20240209 09245700 1.0 FALSE tl_2022_us_state_AK 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> 20250324 23140100 20250324 23140100 PAD-US Team U.S. Geological Survey (USGS) Gap Analysis Project (GAP) PAD-US Dataset Manager 1-888-392-8545 PO Box 25046, MS 302 Denver Colorado 80225 US pad-us@usgs.gov 20250331 ArcGIS Metadata 1.0 U.S. Geological Survey - ScienceBase 1-888-392-8545 Building 810, Mail Stop 302 Denver Colorado 80225 US sciencebase@usgs.gov None. No fees are applicable for obtaining this data-set. The File downloads in a .zip format https://www.sciencebase.gov/catalog/item/652d4fc5d34e44db0e2ee45e https://doi.org/10.5066/P96WBCHS https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-overview/ Protected Areas Database of the United States (PAD-US) 4.1 2025-03-31 4.1 U.S. Geological Survey (USGS) U.S. Geological Survey (USGS) https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas vector and tabular digital data PAD-US Version 4.1 Protected Areas Database of the United States (PAD-US) The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme ( https://ngda-cadastre-geoplatform.hub.arcgis.com/ ). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all open space public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, permanent and long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g., 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of U.S. public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. PAD-US provides a full inventory geodatabase, spatial analysis, statistics, data downloads, web services, poster maps, and data submissions included in efforts to track global progress toward biodiversity protection. PAD-US integrates spatial data to ensure public lands and other protected areas from all jurisdictions are represented. PAD-US version 4.1 includes new and updated data from the following data providers. All other data were transferred from previous versions of PAD-US. Federal updates - USGS remains committed to updating federal fee owned lands data and major designation changes in regular PAD-US updates, where authoritative data provided directly by managing agencies are available or alternative data sources are recommended. Revisions associated with the federal estate in this version include updates to the Federal estate (fee ownership parcels, easement interest, management designations, and proclamation boundaries), with authoritative data from two agencies, the Department of Defense (DOD) and the U.S. Forest Service (USFS). Additionally, unit names were updated to reflect recent name changes to Fort Benning, Fort Bragg, and Jocelyn Nungaray National Wildlife Refuge. The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup/ ). This includes improved the representation of boundaries and attributes for the National Park Service, U.S. Forest Service, Bureau of Land Management, and U.S. Fish and Wildlife Service lands, in collaboration with agency data-stewards, in response to feedback from the PAD-US Team and stakeholders. State Updates - USGS is committed to building capacity in the state data steward network and the PAD-US Team to increase the frequency of state land and NGO partner updates, as resources allow. State Lands Workgroup (SLWG, https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/state-lands-workgroup ) is focused on improving protected land inventories in PAD-US, increase update efficiency, and facilitate local review. This version includes updates and additions from the following two states: Texas (state, local, and nonprofit fee) and Arizona (state, local, and nonprofit fee). All state and NGO easement submissions are provided to NCED. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas . For more information about data aggregation please review the PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . A version history of PAD-US updates is summarized below (See https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-history/ for more information): 1) First posted - April 2009 (Version 1.0 - available from the PAD-US: Team pad-us@usgs.gov). 2) Revised - May 2010 (Version 1.1 - available from the PAD-US: Team pad-us@usgs.gov). 3) Revised - April 2011 (Version 1.2 - available from the PAD-US: Team pad-us@usgs.gov). 4) Revised - November 2012 (Version 1.3) https://doi.org/10.5066/F79Z92XD 5) Revised - May 2016 (Version 1.4) https://doi.org/10.5066/F7G73BSZ 6) Revised - September 2018 (Version 2.0) https://doi.org/10.5066/P955KPLE 7) Revised - September 2020 (Version 2.1) https://doi.org/10.5066/P92QM3NT 8) Revised - January 2022 (Version 3.0) https://doi.org/10.5066/P9Q9LQ4B 9) Revised - April 2024 (Version 4.0) https://doi.org/10.5066/P96WBCHS 10) Revised - March 2025 (Version 4.1) https://doi.org/10.5066/P96WBCHS Comparing protected area trends between PAD-US versions is not recommended without consultation with USGS as many changes reflect improvements to agency and organization GIS systems, or conservation and recreation measure classification, rather than actual changes in protected area acquisition on the ground. U.S. Geological Survey (USGS) Gap Analysis Project (GAP), 2025, Protected Areas Database of the United States (PAD-US) 4.1: U.S. Geological Survey data release, https://doi.org/10.5066/P96WBCHS PAD-US Team U.S. Geological Survey (USGS) Gap Analysis Project (GAP) PAD-US Dataset Manager 1-888-392-8545 PO Box 25046, MS 302 Denver Colorado 80225 US pad-us@usgs.gov United States Alabama (AL) Alaska (AK) Arizona (AZ) Arkansas (AR) California (CA) Colorado (CO) Connecticut (CT) Delaware (DE) Florida (FL) Georgia (GA) Hawaii (HI) Idaho (ID) Illinois (IL) Indiana (IN) Iowa (IA) Kansas (KS) Kentucky (KY) Louisiana (LA) Maine (ME) Maryland (MD) Massachusetts (MA) Michigan (MI) Minnesota (MN) Mississippi (MS) Missouri (MO) Montana (MT) Nebraska (NE) Nevada (NV) New Hampshire (NH) New Jersey (NJ) New Mexico (NM) New York (NY) North Carolina (NC) North Dakota (ND) Ohio (OH) Oklahoma (OK) Oregon (OR) Pennsylvania (PA) Rhode Island (RI) South Carolina (SC) South Dakota (SD) Tennessee (TN) Texas (TX) Utah (UT) Vermont (VT) Virginia (VA) Washington (WA) West Virginia (WV) Wisconsin (WI) Wyoming (WY) American Samoa (AS) Mariana Islands (MP) Guam (GU) Puerto Rico (PR) U.S. Minor Outlying Islands (UM) United States Virgin Islands (VI) United States Common geographic areas Protected Area Public Access Land Manager GAP Status Code Land Stewardship Land Ownership Gap Analysis Biodiversity Conservation Protection Status IUCN Category Federal Lands Public Lands Outdoor Recreation Public Health Public Open Space Parks Governmental Units State Lands Private Lands Local Government Lands Forest Service Bureau of Land Management National Park Service U.S. Fish and Wildlife Service Department of Defense Army Corps of Engineers National Oceanic and Atmospheric Administration Natural Resources Conservation Service Bureau of Reclamation Tennessee Valley Authority Department of Energy Agricultural Research Service Census Veterans Affairs Federal Agencies and Programs Geography Land Use and Land Cover Protected Area USGS Thesaurus USGS:652ef930d34edd15305a9b03 USGS Metadata Identifier alaska earthquake Hazards Volcanoes The Digital Object Identifier https://doi.org/10.5066/P96WBCHS for PAD-US provides the persistent reference that should be used to obtain the data for use. The U.S. Geological Survey and all contributing data partners shall not be held liable for improper or incorrect use of the data described and (or) contained herein. All information is created with a specific end use or uses in mind. This is especially true for GIS data, which is expensive to produce and must be directed to meet the immediate program needs. These data were created with the expectation that they would be used for other applications; however, inappropriate uses are listed below. This list is in no way exhaustive but should serve as a guide to assess whether a proposed use can or cannot be supported by these data. For many uses, it is unlikely that PAD-US will provide the only data needed, and for uses with a regulatory outcome, authoritative agency data and field surveys should verify the result. PAD-US is recommended for users seeking general information about more than one agency or organization's lands. Users should seek authoritative source data directly to answer questions regarding one agency or those requiring more frequent updates (See PAD-US Steward Reports for contacts and agency data download locations: https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-stewards ). PAD-US includes the best available representation of federally owned lands (meaning a federal agency or the U.S. holds the title records), developed from authoritative source data in direct collaboration with federal agency data-stewards. Several ownership related data gaps exist and USGS provides no legal warranty. Agencies are always the official and best source of their land data and some update more frequently than PAD-US. The FGDC Federal Lands Working Group recommends the use of PAD-US to describe federally managed lands (i.e., “Manager Name” not “Owner Name”), unless spatial data inventory completeness is over 95% and appropriate scale for display is 1:24,000 as illustrated in “State of PAD-US Data” (e.g. USFS, USFWS, NPS, BLM, DOD) - a graphical summary of inventory completeness, appropriate scale, and update frequency available at the Federal Lands Workgroup (FLWG) website (https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup ) . Ultimately, it is the responsibility of each data user to determine if these data can answer the question being asked. Furthermore, the database is released on condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from its authorized or unauthorized use. Inappropriate uses include: Using PAD-US for applications or analyses associated with one agency or a particular unit (agencies are always the best and authoritative source of their land data and many publish updates more frequently than PAD-US). Using data to map small areas, typically requiring mapping resolution at scale finer than 1:24,000, as boundary quality varies by data source (See "State of PAD-US Data") and using aerial photographs or ground surveys in areas where data are incomplete. Combining these data with other data finer than 1:100,000 scale (except for select federal agencies or states identified in "State of PAD-US Data") to produce new hybrid maps or answer queries. Generating specific areal measurements from the data finer than the nearest thousand hectares. Representing boundaries as a legal representation for regulation or acquisition. Establishing definite occurrence or non-occurrence of any feature for an exact geographic area. Determining abundance, health, or condition of any feature. Using the data without acquiring and reviewing the metadata. Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This database, identified as PAD-US version 4.1, has been approved for release by the U.S. Geological Survey (USGS). Although this database has been subjected to rigorous review and is substantially complete, the USGS reserves the right to revise the data pursuant to further analysis and review. These data are in the public domain. Protected Areas Database of the United States (PAD-US) 2025-03-31 4.1 USGS Gap Analysis Project U.S. Geological Survey (USGS) https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas geodatabase https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas Protected Areas Database of the United States (PAD-US) 2025-03-31 4.1 USGS Gap Analysis Project vector digital data https://www.usgs.gov/programs/gap-analysis-project/science/protected-areas Python 9.3; Esri ArcGIS 10.6 (Build 8321), PADUS4_1Geodatabase.gdb true -180.0000 180.0000 71.3120 -15.3861 publication date 2005 2025 The PAD-US database strives to be