAgICAg ICAgPGVkb212ZD5MYW5kIGFyZWFzIHRoYXQgYXJlIG5vdCBwYXJ0IG9mIHRoZSBOYXRpb25hbCBG b3Jlc3QgU3lzdGVtPC9lZG9tdmQ+DQogICAgICAgICAgICA8ZWRvbXZkcz5VLlMuIEZvcmVzdCBT ZXJ2aWNlPC9lZG9tdmRzPg0KICAgICAgICAgIDwvZWRvbT4NCiAgICAgICAgICA8ZWRvbT4NCiAg ICAgICAgICAgIDxlZG9tdj5VTlBBUlRJVElPTkVEIFJJUEFSSUFOIElOVEVSRVNUPC9lZG9tdj4N CiAgICAgICAgICAgIDxlZG9tdmQ+QSBjb25kaXRpb24gd2hlcmUgbGFuZCBpbnRlcmVzdHMgZXhp c3QgYmV0d2VlbiB3aGF0IGlzIHNob3duIG9uIHN1cnZleSBwbGF0cyBvciBCTE0gbWFzdGVyIHRp dGxlIHBsYXRzIGFuZCB0aGUgYWN0dWFsIHNob3JlbGluZSwgd2hpY2ggbWF5IHJlcXVpcmUgcGFy dGl0aW9uaW5nIGJldHdlZW4gZmVkZXJhbCBhbmQgbm9uZmVkZXJhbCBpbnRlcmVzdHMuPC9lZG9t dmQ+DQogICAgICAgICAgICA8ZWRvbXZkcz5VLlMuIEZvcmVzdCBTZXJ2aWNlPC9lZG9tdmRzPg0K ICAgICAgICAgIDwvZWRvbT4NCiAgICAgICAgICA8ZWRvbT4NCiAgICAgICAgICAgIDxlZG9tdj5V U0RBIEZPUkVTVCBTRVJWSUNFPC9lZG9tdj4NCiAgICAgICAgICAgIDxlZG9tdmQ+T3duZWQgYnkg dGhlIFUuUy4gRm9yZXN0IFNlcnZpY2U8L2Vkb212ZD4NCiAgICAgICAgICAgIDxlZG9tdmRzPlUu Uy4gRm9yZXN0IFNlcnZpY2U8L2Vkb212ZHM+DQogICAgICAgICAgPC9lZG9tPg0KICAgICAgICA8 L2F0dHJkb212Pg0KICAgICAgICA8YXR0YWxpYXMgU3luYz0iVFJVRSI+T1dORVJDTEFTU0lGSUNB VElPTjwvYXR0YWxpYXM+DQogICAgICA8L2F0dHI+DQogICAgICA8YXR0cj4NCiAgICAgICAgPGF0 dHJsYWJsPkdJU19BQ1JFUzwvYXR0cmxhYmw+DQogICAgICAgIDxhdHRyZGVmPlRoZSBhcmVhIG9m IHRoZSBmZWF0dXJlIGluIGFjcmVzLCBjYWxjdWxhdGVkIHVzaW5nIGEgcHJvamVjdGVkIHN1cmZh Y2UgY29tcHV0YXRpb24uIEEgTkFEIDgzLCBVU0EgQ29udGlndW91cyBBbGJlcnMgRXF1YWwgQXJl YSBDb25pYyBwcm9qZWN0aW9uIHdhcyB1c2VkIGZvciBSZWdpb25zIDEtOSwgYW5kIE5BRCA4Mywg QWxhc2thIEFsYmVycyBmb3IgUmVnaW9uIDEwLjwvYXR0cmRlZj4NCiAgICAgICAgPGF0dHJkZWZz PlUuUy4gRm9yZXN0IFNlcnZpY2U8L2F0dHJkZWZzPg0KICAgICAgICA8YXR0cnR5cGUgU3luYz0i VFJVRSI+RG91YmxlPC9hdHRydHlwZT4NCiAgICAgICAgPGF0dHdpZHRoIFN5bmM9IlRSVUUiPjg8 L2F0dHdpZHRoPg0KICAgICAgICA8YXRwcmVjaXMgU3luYz0iVFJVRSI+Mzg8L2F0cHJlY2lzPg0K ICAgICAgICA8YXR0c2NhbGUgU3luYz0iVFJVRSI+ODwvYXR0c2NhbGU+DQogICAgICAgIDxhdHRy ZG9tdj4NCiAgICAgICAgICA8dWRvbT5UaGUgYXJlYSBvZiBhIGZlYXR1cmUgaW4gYWNyZXMuPC91 ZG9tPg0KICAgICAgICA8L2F0dHJkb212Pg0KICAgICAgICA8YXR0YWxpYXMgU3luYz0iVFJVRSI+ R0lTX0FDUkVTPC9hdHRhbGlhcz4NCiAgICAgIDwvYXR0cj4NCiAgICAgIDxhdHRyPg0KICAgICAg ICA8YXR0cmxhYmw+UkVHSU9OPC9hdHRybGFibD4NCiAgICAgICAgPGF0dHJkZWY+VS5TLiBGb3Jl c3QgU2VydmljZSBSZWdpb24sIGNvbnNpc3Rpbmcgb2YgUmVnaW9uIDAxIChOb3J0aGVybiBSZWdp b24pLCBSZWdpb24gMDIgKFJvY2t5IE1vdW50YWluIFJlZ2lvbiksIFJlZ2lvbiAwMyAoU291dGh3 ZXN0ZXJuIFJlZ2lvbiksIFJlZ2lvbiAwNCAoSW50ZXJtb3VudGFpbiBSZWdpb24pLCBSZWdpb24g MDUgKFBhY2lmaWMgU291dGh3ZXN0IFJlZ2lvbiksIFJlZ2lvbiAwNiAoUGFjaWZpYyBOb3J0aHdl c3QgUmVnaW9uKSwgUmVnaW9uIDA4IChTb3V0aGVybiBSZWdpb24pLCBSZWdpb24gMDkgKEVhc3Rl cm4gUmVnaW9uKSwgYW5kIFJlZ2lvbiAxMCAoQWxhc2thIFJlZ2lvbikuICBUaGVyZSBpcyBubyBS ZWdpb24gMDcuICBSZWdpb25zIGFyZSBsaXN0ZWQgb24gaHR0cDovL3d3dy5mcy5mZWQudXMvb3Jn YW5pemF0aW9uLzUwNi4gIFdpdGhpbiB0aGlzIGRhdGFzZXQsIHRoZSByZWdpb24gcmVwcmVzZW50 cyB0aGUgTGFuZCBTdGF0dXMgUmVjb3JkIFN5c3RlbSBQcm9kdWN0aW9uIFJlZ2lvbmFsIHNjaGVt YSBmcm9tIHdoaWNoIGRhdGEgd2FzIGRlcml2ZWQuPC9hdHRyZGVmPg0KICAgICAgICA8YXR0cmRl ZnM+VS5TLiBGb3Jlc3QgU2VydmljZTwvYXR0cmRlZnM+DQogICAgICAgIDxhdHRydHlwZSBTeW5j PSJUUlVFIj5TdHJpbmc8L2F0dHJ0eXBlPg0KICAgICAgICA8YXR0d2lkdGggU3luYz0iVFJVRSI+ MjwvYXR0d2lkdGg+DQogICAgICAgIDxhdHByZWNpcyBTeW5jPSJUUlVFIj4wPC9hdHByZWNpcz4N CiAgICAgICAgPGF0dHNjYWxlIFN5bmM9IlRSVUUiPjA8L2F0dHNjYWxlPg0KICAgICAgICA8YXR0 cmRvbXY+DQogICAgICAgICAgPGVkb20+DQogICAgICAgICAgICA8ZWRvbXY+MDE8L2Vkb212Pg0K ICAgICAgICAgICAgPGVkb212ZD5SZWdpb24gMDEgLSBOb3J0aGVybjwvZWRvbXZkPg0KICAgICAg ICAgICAgPGVkb212ZHM+VS5TLiBGb3Jlc3QgU2VydmljZTwvZWRvbXZkcz4NCiAgICAgICAgICA8 L2Vkb20+DQogICAgICAgICAgPGVkb20+DQogICAgICAgICAgICA8ZWRvbXY+MDI8L2Vkb212Pg0K ICAgICAgICAgICAgPGVkb212ZD5SZWdpb24gMDIgLSBSb2NreSBNb3VudGFpbjwvZWRvbXZkPg0K ICAgICAgICAgICAgPGVkb212ZHM+VS5TLiBGb3Jlc3QgU2VydmljZTwvZWRvbXZkcz4NCiAgICAg ICAgICA8L2Vkb20+DQogICAgICAgICAgPGVkb20+DQogICAgICAgICAgICA8ZWRvbXY+MDM8L2Vk b212Pg0KICAgICAgICAgICAgPGVkb212ZD5SZWdpb24gMDMgLSBTb3V0aHdlc3Rlcm48L2Vkb212 ZD4NCiAgICAgICAgICAgIDxlZG9tdmRzPlUuUy4gRm9yZXN0IFNlcnZpY2U8L2Vkb212ZHM+DQog ICAgICAgICAgPC9lZG9tPg0KICAgICAgICAgIDxlZG9tPg0KICAgICAgICAgICAgPGVkb212PjA0 PC9lZG9tdj4NCiAgICAgICAgICAgIDxlZG9tdmQ+UmVnaW9uIDA0IC0gSW50ZXJtb3VudGFpbjwv ZWRvbXZkPg0KICAgICAgICAgICAgPGVkb212ZHM+VS5TLiBGb3Jlc3QgU2VydmljZTwvZWRvbXZk cz4NCiAgICAgICAgICA8L2Vkb20+DQogICAgICAgICAgPGVkb20+DQogICAgICAgICAgICA8ZWRv bXY+MDU8L2Vkb212Pg0KICAgICAgICAgICAgPGVkb212ZD5SZWdpb24gMDUgLSBQYWNpZmljIFNv dXRod2VzdDwvZWRvbXZkPg0KICAgICAgICAgICAgPGVkb212ZHM+VS5TLiBGb3Jlc3QgU2Vydmlj ZTwvZWRvbXZkcz4NCiAgICAgICAgICA8L2Vkb20+DQogICAgICAgICAgPGVkb20+DQogICAgICAg ICAgICA8ZWRvbXY+MDY8L2Vkb212Pg0KICAgICAgICAgICAgPGVkb212ZD5SZWdpb24gMDYgLSBQ YWNpZmljIE5vcnRod2VzdDwvZWRvbXZkPg0KICAgICAgICAgICAgPGVkb212ZHM+VS5TLiBGb3Jl c3QgU2VydmljZTwvZWRvbXZkcz4NCiAgICAgICAgICA8L2Vkb20+DQogICAgICAgICAgPGVkb20+ DQogICAgICAgICAgICA8ZWRvbXY+MDg8L2Vkb212Pg0KICAgICAgICAgICAgPGVkb212ZD5SZWdp b24gMDggLSBTb3V0aGVybjwvZWRvbXZkPg0KICAgICAgICAgICAgPGVkb212ZHM+VS5TLiBGb3Jl c3QgU2VydmljZTwvZWRvbXZkcz4NCiAgICAgICAgICA8L2Vkb20+DQogICAgICAgICAgPGVkb20+ DQogICAgICAgICAgICA8ZWRvbXY+MDk8L2Vkb212Pg0KICAgICAgICAgICAgPGVkb212ZD5SZWdp b24gMDkgLSBFYXN0ZXJuPC9lZG9tdmQ+DQogICAgICAgICAgICA8ZWRvbXZkcz5VLlMuIEZvcmVz dCBTZXJ2aWNlPC9lZG9tdmRzPg0KICAgICAgICAgIDwvZWRvbT4NCiAgICAgICAgICA8ZWRvbT4N CiAgICAgICAgICAgIDxlZG9tdj4xMDwvZWRvbXY+DQogICAgICAgICAgICA8ZWRvbXZkPlJlZ2lv biAxMCAtIEFsYXNrYTwvZWRvbXZkPg0KICAgICAgICAgICAgPGVkb212ZHM+VS5TLiBGb3Jlc3Qg U2VydmljZTwvZWRvbXZkcz4NCiAgICAgICAgICA8L2Vkb20+DQogICAgICAgIDwvYXR0cmRvbXY+ DQogICAgICAgIDxhdHRhbGlhcyBTeW5jPSJUUlVFIj5SRUdJT048L2F0dGFsaWFzPg0KICAgICAg PC9hdHRyPg0KICAgICAgPGF0dHI+DQogICAgICAgIDxhdHRybGFibD5GT1JFU1ROQU1FPC9hdHRy bGFibD4NCiAgICAgICAgPGF0dHJkZWY+Rm9yZXN0cyBhcmUgc3ViZGl2aXNpb25zIG9mIHJlZ2lv bnMgYW5kIGNhbiBiZSBmb3VuZCBieSBkcmlsbGluZyB0aHJvdWdoIHJlZ2lvbnMgb24gaHR0cDov L3d3dy5mcy5mZWQudXMvb3JnYW5pemF0aW9uLzUwNi48L2F0dHJkZWY+DQogICAgICAgIDxhdHRy ZGVmcz5VLlMuIEZvcmVzdCBTZXJ2aWNlPC9hdHRyZGVmcz4NCiAgICAgICAgPGF0dHJ0eXBlIFN5 bmM9IlRSVUUiPlN0cmluZzwvYXR0cnR5cGU+DQogICAgICAgIDxhdHR3aWR0aCBTeW5jPSJUUlVF Ij4xNTA8L2F0dHdpZHRoPg0KICAgICAgICA8YXRwcmVjaXMgU3luYz0iVFJVRSI+MDwvYXRwcmVj aXM+DQogICAgICAgIDxhdHRzY2FsZSBTeW5jPSJUUlVFIj4wPC9hdHRzY2FsZT4NCiAgICAgICAg PGF0dHJkb212Pg0KICAgICAgICAgIDx1ZG9tPkZvcmVzdCBOYW1lLjwvdWRvbT4NCiAgICAgICAg PC9hdHRyZG9tdj4NCiAgICAgICAgPGF0dGFsaWFzIFN5bmM9IlRSVUUiPkZPUkVTVE5BTUU8L2F0 dGFsaWFzPg0KICAgICAgPC9hdHRyPg0KICAgICAgPGF0dHI+DQogICAgICAgIDxhdHRybGFibD5T SEFQRTwvYXR0cmxhYmw+DQogICAgICAgIDxhdHRyZGVmPkZlYXR1cmUgZ2VvbWV0cnkuPC9hdHRy ZGVmPg0KICAgICAgICA8YXR0cmRlZnM+RVNSSTwvYXR0cmRlZnM+DQogICAgICAgIDxhdHRydHlw ZSBTeW5jPSJUUlVFIj5HZW9tZXRyeTwvYXR0cnR5cGU+DQogICAgICAgIDxhdHR3aWR0aCBTeW5j PSJUUlVFIj40PC9hdHR3aWR0aD4NCiAgICAgICAgPGF0cHJlY2lzIFN5bmM9IlRSVUUiPjA8L2F0 cHJlY2lzPg0KICAgICAgICA8YXR0c2NhbGUgU3luYz0iVFJVRSI+MDwvYXR0c2NhbGU+DQogICAg ICAgIDxhdHRyZG9tdj4NCiAgICAgICAgICA8dWRvbT5Db29yZGluYXRlcyBkZWZpbmluZyB0aGUg ZmVhdHVyZXMuPC91ZG9tPg0KICAgICAgICA8L2F0dHJkb212Pg0KICAgICAgICA8YXR0YWxpYXMg U3luYz0iVFJVRSI+U2hhcGU8L2F0dGFsaWFzPg0KICAgICAgPC9hdHRyPg0KICAgICAgPGF0dHI+ DQogICAgICAgIDxhdHRybGFibD5TSEFQRS5BUkVBPC9hdHRybGFibD4NCiAgICAgICAgPGF0dHJk ZWY+QXJlYSBvZiBmZWF0dXJlIGluIGludGVybmFsIHVuaXRzIHNxdWFyZWQuPC9hdHRyZGVmPg0K ICAgICAgICA8YXR0cmRlZnM+RVNSSTwvYXR0cmRlZnM+DQogICAgICAgIDxhdHRydHlwZSBTeW5j PSJUUlVFIj5Eb3VibGU8L2F0dHJ0eXBlPg0KICAgICAgICA8YXR0d2lkdGggU3luYz0iVFJVRSI+ MDwvYXR0d2lkdGg+DQogICAgICAgIDxhdHByZWNpcyBTeW5jPSJUUlVFIj4wPC9hdHByZWNpcz4N CiAgICAgICAgPGF0dHNjYWxlIFN5bmM9IlRSVUUiPjA8L2F0dHNjYWxlPg0KICAgICAgICA8YXR0 cmRvbXY+DQogICAgICAgICAgPHVkb20+UG9zaXRpdmUgcmVhbCBudW1iZXJzIHRoYXQgYXJlIGF1 dG9tYXRpY2FsbHkgZ2VuZXJhdGVkLjwvdWRvbT4NCiAgICAgICAgPC9hdHRyZG9tdj4NCiAgICAg ICAgPGF0dGFsaWFzIFN5bmM9IlRSVUUiPlNIQVBFLkFSRUE8L2F0dGFsaWFzPg0KICAgICAgPC9h dHRyPg0KICAgICAgPGF0dHI+DQogICAgICAgIDxhdHRybGFibD5TSEFQRS5MRU48L2F0dHJsYWJs Pg0KICAgICAgICA8YXR0cmRlZj5MZW5ndGggb2YgZmVhdHVyZSBpbiBpbnRlcm5hbCB1bml0cy48 L2F0dHJkZWY+DQogICAgICAgIDxhdHRyZGVmcz5FU1JJPC9hdHRyZGVmcz4NCiAgICAgICAgPGF0 