a complete inventory of areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational or cultural uses, managed for these purposes through legal or other effective means. PAD-US is an aggregation of “best available” spatial data provided by agencies and organizations in the United States at a point in time. This includes both fee ownership of lands as well as management through leases, easements, or other binding agreements. The inventory also includes Congressional designations, Executive designations, and administrative designations identified in management plans (e.g. Bureau of Land Management 'Area of Critical Environmental Concern'). As a result, this is a robust geospatial representation of the complex U.S. protected areas network. It is important to have in mind a specific analysis question when approaching how to work with the data. As a full inventory of areas aggregated from authoritative source data whenever possible, PAD-US includes overlapping designation types and small boundary discrepancies between agency datasets. Overlapping designations mainly occur in the Federal estate of the 'Designation' or 'Combined' feature class (e.g. 'Wild and Scenic River' over a 'Wilderness Area' both within a 'National Forest' boundary or a 'State Wildlife Area' over Federal Fee owned land). See the Entity_and_Attribute_Information Section for more information about PAD-US feature classes. It is important to note the presence of overlaps especially when trying to calculate area statistics; overlapping boundaries count the same area of ground multiple times. While minor boundary discrepancies remain, most major overlaps have been removed from the 'Fee' feature class and this is the best source for overall land area calculations by land manager ('Manager Name') within the PAD-US database (data gaps limit calculations by fee ownership or 'Owner Name'). Statistics summarizing 'Public Access' or Protection Status ('GAP Status Code') by managing agency or organization from an analysis of the PAD-US 'Combined' feature class are included in this data release. The PAD-US database is a direct aggregation of source data and the PAD-US development team rarely alters spatial linework. Exceptions are: 1) to “clip” polygon boundaries along State legal boundary lines (using the annually updated, national, authoritative State boundary file provided by the U.S. Census Bureau, https://www2.census.gov/geo/tiger/TGRGDB22/tlgdb_2022_a_us_substategeo.gdb.zip ), 2) to remove the small segments of boundaries created by this process associated with State or local lands (not Federal or nonprofit lands), and 3) to integrate Bureau of Land Management Field or District Office boundaries into the large boundaries representing National Public Lands (mainly across the West) to attribute PAD-US "Unit Name" and support PAD-US applications (e.g. Wildland Fire Decision Tools). Some boundary discrepancies (or slivers) remain in the dataset. Data overlaps (see ProcessStep10_FeeTopologyOverlaps - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ) in this data release are shared along with the U.S. Census Bureau national State jurisdictional boundary standard (updated annually) with PAD-US data-stewards to facilitate edits in source files, as appropriate, that will then be incorporated into subsequent PAD-US versions over time. The PAD-US database is built in collaboration with many partners and data-stewards. Information regarding data-stewards is available at https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-stewards . Story maps, presentations, and other descriptions of the PAD-US and applications include: 1) Conserving and Restoring America the Beautiful, 2021: A preliminary report to the National Climate Task Force recommending a ten-year, locally led campaign to conserve and restore the lands and waters upon which we all depend, and that bind us together as Americans ( https://www.doi.gov/sites/doi.gov/files/report-conserving-and-restoring-america-the-beautiful-2021.pdf ) . 2) U.S. Geological Survey, 2021, Analysis of Updated USGS Database Finds Increase in America’s Lands and Waters Managed for Biodiversity. U.S. Geological Survey Technical Announcement: https://www.usgs.gov/news/technical-announcement/analysis-updated-usgs-database-finds-increase-americas-lands-and-waters . 3) 2021 National Park Service's Connected Conservation Seminar Series. Protected Areas Database with USGS ( https://www.nps.gov/subjects/connectedconservation/webinars.htm ). 4) Davidson, A.; Dunn, L.; Gergely, K.; McKerrow, A.; Williams, S.; Case, M. Refining the coarse filter approach: Using habitat-based species models to identify rarity and vulnerabilities in the protection of U.S. biodiversity. Global Ecology and Conservation, Volume 28. 2021. https://doi.org/10.1016/j.gecco.2021.e01598 . 5) 2021 The State of PAD-US Data: Completeness, Scale, and Update Frequency for Source Data in the Protected Areas Database of the United States. Updates are posted periodically on the Federal Lands Workgroup (FLWG) website ( https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup ). 6) Morgan, J.; Rhoden, C.; White, B.; Riley, S. A state assessment of private lands wildlife conservation in the United States. Wildlife Society Bulletin, Volume 43, Issue 3. 2019. https://doi.org/10.1002/wsb.997 . 7) Completing America’s Inventory of Public Parks and Protected Areas: An Action Plan for 2016 - 2020: https://www.protectedlands.net/vision/ . 8) Online PAD-US Help System: http://www.protectedlands.net/help/ . 9) 2020 USGS Supports Wildland Fire Decision Support: http://www.protectedlands.net/uses/usgs-supports-wildland-fire-decision-support/ . 10) 2019 How to Use PAD-US in Base Maps - Guidelines for Incorporating Public Park and Related Protected Areas Data for the U.S. into Online Base Maps ( https://ngda-gov-units-geoplatform.hub.arcgis.com/documents/guidelines-for-base-maps-data-use-version01march2023/explore ). 11) 2019 PAD-US Helps Connect Trail Systems Nationally: http://www.protectedlands.net/uses/pad-us-helps-connect-trail-systems-nationally/ . 12) 2018 DOI Office of Policy Analysis Seminar: The New and Improved PAD-US 2.0 (with FGDC Federal Lands Working Group panel). Posted on the Federal Lands Workgroup (FLWG) website: https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup . 13) 2017 DOI Office of Policy Analysis Seminar: All of America’s Parks and Protected Areas - Building and Using the PAD-US (with Federal Lands Working Group panel). Posted on the Federal Lands Workgroup (FLWG) website: https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup . 14) Lisa Johnson, Mason Croft, and Larry Orman. 2017. "Building a complete GIS database of protected areas: USGS leads inventory of lands in the public interest." Esri ArcNews. Spring 2017. Volume 39, Number 2. https://www.esri.com/about/newsroom/arcnews/building-a-complete-gis-database-of-protected-areas/ . 15) 2017 PAD-US and City Parks: http://www.protectedlands.net/uses/pad-us-and-cityregional-park-agencies/ . 16) 2017 The Lands We Share: America’s Protected Areas: https://storymaps.esri.com/stories/2017/protected-areas/ . 17) Jarvis, Jonathan B. A Report on North American Conservation. Presented on behalf of NAWPA. 2016 World Conservation Congress: https://story.maps.arcgis.com/apps/Cascade/index.html?appid=6d3a412ee9f34ce7868667bda19e5679 . 18) NAWPA Committee. 2016. Conservation in North America: An analysis of land-based conservation in Canada, Mexico, and the United States by NAWPA agencies. Report. North American Intergovernmental Committee on Cooperation for Wilderness and Protected Area Conservation; Canada, Mexico, and the United States of America. https://www.napacommittee.org/wp-content/uploads/2023/11/Conservation-in-North-America.pdf . 19) Grant, Tamara. 2017. Federal Agencies Working Together to Improve Data in the Living Atlas. Esri ArcGIS Blog, Analytics: https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/analytics/federal-agencies-working-together-to-improve-data-in-the-living-atlas/ . 20) Building Green Infrastructure in the U.S: A Framework for Sustainable Growth: https://www.esri.com/en-us/industries/green-infrastructure/overview . As a compilation of many datasets, attribute completeness and accuracy may vary. Federal and state data providers reviewed the translation of their spatial data files into the PAD-US schema and several provide data in the PAD-US format. In addition, the PAD-US Team summarized and reviewed the final aggregated database and each feature class for overall attribute accuracy and consistency as described in the PAD-US Review Summary Tables (see ProcessStep9_ReviewSummaryTablesandScript - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). Boundary discrepancies (mostly small slivers) between agency datasets and major overlaps associated with fee ownership (mostly between Federal and State lands) have been identified and are shared with data-stewards, who will edit source files as appropriate and resources allow. Users are encouraged to review topology overlap errors between Federal lands and between Federal and State agency lands in the Fee feature class. Duplicates were identified in the geodatabase. Some are legitimate while others are difficult to remove without further information and will be edited over time as legacy data are replaced. This dataset is considered complete for the information presented, as described in the abstract and supplemental information section. Estimated completeness of the PAD-US inventory, by Federal agency or State, can be found in the "State of PAD-US Data" document provided on the FLWG website ( https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup ). This information is updated, with partners, after an assessment of PAD-US following each data release. Qualitative completeness estimates balance acres inventoried and the quality of data/attributes in each inventory, including fee owned parcels, easement interests, and major designations. USGS seeks to increase the completeness, efficiency, and accuracy of PAD-US updates in collaboration with data-stewards, "Completing America's Inventory of Public Parks and Protected Areas: An Action Plan for 2016 - 2020" (November, 2016), and "A Map of the Future", published following the PAD-US Design Project (July, 2009) available at https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-vision . As a compilation of many datasets, attribute completeness and accuracy may vary. Federal data providers reviewed the translation of their spatial data files into the PAD-US schema. In addition, the PAD-US Team summarized and reviewed the final aggregated database and each feature class for overall attribute accuracy and consistency as described in PAD-US Review Summary Tables (see ProcessStep9_ReviewSummaryTablesandScript - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). A formal accuracy assessment of the vertical positional information in the data set is not applicable. PAD-US Planning, Blank Schema, and Data Manual: The PAD-US database aggregation involves the compilation of thousands of agency and nonprofit organization source data files from a network of nearly 100 data-stewards, with select updates prioritized annually based on needs, the availability of source data, and resources. The USGS is committed to building capacity in the state data-steward network and the PAD-US Team to increase the frequency of state land updates as resources allow. The USGS supported efforts to complete state inventories with the integration of local parks data in the PAD-US 2.1, and implementation of several state translation scripts during the development of PAD-US versions 3.0 and greater. Additional efforts are in progress to support the technical and organizational strategies needed to increase the frequency of state updates. The first processing step