dHJ0eXBlIFN5bmM9IlRSVUUiPkRvdWJsZTwvYXR0cnR5cGU+DQogICAgICAgIDxhdHR3aWR0aCBT eW5jPSJUUlVFIj4wPC9hdHR3aWR0aD4NCiAgICAgICAgPGF0cHJlY2lzIFN5bmM9IlRSVUUiPjA8 L2F0cHJlY2lzPg0KICAgICAgICA8YXR0c2NhbGUgU3luYz0iVFJVRSI+MDwvYXR0c2NhbGU+DQog ICAgICAgIDxhdHRyZG9tdj4NCiAgICAgICAgICA8dWRvbT5Qb3NpdGl2ZSByZWFsIG51bWJlcnMg dGhhdCBhcmUgYXV0b21hdGljYWxseSBnZW5lcmF0ZWQuPC91ZG9tPg0KICAgICAgICA8L2F0dHJk b212Pg0KICAgICAgICA8YXR0YWxpYXMgU3luYz0iVFJVRSI+U0hBUEUuTEVOPC9hdHRhbGlhcz4N CiAgICAgIDwvYXR0cj4NCiAgICA8L2RldGFpbGVkPg0KICA8L2VhaW5mbz4NCiAgPGRpc3RpbmZv Pg0KICAgIDxkaXN0cmliPg0KICAgICAgPGNudGluZm8+DQogICAgICAgIDxjbnRvcmdwPg0KICAg ICAgICAgIDxjbnRvcmc+VVNGUyBDaGllZiBJbmZvcm1hdGlvbiBPZmZpY2UsIEVudGVycHJpc2Ug RGF0YSBXYXJlaG91c2U8L2NudG9yZz4NCiAgICAgICAgPC9jbnRvcmdwPg0KICAgICAgICA8Y250 YWRkcj4NCiAgICAgICAgICA8YWRkcnR5cGU+cGh5c2ljYWw8L2FkZHJ0eXBlPg0KICAgICAgICAg IDxjaXR5Pldhc2hpbmd0b248L2NpdHk+DQogICAgICAgICAgPHN0YXRlPkRDPC9zdGF0ZT4NCiAg ICAgICAgICA8cG9zdGFsPjIwMjUwPC9wb3N0YWw+DQogICAgICAgIDwvY250YWRkcj4NCiAgICAg ICAgPGNudHZvaWNlPlBsZWFzZSBzZW5kIGFuIGUtbWFpbCB0byB0aGUgYWRkcmVzcyBiZWxvdy48 L2NudHZvaWNlPg0KICAgICAgICA8Y250ZW1haWw+ZGF0YUBmcy5mZWQudXM8L2NudGVtYWlsPg0K ICAgICAgPC9jbnRpbmZvPg0KICAgIDwvZGlzdHJpYj4NCiAgICA8ZGlzdGxpYWI+VGhlIFUuUy4g Rm9yZXN0IFNlcnZpY2UgbWFrZXMgbm8gd2FycmFudHksIGV4cHJlc3Mgb3IgaW1wbGllZCwgbm9y IGFzc3VtZXMgYW55IGxpYWJpbGl0eSBvciByZXNwb25zaWJpbGl0eSBmb3IgdGhlIGFjY3VyYWN5 LCByZWxpYWJpbGl0eSwgY29tcGxldGVuZXNzLCBvciB1dGlsaXR5IG9mIHRoZXNlIGdlb3NwYXRp YWwgZGF0YSBvciBmb3IgdGhlIGltcHJvcGVyIG9yIGluY29ycmVjdCB1c2Ugb2YgdGhvc2UgZGF0 YS4gIFRoZSBkYXRhIGFyZSBkeW5hbWljIGFuZCBtYXkgY2hhbmdlIG92ZXIgdGltZS4gIFRoZSB1 c2VyIGlzIHJlc3BvbnNpYmxlIGZvciB2ZXJpZnlpbmcgdGhlIGxpbWl0YXRpb25zIG9mIHRoZSBn ZW9zcGF0aWFsIGRhdGEgYW5kIGZvciB1c2luZyB0aGUgZGF0YSBhY2NvcmRpbmdseS48L2Rpc3Rs aWFiPg0KICA8L2Rpc3RpbmZvPg0KICA8bWV0YWluZm8+DQogICAgPG1ldGQ+MjAxNjExMTg8L21l dGQ+DQogICAgPG1ldGM+DQogICAgICA8Y250aW5mbz4NCiAgICAgICAgPGNudG9yZ3A+DQogICAg ICAgICAgPGNudG9yZz5VU0ZTIENoaWVmIEluZm9ybWF0aW9uIE9mZmljZSwgRW50ZXJwcmlzZSBE YXRhIFdhcmVob3VzZTwvY250b3JnPg0KICAgICAgICA8L2NudG9yZ3A+DQogICAgICAgIDxjbnRh ZGRyPg0KICAgICAgICAgIDxhZGRydHlwZT5waHlzaWNhbDwvYWRkcnR5cGU+DQogICAgICAgICAg PGNpdHk+V2FzaGluZ3RvbjwvY2l0eT4NCiAgICAgICAgICA8c3RhdGU+REM8L3N0YXRlPg0KICAg ICAgICAgIDxwb3N0YWw+MjAyNTA8L3Bvc3RhbD4NCiAgICAgICAgPC9jbnRhZGRyPg0KICAgICAg ICA8Y250dm9pY2U+UGxlYXNlIHNlbmQgYW4gZS1tYWlsIHRvIHRoZSBhZGRyZXNzIGJlbG93Ljwv Y250dm9pY2U+DQogICAgICAgIDxjbnRlbWFpbD5kYXRhQGZzLmZlZC51czwvY250ZW1haWw+DQog ICAgICA8L2NudGluZm8+DQogICAgPC9tZXRjPg0KICAgIDxtZXRzdGRuPkZHREMgQ29udGVudCBT dGFuZGFyZCBmb3IgRGlnaXRhbCBHZW9zcGF0aWFsIE1ldGFkYXRhPC9tZXRzdGRuPg0KICAgIDxt ZXRzdGR2PkZHREMtU1RELTAwMS0xOTk4PC9tZXRzdGR2Pg0KICA8L21ldGFpbmZvPg0KICA8RXNy aT4NCiAgICA8U3luY0RhdGU+MjAxNjExMTg8L1N5bmNEYXRlPg0KICAgIDxTeW5jVGltZT4xNTI1 MTAwMDwvU3luY1RpbWU+DQogICAgPE1vZERhdGU+MjAxNjExMTg8L01vZERhdGU+DQogICAgPE1v ZFRpbWU+MTUyNTEwMDA8L01vZFRpbWU+DQogIDwvRXNyaT4NCjwvbWV0YWRhdGE+ iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzsvelyI0cOtluUqLUX2+OZ+SbixPfnxLn/+5rNdm/aJZ54kPkU weyqYpGi2rKnMe6RxKWWrEwk8OIFsPy//+//t+q+y6uSk+Wy+/Hdm72+++nLVffw+BTfXywW8Y/j 8ZDv7+/7zx0dHXWr1Sr++ffZ2Vl3d3vbPT49xWtPT08db989PHQXZ6f9546PjrqHx8f4/fHxceOY fAfx3MvlMj6TP4ccHx/35+A9vntychKf5/fT09Puv//9b/zuP4/p8bhevsM9XF1dde/fv+9++eWX /tj5XOVeNqc6f/OdDx8+9Oflcw/c78VFd3TMvR7Hua6vr+Pn8fK4W3SL9UHSr628uXwT1xfffdq8 /3wNjlcWrmF5XK6Ja1sccdZy/zFuq6fu6fGpu7u/W79Wx74/xv1Df73xmfhvsTGOHPcQsnpadfcP 9/0Ynp6cbowN5+X19nyPD48x1rd3t93Z6Vl3fXP91fPjWo8WRzGGy4Nc7Xc5mLy9OO/Oq3LYR55W XSicp9WqO14sYjIwRVQwTup2l2JhhdI4Pe0WDw+xYG7v7rsf37/rzp5W3ePjQywuJhPKZFkXdquI 8iQ7Pzvjl/i9VRgqKf4hHIvPuEARrp3XVbQqtVhoi0V3c3PT3d7e9sfk97zwPfbyZBmfRQGwqFhc b94UZdIr6ru7uL5QmifLuM8vV1/ib4/Bv1axjEneDKZk7HgqUBa0ym5RNE4IY3V+dt5/nwV9cXnR nzs2guVjP+78RMFxP4wp/y4vL0cV6a7C8UPBHh+FouT6Hx4f+veHxoLvMPYoq3ietzeh6HhWJ6cn G9+9f7yPzeO7wnpF8u7NRXd+ur+yygvl+ua2e3t5sWHx5B141ezGvM8k9idK7+KcyXRXPl+NiX5n Xiy+moTtDo/S5DxDn/WcKAaUh4oJSwmLhNf4mZUa4jVyvHaxM9F7JbVc9ouTRc/uzblYpCwQdnJ+ sohPz07jX7nPVdxsLPiHx1DOz5W4Vv53VCwFBpLzoixU1HFax6jeFtc6ZgEdHR2FdaUwdlhdg7Lo QpFwrPPz8+7T509hWX7+8rlXyM8V5oRKhvuI55B14aJYuigzrgXhmbCB9Er36CieCRtVft33OO53 hfWKBFfrORKLrO6Y17d33enJ/MfLYs/y+PjUX8/TU1GCx8dHYYnMvZb2mEOTnAXLovny5UuvwJDP n8ti+koJPj2FMkOxcU1+/+3bt73rx7GwthiLk+VJ+Xl8EovAXV9FdPd4V9y+xtJAGbC4ES1JLZRw UVAAVbN4zS5ElFK+F8bh/OK8X6wuxHDXcWmfVuG6cfyXlKOjo+7Tp0+huHiOh1JWSFjHi6NQ+P29 rxGIEK3xsKyqsmolLLOHh3g/LOassBfdd4X1GiTcp9OT7uPnq+7NM13CsojKTn1799CdjkzK9ae+ lvuHh17ZxeI84rXH7rh7nkIdvI7qMg66GMtlWFliW1p3/M6CcMGx+D5+/Bjvo4j4Lu/zORcQrw8u kJNlb01hIaC8WDAMzrv374p7guu4OCqu6aJaM49rF1ccSUtKQYnyXY57f1e+q9u7MQZHa4xpX1ky Jss19pMt2h6nXBx1T8syNrc3txtu13MlxvloEcpXa6oV75ENB3d71L1mjB/uixJvNqzvFtYrkPeX F93pacFTPl1dhyIR5J4rLgImiqB5uDcD4g4YuAaTOU3uu7v7uBaPeRSTbNily8dDAPfvErA/Rzyu 1pJu208//dTfD9YUioPf4/4eH4sF1QD+KrShsYn3Hh5DQaFw7m7vQqG8f/c+PoNixDILRYjiqosf ZeTYhiI8KtcwR3rrYNXF8Tj+jz/82I9/exzHwH+7AOIP9TvtufOGoAWIpXdIZaWEQuwKBDAk11fX 4YrikoK/DW0gys31Tffu3bvu9nETl/yusH5HweV6//YyfjJ5UVIoiKub21gcl+dnkyDvkHXyw1uA 1KdQPPePjz2QzEJWOWBt8Deg+M3dXfdUF7nROW0vI4Iu+C9X193Jsiw0lZPHBDzld9wolMkcwFnh +HyPc4hj8Q+rISJL1UJSOH5rpSDiWn6nREhPAtsR5OfWLi8ue6Ady0z8BbctC+/336vWa+AwCUye I5z/uCtYXeBOFRAcerZYKAGSr566o6eC28wF+o+ThdUKypr7YHy5jhwxPoQUS7zgVkPXyziCTcXG szwOZQVI346lgZ3LN5cFk6xKVvmusH4n4aH+9P5t/PRBsvuwgHDHfvn4OdwwFFCeAP4+NpGJBv76 8XN3dnLSvbk8D+NpY+etVksoouPjUJAa3bikby/Xi1Y3rER8HuO6rq5vu4vz4nYpHMPIXgvmzxGO lbGxIWWUhbEygijFAYWHEkKxSXPAaro9uo1r+3TzKXZsFog7e7iMq1V3enw6aI2C93DMPHihvJ+K xYkSCGXIz+SG+i8A9qqEuqpLtrl+0heO+N/xUfd499gtjrcrrFXaIHI0UcGaDMvm/DzG5pD4VZyT DUKrrmvm6KoLiwoBVM/WK1FBlVY8i5O1694qK+S7wvodBGXx47uirPqw7f19LDB3/r/88K77+PlL KB+sGQBv8K0M2Ppdf8LBuq07Jz9vP5Tf//L+XXw/Ptd1MWFbAVjPygoZAs0vLwBLwZHg9xTBogMk P7TIYdJyk3PF+IhVCcyjvFAwKCWuRautP1Z1uTciV815WDhYZBy7KPXjYpUk18UFGNbn2XH/twEP lJPumdftMwrgXnpHjQpmd43zGUn079vVbSivbbIgunu/Xvic12gu/7i/cEWhBtTN5ZCyscnoCRMt JABxvAjlJNgeHLNK23DMmWvO/SlX+LvC+sayPD4Oy6pdMH/729+CwMgD03UJ3OXpsXus1geK66zh p8ix+fjlKhTJkGAdqbCGJBTmw0OA/XNcOdxCOFr5WvYVF1QmbTIeKA0tJl4D/8m0hbBwGkIqSsbX WytNkqsKgnEGOOccQa14+yb+ZmGj+ELBLXSR67VW0iWLDBdv8F4GrCEs5z7UXyUoDfeF0uAzVMn5 j+OdnScLb0Ii5F8DJQDqcb8o0K4er1sVS7NaWYcW3XmwJ58D48X4wa8St+MZ4JJndw9lhgX424ff Ni3aAfmusL6h4Ka9fXMRD5MH40N0MRlBurm9CxxL8Fz57dPn7q8//RAuWFYsv3768lU0JQvHvn8o jPchQdHBuWJybcOfxLOIWYc7OfJZo2Yonym8JBNKjf7JLOd1FJUEz41rHjmmO7XAPDs6ix7LJ8bh 7j4WNotWLhR8pFjwNdJ2sbzYGLv1TZV/un/bRKoEC5FzgZEN4lGVJzXkAs2VVXJp22szmIGCfAll hZjRIHcssMTV0wax12vjNTlyfhZe3Lu373oS6eh5XuTqv8tXAoCOS+fCcBKhJMCtVGI8TCyiVlkp YYEkxROs9i24EVP5gbB9/Z4sdKyq29u7sPqMCKpgcsoOks8RoL3coao4SnTtNFJ7/CznGFNoWRgP jinIrcXFdQxhLbrQKs+s8Pn3ww8/9MdB4d1/LscJSkS1QlREQcC8vSsRqbvbwfHOYDaKB7A4rIin Ao5rIYVrWFNmUCAoyzgHWFbwRQ+TBjMk4mWZZIlwLW/fvA0aAcoqp/IcWlRSuN2ZBLtYbRJ9UVLi jqHQ6uVoQQ9RP5TvCuuFhYdEXh9KAeEhGdLmPfAkHyS/T+3cWGitlRTg+YSl038uHbcw4Qs+hasI K/79+3cBmAdfKVsvHDdNcF2ot2/fhHJSwj27vu7/jhSbSgjdNj4oBVntWp5aWLgKHMMJzj8XJOPF tTqWWmc98fS0pNkoKJohcD1C/It6DzWaCqgPUIwSzZGscN34u0b5AiAHb2rGd4O5ruJ/OX3V5QXO 9ch6534Di1wVbtNLKatBqWMQJFE2wTz2iy5cRfArxzfSegKaKOP+HXT/hhJ5b8vj7t3lxcYkYcK7 yNx1whK4vu6ub+66y4vzoCMMCZbXzd19WEvQEc5Olt27N5dBjfjt07RiOJoAMnEH//vLrxEFjBzE NPlbnhaKxPtYYOGMHJOFPweIb1N9AnRdLCL0Hvlyle7A75wba1T6hTtxm7eXAxE5ONG7I/CsqnIL 5Yxl9PgU2Ao3xDWwyHEfAwTP2FO15Prj8j+igBMS+NUz3L25cndbxs5kaf5m/LhHLMiPnz6+COA+ JJlGk1OJsmIXozWx2WuPvM9KaWktre8W1gsIrh+cKhdhzmvTf8dysBoBmNXnq2LxEOkbnQRPTxvv o7xOlkTMTrZaWdvSfgTQ5y6rkvd1GOBdJbhhAV5fx2L7z3/+E2Pl63nCG21qRVIpO/fF+UVYS36P 7wgMY30ZecSKC6wrcdW8z+wOBz8quV9TYrRLwJvqDRz/119/nQ2mz5XF0SLyIaU0cJ38HRkDJ8vY PL6VskI2YIrKXOdZgBfmQIbufb42rhdlK2/tO3H0BSQiOqcnoahw/4JTQuWDGj1xwrD4WFD8i7Ia kCCPj8LKIT1HJssvHz/NOq/RvZOTZSiQIeH9ua4AOYRQFrwnvzeEk3G/KFroEKUEyKJ7qDgS6/74 iIhawXh2yWtEjPbJdJevZrIwP6NqRErZERdEyYhjYS0FzeF4HXnNyqJVUK200UWsKdzWwM9USJI9 awABRWmErB9Xqi5gna2e+gUZuOFxqU6xDYecPW5dcUd7qYnW27hth5ZcNkfsDmAdKzYi3xBZq9UZ bvuqjmNXoqkoW56dVR8c/+8W1gHkzcVZd5miLyycn3/+OawDXRtdQBYPi8nFFSxuiIYVvxljcY8J Vhalsy5OTwYVVuHerKkA2xQXyurufp1LiPINpWtVgRQBRE5PinIjZ5FXHqnBlC4ftxiBcAqHKx97 