in the PAD-US development was to update the Blank PAD-US schema (see ProcessStep1_CreateBlankGDBSchemaGDBandSHP - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ) in response to data-steward and user feedback and the PAD-US Action Plan ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-vision ). The blank schema provides a blueprint of the database for the PAD-US Team to load input files for PAD-US aggregation and it is shared with data-stewards seeking to submit source data in the PAD-US format. Data aggregation and development are an ongoing and evolving process as land management agency and nonprofit organization GIS systems mature and stakeholder feedback improve the process. The PAD-US Data Manual and schema has changed over time to better reflect user needs, providing a more stable format to further develop data partnerships and increase automation. The schema includes all the components to build PAD-US, including the multiple feature class structure ('Fee', 'Designation', 'Easement', 'Proclamation', 'Marine', 'Combined'), core attributes, and all standardized domain tables ('State Name', 'IUCN Category', 'GAP Status Code', 'Designation Type', 'Category', 'Agency Type', 'Agency Name', 'Public Access'). A "Feature Class" (FeatClass) field is available in the fully 'Combined' layer to describe which feature class the data originated from and for users to extract data types as needed. The 'Marine' and 'Easement' feature classes also include fields (in addition to PAD-US core attributes) unique to the NOAA Marine Protected Areas Inventory and National Conservation Easement Database. In addition, the Blank PAD-US Schema includes the U.S. Census Bureau State file (from the national sub-state geography geodatabase: https://www2.census.gov/geo/tiger/TGRGDB22/tlgdb_2022_a_us_substategeo.gdb.zip ) that serves as the common standard (updated annually) for legal State jurisdictional boundaries, the 'State Name' field in the PAD-US, and the full extent of analysis products. The PAD-US development team works closely with a large variety of stakeholders including development partners, data sources, and data users to develop and maintain the "Data Manual for PAD-US" Table crosswalks (see https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual ) . 2025-03-31 Source Data Documentation and Translation: The PAD-US Data-Steward Network includes Federal, State, and nonprofit partners that provide source data files for PAD-US summarized in online and pdf Steward Reports. Information and reports about the PAD-US Data-Steward Network is available on the PAD-US website ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-stewards ). Two federal agencies (Department of Defense and United States Forest Service) and two states (Arizona and Texas), delivered data included in PAD-US 4.1 or USGS compiled data from agency recommended sources (see ProcessStep2_SourceDataDocumentation - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). The PAD-US Team translated individual source files into the PAD-US format (unless provided by the data-steward in the PAD-US format). 2025-03-31 Quality Assessment and Quality Control: The PAD-US development team uses a Python script to generate a Quality Assessment and Quality Control (QA/QC) report each time a source file is submitted or translated to ensure the major components needed for database aggregation are included (see ProcessStep3_QA_QC_Report_Loop - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). Subsequent process steps will outline the general workflow and processes used to compile each major component of the final database. 2025-03-31 Local Agency to Agency Name Crosswalk: A Python script was used to crosswalk data provided by PAD-US contributors, referencing the land owner or managing entity for a unit, into standardized PAD-US geodatabase domain tables (see ProcessStep4_LocalAgencytoAgencyCrosswalk - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). PAD-US retains source data as provided in the 'Local Owner' and 'Local Manager' fields. These fields often provide additional detail to complement the standardized 'Owner Name' and 'Manager Name' fields, respectively. 2025-03-31 Transfer Locally Reviewed Conservation and Recreation Measures from the last version of PAD-US: Input files are compared to the prior PAD-US version to evaluate new records and assign identifiers to join (ExistJoinID) source data updates (input files) with the previous version of PAD-US. File records are compared via automated scripts tracking attributes and polygon location followed by manual review to ensure existing and locally reviewed data flagged for attribute transfer match updates correctly and new records are identified. Once a reliable JoinID is confirmed post review, python script transfers value added data managed by USGS including locally assigned conservation ('GAP Status Code', 'IUCN Category') or recreation access measures ('Public Access'), the World Database on Protected Areas (WDPA) Site ID (a unique identifier assigned by UNEP-WCMC and managed by USGS), and 'Date of Establishment' (see ProcessStep5_TrnsfrLocReviewedMeasuresfromPreviousPAD_US - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). 2025-03-31 Categorical Assignments by Designation Type: The areas in PAD-US are assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant 'GAP Status Code' (that also identifies multiple use areas) and the global 'IUCN Category' standard. In addition, a general measure of recreation access ('Public Access') is also assigned. After locally reviewed measures were transferred from the previous version of PAD-US (see ProcessStep5_TrnsfrLocReviewedMeasuresfromPreviousPAD_US - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ) input files are checked for completeness of required attributes and that all domains and standardized field attributes are completely assigned. In the absence of other information (e.g. local assignment or review), 'GAP Status Code', 'IUCN Category', and 'Public Access' are assigned categorically based on 'Designation Type' using a Python script (see ProcessStep6_CategoricalAssignmentsbyDesTp - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ) that references crosswalk tables (e.g. Tables 6 and 9) available in the PAD-US Data Manual ( https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual ). 2025-03-31 Multiple Feature Class Implementation: The major change from early versions of PAD-US involved the expansion of the multiple feature class database structure; primarily, the removal of overlapping management designations from fee owned lands. The expanded structure, defined by the addition of the "Designation" feature class is replicated in each following PAD-US data release. Building on Federal Lands Working Group ( https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup/ ) efforts to collaboratively develop PAD-US, it was fairly straightforward to determine feature class placement of Federal spatial data. Federal data-stewards defined the 'Category' (the data type field in PAD-US) associated with source data submitted for PAD-US as fee parcels, easement interest, leases, agreements, overlapping management designations, proclamation, or marine boundaries. An automated Python script process compared State and other overlaps to Federal fee data to determine feature class placement (see ProcessStep7_MultipleFeatureClassImplementation - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). 2025-03-31 Database Aggregation and Load Order: Input files referenced in the “Source Data Collection and Translation" processing step above are aggregated into the PAD-US geodatabase in a purposeful load order to achieve the necessary visual and analytical results associated with current database technology (see ProcessStep8_LoadOrder - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). Load order strives to account for boundary size, type, and spatial data quality, to increase the likelihood overlapping features are visible on maps and to support assessments of biodiversity protection status or outdoor recreation access. Files in the PAD-US geodatabase feature class loaded first, remain on the bottom in cases of overlap. Feature classes are manually loaded separately (agencies referenced below are listed in geodatabase load order within their respective feature classes - bottom to top) before the PAD-US 'Combined' feature classes are created. For example, the combined feature class represents this load order (PAD-US feature class and a general description of agency source data listed from the bottom to the top): 1) 'Proclamation' feature class (FWS Approved Acquisition, USFS Proclamation Boundaries, NPS Proclamation Boundaries, DOD Military Lands, Census American Indian Areas (AIA)); 2) 'Marine' feature class (BOEM Blocks, NOAA Marine Protected Areas Inventory); 3) Federal fee lands (Department Of Energy (DOE), Tennessee Valley Authority (TVA), Agricultural Research Service (ARS) legacy data transferred from the previous PAD-US, BLM public lands from Surface Management Area database, USBR legacy data transferred from the previous PAD-US, USACE lands transferred from the previous PAD-US, USFS fee parcel data, NPS fee parcel data, FWS fee parcel data); 4) State and local government fee lands, in alphabetical order by State; 5) Federal designations (USBR designations, BLM ACEC (transferred from the previous PAD-US), BLM Monuments/National Conservation Areas/Similar, USACE reservoirs (transferred from the previous PAD-US), USFS Inventory Roadless Areas, BLM Wilderness Study Areas, NPS Other Categories of Wilderness, NPS designations, USFS Withdrawals, USFS designations, USFS Special Interest Management areas, BLM Wilderness, USFS Wilderness, USFS Wild and Scenic Rivers, NPS Legislated Wilderness (from Wilderness.net), FWS Special Designations, BLM Wild and Scenic Rivers); 6) State and Local designations, in alphabetical order by State (mostly transferred from the previous PAD-US); 7) Easements (often small) are loaded last to remain visible on top of overlapping records. 2025-03-31 PAD-US Review: Once all attributes are assigned and feature classes are aggregated, the PAD-US development team conducts a final review by summarizing the database (see ProcessStep9_ReviewSummaryTablesandScript - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ) and reviewing tables associated with each feature class. In addition, 'GIS Acres' are compared to known sources and spatial data are compared to previous PAD-US versions. Federal Lands Working Group data-stewards reviewed the translation of authoritative spatial data (federal lands and waters) into the PAD-US format. USFS, NPS, and FWS provide data in the PAD-US format. In addition, Quality Control / Quality Assurance (QA/QC) reports documenting edits to source data to meet PAD-US requirements are shared with data-stewards to continually improve update efficiency and accuracy. 2025-03-31 Data quality assessment and appropriate use of federal spatial data: The PAD-US Team and Federal Lands Workgroup (FLWG) recommends users review “The State of PAD-US Data” document that is periodically updated and posted on FLWG website ( https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup ) to better understand the appropriate scale to use data, estimated level of spatial data inventory completeness, and update frequency of agency source data aggregated in PAD-US. The summary graphic, developed by USGS cooperators in collaboration with the FLWG and SLWG is updated following each PAD-US data release. In addition, “Guidance for Base Map Developers to Use PAD-US” is available at the Federal Lands Workgroup (FLWG) website ( https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup ) and PAD-US Steward Reports ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-stewards ) highlight PAD-US as the authoritative source for aggregated data only and document data-steward contacts and data download locations to obtain source data directly. Agencies are always the best and authoritative source of their land data and many update spatial datasets more frequently than PAD-US. 2025-03-31 PAD-US 4.1 Improvements: A new workflow management system that centralizes PAD-US updates, allows multiple people to work on jobs at the same time, and automates standard tasks was deployed during this update cycle.  