SrKb5zUbwWTcGEPkX//6V6+kEHGosGgfNy0wXicVh12+FYB16AD8jFIz8NLevg0io697DFNoTGTO tboiQbee0+/AfcqVFNq0HBRKWG4vpFROTgrPKeN531Rq4qpZAoznjz/+WDYioQpc8du7jZQhwXnT yJDvCmsPwWJBCbCY8+JjULEC2Fl/++233g1EPl9dx2L98f3bPlEXl4cwsNyr7LO3rsg24Vw/vXvb /fb5ywZ2sEshwKiFBY50X/hAWhJhMVbuEuK1o0BCUUWu3DJcVtxhAH2v3TQglBVyeXFR73dccXJu FJLjlEU8i0J9XB/jp8XVkzDBSwZA2z4P8eY2rissYKxAStvg3tb0IhQVFkCA1dW9kncVCpP0pIk0 GEXXketAAYa1dr+JTxIICAU5mor+PHmIRPbCaQsMbwtt4CUkivehkCvggIWLsgqiaCqRg1XFOOX0 Kr9vOtN3hTU10GHOlgXAQhyzDBxgq1dqOSEbResCcIeWUHZYq2SyIweGUklzfA53alcvgYif1UCV vGtb1G9M7qtC4j7hZrUcmv44FQBf3/+aPd9+oy1H81BZ49usvQ8fANeH616Vc5YSKVpcEkx1zXIy NDt3RP0qgB8pUJ8+xuJF0Yf1WxVG0BLu625+sq5C+lWS71jtKSVFCVGGUThwtQoFmyWqdL4gIP/m zZsgwiK4Y5ny8K3k6voq8DsJpAgbBfMru3wSb62UWj5YxohrZ40sf/rh3foGwv3FFK9/1mz+Esrl 3yby/0cXS6/kCgMU0Dupbk6kxIyY6T1Jri4cJj7u3lAGfpyjWgBLdtvEceIhqLScWJ++XI+y1r++ h+VkMjSY1FF9+Ls8u5fchFFEU65hYEFcwwoXotTlKkqcROxhi0vFhmKyNA1KVEuKZwQXiZ+4hS2j 2sjjhpuipGFDUXGe2+uCPRYLtCg2cS3rQuEKIipFQ/l5E3lJa2e1WvXWJNcIhnToHMJZNItq8WbX Lrt84XbfraEQlFVf6LBWyDBYtQTs3UVa5ebDlMAYybbBrK5Fz/Ii+Ya6DhAaS6akU1S+0oDyIUKH wmLi/PXHUmokizu44DkLwagTbp9KotQmf4ryMALhl1EiuOs+fCpu2s8/vNsI43t8lBZhZxcdJNPP V7CwE1mT3Z4ysg1OtQ0P+vD5S39f2xRWZqXjBn65uokE6iz5fudITFI2uuZ1rpv7i1rgjw8lDeZk GYUH4Zuh2OOaqrI9YtLeP3RnRwVkb+9FzCuwpYxnVba5GwmcoLFxEOin2B8XHBGqWos837/KDssg oo73N+WYtWa6ygmrIJRFrbn1rWVR8xxz8cFvJVIrlADTUeS4fE1RvogcnpS0MNdF1G+HoHtUsF82 iii9PMQmxoRtyXBf7Qj14SiTZq3KbQcZXVwjpTnMnt9XXCC90ri87HcGdwfdDiwhd1SUE4uM5OFw SZIiFATnmCQgZ9dRl8r0FawzXifkzcINrOvzl7C0UFTwuQr58DqOvb7vzfsYGpcp5rBiyRgXPQLu FJVHm2erYovk1frZxQBL3uqcTN4h9zKs1yNwrpNQAh7T7wtO61YSRQUrQwHCtO8GgGp5XEYPW2Ge Rj2s+kxxE63aIMAbC6Om7wxhaPHZyhuKtTOgBzZqqf8OygqxyKBj6/29tIg/tc/GQJNcOIXri8Yf 56UZhZHZXLmB64dQusQ8RnvBTbGrhQ8qSkHMuMGcsNlKfuBDv28Aa02XjcDaml3zpWRdDriwvQF8 MxaFFaarQq0pLJ1tFktYZ0dH3V9+XCe/Yp1xbLAFHhyKEXBXpfKXv/ylKMQAzN+GdYaV4/1jtd2m c3+5hi1clI2Lui2ih0IFg9t2rVjDHkcQm4l1QmnkqoikErBQMz4l6XPDxWIxV4syBxVKWeCn/joF 98/IZYRZXpVgm9wc1Tvr5qrSYcOwble+FsdYxQKOZRWDk7OTaNhw9eWqFO2rmCLPg3w28SYXeH7O c104rAlB/jkbxqHl8fGxT8kxH5MFj1v40nysiHraeQlIom54Jo5HOaXbQg5VrC4L8I7BlK+1T5jm O7zY72jVd8SPZyGpERV2HibBGE6Ts877C07JrWOFz/rs9NTKSHyAicnFukBiZxyI0MydSDmHbyiB 1kkWjFsYzzHRKxi7hdHcCq7dRY08MW5YUVIcrOlkCkpf+7umn2iB/dBE+SIDv1GUH79ch7spN+rt 03n3+XpdGmZ93YutNdhbd+vx4aH7+PmmW0aplfKe1uWU5ZDTfzy+P1try791l8ekr8SZXFIULAq5 rdAahNyamxbtwE5L7fSo616TbpljZ8drSIQ0kVaxtC6M4xNlkqtLG/O32ta5NVdYa6kW2beUo7qO jXpy38ydb2HtMV6cW32RW3f1jPdairoljLqpqNAwpNzcg+zbFhXjYCordhsJeREC7hZrEp4XJ7rf Koz6Z/7snFBwK5yXXSLqQIP1vH83mf1vxE1Xy0x/il2Ukhur7ur6pruufCfTYLCYbu4+zMrL23rN y2VgWCiP4FlVMNfFAADPZ1xQLkL+wX6nPLCTPY8r1sSHz18z4aOMcRJwSfAhFnK5t7v4N4fi0CpD Dh2VT5saXFhCKEKsu6HqBWMW95DMXURjnxtVw7UKgty2Qm4tIPlQXh3z04iVbs0QlMG9sjb66yIB ulaDiM0avMVnar32bywn8PJuCoUhCvadnoQCOUQXoK3nXp7EOalOoXWXLS3dflzAXGtMN9Dr5e9Q Vnclmoh8ZRuGCQZQCRhWLQJ4E1Lk+f3QWnoIRM0SXJ6Hx54lPmZeC4zDJ/r146dudQNoWrH+2AW3 y3OVFW4c5EtcHq83Wy6A4Jzh9N3b3iK14qjjz7hDrIMikcfa9J2vz/m1IqLFV0Qhk6W1z63FIh9Q ZJHMXXVU2QhYpLTT2g7szuWYTTXKyMI5M5XDRPP+fGmhRIurd+9LNLArGFTgWPQipIDeYhHBlGhA mnr+fWWN3g4/i/AMumLdZUztJeUplYRWIv0o5uGqx4tsxPHS1xPKpZ6Cc1s/P0dIw02/p1JI0TeR 7/j2XVAg4jt3JTVH6kN/bP7PSocsMiNTYRkMmNmlDEmpFDgmDh4nwiqYKpsbOFFXdrKpppy8zzmn sIB1BHMV9AQsjUVSRGA/eQHvmnaDpUFlAy0XFwdWBuczpSVcgtPT0lKpjgUWDnQFrCGO4/Va0jcD okYOsXRZWD0Js5YqzvLm/KwvdGd3YgU3ibpajsuuG02hYRDxol7RbbccKdUb43Ny0l2cF2sRN5ox 4Vrb6hKBN1UwfcpSFrTl+1RPnZpD/XVW8T6PF5uKi/OhrPoqoHB8sKxRLrdVkRJNS0o3jpVue67V GInU1c0fsmrCAq2pKHHMFExa1xybJ8ug35Tx1N2NUjKVpxZKq2J/38Lai7ZqKZCHHsEttBxyxq+j auyydCsKL6RmDzB+Q8bJUhA0mKhEYCItoRLnqvbzIVEuZAWAysKMsiDr2tjBlaj1hFRCHtsyJEWJ EUm6S8AsCZol7K3FsU2woCQ5ugCkHFh+5Md0vChDAsB9fhYLgEJ4+3S10XKJulbWc0sTIHczdmfl /P/9UPhVYEA/vX9Xcu4eHiIqqPsK2E6EsHcbax4V1pclWgDfr+skVH7+y09lY6iTNXNdigu06B4T xriLGOUz9eW3j59CCUbDjPPz7kvFSGy5ZUQKKRORgnjL7uPnUmM+MgOoshAt30sUT6A+yhIfUepm bWnGuamVRQCovl4CAaXu1pho8bFZ5nSUKF/yWErZcL3s5m3hPJXF2FhF3l+tgdUuftuFYcX8/W9/ 33iN5+h4bhPm0a+//TpabG9VlVCQVxt6UdxDV7DffF+7Ns6YI4FTXl33pNwcmW2NDyEOU6baOvkR HazKKlz2GjHePGHXLQ3Rxk1FP7bV6E0GnyYQaDhHD5tgaLdZM0izP194ASs3I0ucIx7+TAsgCrEl IDOHjcPl+vAhfsey0JLhWlAO8sII0xOunyOFUFiUlUXgCq+lKCcelhEysT8Z11wD/xAstPdv1ixn vmftcR4S1234WeF9PqfS4rNwqiBdItAfOK/4WHTMrdE8Jw6gfSGirikXcyWnR0Rzy1p+pqN0TKpz tUrPucWueFZvmjzL+Bx0kKiq+hiW4yewjpQTGONbJ3k7h6aUlWLUkHO0XMNwQa7Kghb4lasUzOvE tI4mp5UAijAesYFUJrsAO7+z0PinRRXBm5p6g9iKvb+Oel+8bwDGewTfcf3sstGsVqvg9OH6vmTB wD4S+e5tn2CuK4jFNKTQsfyCeFtTdaKjUXWvY3OCc9WVwEh76W6cobDmtvzJ4eYpmcs92eXcytTn 3e1ZnIDoZ7Qgry4Jpnm0KadsLrvr4/ZJ3wLa9q2zvTr3iNvnzmK0i0X9y28fixW2WETnGzlOUkZs CmC1gz7smyInsfNU6gOTUEsrk0VzLSlC+QD2lhguk+Cox7hwS3eRNsIVAYKqSLJwv3M7Qudjwn2T /8YzUcmz0WAhjVVdnSsl6jgC1Nd6UYxXBtkRAh8tWTQaoU7MdWs4ISpdo3RGLMElbaAhAZX50y5u LU+jy8z5uevkqaZNfQsahZQN7tvqEzauRfkPBdn4jgX9ckK2jSiGErTDql5C17mbziXcBobv+rld ZJ9z55QXnj8JxyfHxYT/4W2JMrKTWYNqDsDOArXuU9sbD8m+OtgW1g/8IhQFCw83CGzL8Lq7KLgM BftYlCosHuJf//rXmMR5U+BBorBMMRkT3men42cG8pWxmu67SMET5xfPnAuw+znGjA1n7Fp3mWtC AmPKRoA9wwru5PkYlrRG+shVrRwxFCHXLQ5LqaYKudkJG/i7/fr4TtvNyAifCm41477DUrsp3Zde WnJScvCrji563hs/hxp1yKuMjZlsh6rAAgJplFVE+pfFqzFJejk0sXwA1umZsqjywz6UCEa3xMFo vtAopjC5681sTqCyuy46BrB8X4oBCxkFRhpNC2IPCYoIpdOSEwnro/ToWKMbTNIyLbr8rFaT1AYu BuKpAPxP1frh+ywEcCwneQbLsZ6oYLDNktHSs727WFqxInBvumcJ9wWtCzwu8LE0ZzI/qp1DU3wk MbDoZFOxr6vb23Al8zEzvsTR51hgc0rZONZYsgY72qKC+Vpzow7XR45k6RZjTWOtudkgloD2+0TP tllDQWjFzftUgjhTknHElxbXm1aV12YaTRtsKM+teBeyDRhPEtHbpPBCui5ZDpka0vOwvtolooB+ mRjuVItFidrIM4mLe4HUg9DQD6VFUfu6N4Poni2fSsZ3r7D6e1jjRu6MDBYKAeVBuy3xoAAQb28H k47Z8X/7iI+eI1Hgb+WzWFHv3pa67SbnyphXocckJ7H585c4J4x0amiBp9mPzUJ1FvfLOy7Hwxqw 797Ubiu3i8Ug0JlTZp4rlHF2TLPScB55HkFjlU7PdI85tIYDbOxq6hP/YPTDkcNVzPeVo6q2P5sS jjunBle4o7XBqN2DbIyaFS4/tbAQra88N6MjT4IL5Gex6SBZGYo5+fuQQuI1m7re7ejWv6SY7B2l c+g/yNx/LOz2VowGRsfnZFkJeQxZVm3gAImn6ARozf5yUevOKKsV6RTfZsAMBGy+1pT54NpsCpB2 4F4bJ3YtgyLIHQuiAuQZv0DBYU3hSrYSOE1Vbv35F8WaymFad0smtU0Swsp6fIroJL9DKiU3UJeh BcqlNegC5nuy/K+0kbHIalApbm42MLFD6CsjXSQiZ5bD0Bzy9Wy9B9O9WXThHlVllo9BUUNq3Vs1 Q8Lh3NA8rjyKapdqpzwLNgauU+XAs8yScyNVSFxbjpT1/SWrkpviDprRMXVvPSfsaNzFjny8y1KV 9VvIBkZVo31I7k6ULdjYBJbHfTPVcHcb6lTc26obxbMGn2RJn9idr/Stpb3GtnyFIrUhTxpBUiaC jS7DHTs7DUWEm7dNgudVFYcWkQ8H5RgTlwdzXaJhca43l7GAQnHVtuFORhQai9MOzzxgFZ+KVSWm Gz62EILwW5NKs1v1XBEAzsGCsfOPuVWtTH0Ofptj+vHT59g4dL1jg+JDdfyur2/76hJD6TpzxGeR OXGF2MENAAAgAElEQVQbsESq+uGz15XlmUNPQYyabas/5XtDXk4rt9XVz0nnWaziuU9GyT5iqzMk X3vM0xoNNXrqtfPAoojgAAqqZTVUBidgopPT3Qv4vQTAvou0AHuWdhAilL+qddUfHiK/btGz0QvX g/cw1XMVBUrTWINpSsSpeBh5R43Q+/1DYGReJ4sHDleYxnXSGcnDtaTrTZTBSe6uQKxWjVFOFN3U rm3+mBalofFDcgYtjbyP7DqHvE8s0ylBWTHuRB6hYGTJrj5uuNFfezbiym9r1OG123JMMD1fpxHg jGlNKSI+B841VBli6NwP1cVvE6p7tvtEJddDC27g3UPZPPO1sDlHUv/tTUmEbsi4zkk+E2uw1sVi /d4+lvpdG7JivhW4oB/V3NNtTIygbMOt8i4VOM/E5IzFNDOp+KsC+wNAfVybRfPuH2ozh8Li51Vc McQFrxluBVBxAtzJbQrL87gb8/cHrIAKxmshUPNdU94kaCtBwLzHGgjyKKTSitPwvgrNyWzD1W1u keVqsiUgBnno4odKIfwVSsmUaJUYEj+0RKuyOge826Bi1CABT8XO2TwicEv5ejyLsaoWwgEc5xNj O2ARZf7VXLH+/C5jcX19HZtrxjgZ0+DyHbgbz5SAZYM1SxR3bfZkdOgejyVFqJVCPyrt7ixxJRif pe9TWFMDlxE5g21ONw9qDzX1jErtoZrqgAtVS5DkpgQFNOW765rfgs3BiK8YmHwKy3cgZrvH7wmP MaI3lqbgwvU7uQxISSM5CversGjvexfPXVoLq1hCV90Pb99GOon8l60lcGuddkoeRx5dg99gUaGs mOAoHHdlHkrfkOL6JugVAPBYX16X3V7asHjGyqZE5Z1rVcXP7jCiUoWVLtvfeujnFd/xWbTR3nDD zWurNZp83QyB50rcbz1/KSyJO1E7AaXPYAlkBcXvPM+IRIdiK1bE5y9XG9Ydx2P+t0rbgMCuEfO5 mJyiG6pEkn/Nv/uWIgertZq9n6jKMOGe+gzsa9AqK5OhOY6b75KdwrIOccI02O3AB6epXmTeSVv6 QTRosCwsKSP19eIqDQ8qD1tw0yJ5eQcRO2gfbh9KTTsU5EMY4Q4iYPq71UW4aFcQSKtLFdGXcNsK fvS3n0onFlJpHHxIn0MVEhT4VFmIPNrmi2sC0/jnP/8ZC9oxKi4gkb4uGkcQfWxrwqusGGubh84R o4PgcVozjkNsSgPcmF2Fa/33L79GJC/cq7qjIlHnKk3er2u6P5SaVHXDyK8fSrT2GGd+jrl6bZI0 AhzQyvFxm1O76E6PTspmUxWZVsIcC/gQcl+bo9oVe3X38udsJYwK8lWvrjYA8rkbq58xAyBXbqDS RBQPSKWTkSU70LZ24gpgWBys5gyOCcpsm2uQL1gOjI1FlalSGFz37W3T/rqCrXlh+VClG1zfQgI9 jS00JwYj//71w8Z1CZATCaSB6VSddVxNJm9O1eD80TTzbO1yYNGxkKIEzfk6YTrK6FRyIWLNLomN 28T7YBxR9nC2fK4qeqxga6M/R8giwCL0nCwY69HPuU6szHlw/PNkSCEdUsxeYGylJtDN51uwzBc1 EhmBlZRQ/K0l2s3X7lCrk/2wbbE5a2RFGlgUGvi62ODv3jUnD3QOhWcrp901NyIr7fFi8ReQOsqr 