This system created new and leveraged existing tools to improve data quality, increase communication, and simplify training.  An online PAD-US Data Steward Submission form was also deployed allowing stewards to submit data for inclusion in PAD-US and update their agencies information in the PAD-US Stewards Database.  These tools were designed to boost productivity saving both time and resources in the PAD-US update process. Scripts used for the major PAD-US data processing steps have also been continually updated, refined, incorporated into this new automated workflow process. This included converting scripts to online geoprocessing tools and adding workflow steps to the new automated workflow process that reduce manual data management steps, provide consistent processing, and increase process transparency. These updates included adding several additional checks to the QA/QC, Reconciliation, and Conservation Measures scripts as well as developing a new Schema Compare script. This has led to a reduction in the number of records that get flagged for manual review through increased script accuracy. 2025-03-31 642931 PADUS4_1Combined_Proclamation_Marine_Fee_Designation_Easement The 'Combined' feature class integrates other feature classes from the PAD-US geodatabase, as described in the name (and in database load order with Proclamation boundaries under all other features and Easements on top) including core PAD-US attributes only (The Marine and Easement feature classes include additional attributes specific to those data types). PAD-US Development Team OBJECTID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Coordinates defining the features. FeatClass This field, in the 'Combined' feature class, identifies the original feature class ('Fee', 'Easement', 'Designation', etc.) a protected area unit or record occurred in before combination. This is included to assist users seeking data in the 'Fee' feature class as data gaps exist and 'Category' (which would otherwise define feature class placement) may be 'Other' or 'Unknown'. Use this field to extract select data as needed from the fully Combined inventory (e.g. Fee_Easement), and see the Federal Data Reference lookup table (DBF) for authoritative data provided directly by federal management agencies by Aggregator Source. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . FeatClass U.S. Geological Survey Category The general 'Category' for the protection mechanism associated with the protected area. 'Fee' simple, is the most common way real estate is owned. A conservation 'easement' creates a legally enforceable land preservation agreement between a landowner and government agency or qualified land protection organization (i.e., land trust). 'Other' types of protection include leases, agreements, or deed restrictions. 'Designation' is applied to management boundaries not represented in title documents (e.g. 'National Monument', 'Wild and Scenic River', and some 'State Wildlife Management Area') overlapping fee ownership parcels. 'Marine' includes outer continental shelf lands managed by the Bureau of Ocean Energy Management and Marine Protected Areas inventoried by the National Oceanic and Atmospheric Administration. 'Proclamation' defines the outer boundaries of areas without internal ownership defined: Tribal Lands (Census AIA), Military Lands (Department of Defense), Proclamation (National Park Service and Forest Service) and Approved Acquisition Boundaries (U.S. Fish and Wildlife Service) for planning purposes. See PAD-US Data Manual, Table 3, or 'Category' geodatabase lookup table for full domain codes and descriptions. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Category U.S. Geological Survey Own_Type The general land owner description (e.g. 'Federal', 'Territorial', 'American Indian Lands', 'State', 'Regional Agency Special District', 'Local Government', 'Non-Governmental Organization', 'Private', 'Joint') standardized for the U.S. This field is assigned by a crosswalk from 'Owner Name'. See PAD-US Data Manual Table 6, for the “Agency Name to Agency Type Crosswalk”, PAD-US Data Manual Table 4 or 'Agency Type' geodatabase lookup table for full domain codes and descriptions. 'Regional Agency Special Districts (DIST)' include limited purpose governmental units that exist separately from local governments such as county or municipal (e.g. some Regional Parks, Greenbelts, Water Management Areas). 'Designation' is applied to designations overlapping fee lands as ownership is not applicable. Use the 'Manager Type' field for the best general depiction of Federal lands as several ownership related data gaps (i.e., 'Owner Type' = 'Unknown') occur in the Federal theme. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Own_Type U.S. Geological Survey Own_Name Land owner or holding agency (e.g. 'Forest Service', 'State Fish and Wildlife', 'City Land', Non-Governmental Organization') standardized for the U.S. See Agency Name domain codes and descriptions in the PAD-US Data Manual (Table 5) or 'Agency Name' geodatabase lookup table. A Python script assigns 'Owner Name' from 'Local Owner' (see ProcessStep4_LocalAgencytoAgencyCrosswalk - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). Please note there are instances where 'Owner Name' = 'Designation' rather than an 'Agency Name' as expected. 