1EX7qZZmQYn88qFWUei6vt45LuMapyjpLMFWrxUTCj5TFJaWGC4d7mfemU1CzpMWK+xjtdI4L8eW ya3rm4vacY2kjGBtzZ38Rohkt4t/5XHFGiqWFryZ/SY4brDu6++1SF6LBAep5j32FSC+kZzXNmsG AVp6wJgcuvqp2LdBiH3HIHIIyRCpaW851UkBL5tUWJLmtgHskuemLrad3O1nvVlehaQZVtc5YPWi u7opYWOtNoHzaMwwMfimqmRQk8XGlWBl5UuC+a6FBftcS4mBM+pXPldIbtHFOXrw3fbWExZZ3xKd fL7bkqojextcS0qDLl+UY6n1shQffm5Wse0Z2RBDcN88NQH3XF4EnGbXTswILtC7N6VT0FS01vNE mLomjH+LSpffWlD6peFIobeYoO5YbZuf+8ii4oXythhXleW2im+RFsOz34PuMSU2SA0AHo+hr/K0 m5sKSbSHlpqv9TXd84t5IgaPopLBMg6RraC+djVZ1seFr9Ky0PN3URIs5LJo7jcurM/ij+oR8DgK HwmhzDATALyJ12y9HmxZyt/WxciOIw0gu1bZKpLIqEltEnNf5iT1otNNwwUy8BAs7VqcDyWhoJiw PnDxqGhKZdNFfQhUTDAJW74NkwxsSowp73y7TPJMfEUiH6+Gi7l+r3Oj0/AeyoO8x4vzdXoJ5E8s UJ9jwTPOopKCOI6usCWh/4yC5c3Gg0RDVqwAaBUzChnuI6uai+fCliAcBGR6HE7MnUgRO7CyytIX CHxGeCcqxFJh9Hitmqx+TDmgDYWVd0s0ZqQm1PB7m+iZo0Bc3+nRaXfzVNsdjTQQiOhS7UoyBZoj RNg8fvjqlYXeDhAPS+JhpgB4frAF/9Z8zXQBM9upBIqQChLRzJOTUFa5REzbEy83eyipPXfd4m4R SpXFzK1l108elURWTV674/xc3VOt2rmgpeNtZr81+ePYtZnG+rnOqwqaBRfy9LSWqK21yu3gnO/f mlWIaS2vhb/3UmLAQSVCpNnkcPhdOZ3rELIaafTCPI6NaqKiaBTKfMGAgKVjnhuOLjXTnmp6YKnL Fyx+glCjJ6+LJkdy+kjiABC/TaKBxA5YlhZNztMiAvfrx8+lvpE7TeM3kwJjL7vY8WqzADCeHsCO jkDlalAUG2WEU4Z++OZVUaKA+F3OFq5mBuFRTLiLWaEb2ZRzZXuwcp1koD/EuZnULWt8jkWSqR1W mNSy8vtDk3PXCVvqRB1vMN1zvbEhYezmBnP+qMK4E9wQbO/d7vo+G9yhMaOjav23ikfguo22bcgL Q466p/RgCNmlrMcAPkgRw/i9ViQO+OmA17vfhTWpECgGCrmxIHDPuECz6AtedhwYl6LCysx0o0N8 FrxLsquKkEoJ26o06LYyCQXgfS2XF1Hev7norQitOkDznNoROWMw7q9u+nb0HFsr1gfOTpKrj05d o8pVTMME7zHu2j4RwqFjDSW4/q+J3DE2h6EmpbxHWhb9HQ8lqxQNzmldiKla1KYacv3wbMZ4jYcQ KQpwLbeJG20UOahrZCPIdlQ4m7aUszjgzgrLxb/NvNd9nIuXDLkPRNawqnBroog99bEBwpua6nxG AUfSdUQpYZbzvhgZFpqAaU+ATfcSFSrPCnbF7hm5WfbSS+264t7S93LiJ5ackxkplQmKNRX4HPmC by6CeCggrvvqsW1CsW1yMUlRcLqxLYCfJVufc8VaYK2s2oqQMcnm1b76M0jG6KaIoifPSGGaOvdN rRXfNrlgs2KOZrLlUB7kS4mWHpJJpe2/MYlWZI8l4ISlGE1cUs7wTgqrUPBLdcBtVRuMsoVC2GLN jDWbZHFjjbx7UyoaRISExZM8Dd0SHhIuV9stRsUalQuSVfDTD6W2etAcalTSc3qvlhX5+eef+yic lh7KNJNGTevIihfF+gX8q1IJuFa5Wrxm6WasqVy7yhI4uqVTwudRcjZkndpIrO45V0ri6vCCo5LC VyzvqrjaagyHECsivBYqhdE6YZOx64r6YZRfOXCO36pWP9Ci3rDqrq6iakM7d4ZeewkhUsic9Jlt NEie+/wWm41zlZ0tLEq6wOc5fmIxrXlLOYPcphS6ebeZBZ9yFvXHcYPEl1jYD1QrPD4KS2RowcCd kqdFNQSUGMrKNJbzoBEcR1TRiEUMVB2soEsk/hN/q+B0mTRTW/esUBVKSk+WIKHW76OodDmjaQP1 1qtiFc+yKH9mtktjMDI75+FaOkdOzpTsCrjyLMaSaQPUr80YAmCvFmhcU5O2dYhFYoLtRoHA+G/A 1PsG7qsVPiT7jlmWbp7bOm/vI0c1StsGNAK6oLQOXZSTMg1Mt77+0hI0hJRRsuEKpuazG6Woa+Ma n/XQBrWTwuojf40F3HK1+qYUAxttnrx+xzbVXOB/f/tY2rvXTsZ+B3eJzwFuxu6G+1M7M1NZFCzI qgl8tq/dfnMb/CqO+Y+//RzJySbIClRnUbGwc0k7UFllJvyQyMnKKTpZcPNMmWnz/LxPCKPcIwvB TjpTInVkjiLKCcFz3cExYJ1mIt7fFMA+2rqtdvluC7SNRrhqpHcOPtIK0SZL/7TdifaRXJSRhYml ZcPQby0LWeLNXItn8vlLMR4qDCDUACj+0pYquY1EDYFyps7lRs0cDjewRrmVcCGPSied8Nq6VyBt CF++j6RIOUuW0o0CfOcljw1BaX349CV2MZN+1/XB8YVLNJGfAcIfcZyS3c55pS0gxRArtaiCOHpb uiYPpeUYFbTmFSKLPUfvdHlVVioDrLDA4ygE+L48WJSV9yCIOlagzxrxsyffageuD+U/JqKAX52z mvD7SHE91wsrXyeTHgup5ISW+zXZPVvq1v5SEeVrMRmcayb9q2VQ7yKc1w5MVsTAFacWP9c2lIDM vOyj3lh7Nb/1EHJ3dxfXkyPQSh+ljpSsMlZh0acmsS8pjLt16LZxxBAUE9bflAX4bIWVKQDbPpfr RQ2Vy3CXdoFqhQgkZ5wLZXV5XBYUltSvnz53n66vux/fFi6SO2nuikzViL/99ec+743Jh7meryd6 WqaqEeHqUhu+4Z+VPMPa/ivwp5IjqLLCUmJCtx1Motzyp7U1wnHpe5gjfj1YX0mgQ7W8tUp3mXhz mNC4uiymbQ0rCGYcn263UqYqZK6P9RDJrqFwgAJOTku/wKbe0/EK17N2plmUfoL9BsAGQxJ/Bx+s JMy6SC232yoqKyvs0r5dkmhOSGdT+ve//x3WRG6Im0WogZ/gsodSWIsajTYo1Yr9BOyliOUzt5zT IYTnwXXRDmxsvmbu1sb79lw8pMJCe5vsm3la+qFGUMKcozErDVsbV0GAPpKVL0tVBWo3aSHdRLXC ZS3XUjAbIyUFQyntovhs9B2k6edvv/Xlh60ImQFtCZw54jjUKQX38ecf3vW7OlUWOI8Tbl1hobTA ctBNgrW8DYrANlu8D3sfnE331DQdxy9XsMxVK03pmYNZtYILV0pKl3pRnN/yK+YWzl1IeQziGS5Q NJQOWt9DxiKmqjFIRj3fBedZbPJ88qbTAr2+p3LSjRpqVOqzGGqVFVUmTk428j4jUbd23uZ15oOR 3iGJLImJSq37yLIGbJzv7VhHnanITihKPebTzl0q9xeUpERp5okGgelnYrfit7qB8XfdmPgZ97rX BaTyMlxMMNgrYU1F1DLdYzd7oMb2ZrEyL1Tzmigax8byyUB4XySv5s3lLrpPadHFPF6tYuKgNKQi ODm5JhRdlPBlVx+xDM0jhNrgubHYjDRmFnO4HNSBursP68lcR8D5XJoGpQYIj7JSuB6xLS0Aia4o Ql7nXmxggOXGbr6P+1V4MqTYrM+/b+WGNnmaHTwz/8ucOPmqd+LwsY66x9Xmc3Dz64sQNmh6BCae 7rrl0Tp03t9nEyjIREtTrsxyaBULx8WiBQdtKSIGdXjfOcHzMPXJeTzlcRT4YXFwpfVUS1JzX6aU OS7cO9fFPAq6A5vr3bpZ7LeQwPxuSlTTYnx23T7pxucyijV0Cd0t9lVYuXQM/CKE5zonGpQndVxQ SuVxcKEmkL+HRC2r5DLpPmr+ijFhKcBE11pjgbuo20aUPNRffvsQtbGwcCJX8e6ux5UWi1Lxk+Po jrX8Ee7DOlaIeBpjU6qcJpevdu4x4Zh75R5k4Qvut4vGiR9jUsHLfF/7yKH21a/4Rash97I2Vqgp IWOiG8WzxXXAEu8zLVKqSSivNMXGXM1WCbXRUWvij4nWkmWmERntmYO4hic2O0O3nXSy5LI8LyHX 16UsN9dgaznXBPe0rsr7NNg38CUlopZgWXTYCR7j7tHb5XNTB54GutvsKm2JFRRHXBwAZ13suoIm PAf4ulqF+6hQSUDXjQmTSaSlQsNJd/fw2P3fmhzM8anSoDJZXa7C5ctJpgUwpOUYUcA13kXXGAyp Pgk1WQAosmj9VS0td3VZ8iqpdWWHsgjIZ6QChBaQStLONy6e5whjcAhe0CDG1bhoc+kM7LLcH0oh rOfTwmw2MXxIwq0Y6+o8YDXlGv4IG95Y0EJAX6qM1A2+o6WL8EyxguXAKduqbBRL7/DcrJawbSEA gzeWYx4q3fItJaymh9L6jGedx4rACn0KJeVG1P/tu74G33LXzOop037vG6i4TMGkuiBbsuABzDmf aQhaO0Pnt1uK7lNEb2zTdHEeSlCrDVeQnU7+jDiUAHt8ppYyxnLDUijRnfX5BHTbRYmLhRJkVAX/ +7bcy2VPPA06gux3rKia8H1WIyQC7tw314LrcYjEVa5PDEHe2L7y1Wb3jEszQx8cqw1wjJ17DIdh B8/Wl3ilm0ZLvMzlpxHdRSUnlZvx4LMxSog15vzks87DKYX70sl9R6mlnfPZex0qSfwtJSKCMd/P SvCkK9cUUdbVem7Fc0oFQ5douLnlaV1o7e4ZD6VB9OcqtkIWXWMMKAcu9ueffuh3tjXHpzxg/o4C ZrXECUqF8s0uRI6JpcQCQOnFBEsP5+G+VGpUxCRy0wknHZPSgnUIn4l6XfVeLTr29PSwBpqrW8A5 cmmXaKgZKQePUYJm1VuXm25v4D/VnHdcuMahxaX5L4A5x1p2Fw7y62rtzu4iwYsKK6HbKCeUI6x9 9Gcg2tOKFgCT1xyzVhlmJUSki4BPvp6Nwnobkd8yplrMHkfip9YX72HlZYzKAE/O2zNCm0VXXetq O6H08InRQ2KgyUhozjkd6/23i0TlFXL8drTYekv39qZYW5DQVwUTZ90hKK/Li8s+zSjcbU84R2J3 weWKRgK0p6rAO8mJx8uo3KCSQbamldSFeXNdGn4iKCFvJi9A01yI2Hl8FEMskq6Y17pNWkr2pePh tLwcI3m6HSqilhzoRMbCYQCLpbTuDrPeudd/604iXitga3THqZaNfLPLs/PeNTD7n8nfuipcB4sn dy3ifd0ofw9lXRuBbktlwQ1GeT5imlfQeK5EVPPxywbAzvOUpS+T+fzsIjaIbcnmjlWJYpb6R5+/ lO5Cjo0toWKcV5uLPQPIukRDWJbFDeVLybnDEmbctZqYL/YYyEEOnqvPaMzt1DKY2rCdcy9fTLnr x8NrC+4hTUzrpth2Xt5F8DQuzi/2wqO8NpRmVpxaVDF+tSPIm8s33YePH0gJKxbOHIndgmOkbsvr 0jGbtZFmuY0Vh2ASOvmY+OBD0UCg0iUQsSoWWITje+xozZ1qgU4Y8IiWSi56hhZ3geAqohBNZkYZ gdFwTbLmUW5GggqIvO4a4s6Ntcd1m+Tcpu8UsmdN1alFCIMbUyOe/G6K0hAOg7K0coWdRnLNdyyD 6Lq7XPZ4n/yjsQRdk6HBVMp35wGxYXEIWtVcSXoqthbFzczyQ0ITQQI9LtVSncQSS3M3cNM4xgQL bFFbU2v5uVFlYByJDkAVrGZMc7cmK9YqOfezneOZfiI9om3gu3GN+5YTXpU5k4teit1uI5jm6GEE Ft68DQtmX0zLNRHjfWAyqmuCzQhlFZ21A3icOal613HLZjk3Y79Ekoq556RCYR0d3UZVBbAgrA+L 6yG4jMFfInR7tU5Ahk6A9RWh+7rD895/fvsYJY/hdTm4npvjtkoFAe9CYeVif3wXpXl3R+OL+rn7 oiBLe6f7SCcifactNMhnSNXJeBEKBKutDZOvLcrbIBhS1M8dkmflxBLkbReD45hdljltp8JF2XH9 YMWe1vxPMwP2aeQZi/v8ItwDSqPEfaYdl8VwtNzcWE3tGZPsgrY8MCOALF5LCAnImz/qZpbTnmJz q1QHU7faRari0IppAfmNz7Kh7qAnnmpqEc82K1KtuymPxsWfcdDgCJLCVhv27sSDE2e9uIxUHxRf cNf2gBfmiO72Mh7M49OzTvRcIF4/24VDyguLNSsqRdfq//k/a7Me4fwop1Z4nWoMWaA/MJEgm1Yc fiPVIxRRbTMUf6e+hvCtYneKnnpPGxFOJoDtxfL5I7J5etpPKltxCdL2SeLQL4IoWxQuwj2Bv4Gj iZMYBT20RJOPwBMet3ZZduJjjbIZBDWBlI89gGQXN98HCLY2uGVGosY9LcqWy+7qS8GScidhrwd4 IyzPgdIqvJ4Jnfwu1wrxJ89FKCBnGHA8LSZB69aqGbK4xjhopYrrPHqK1t75+XmcH0XLtfC66yZb T0MyRTaWWEpiNMJmMcdainVwV1rQM36ShOf0IthXQr/zgM+P9yOyxeSpO9RzlBaDbWE8I4TgWV/I 0WtYy7gvHz5+6t69fdtdjLCV50TA6E/4pqZaxDVc34RCjJBwqkKKxYb1lhcBioSuwRAAc7hctyDq UL9715cgwY3I7eydPCUKcr9Bz2iFa4LqYOYAltlzE3jHJCgZy+O452jUMfCZVe0YJG0DoRhhYDJ7 XFP0BGiY6igmyvoYcECBoZBUKMxZ/tai4zth9Xz6+BWDHWUnRUHqjOWIzMPjWYldSTvJ98IxsyUc 3cEbt3CoTtyY1cPGUApOlKKUU+K5Huuxcklm55nXojXOvWqF6eqOEnfrvBJumCOcF1wJ7yzmPv8d LcJCfknKRByZHW2OFLeq1HISRLWUDEcC15rjDuYdJ1yYp3Wky2J07mB/+eHrnZ42XXaMbcHPFkuY uoZ2F4h6VgnQV+RqZaHCKO6kfCEUE7uM6R8GANyRW3whuurc3IVVNUfR0xexuMhHQcGwzZOLJLu7 hxAoFm0ZZKyCoowfN5RVSKRVfB2123pvq00AnbkQz/bNZTQdwFVUa+IFRB22+zJnUV7CGY4LNZ+G RPdHZaZFBQbIPDJlR8tqSPHm8TUlJ1u6Q7STTKfIY0HAIyyROlennh0Kqa0u2jZ60SW3qB9WE99T sW3rEaCVqzU7JVwvHWx0AWP+kWCNyybuSAmZCIYddlONo89lTq9WFLTbvBkGnAkWoeSHeRaWZiNS OEhrioDsbyNmYjy5eiG4jjmA7qz99aSHYrqC0ZE5si2XTrxNMJ5r4xyZ5Kir2iqpwjCGnPplZ2u0 TYVhYtneyYhgrq11CLedseh37Vo1ldcWJwMTP+ocPXZdSpVxdxfg/for5DOebHRaiVIi6RhsSFHx gjnWUBfy3+Ytetyxxam751i4mfAz1ycbutY2GTsD9742dF7u3fzE/D5NfYFAGNPjCWUyVUVWkRvm 9Tv+5qfOdfH6OlYpqNaKHLZctiboPSlVzRptbCjRTGJRxiHTifaRpQefusApoa3TrrKN7uDEwEJx h0JQTDyQ6AnIDnx1FcfiNaXFjxDrQmfFzEMVoxoTP5OtBUxmflrxYeoBsMhLviJKvlgmuazyXClN KjYtB0uZ5GvjPi1nkye5Fqf5kd7btkksybQkSNPFxHb0q24VvTxyqtJDd5ZauvP5ISWVxYk+BNRn Czys2EVxeT5/KjiUJVIsOQRZ9N17qsiWzdB8tXw9AuBuiHyPuaUFlF2+setpN645FUlasFs5P2M8 6cg9vZlus45W9bxEsi3rzZhhPTJ/pyqiDh3LzIoxnRDE3KO14RKJyWkoIrXsc7FSSyXaUhroEMUc l5q291/m39Shhd0V96NQA2qGdkStanOJatLmTreZorBetCU6tGhe97sqmzmSd+AMfJZUHWgXpb4W AH7+Dq9H9dEt5+G+WquPU2FJAXhvK+8ytAiiY0nfrKO42JnIyYRhQqu8LGO7zVVg98+LaoilHaV1 HlfdwyIiOZPXDj6lOyNmlNuCbTzTbtVdU72j4iOSeXEJ//Of/2xcJ+5ITz1JXCzclfN3ZWwU3lNh mYbTpgKNgeiImJEROhslaKnl60JyfX5/Ok43t0Qqy3UPdeSeej7HtVNydmcNylgFYxvloRVcwrhP 11NTZJKIIO46wjn5O7PRS5el9fylMMLHDx93jkIOyVKeztybmtuEYkzGsI3BYnERYSuKAYtKVnIr lkgJTlE6LGA2pyk72ddsXL6Tv7DhcgxMEtzQ66iMuL7/ofI02wQc8Me3b7fmkrVjlK8p1/xCjCC5 UN1ZI/pWdzZeV2mruIZclTnXj7WIhpXHxfNbnjA3iutIOaB201CYuFp9uHqhVB9K/fxyo+t7jUVc I9hEEI0mjlUaCB7VyWncl7SU+8dSYigLik+XlTER63ET6atEVEKueKFKyci2wHcQXqnrVTdV14il lLXUPa7eQYxHnZ9EvyU7z5WnuhlnixpLMgIXV1d9ruM2a3dDqqLi2cB/i3lYpwfnYKPL7l87d1qL OTPtnyvhEsY/Fu8WfRULvuIO25pQzLVegiOzWhP4xGAccOT4uHZ65hoJedPSuuI27LQsDlkZefB0 YfgsygvXinejbjzpManS6EtIqdNV/fwOy6kUxgtF2mHlFOvCf4aFbTqbF60coDx2MXHqeOUFyfcN Rqi4wNzkDYkp8T27Bluidi7WwZhrHdBkNebPqrivmTMXncF9OGnHbksMKRIQZTlnPpXfDVymIY0F h+/0NCJX0a375qbfgPPxTaJnjLhnxtAE5zZgpBWIJccxzCm0PLLHE7D3NfE0ztFiYoLkQxvvLpvG IvGqpNS4fpwn5q/mwgK7SElXK5aWXeBZ+5F2VJ+z46hF14qb0vt34M7P7/4dTPeYxDMIf3K2Rhs1 zpBsNGT2OeIO1Z8rhckLlylhUH0p3O0hVD7bWnDwqTC/Cc/Hw4YN/lgWwj44k+chCTv6DA5EIlU2 UTXi/n5joknubOuI5e+bS6hYy9sQveewxLJWAC5/az3n5gUWq8tJ4HMFJRzPKQooPnTHT+vvcuUl cmwJh+ljcS2SY9uSO96v9IO2SJ7NY72vIW8hsM9q6XDPudmsCc8Z9zRa7XWwgUK1oMyyFiLH60Tb F8AAACAASURBVJN2q/Ce7nlOLeLap3Cys5l5fat0LMV7ALfy2c+O1G4h3eKSR04l1UNvS404XELd b/QBGwW4Vbak2Kx0A3O+8HNkqbk9Z5Luo6W/lvHBy8miQyHcsV15H+H7cJtyMbs5YrHAh2oVRWef xj1x5xND0B2Lqo8q5GCId30u2ZzcP60Bd3k+ywTJCdbuptkV41qswOoi5ZpyM85g/u+orNb323UL u6EsGoIk97WYh5+oIAzJq3zkr9kTMjL8Ex1AiscUYB7WV8V6WOi5w5PkS46TqzlkLEqLCWUlS74v c5SSqbW2JPk6tryelWwbtQVmYFFvwy6RIeqQm38+PtfHv6ES27ssUagiGWdEMQGiYzkZfIjxOKVC cJmbHAPPiXzQyAVMkfznSNTDEqT9Fj3LpsQbb3EEF/+cFJMhxXFILkhx2+CDfL04GEsWmmYy+JLu HRItxSo5Lx5qnXh81sqVeVe0eJ/RTZ+VOYJgWC0/p3Vt7MKj4sxKyiqULqRdxymsM4iC4TqhnDev A9LvPpU1LeaHmBXAa7rAvIbyzRUskLHrzxFhMT/LCuXFbBPSbAU5fwS1zem0SmxLLs0ETRWuDPks X+E+NPE4nmdhHaXk6jxf5OOJtWm5HyKYhgcmLWFxWjYR5rrEUQIewEQ/vK9UpM+fNgpoZlzyObKE jh/Z1r9j6/G8KzAIWiSZM7PPzVosTxN5bjusfUQLKu+iQ5QHJjsT21QG2Nq4tXxPXpUJzC6SzHB2 IfMei8DFowWVXRM+k90S+UCWWOH1IULi/HsujVatpIqU63+KFfjcMsC6XDmHT7GGuQp9bLNlHJlT WpBaPY5Na5FE1Ku6edZ9zxih0UVLHKmg/K7KyutSoeWQvsRilViJLj92q6ZO/pgsqpVohNIKGdki tCfgPkbImAsZxfbgvz2V1Cj5h7j9RmOt2KKyCmPjuNzrQRSWXIvAQ75hjecxyR1ynlMKmEmqq8Sg YY3w8NgVdwnx7nK+qeYDiovPnRBlRbUIOpsZaBhbgCpETXN74XGf7vj53rT0FBa4Lo2u6b7RXgQw va1zVazhw4yvkc/WcjIKikxVYdUNNDXK8f3b3/4WQHrGyLQ8uX4UD2Plaz4LFaiKTyU01JfQ4wjG 2/1ISzpvZmJuobR2IHmu6jm00D0/f09hZdtkqnZZVAmV7BvUo6eIymJRgWOpvNogyqEMhaVs2PDL r9bu2CFFM37bRfsQvEHrUO8qmsbZpWTSMlFYBCrE55rLHJcFYY+6bJ67i2YLKUf4VCbx2eWmBZSD ERmIzgsiTwJd6TxBh1jYbgKmDw310Nv1/rGwiML2PK1wWbHevm6Quo0AOUTybOejuzcLMiuN9jO6 5ob8jcBGPf9ffulzPDO1w+fjWElZ8JoF0rOrg6LgHPnZyC3LzXI5FoqS2lpD0bRotFI7LO3aAuy0 Np1wfMeCDnNlKoE9orSPRWmBYcU4dY+hrHLvQS2rIPIeoIy6suQCWMg0gsQ9PHTZ1DCT0bIzy47k Hf8QwPpQkifnYEEwUWXOzy2Jk68zJ8Tmc9kjLpd4MYrVl4+pta20IKhO8eai5KblqgC6svxDOTo+ PYZQQd/Mw2pZ7YgVJhErIMgf2ldQVKV1GATfOsaMw3HpzpMrPmgVzsEhBYpbCzvjQdIbJH660WlN O8ZtpVABfMeAcwGQZ1fO8sYqTt3PjK96naydHBmzyUMGwG3h9q9//Wu0f2B/TFpi3dyWdJ0djYej Axkbc1qAoZwA2TUGAr6p7IHYZE9rNZUDYVdKqHqUFAfHrchVHp8t9b4L+3x/hdVGVHY5xtDfHI9J w6Rywmt5iWvMGeTcfcWdurW2cgSQySpuIQZl9UvwnihaWHk0GRzP58uERnf8rIiNHOZFoaXqOFiw LrsQ+4jcPcr0xH2WSor9+GX3pi9yuCU9g/u2RlUWU47aMWFsVcZWDlWM1Lkh5eip9JFME7EWlpUa HGu757RjLy1FrMvNxfvTdeVzNoCwEYljMjgGlNhB6WXL9VvKavtHwtW9uy1J0DelXjzWVLi/F5fx 3kvgxctssgbxrJb6OMTJYuHVTjZzJDPo53JIdlVmWXJdKcvbGPrW8hkjU+bzqiT8Tvt58a0WINZ0 d7xLffpireh6ZJeE8XRx8ho4jKF4Jgobjt14cni+LWBnlInFxff3zfFalyuO8qslL05W+oBbo0ua LaJ8TWJBBg8cY6siOBb5u1qe/I3L5ThZMkZFmcdRl7HvhVmVj4opF1OUouDG4ucziTe74NmVtwZX dpM4tgndU2Kvgtcsi7rBx9hAJF91UdpaBfYS0jvTYc5dF9chJv0zgVPdy11cjqFFcwjlOfT9TEpt rRAnlsxmH8yQya1CaCtCaHFxHi0uFZsRHnffbEkCY4sBMR5cw5rxv8YCvUbPZcTPRecxW0utVV5W xxAUbidai4VtvJfOT5R5TkE6FVHLq7M8D+/JwwIoRwkLhud79bsm/ULoRHhOcrIEyQk05LES88l0 E8iQmZXuObSiVEB2QPJ67ErjM5UWIVcrzwkpGEb2tkm4WjPKz/yeEnSGuvGhqCCWgm+Bc71IvTZ/ cSJHcmN1XfYpd6tYEmS21Easu6YsRD2hRtENYVctb8XdMzObjdCJjyBOTi2bvKu6INqiZy4Ka3rl 67H9PO+1HXDW115QhEVis2c3I1uGWi3iUVk5eR9jCdLeN4uS67LRhorbsLnHEptRWXheFNeqJoUH HWP0aaXE39QnMNM1/AxK5h//+Ef3z3/+cwMjahUd1wn+Gpyw6+t+A9Dy5Di2ueI4nKvFtaxskPMq W8tdly6/ni01FSS/ozzBq7Jbq/WYn82UuKECwodbCDR4NE0s/r0E4wbmO+4hikoM6zkZMWOyoR1Q UIZeWaClWem8yE4r3MAutW/AuCS8tS3up+RpwpXJCqol7rVu0FA0ygilLiLXxrjY+EHQPX+Xz6LE 2oqVHtPSyFNVGbGuSN2hvn20OkrWj7iI1yAZVMtF10WlmS04LQsXXds2zEWvmH/oZ7FAOL5dVkpN dIDvspAjYkhpm9u7/u+xiJdAtgqyFZQQ94jl07bUslM057AjM89HRWu5YJV77haeE71lpYv3+Tnu M2804lmcQ6tZy8rk8jxmKMnAg6s7KFk4j/M2l6kPzjzedqcn50HQvfwd+whuEyOjgu0oq8g5Zl4e sGHsV6sGQthvH0oVxsxD2aXmOztbFO3aQcTRMsZj8TFkF5zKY7VYhzl2fkbrxb/zJDKNJQOt8rhy smxb1E2F9HXpmKJMspWW2021QooGCdrsXkx8ngXHl0GfM/AlnYqxiPu0+Fu7CDMZs03xMXG3Vdgc k/Nqud2DfXZFKamkcu0uAgnFZly7kArnb3E6o4mmCVlNJFuU3KuKQHqKQQdBc4/n5+W+OaeyVdqP ed0gBMdbpaa7yjMWsHe8Bfd99vw0hzNvlmJ1ObVoSmzr/pqVlYJfoIIKMiwW90l5doeyDAe3eUPi TyclAhMlSeaEDmpjRerj4Mvu0pAgSGjVwsqJwPveqOQ+lV+rQARjlVb5WFi/FbPtrYCQwWEtkqFE Y4Hd/JpcsSGcLxZ/bWcWrkFVEli/LX8sK3OeFS4JyiffG24oWE9O2jUtZax6Zj5+fj9HUbftI1lJ tSWXtehMD5JrZjI2YgSuVca6WxJCeY3P5XSZTFHwu+KSnE9XU2uUc6n8+JzdZFqKQnRNPishfaR0 TSrVEbLLJ9Ndq85r53N+f9v8Jtf1d4sW7iO1qgO1y6IOP+ts8TXBeF8Z9UvipBT6l1T65ctWS4sL CyyoZnLvItG0qbFyWqUy+t2BiGIbkctgM4uRiSduJVHThSgomrvhtBPL3VjeDWI7cMXdvXXN8vVt I8YW13WdGCs/KAD6hhjr53PHaITz54Xc4jitMm2Z9nnsVCD+DR1j7oKCl9WSSs0RFD4YKgec6R+W huH8WoTiavm7jn12zXUlJc4qmUTq/WrdaR04Z4xWWh9eSz0reDciybwqXJPfd41qY2nfPpENsU71 GROxWonLKkotnvz+nNLL+0iuWNp7MEA+e8JLWSazLR0cHjo7FYMNv2Js0FwIe0UYK8EsL3iB320P mM45YD7ZQsihfUQ8Q3OcyZ5xpByONi+Ln2IkQ2k3MqKdlPkzvJ4TmltlZTQvV1CYTIGBN1QVQ7sZ uKAUjqdloWLL58+f9/fsemeXSKvEY3ndLQb3dQ3SrwVSaao+s3498cgGv1dz5Ti31ozNTLl2S74g biBYu5KCFcbabAfvjc/lSrQ+NxPXVTIbSeup+ijjrOWKaBFrBbu5tB1pWlB/SnCrz2Yoq8fHxxgL 2f3SbPjHdWbLlWfIc31utsOQxL119BgtmCklZqLDfI0qPkfmfXtRugozYSIt4vNwnpIJofvUhx/S vHLDtvXgQ1mN8Ygkc2qtCYROgd7ZTXKSGU3KDz1fp1ZC5jfl6guKxzEHThLntp3HnoFDvc0lZOZQ v5UMxF3Ggg054pjzFb3HFqj3XFlQotR0z0nQY9LWg5e4u60JKPfSKivEVBuvyZI+uTqtLqPWsqk0 2cLOVpmWm8rGTSVTI+SG2XXHYnltGprWu8dyQ3COZYx0TOjmxBU+VGLxmLC5miMpFqgR0FIsrLb6 koKHpvUaRoxE8mfQNGYprKyVeTiUkGBg4FnlE6OowK727UvW7joukG0yptAskTuGU01dR2u1qPSY FDbHaK0WdytblbUPxehQa4rPfYBgWkOKIbuH+TUZ43lB5sqjRhizq4y0fDJfF1Qe2qwolbxtQWkt WgpYMHvbM0FZ5V58UkwsMZMXPf+0APsSxE1xPsS6Ym5kfK/FID1eS4HRlfeZcRyigpZazlZ25tHl xq1ct9wx3UcV6pDE3DmaHqc858RNfXbZim5d/ZfqIyjV43RZIBGUFhWCI7hWI8u7yk5XCjCuG8Ng k8bjYsPkwwQ8RAjTY+puIc/Jedvn/C3fB+GanNCCr0PX5W4rziUu1naz8bO7EOxMgxk6p8rJCKHU DF08MR0Xn9ikY93Wh8oFB/vzN81D89hEjfwZaABYlop36t45FwpVC0G6hpUUsiXodWWipy5PphSY q2kJaYHxNoFcC0XMSf6ax2yxslaR83vGCvuoWbWujYRq6XEe3dMhuaOix9l0XfSsXAX3h/iDihHP bZDEcyQ28vsSeY3+k3X+klGzrf/hkOysWiPM/uVzRAKh4fNAYLiSmd32ittV2u+2mNa3EgmsQxE8 FzcPewp/Mhyfm222lpTuyS5jNrbABX+RtrKl7b9ydLG19HC3MkCd8cPsyky5r1hZc6zYAL1R5tTj Dz7V5vue23LGXJcKWNxK/lO2rrNb6XXkMed3LOQ2kjtUDbSNEnPfRFpRTHlO2OQ0ewNWkXB8Bbm1 8rTSvSYVytS4oaxumoTywXGtbrNWX84xbZWWinhoDh+SXR/rKIJGpRdEWFqmp+1o4OxlC0aE4bYk D9s1N8qoHLCMBPISEQwf2tSxBVS1QoZIoGJDKoMW4NXlyi7MGNnu0NK6dFxLLiGsFZZ3f8FZpX1/ KBl7zMrKUUPyDNvWVaVbEXX1jwcXIddpsAOMyMiWiysrJt24VhkjmQulC5lzBY0U2tI910LPilnX zuNJSm3ToBhjAHubYDjWbmzZZbXqxC4cpeWWYJZKXGXN33opzs1sMVtt4lsJygovLGppCWMsdvOe 9nZew/99fOhxLbTm3fW6esG+kjvV5l3hUADhnFLQRpi4R37maEoeXJUSC8ZE26GqpiYyZzxobm2o 50gGh1ullBd4pmZ4X/n6ZIsPYXItWz4imrX5avReDGzvPqJD/M7rWUGF5XB3H8pLi1plpfWpldh2 bG4XaXbxVBAy6m3aoNWlC+k4MEYW+2sVsziUmJtlfrILqWtIQMBIdBS7a6xSfrrBT7mAQ/L0tOqu 7m66y5H+fjm1zQi2yt7opWN1SAtqrjjOUSNrRVPhp+54UZ773PX9LLTNG+YhgWnhFuIuPifpMV94 C0w/V0zybdN0svhgvYds2vMPnMe0GMUF7a47lCMoTUBsYYxkekjR3fBaZXHnxgQt/YP7x/Uxwmlu 6VAjA12pIeszt14ndQdLC9wq3mumB/wiF3x0Z1mtIvKXQWStWQF4X9Od4p7MBczK2ChxpnZkft0Q 36vFp7IC071rlZVlqqU08LOtAuv8cP5ZmYKffHabnMIan9hstazyhiwOyDi5meoVZTpGKy+l0KA7 RB2zk9PwyPgHRyu6Sc/AtA4SHiBaSDoPmJa41q7pPEqebHnAtIwEkPexUHQJxh6SNIqhsrvuVKbF aLVky0RWc9uMoL0/iZfPUexzZOj47rZaLNaZassou1Obxzg21nOfAdbVFO3BgoqMSyEpQyvZBLFl xtvAFEHBiNvklKHIa6t11nlNzFE3PY9NbullowUXbMb5pAswBxg3CbZaVm31DDElr1XFkZ+FXDA2 Ly23qTG9SAGLOc9DD0DowtSqQzU23UdKOeiHvu9kbCaVOE7Vjylc62DxTDkt1tG2Nfzpjp1sh4BB Tfec/iCgqJWybeFoIk8pCYmlWhZDBEk+Iw7g7pUXtAvHFJ7WgrJkCecB7+B+GDOuS3D5pUx1Fbap J1x75jSxsC3HrIyVkc5F654j3C/jIIBu3TBz0HCDcBvzeXL0WOa5r+tutUX3VHhYyPYVRFQ6boDy 7wystG6zlpnPVqwvP+fceUeGvuB8vm87d2dC8zZZTCh+caGWquB8lpZjcvek1/KyFK1+g4jNoaMX 6FOk81iqfayfw0EJGGhGwXguJNpQXV+F9oQhv43v0WInSOYQIT5UwVgrB2RXzrbiLYg8VZ7XiSo2 gZh3Zti5XZwuMN28fD7D50jLJlbp6c7oQkqFMAR+KMUl8JuBd5VmtgqMXokpjEVBeQ8ls28fw3wc Nh5d6uxmcedEEnn8pTnDmosEXkqVDpWQx8oh/UyU1I1jjqCsdB3tiJNxRe9Z5cfntKizJeqCMt3H eWuvQu+DZ59d7HweCa8ZU9v2zFerUpr6eCAir8Ky01CbKpZx4W3R6UPl/k0JxozWaHg3Z6fBOKBw QuCQA5zOgzPG4uGtnmIyM3C0EGNgJOpFx5BKOJ1yM5yIbQOH/Bm1tOJuy0RkIfDQWIB8hp11qs2X FIbsAmhJ8eBZzC0RVWHn5HzZ0vLaTItgPHLELbeNH7IC3QkPobR0bRTuwwJ5lmIxYuRC1HIYUki8 li2zfYTnZIVQxvm/v/wWXbO/xsPijF+9HkoO1wYKQVJMumE5uJKViNYRmKsWrd/1ObnIGZe///3v XzWOEKfK18LfjqXXKlEXxcRacO6YiJ6ViUpyu6zi32KxOR70gASBub657W5vb8IF5zzyzRShCi3E l2a7z6qD91QgCtZPNG1dPXVXX66COtVmzSxfUnsSxkRjRvj+sYSGmaSa1mGRXd/ERceEWJAXWEBI F6oPv+W4iJO1O4gmPosv5/kJhEroEw/J7oU7XcucN0GX43usFtiMwU7JsQrHZxEI3o5F3LL4HV3F QyepZhqG6VSOrePQWqjSMzKnrBW5a1N5gR7L2uuMBWP79k3Z2IYkgGSTu9M1XUCQrUo+GmHUCKWu hviSlTG8bvM+3dmt5d42UDWymGkpQyktgu656iw/rS7rM9eiy4noWn5a1HoJY9kbi1pKG6uTe2bI +PsvP76vmQ3LbvXEGnjqfvn111K0MHUgZ93lpOhR+cZ6zFzR+P3+bjTF78UUltKHnMlH/PypT8x1 MVKlEAkw9e66e//uff/dHN1x95GHw8Rh0vO6KRFiD5rWOXE6d1oRiJUxjciknnJxVHItUI3I3TEd oqUJcH6sJo4xFB3U2spVIwwujEUe9xHxxZzOwrFZnGP8MD4j4XIMyB+yeMeE4nw+y3ieT6vudMu9 WSp46HXk6anw5hSehVZvfl0sSZePa5Zrl3ETgy922pEeMlTax0ifykzCcLa2hhTdUIcdI55TLegW te5YyclceyFcn52UrIhxdX3TnZ2UdZEjsXofLx34mSsE6LC0Yl2e11p09R42gm/f9KJq0TUuyvSV 2MkXxe+2MJ5dRZA25UGsh88JHgpaquAEzsWizP3KOWISBa2oKZAvZjGmIHgtL/h2Yftea6lxbu7F pg/tuHiultckAZDrtePwvpNMTpBRNSe6GF3G+VxEWgpTk1urdltnbe6b58y5GQvxwbkyVXWTiGKU aK5ujhy6XCVBxaLisMtOdoW1op2fiM9TS0lxfNwMre5hwCkD9uJGQgK6r+3GJ27GuVrKSSulh+Fy oyqIKVpiuVBGtE59TkbBX4uyyhIbxP1dKCuwb3WENeKXv+eF5UH7+Oljd3tTOpc4OVQ+PEBpBG0l Ua2o/GBlEFuOxM9p7Q0lLudQtB1U9PeHInccY4ypnku35F01J8Lmc+e2XFbFaMmL7u6WQ941mqib Jxibj+M1Cxpnhvu2ahKOf07/aNNMdMO0ZvN5EXCoOYKywg06Ggl7O7l9VwVj7bOcKO3cIok/N201 UTqLG54RVKGIHIzxHjNWZiAnV6NwcxpSVpkRnz875rodHa1xu9Z9Fz8LGKLW2z96xc0ssuRrhBUP nET3reur699PYbXiTm7kLFtDDLw3oeLipxNwyL1ykjmhnDi6AFmxOcFcqC3O1Ba4U1h44jatdSEG pMIdWggGI1wMljAR6zJZOTeCULF5vDm7pJaNAGx2XxEXjhQLeVpGM4cmuZaCPfc8jrhPdtFR1J4r d7VxUbddorcr3uG8O64SsFkIQcXCffnMWza87xuhbXlSOcld5ac1pXIxcVzrzVb3SN54JOG2ALtR 9RardIPKJXCygE21XECF141gB2EY5bpHV+nfW2I9ksJV5+arUVhZxHKc0Cw0q00KGLIAnBR2S5Hl 2wLGOUlWGoE4GAvMz6sAVGxOEjGMlgyar3OIAsBx7Zs3BESrOJx04iRaQix8o5stvibXyMDB2M6p tRPR2Vp9wc8OhfatGsAiyYX7WlFZtZSA3CzDBa+yapN8Y+OhPdgOronKDYuBRdjeK8cjCTtbe/zO ddmmS9d9fczjHs/ye/xs79Fx0kLys4xrji7q/uUmLLyWI4V5DgjqDynhjI3dJ1xLNy+KIjblrPOx cymcOfXKDilcI1frOBEIKAbG7q4oVtbx2fHrVFiIk0bQ0585v8xW5SxqlVcmxKnohli9Lip3rxwh s8Z45viY1tJyWxBB/L6nY1MmmXPkRgiKO7WYnL+rCLW2NO/biqYWqfO8QxM+V2mQniH9woWrFaGi 9nqHqAvmwLV1xixNk1NTOJffN+3FRGMkdvwdicXKWN0tVauWcsbitFi4TkWQ3PvRIrZrlHMg10JD HPPcvDaPuda7n2N8hrpW58KCQ5I34Tdv3vTUmtwvISupoU1RizmiikdFyb20QK9gQynAOXOtbDYx D2+gYOBRzbP2xLVxD1+twkLyws2F1pBMOIPTYgjbBcKiAIz0s3khaSnlSJm7McKEbith6oaK/bQT QyBZF6+1Smw/n3d2jtfyt3Sl7GuIcJ19NdfUAdnxYUGYdjIUXXIMLSHjsb1/FoDWgAvcaG5b+E58 LS8wLTLTfVSiBh60LjO4zW67rb7TlJRrKgthTDIU4L3pjmoZt6RgrhcgHospk5blzmWOFtHOTFHQ osk0irxJZKUmPWdueSE9AET6TE5wVlr38CvyaPeyEhvvPZG+Njiy5hzyHpd8e8sGXYILU2LaTmzo 3SsVwW7JbSgfI4M5Kz1PzMyBkv5gjWseslZY3jWZhPxkcWYQVExKgqVWhIvbBZrFyIzWRitm+otL ac207qT3kKtiIk5ulFwmHnpeuUO6J+7eYjYqKTsdZ0Vp3XLxFS0yE4VVeFlZGfWVoa6byusqJssN W6jO8Y9M/aF6zzOl8K42K8mHq/aIwt9MNs6WYnbvtdqzspKBroWFGIXL460bKGbn2OfqCz6DzOAX nNei3gUEX6Rqop++XHU//fC+55Qp7UZqon2x7l8+Kng302rmVvhclP2eOt7tXamx/1vhlL0uhbX4 2mUzzC+FgUmWdxgnYq6okI/BZEIROZHkfyFWTkVMvZDEZ/TL8jJMDJOCWcAmqrY7JL/zHSkabSv6 bCkhKrBceM3PqxSlYGgFsqAEf9vWUlp52WVuyawSYVtMy/O5SWRFw/ezS6MSzE1htRqy+66iyzs/ 5WRI4n2OjNWGgkwqvYFrtfSPlqJjpquMGA3N3Ck3uZboad6qyowxkaZgBFhcy+edvQJ5ettKHG1T 1hdV6br5mBXh5q3istu1GyIKYltdrX1lW4HBISkk2eFrEp4hvU9Y51UprLaPoQnVQ+kzilEqdlKj ebKYLYXr4kLywjW7HxeA923aIFN+HcU6jvC3O5XYD6+7w2al5ffciTOZUkWCOKkEcRE7tmSXz3Qj gwImVvMdc/pyVJXv2DVnqgSzFlLGo/L4qDxzcjCiQlPZSTXhWlSaWis+A68PZfJcZYW0WQ5ZwE58 XxxQN9VNxzpZwbKvFJZMD9BtdJyU1gWToZ0xT5VhHjMtsNbF3l8xnAy+59wU5pB+o7LGXXsJhXVz Q9uz3Zu9QlH5cn3XvVuum+8q1H8Xw/MZvCqF1Yq4lDSDIaKhO4ptyPPuZuhdbKXtMeh3Ob71l4wc 4nbZ7ovJKE5jpElrTIA6Z+xnoqDukYs+S+bqqCi4Dr6fq0JoFfi652r5QYLwBgdafo7iDqzLN5SO ZNTPe/V8KtxsIai4VbwqOrlPL8L9SdG84bdL+gqWlgoWxak15NiTKmavx2wFZTwwZy+05Y/ssqMF ID7Y0hamyMi7ytnp18s2UyeyIm8pOnPdwl2Sn0spoP1Vybs3zDOKHS6/iqoG9pcU7OtSWIvh3cKH YCqOEZg2FSdHDxGVhPgOVoeKwEUvoJ0tMK0p+9jlSItUAJWB1yN+0TNzU8kT00CQ7ILJVxiwZwAA IABJREFUvFYZeEyBaiwCGebeF4sBZco5jVza2JPXBf/lRLVh9EwgVcHkHdjPeG259EymIygcx+BG ppNIcTA62hNLDzRVIlVny869elzTTowUZqKsILywA+IzzvfKd1tlJRDvZ60t1gYktKyGShXtI0+1 BLVR0jEeVhbnbvC9arHEQ7Pcn2u1ZTJw3izbHqevSmGN7T7uGKbR6Go5GQUx5SRlsz7/ndMy5N3o NmRcQYxH5SAB1Qia+IaWBp+3eqSWVSsCrOJXWkGILlVb3jfqiVWrSheD9xkH7j8z4sXrWjpIboqq pdGy5NuF6HEzSK5rK8FX61FlpVtqNUuvy8XU43C1nvshhF15iluENVHSOh4j/au1LpxXPk8ku9At cVTMz80nt6A3i6EtUSzx8xDKqshmu68MJwxBDrr9GZa4f0BxbVFYMx9TWTPPtxo5nZso1UjJeom5 3GQ1vCqFNUecIPkhSQSVTMp75t9layeD8tmlMf+qxS04juzmNqKjK6aFl1vXe42t8JquXZsknK2e nBSrteUiyfSLobzCfI1RY6geK1t8YxuDiimz6530uaa9fCapEAZExIWyAjRKpXJ+Ln6TZVsPRIRr d4zGmN5SVrK1jqi4M70BK5178h59Xpkwa06mjSa2he13kaub26/yKdvKIebiuokb+e0TsQ+IYd3f s+5OD/IsP3257i7PS5AgqDsDKVivSmHt699nWoNWhhaGVTSNlokj5ORldyV+ZnKj0SCz4G3/7XXK vtf6MSDA+xIUh9KGdP3ahpx58SBaMvk7puxsqyyhSNjM/K0hyVUhsrJSubaRUJUVAYLskrcLSQqG 1uMhXRHciDnNWxWU1eer6+7t5SbAq2JR2fD7kLKSm6fVmHMP83M2jzXTGQ4hK/C1gYBFpjaYIdF+ L9M0JJA+1y4qY3I4FfL2ouSbRqBshFT6qhQWkgHR5ygwHpDcGcO/ltdwEbbVRN2RcodelYV8KblT iPllYhf5HpisTNrsSmYRW8uEz/x9JNdzcqEYMZxbkVSrMeM0cy0rQ/jueIhWbKaKOHaZ58Z3LMGc x3Nb9+KXFpSVSk6FnO+D+4QQmhs0iKmYaeA8sFFqFmkdYo85wvVcuQOYbqyj7Mq7obUBlNbiB2/a RdFPueT7Ziq0EtHMZRnPMWX1ahUWArfEmu1j9Z2njiE2pYjzGMXyM1aKNGdORnHuw2eUTisEyTwm o4c5ZK1iM0Wl7bTjZwSkh4r/ZU6Y19PmrU2JNA/TeOxenPEUozEtKCxYrjVh0wUjrpmsyGesl2X3 GjYEsRs73pTFe9iI4T4KMEDoAVKnaUcGC0xXMv2mdy0rGbcNaDh+bj453/MQcjLiylkg0vO2oLoQ is/ZcZtqZiH0MLYpPietakhQVrGe7m67xWo83/DVKaxM2DTComUhgDyn48wQ0zxLBoR94DkSpEWV 6zzZ9hzlIes9p7fodoopuLNhZVitcyh1RsVltFCSaD5GLg64NZWh4irtcbL16GTUncih+txUNFtM 0kcy1UG3KNd3b5PA/VxOKj8U1SHGbkfCIu3ovE4LGqq43WS0lFhEmSlvOk/GIB0fJEfsDMYcwsKy tv1y4NnnzXhobL12E6kNmOzqUitw6Q7Jmg+v4c159+Hjh0JyvaV88+kfQ2Ep2bJRck1s6QS81lpg Y6kzYyKo3Lpblh3JdYqMGLHwJZRKC3Ai8F5O5bCEiS7pWP6Y3C7bTLWfs7ztlGQ6Qwtwaz3ahAHF m5WVvLXMF9JF8t61OqVxtInXLXCd60blnLtDyq4lU6KJw/G6FDHPhN9zkUK7OLdusik1WVQCQ57A odxBhuxoggBsZDrjjW4OGZQ3sTvmUnWLhypfTHGuokHuge4rksrf/9AHvhD4WHGeAaX4ahXWkDhI 1mtXORihMtK376KQQ6XbI6Yh1mHIm9e4BnZkFjPWhcL3Tc3Rqsm5d9ICsvXTiufRqlGZiu+1xeAU SY9TjWIR7q3NJdTayqk+mb1uwMFAANdkvS4/n0H1bHVkxXtI60oJnHGHRdfyyNpn4TiCYwmqS0Zu AxBGoneFLXaVePaL8XFr8yL9ztDnjDr7ecbNJrdjbmeUs6l9BI+PDhdIoER6NHm9X7fEQyFiZT0+ slbWmwWY2R9KYWUZcj94EOaJkSPI35jzRvzmSHY/c5a/ReBc0Lp6MKVZ1Exq3QktNls8aYH4OseT szXUYMLjSwjF/cxF72TvYxFkkmyrhIbECKp4k0nibd88zsV5HWMtK35yzyjsFvjP9Z8k6HrN/fiC Hb4A851FN9c1bHE0AxoZPxVz5Lkyl+znmO/3JWgLY4Lrdryl38AcuADxcznDQSwLpYBk1jl14Rnf /Noh5MvnLzGX6BbfXjfPESX54dOXuG+alFCO5g+rsMZEqwNlglhDXGa8D6mtTdUeAxFUz2Z/tkJy y3erFOTuw9ZCN+Ha97OrK5drrEuK15hrjCO6lyogS8dMmeoqD8+dSy7rBhoA0C01/cj3MhHSa/a4 YmQGEKxIkSWIoy8UKJzrGg49d7E7rlk8TjqArqJWvdZoLiPz0tKX7jkePp8kZ639zNcTdzPqK8fQ +8ipOxtKqRbDuLwoBRgPKqsuWqhFDbURPAxF9cO7dX8H5NUpLMFcQfFd3Yf8fWSD4VstMMTIz9jx 3XXtJOzDtxKnPCgjM2BZWFr298vmuFwwsZzsFsmcnkqXGEq9yC6XltiUsnJcMn3C9J/sshnl45ym JflexqKkMIireVyuRTd4aGyxsF5K5s6VIddKhZzdqlwmyIRyxsRmJd9aFhP353ibeYAYHDFQJf6a I+g51SzTH+JcL1Q8K+Z/V7mFO4L3r05huROYMMrAmRozB0S3acKY5DQfd56xziRaZjkfTgA9V5/0 uFIwmNDW2vI4Evp4XzxMZSBD3pSgFg8ZswZNhN6GC6nAswuX61WZMG2FC4RrzQRJ2dttVNTIrcfN JVsGFdasZqH7SyjEpglGK1ORMa7ZOZgjzTn9qq0c+i3kGqjjdNrdxauQUtLKGGlXS9m1hhjNfinB yqaZMp2ddwXvX53Cgo4vCMokkXOEEkBsoCpA3lphFtzbNhDuJlo2YwspEzxzNQgsKlMg2sJ/Klfw KzGOti9i7qDj62JeVlqYA1RvS3VxombyqulDgvtaX1pWOTxuPfa2yqouUzv+EiXHruulF3pYT9U6 H7dYV1034ckNEX2Rfa3+Q0hYf/fbcidrD9Adjqm0jS4OnRytWONubqbGq1dYrWhZWG+oZV5z89w4 Ay6AvMtAODm1ooZERrtpO/w0d1AsS/6VREmvVUU7RCq1IqUYiYnNvD/UEmxX0SryOqVj5MYVJujm 5F/+ZdZ6domNoKlg28VrFyJ3+kPmDu4mi8EFHhvhDPKqCelt1O33UFbIG13wu/vJXEA9AMSS4eJW 2b1H2mejRyHFY/kCTSvERanP/qdQWHlA290im6yKOWC8Jz8rP5w5mjy7fmJMQ59hIhAx0tXLr1sD S/a0FhxuhfW1ort1AjhNbxmqxy7Haazg27aFI5jv2KhobFHvMSyyZ218zmmFSsstZ+rDtr6IRjEt oth+5tBM9zHhPMvueENpEXXCApsDlGvhv7QLuztD/2jyM5JhhRfEHHO7sPxMxp7hS1hYkSnyptS4 2lcZvmqFtQ/FQWUmIO4CzK3AhsS0GJnfQ3gZk8BGCtbKclFaebKN9snZMgdPKkHGsAS92+qkuTTL XExhiDjKT0P1+b4kv4q3CapbCx/RQvR6comeIZHOoFv4tcL6drmEKi2E9l9YVrvOrwxE/95W1u39 Q3RynhJJ05JhFdOjfD5T9zBVzfU5QgVROjg/59ivTmEpucOuCczbRFA5Y1M8KC2enK839sCMArb8 KOkD5vex+HO6jTiVibJWbnDhch1WLrUDslUePL7RRO41m/YSV4fqx2fx3Jmpbqg+5zLyHgpMHKvt 7GzSsq953NzOfsrycPyVvHC+RYup5mrCPcQyoQ7UrqVVMo74e8vleakBR2Ah5mOz8HXDrXvWzhnh Euk6meqgSId4CctSitFQ2Zg/vMJyMWmBoBwEvm3D1cpQ91wkp1vw3pSpL08puzUMsiHtoXQbCZZy snzdyqDZ6uM9jov7alVOFagAvxQI02YMQpjyk/PaFOu7Zy4WP5kkufJATrUxqjRFc2iPizIcqmSq 6IIOuYM+128pMODPUi2xfSQrrd/TwkJiA0+NVLPkJhrOmbYZrJsNz5S5Kdk5b05Gzw95r0HM7Qp8 siuV4Q+hsPJi1FWRWoB1IObDe1pSY4tkiL+kIhwSQXEetoX0VF5D14nSseaWQLQAOt+Ry5VrsKNE UCZ2dvazgr25xZYTyrZSbTkaREWjgnXCEc00oMBrMIsRyyhLOrWGU1seeKhJ69QYZ0v0917cSE7X eU7hutdkaUmqBIAPTItrG8E5TacyEq5CMvpu/XrvyzmYi1keSuBekYJzfnz+51NYY2xk/uXd3Tw7 FrIPRqby2GIRiOc7Y+RRFRoWCIpmqoGAGJYLPEf3dCGtz5WJqLqJ4EVYPSgXftci0rqxKKENBRAn GMqBSZcZ99bv4rumFXF8xQqhHk/3ISsrLcS2LE4baRqStqnFBu2B835DHCtbWFqx++JoLdzwe8vZ aUm6x0Xk2v7973/3qWA5UOJ8M7Hda1dRMWdyk1vv75AKy3nz3HF7tQrLHcFdegyok+bA+zwwLRp3 COkHrQvI3yiL3D5rTEzJabvFDF2LpZnFpHzdgn5SMLSA+BsFhdWIUsmKUTKqoemhigf8zBUXZGKr uMXZEM4nzpZTTRBzMKVvZMW/i6hY899DWNu3WPAs5NNEwgV43xZl2yZTnL3fQxYoYSK2XVkH9olU UeV5orVl+zw3deZPpgepWHbpnDNXnjt2r1ZhMfjsForlZCzj4W6ZTXQflGVaEPvjDZWr1coxgjZU zjgTPjNYOSW5BLKum1aYScpG29x5mGi4hzZozRwncQcUEd+XUS+lIl8338+UAy0tPsvEdFeVf2Xn GIRrwMIzsVuFyrEyG9664WO75pQFhnU1VKb4JWQxRJM5QB2n12BdtW5vSVpeg+s8Jwv2ZaWVOyzJ 5M8eggUM4x4PqK/E/57bhOTVKizrs2cwMDOvVUgoo8wkb0UX0ny9FoPQktC6yLWP5K60LqJpG1Ml RTIlISsf+THm40kg5X2UJq9ZSM5aXyYSm6Jk0vOQtZepETaKkA9mCRJd17b6AIoUsXih46WCy8Ta XFa4FSa9YzuE+by5OD9Iid5tkq+N5g2HaOD6WuXo+GjD3WZu2AUcyXit9Byr5+bKum1N/0NL27br T6OwWslRrixaGC1XxoiiD6Ktj94e211HLpc1vFv8xgRq0262NXawKzXHb9tp2ewgNx/1mlE21rbS JfZcuaTMmHLmXsRcZC9LZ3AzWJctLjW6rNpgeeD22HmnnkPG9bOtHALL2KVK5+PT41edZv5schyY 50PQRhxzo9J6HnmNWIrIpO7M2+shhBdwCa32uvf3uz+JZGzB2uVaCT4AlRvWRW/2pu9by1t6xNii yomxNneYAuS1RtpOLGIGGefRDbVxhLwZXTl/+nvLoUHR6K7xd+aLicNlS1JLT5zPKN8U7+0QO+/D w+NkXtwh5OYOq+qsO5lKHPwTyflZ8SIINGC95s3aTYm5aDqYrr7KKkMY8YwPqK+8ljAunnHgV6ew AA/Fp6bERRvfESRMWfpaJJYIycX4VGYt2K7bJyY0B2DNDSi2iSB/S6dolZ2YAtfBsXMFU787pExt BuH3wbpyDXdTinKIfigoMdd6mpJtxeSGeESHlLCSU0HB/xU5YoODDtPkHJoPy3xog0f5eaLMXrR0 DlPvGYrw1Sksa/A44Y1qDIXTs6WRSxrnkrdWVcg5fogPL4OSiLuPDPuxnLks4lAolzb9ZePWUp34 Nq9vSFSoNu+MUrK1WWlr5gvKmxXgPWSKRWuNZXJs/sw2hXUIjhWuyxUE3YpJHlIKSfH35X+9BsrD ze3dhhUrX3FMpD/kRqyHFsork57z51FYDX9J10SFlReJv4vFIEO7usxtrQmTOwUlrQlvgTutNX4X 4J7Kv9IilEYw9XlNdKydoRSgVqRDyAfTXeT4vG7aDP+8bkmoY6LbN1bed1uu1zZlNRTcaCVK7nbL F+Fl0cDg0OV8/4hytMe4Zhw1ovHd4qBY1nOJxK/zqS6KSX/IrHGVCNaKVpVguz3bLDOc8SSrN+QW 5WNiYmnOvdv2WTvyTF03YpG/3HQDxQVlwWgl124JmW2laeY2Yh2SbW7yHHceIBylhXI5pFwTDfyT A+xzBRyrRGOP9l4vzCXmVzTkeEap5N7gOPoTKiy0OhN6KCyesauhJgL5fblDmWwpRSD78HY+ydbV xvVUnpQg5RilQOEYdvHJrc2HxPpRQ8eTa5XPzbFzZVDEgn9iblNBAO9nn/eUbdbTLq4ECcmHrAyw a8uvP7+s9v5mRLmfHrvrj6U1WHgSqwLVhJWNZRH/FWjCjQiuFfM6E79jXZ3R+afwuzjOn6IeliJ2 gwzhV1NuiukolpTJ7uRQBx2/a33rbBa3n0MxtOWCx67H/MEpIDM3a3Chc/3QJiR6eh3/+te/un/8 4x8b30eZGfXj2s0/NDn7JdpPbVNIc9jMMdlrZOtQ8vHzl+79282mBf/LcpTK6+wjwb97XLdBi1St D6Vfwd3tXXC/6NgMtyo6qL97X/CpRTdY7yp7C/vOy1epsLSEcHFcsFMKy+z0VoHkYvv52O2xjPLp AhoCzuk1+fsmMBsmnhKBzKmIo5QD8SpL1rTdl9nlclqLriHsdPMNVdDmL84py7MPTtXyerLMajd1 YEz8jgXzXVltyDXz9BkblhZ+kK5XT9GZmT6CoZCqtf9VpZTk8rEpCfSDg0Utd/o7Hi2ipnt4DjWl 6OT0JKyv4CdelxSiP4zCyspmrnsxxwLzZ65IKos7L1AJnz6w1k3UxLVtfZuQ3ArKQ2LmmIA5YVWR D5nbgylypSSb+h1Ei0ragn0M91FWzwVFEZXqlNLTwtpXGGr65d1TEI4yOt8g1eePJo/gg88wsMWc QvHU3my4fFF+6eKyKKE056USWT6Gz5oa5lq2dtz11XX35rIEqFBcKCkiiMwdKoqw/ghinZ6V/gOv XmFpJeTeb7pO+e/2O9uUlURSsaOccpPzDTPe1VZpzMRKk0itajrmJnIfUx1XJJGqpKyJZQE+HqrH UCFY2lh6hN+1ntcUmP8cGUu5Ubg+ccKxSClQhjKXInF9W/hiWg3n56fdRbeudXUIZftnkYdKzN3W uGKbDI0r3gAWFxZTlCiqxzc/9ctVWUcxRy8vojsOcntTItsIbiQNVLHYLt9cbpyPteUcVvH9IRSW 9cPbHmtDn21rUY0tFDW9ismFh7IwNSefQ3qFKTRaM9lVNM/OxOMhy8ZE69xAY+gzWnZaZVZzsKGA yguCqOVh+DzXZychybHPAbPzRBVQ9fjbSo9olU5Wthg519QxWXhTn/qutDbFShVEComekp5UKDjl eYJxPUvJ02T18rIYAI8Fkrm+KXXphqTd5LCwbu/WxQRiMzot7b9QaCiq6A16AhG2rLtXrbCs3Onf yJhvK6A+57hDC0leFj+tG5TpDTm9ZkxpmuKQuV2tmMTcPlQeOtdv23tE+oWpOQYMTN/hOu2PyD9b 2G9LzN5FdJftE2kxP8dA6zK/to3SkS0mEpLnNIMWAD6eCNFP5S/+L8mqyQOE3vBuw4pxTbGxd0Ew DSrOAB1k0q0no+K+0GsMRE3y8+p5PW7k9j7c9/XeLZiZjxHUo7vbsMSiLFP3SmVOek77eaRNgm4x Mcu/Dg2sC9OSM7a7bz+TlegQBWLKNeQ9MKYM1nM8gHOrpmqdmKdopUgtvHz9Xg+KVBY9luJQMCAD /5aJyUEIf5fLlV/3Pi35o5WZqzioJHMFijEJRXyy7K6ub7vLixm8qbi27R/7bmV14Q7mSquttEpf RYXi4r0NIu8MCNnsCiyhyNddDj97MCollzVCWUXzjOurwMtUfprTUeHky+fAzV6lwspgeE7cFM9p ByMD6Fn8G0VgWovu4hgp1WNhpQyZtlpeJiXzd2vN+LflZz2u4jVkvhiWC8dDDCOr+LhuFEjOI8Si wpJxV0KsoDrmillCJ+N4Q/dv0nU7Jvlvz0sqUluQb2xD+PpcR4FDzRGONpe387+utJ5iPmyHA8wh tc4ZFBMSp3EZd23HFhY2vQaPj8IaipJNDdE0ewi4fhv47MMaq9aiyp2ho/fn48PrVFiILpC4ibWg lMytGmuFtRFdGNhx9ql+mCOJNmTIydWIFkcukNbiaubx6U5ZRcESylhJPHSEcxiRlFKB+Lv13L3P ofuSKb/NxEe4FoMJQ++LnaEwOTf3YVHCOZy57CJQEgVroIxRU5nUIMnjY3e6pWhilu+u4bSIRzKv 5ERZnQT3EYrIYlGspF3Scnz2gO72KkCBSTmy43hcQ7cKq4m/Lfu0OE5lcW5vwmJDkWVL/3UqrOg2 vrZAvNkxkfczBma/lEht0I3bReyco4WS8bVcqhYxUsoEYKJZcBBrihAw42SkcAy7stFEK0MKxmsY Uzy8z/GsMYY7Cx0jODY7WDa4Hkcw07mG9DqVBmCso8yWy+OdlJXyv2xlrRJWNCY5gMW8sgJpYJLU 5LfA4h5E+cBp724Lofm4QBQEjqLyLWnp1JWjgcZJyRoJy4kyNzelPDcSnsX9XbiBRh3j2N2fQIwS bqvNPlckaUrE3GaJSZrb5Xot6teeV8UjS15qhzmHeSHq6/M5LBwbcgwtVAsSZjd3bKx2WexZge4j Q+dhoQDIUx7lOSrntTSL+Nay2qKveL55zjInfIZ5U8sNPPZakyenoZQ+fvoYxFB5WPk6/CyWFG5g bJYVY9MgiNS5elN/GoU1xm96KcndcS1V07bDGhPJpkwOFI0J12HypjbyTh6tKyOCCAoa68zoqA0I xiwjmfRzpI3UDInWIJbVvspqTAB+H28fA5T/LuOyqpwlxPr8yP3TYzdFozWim8nMRnvN9IhN4+a2 e1zddu+W6wjjLgKGdXN9E0qLCG9AO5XGIFUmwwwopSBNw8+qc0oA/+nhKRTZq5wR+ygeuVJtJdHn nF+3dMji0HSN3aG21dIly/W5WtFScvd3Bxly18S5vB95ZpZXzulDQ118FRvHzh1XQ85TIj9tylXf V9jZD1XS2Pv+o7qHRq4Z59PqRfAPD0BMqO1m/u7yYmvNfOd03njNrvBYRA8p/3NzcxfBkV3dbJRV //kK8xARjHVSU3Fw+zJZG+xKBrxAPG5k5PAen71OhbWP2NwBS4eb2yUtRaIjIoWAQYXWYPeR1jpR wVhHC7En4RDD2xI1AvHKlCLhWFhVttvShWzbaGFp0SKM47d9FiXJgiGY3rNNjExuk23dg/aVQyuX PxKe5bXyj+cNPsjcE5pY1Ahttq6GMj7m1BjjmOCoBneCV1VLbAs/gGfRwOP0CYzptnuzQwoUllVu o5cj8xz76uYq3MBwDevjiQyJp8dgxf/w4w+FyA2mWQ2EP43CQnJj0LGGE61I9JTDZGRSLMlFPkSb QLRypDiYTmA/QZWbpMuhhcNE9MG270uvsPig15xJrE5eI47ekwUQcxMKd9Qc7ZStrNVmWs/v1X+P kjP/K+6gTUoMqPATRWLWhBvcrkTgxQwFncnSOfBjlY+Ybwvm+En0dDzfo+S0BSqNlOeuOQZpuF9y BrPE/dblRj5jRKO/fP5zKSzFnUIlM/XwrLiQo4yWhHGwtaLG8uc0y+VO2V9QhWmHkimQ21DzkIL1 fV07OVm5W69uAxEZrjeXjHbCZNJq21lF9y6XYfbcElkPDWB7X1ngAP2vKCuEjUpc0nkmteVbBQwW zToxSyM8jaNlX2MMQuqnL1c1xQdraQerdbXpySi4hEQPpTisL6ps9CZaI+FOdn9iiTykSjgdIoJq YrevGzVpCwBOiYpBsitiieU5uFrsMgk/GDq+16mllnddcwqz0lOJZXqILPTsilrehs/a4svqqzLo h1qpvYSbdUtE9E/cP3AInzpkAUNlF/Kn6WLZtVS5MB8kcEIxeXuM5f7Y3T9QiZd8wHkBFxu4Dp2b tRaVURKHAqKLnomW5qvOJTyE6AKxAF14WipSF9omFL7PAObKCEPiA84KAsuMB8BA23l37oSMzPcJ K0sLcEhRyM7HwuK6reueo43t8QKjODnpI5zSONjxLL8sfpYrMOhyznG5d5FwjV8AxH/NMlTH7RBy x2Y5U/GzLoxA5/mnxxBKK6XcoLgKs/2hZ8ZTQ59ZWebbY3DpTk+XfYqQZWkA24ewrsw9DCW1WHco Dw/huFiBf2qFpVh900iLvQCHSgnrOvGTRZwbkrai3x/VFmuteE15zgPQvQv24G7LpNmHBKtS85zc B9dP8CB38/X45iqqaBkjJieuptae5aMjnaLidAjHVLHtK0N5mH8QbPzZ4tjOrfe2qxzt4K6ZX5u7 RPnMsXqslEBUD8VTvBKe1Un3hUT9FR7CXXd2dlrIwGBOl1hmcOnKOahGSq7gmEAepaifkcNRI6H7 HxHpBz4IAc4hayVbH30qwUhteRWAxfRkvbOwicCMAe1jkgsH7upyqWSJLFnE77///W9vQdkBSN6Y uZWICnIosVtL1R2PHRAL65BVIeIauPcXijy+NnFDeCmc6mSHcfRZu/kIhsfGvap5ut36/cA0UVxE xkcaU5SyMKyxEhTqcSg3uIpphRs4oLMfu+GN8NXOjjGr5rkSWeFXVzGgLmpBT+Tvf/97uEFDtIT2 +qyfrhihc3FjqWyjEozlvW0rkjcmfE/rR46U+FjGsnIuoPXioUbYfowxsnUYikm6iJwflNahsZeH h6d+Rz6kvDZKg5vRS4LqC6Jvd3c7M9WN2knDYS4NzcOxRqz5NTdziwB8+XzVnT9lJK+cAAAV7klE QVSTX/dqFdZLiZaEVpCKS6xH9jiiRWFycittT0GtssxQ3was2gUnH5/Pm1Q9ZNlJ2RijHWjSm4nv a0N1rmg0y3s2lc0RKscIfMN8TROwX6LBBZjHcytk/hHE+fTSivTxaV3+e9fNRXoDOCzfz3M9N07R hWwDMlEHvgagLN+NsqJsMzSFxz2t6dc7MxibF3DvjbY5YVqSpGVj5DcZfRty0dpmC23ZGITvY7mg CIckH5ffmSB8x8hiBkD5HMoDN4/P5ZI07TEt+6wCGhIUlOezGatkWa9da8z7fUnCKPgH/6KCw4GU 1mvLJRS7+hZW32W1ZhjPXY1h8U1J2GzqmScojYfNU2qM70mP4XWzT9YpODVPsFYV+XR1HXWycDH5 eZaAeo7/+eo66vX7/VersA7dcbZVMgz0WFVMK4KaazWUniNlou1v2HZ8ttZV23swV0Sw6gE/26il 3Um8BkmFFutHEQ4tSiYJx2TCDBUizDu9tI8cyuZacAsF3ZGx/omHFqJQh0ipeW2uIDKnRdyh5WQP 5Z+pOFpL1s1yI9N99DOZwCyWO3WfvPfDRKejsPzfXPZlhtjMXq3CeknJuX5jk1oi5ZDJi5h57gPJ 5vH/397ZLUeR5FDYBsMMxEzM5c6+/9NxvbELeDDe+KrrM8dyZv10V5nGbkUQQHd1/WWmUjqSjq4K A6rKLd2ApBXGsrEUKEsX0jVM8d4tRaoYmTsbihKLjEUyRVmcxIb2UOT6YlrejxHWvRWB44L7QDRq TnJRZNDgHBXWXr0ip4QFj7yZaNJS31e+UzcpKydMhE4x6XXoXThSJhF0AnI49Xm577sBoD9jC2vr vnVV5nY4rAwXZyorXcrEmHTl+L+0MQmsCvRnW3r7CcrHjjxQw45F0lpcKan0OL5n/SWGZkeglivH 9bznbMIqfvVgik9EVY+RJQEFCm+nONx/BRcwZYiWffzYddH3kjcseLAsIn9fYGO4fpTvNjUWJijr OfB+DSalhWWSMt8xf1BWUn5vIVhX4Jvnq7B+kphDlYszk0f1zxkYXDOVhpFFs8hzInAsUTsLmPk8 GUWrsjFKp7IUT+jVIeY1Fa/DH5Qr7iN5Ya1opCCqLKMC9vU6zy1LlNo5WlE94T2bHPzccjdaSeJa YkM9sT5WTyI9BgM0GazJwn4++/Tp07BWxEjXsIVMQQUXhZWT/nqkcCHp7vrqgUhsCM9eHzh8GIBM GJUN1Elo9reLzX6B0ilrZWk5SSFjkwysLkD1dDX5bVpnKSaAmgeWE9SInqU2GcHM3d7CWz8/ByUg U8BLEefOXr0i56RaOvluWxtDC4+1SJ/56PwEMmAzTpeQjVFMK3P3zBM8VmFzJ2c7I4Z+s0sWzsiz M/xzg4VGtm09Fw0jTZ5Lmhl3IU18LSzTAMShHHgsKr/z905kzsFOxLFyas21JvO7FqeWVlkyMxgx 5DPd1Iz6oBTFr/ZUWrgnuCYU1bZoUMBchtKSF1SmY+nUHvxhS6S+50Nz0h8pLxVaqGkXRqgz4ocI NyBYWWBWyW8lrivtEgrNzXWt1c68OVuFlRbOzxYU1QBKfz8QkCmWuDjQueAffjua0OZ5MeDsNriJ WFNmi2t2JztCSg/8T5whM9ctWM5/m8FcI5GK5UupgLcWyjVQVGRI80y1VhPuJYqfX5KyQsQy9yrF WSv0glQM/rQ2Kjdd62KrmEiMsso5p7gBc/4sOcvu6Yvv+fsrqSU8We5HADtHeTSzxYr01RFTAdxB LCpNxWI0JZkTcjLX/+vieY0q5lK1ooG6hLqF5p7NZfPvISirVMyU41D2DzDMv1FW5+CSbi17luEc I398+P1Rkq5caG7ARsidy7WLkkwmFkdLBVPHzrGWwdZcrmPmGqe+KKxFb+rQBPLbVRD0j5zYvnwV lw0k+Nz28u46TADZD9hts45P359jjdwlR7xm9ZTSMsJXrbO02pxord0tE2l1XbZWHlkv6HsZCtE/ jxQmv21PtXIOsgef2JZuoha4BfMGebIXZo2Uu0nyXc9qTzrthCdcN2vmF8deFNaSF3V1WMh27uBF 484ZGcy6v3TdGFCBbwcMZWE+k+4Xx1cKY/GOxKU4rme6+339HAUl2ynXruSCQ4PKcVdF2CV5NvOv 9kxjyMTCIfoa6SAvTdwszunZ7sguD9hFeiI3xDpmWFrMFzc8NmSpyaeey2TkjHQLBeQ1XA+9iOKr TRxdK2BpKCcWOoPJoBHJyzo9vrOJqfWItnKXwdMIiZzcOSgtRtPEthS7QLc64BgEkO4ZSSDf7H6O 0YITR8qdjwRW7tEs/1MXmYAuMiSDvtkuReKcFMCU7EHSd6pk6/jqvhkkEDhnPvCHjVUFJDllT4wQ tnjnErM1yi5hpHOz5V5eFNaK6CE8PZatyO6ZO4bpCLqB1iwyKJbApLtmxK4SABpVlJ+qMkIIrrei LGa/G4nh3yolQdN671UxJjFhrxPPGhkm7vAO7iYLm3EVn6P052eI5S3nIl++3j4h+DNy7NxCQWkJ Sbttmo4KbeqZnGOprIRKVISmAGmxsU56OYfDOTd+Dy9aLAS24JjFLOWwisoKdcPC2frLcxiFMwtd rKoOflomKTZPbU0WFZ1JfUne5yRwcthOnAki/qagJOV/P7UhqYsjlVXPpf1y+zIpksU2z0G+DRvj +8nAQCUFMJPd6F7mYvXEOe9Ya0lJV9QrF7O2tkmpvPJZX7XIEcQLN5FTa8YGlEZONHelEs5cqORf 19U0odBaM7Er6xWrcnKHqi2/3P2kam4l6RnZ0bprtbEX5PeYY13DQRE23KHeuXr1br+yO3huCus7 +UwzLqpBAhM++QPU4XOIP02xgbQCPyqhubFjDbSijheFtUIsU0CM2Fmjp9slv5aAsmwK5uCIF4lv GRVUTD5Nt69VmoPSARyXiUEczTwwsYFe+Bgsgnov7msKNM2SDCfdqWwBU0ED0h6WKsdfRWGdS+4V 8n2igsDx5b3KEcfc1EqXsUEFlkmjU2JVRZabTSk5GUoqfdPw3ezVLvLjZb29ebCe0gJh0ZvRjmSZ jOkEmtM5wA6KoKa/Y2fRkjOTPQcc4booQ6M2XDuVGgqP73rJeU5G24a3Fn9LQR0TirZJQescLmbf qR1czhGkPlYY43Oxrr5+vR06Olex7IY5w7yTedaONoiWu9b4XHTQ8/L7nLtGzuvcksySd1XLgpSL wlohaQo7gAyIvr+AvMcJzjNAmX+VLZV0/9Ll47ymIZgm4QDnbi1ulh1y8hxT2fGILm2vuFqFZUKq 5Uaef03RakqNeop1qPxvbt4Nbcrn3JZfRXpY5B5yHQ0kWvfRaobK55TdMA8JHDk3scKZG256EvUl hY+/Fw6pG6Rd0/N+7MKTYja9m7RVFxWquCisFVJb0NsKyxZZUm6Y0S4TQoKZ0s7aZ81jsdwSD3C3 cTFnd2jBy1SOLeG6TMQeyZ+Fz9ZDphUgS4RWn5idi2+Je5hAPrWB72d4kX5EKXluWkiRZPrrK62M GG/hxn748KHbPo73zXctJtpDr0L+9ZjWWxw2o9YyiiSRX08JuilWZVXrVZXeO0isVwV2UVgnSLVw eKHsQoZvBQmNsBi+TfMXa8ukUHEqwfNagKpS0LKxXMLMerGwFluDE0Ma5ZZLoltrMmseUzPq5fOy I7D3t3QBVmVluke1LPO5r676IfMtE1r3xsJ0v9dKrUm9D+u2utJipm6APfzq7fVjskNhA++POZ2b c8vq9p2lq5jKytSFVpRvykIX2kB6m+HFwlop1cWqu5zForbBGmhg//rroVOP9LIMqBgBx/tvgHQT T2UjZce0Ul6SvcxryWheS6bcETE0Oz1zHsF7LUGvY6t77mfO0hL0z+ukldlKychSHYTjKYaWw2lr SSbYvcW6U2tHW669OGeN7KrY78e5pfXt2KVykc+t9X7p/ZcWK8cxv+RJczN1nNKS9z5sSoGb18Oh sg9APgMKibml25q/NdiU56kbOHJRWCtkqDa/+/bQHGOKlAwlwuDwwgUuM5ro5M3dymS87LBs1NGk zxbDgZOvlxuTlloVrqmihBIZZaJC4V4MKEjyl66r51vCv+7yNJJqLaXYGNK6971wLBe6z+f966Yn JtiydFQgrXQTnyUhBF1sF2X+Xhw0reRUQC35Z6xlFTvK50pL5ZGUfYvfmgPoWNSaQZlvvWfuMTGt VnSv1dfA/EMijlpgtezM95SBoyoXhbVCBpP77kdzjKmsbF1Bua0taWACiBc4INmKyZbwCBPc7tOZ cQxulu3IWhnuKdwnFlpyxtfn4jooRi0On82ynsQk7HSdZRm5G6b1l997Ly7EOSWHEF0cqJI3LBy2 2Nx3qjXLvaGsM8k377WFGfXu39pRn5u/db9bsiYqej8B4k9ii2U8pEPSa8i/fbaqNHrP67xt5U6l YnLjrN3NvXZevwa5kIvCWiEwkeaOWvsJtoQXjrLSorAgOvEuzqMyYefhGsnDjjIyUqdyqYR9hoN7 lhTnn3J/csfPEiEnjvfh4sUqyyCA0jLjh/uLiSdAq2uA5EJ+tBg7i/MU3MlnkccpLYatCPZckCqP Y7CyfF8tpf9tBPHTGrNjTUZelfdF+WfbLjdMz+t4tKiys+NTizZ5TgxGVU+hRhO9xkVhHSlvrg+M DfyNLJ2AmsP8gVtdHIuBF8S2h6A4Egspxck5tbsmNXPrHlRqrfs2V8gFK65m3ljlczLEjfVoz8Wp 91Hdq2qdVqX3XLJFvlfer8/ZcpMTv8o/FX/ij8qjKrq7cYzFqRLH0kpkToE1cYyNUgYLcRy///7v 89W///7XE5zJzUyl1RLmqQ1aHEMrNtZQH7c8BSPW2Yi4zpOLhXXM5JQCfiWnDxMSBSDjgiU6TpDs bJNYFqIZbTTHLOAcUBVfrxWXrBEtXnEjimBZuo9D3s5oRbXOx/NwHM8gbjKHZ/m9Ec/WwnjOnKXW /WVFgrWgRoL5znZXZnCrzI18ev9aWaY1ZClVy2pig2DcpSNC6SztVHQ93qvzh3OIJZkf5Xn+/OMA fP+HTt8rW3B53hSDBkpLySIVVK8KM602z1Nx4ovCWiFYV4eGjo+tgTUKC3FB1xyqOlgJpPt/Jx6T ACus0nAw4fm8hWUZZapmtiK3EcrUayG9tAmfScVjkmxlp3z0DkcWAJ833ZqeVOB9qzSE1nlQEt6X VotWpuA0YkDFfKjMdzP/zLmh65OBiqlwf5alnPqs96P7nc1OjPiirA5NSqn3LJji2CvBP1CDL02A TdwpaxG5Zuai8V5rYmpuYImV+puLwlohg7aPpLvewu+JSgpJNtHesQywKQaIfPDiX5jhFZeytKUn ldKm9T0iIItwPt2A3j27yGWSWLLQ0gXpHd9ib9hKYSE5frpU+f60BvN4C9gzApbJua3UBT/vSX2m JQGJpcJ5BPy13LCMB8tvcEOZD1jwbxc1e6mia5obcm64+bvMz6qEhlr0zjNhh2xjd1FYK6QWY2qy HoODLJ2MmXDoLj2HS0nP0XPl0tVsiRTJKktTKVJ5Tj1Xgrb1WfJdpcJSnmwAz1g3vMRarmNtrVwm 0zpOdUxyg2ulQ1QsbEvX+Hq09MTA8jkOVh2bKeN2M9nFqnVPPGuC7rqgrfdZu0E5B5zL/J0ElZz7 kZLb6H28ChFHSlxpb7zFiEz2Qsy8LAayxfNuJ+dWhrUJoLVlk+F+LDcAUTPk+ZsJxG6nazFnHbbE XK4qea66kH//bb+27hkIMG2hPlfy23tvqXxk00wFUEu40nXOa+e1OFfdjJ6D5uZ+3BEOzz9/TVM1 srOS2GzNmm9JYndGF/mN+KcwiXNe+OPh/k96+lcmmrm+QAHVPUUgXaDcXKzc7Vq41FRS65BBHsyS muZcB2VlVjbKiQklTiZm4/1Mnb8l9f6UVGL5+d61hC2lUjcgy6vE3tJqTZclj6/vpoLeXrtey3Nl TtTW8nFkEX2Q8RKHe5u2LrkfAwKyhORG2bIeq5VldYHPVzdN76VWAhiwuCisFYJZbKt6X77g6l6S WJZ4AJNfWmMk2SHyd4LsLaVq+RDncdKkAjZfzM9VQi7SqaLqXvTN33v9qeNz958791bibp6LzPtO +mA/r4q7lTi5puhZd8hj9+gSfTNJJMj7nr9Pn6lulHUdcEy18i3izwAFVr0Z8HlcnucCuh+ZOJoL 1ATLvbmOGKxa7pA5PEalKi6VuS41Gomi4ndiBXWyGXa2jVO9H87JxMvo1lQUzM9rWH8Kv3r3DPQy NdFVhZXZ7lq1mQRqIm+6ldWayO/yenbQqTKkGox5U24oW8s/Y9ellswC70Xh+R6MZNuezjmVlQQ5 3jYPVuEJMaSFljCIzA1sGBcLa4UYIUxFkZbOsVLLFFpSWRlYQORM2fiCz9mpMs2Bv2kdjjUkE6mc U06SHhdWMjToFmbZhxMsJy+7qRhXPV9vkUwljBJuf/t2XyaFqmDF7GwkopVgSzfE9539JtkY8hik 4i9eT9rsnvC7vVqCfRl5pnpc73MKi/nOfPEc8rPrKkv5rTJvPWcGhfKdZ6ka50x30STYi8JaaWFV ORUclW10TmExcLbv0kXDyjGtgcWTOVuK3zMhDD/nYptKgTAvJgHpjH6ptA3B8528373zIWnBTGGA hwjsU+tuS6nVAVmV4P3xXlM52aYt37FpAj5fLZ1S3DR+FgPp17HNW0uGLtwzwrtAObspmSKTln5C ERa6185PNXWkRkiTsJL/836HxsQnv4FXKLlITwXdJdtfIlkYnfeR32fCZ15DCwupkcGpxFC+1/VL twjJBMf8rKXEqxvUsrjqZ3O7/d6pDD5bKiJ75mWtnfV7iqU1LezKrHBdSDcRo23OKasH7DO5lYJ7 N3KfScb46N4WZtTz/MwJN6+sL0Q4t+R/vai0Stv3lsA6YrKrVRsXDOtIMbnNQcqBdLH67xZXVv7b c1RFMCWtfJ7a29BWTFJ4MOjsivIepXivPXA+3aA6wXOS1uPnlK3H9oDW21vqGvdLaVASs8pMbl1n JJklzGpHOJbFWJVJjmllp3CDyuTaVF7eC+Omy1RLVpbKcM/FK6ApsN8N4x1ft+iTq4hbZdUFz585 etyvjLrOEQMWvl9+K8eb3oOupZsIn6WryN8XC2ulMDjiP8lgYA5Jzc3KRZmL/1i3kmuYKyVGYsTO yWNpTVpNuiwtUJxnyHSNlBZwPJU6seRZvE7NRUq5pelqUVhbuoOWNtVzWo4jFxQYIVJrJHNj6lnf ifktLWvx3FvIdSdb/qFjU7FgSR6l2e2UZWsDCTdEsSrmULar8/pKNlrxvjg23T6hiiz0zzrMAdvb 5M28IqmlJ7nIe+7QlsL5pXZxtxZjYRLisphUWiNwGXlJqcwMKUnSl+KCrgmrvQWS76Xl3jzJf9ox YTTrJpWW4lKRHw4Ygy4tnXn/I4nYNJA90y+uFgppIVlKpliC9O7q6Tv+/PX26s+bRnRyPE02THFc 08pPS70GIOyHKX6l25dKzqCEIL4EAdbd/h+GH9Som7uOOgAAAABJRU5ErkJggg== dataset EPSG 6.13(3.0.1) 0