'Designation' is applied to management designations that overlap fee ownership or where ownership information is not represented in the data type (e.g. ‘Owner Type’ and ‘Owner Name’ are not applicable to Designations such as 'Marine Protected Area', 'National Monument', or data included in the Proclamation and Other Planning Boundaries feature classes), while it remains a core attribute. 'Owner Name' also contains unknown values where parcel level ownership data are not yet available from authoritative data sources. Use the 'Manager Name' field for the best depiction of Federal lands by agency as several fee simple ownership related data gaps (i.e., 'Owner Name' = 'Unknown') occur in the Federal theme. See “The State of PAD-US Data” available at the Federal Lands Workgroup (FLWG) website ( https://ngda-gov-units-geoplatform.hub.arcgis.com/pages/federal-lands-workgroup ) or PAD-US Steward Reports by federal agency or state ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-stewards ) for more information about inventory completeness. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Own_Name U.S. Geological Survey Loc_Own The name of the land owner as provided by the data source, to complement the standardized 'Owner Name' field (e.g. 'State Fish and Wildlife' is a standard 'Owner Name', while 'Washington Department of Fish and Wildlife' reflects source data in the 'Local Owner' field) as more detail may be provided. A Python script assigns 'Owner Name' from 'Local Owner' (see ProcessStep4_LocalAgencytoAgencyCrosswalk - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). Efforts to complete and standardize 'Local Owner' in cooperation with data-stewards are in progress to enhance database utility. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Loc_Own U.S. Geological Survey Mang_Type General land manager description (e.g. 'Federal', 'Territorial', 'American Indian Lands', 'State', 'Regional Agency Special District', 'Local Government', 'Non-Governmental Organization', 'Private', 'Joint') standardized for the U.S. This field is assigned by a crosswalk from 'Manager Name'. See PAD-US Data Manual, Table 6, for “Agency Name to Agency Type Crosswalk” or 'Agency Type' geodatabase lookup table for full domain descriptions. Use the 'Manager Type' field for the most complete general depiction of Federal lands as ownership related data gaps (i.e., 'Owner Type' = 'Unknown') occur in the Federal theme. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Mang_Type U.S. Geological Survey Mang_Name Land manager or administrative agency (e.g. 'Forest Service', 'State Fish and Wildlife', 'City Land', Non-Governmental Organization') standardized for the U.S. See Agency Name domain codes and descriptions in the PAD-US Data Manual Table 5 or 'Agency Name' geodatabase lookup table. A Python script assigns 'Manager Name' from 'Local Manager' (see ProcessStep4_LocalAgencytoAgencyCrosswalk - Download PAD-US Process Scripts https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-download ). Use 'Manager Name' for the best depiction of Federal lands by agency as the 'Owner Name' field includes data gaps (i.e., 'Owner Name' = 'Unknown'), where parcel level ownership data are not yet available from authoritative data sources. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Mang_Name U.S. Geological Survey Loc_Mang The name of the land manager as provided by the data source, to complement the standardized 'Manager Name' field (e.g. 'City Land' is a standard 'Manager Name' while 'Agoura Hills, City of' is an example of a 'Local Manager'). See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Loc_Manag U.S. Geological Survey Des_Tp The unit's land management description or 'Designation Type', standardized for the U.S. (e.g. 'Area of Critical Environmental Concern', 'Wilderness Area', 'State Park', 'Local Recreation Area', 'Conservation Easement'). See the PAD-US Data Manual Table 9 for a crosswalk of 'Designation Type' from source data where 'Local Designation Type' may include related designations in various formats (e.g. NWSR, National Recreation River, National Scenic River, Eligible - Recreational, Eligible - Wild, etc.) or the 'Designation_Type' geodatabase lookup table and PAD-US Data Manual Table 8 for domain codes and descriptions. 'Designation Type' supports PAD-US queries and the categorical assignment of conservation measures (i.e., 'GAP Status Code', 'IUCN Category') and 'Public Access' in the absence of other information (See the PAD-US Standards Manual 'GAP Status Code Assignment' reference document). See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Des_Tp U.S. Geological Survey Loc_Ds The unit's land management description or designation as provided by the data source. 'Local Designation Type' is not standardized and complements the standardized PAD-US 'Designation Type' field as more detail may be available. Null values indicate designation related information was not available in source files and categorical assignments to 'Designation Type' apply. See the PAD-US Data Manual, Table 9, for a crosswalk of 'Designation Type' (e.g. 'State Conservation Area') from source data where 'Local Designation Type' may include various, related designations referenced in source data (e.g. State Natural Area, State Ecological Reserve, State Nature Preserve, State Critical Habitat Area, State Wildlife Management Area, etc.). See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Loc_Ds U.S. Geological Survey Unit_Nm The name of the overall protected area following the PAD-US Standard (i.e., full name including the designation type in Proper Case without acronyms, unit identifiers, special characters, space or return errors), complementing 'Local Name'. As null values are not permitted in this standardized field, categorical assignments are sometimes made from the 'Manager Name' field and an auto-incremented number for each protected area when data gaps occur in source files. This field is in a state of transition as data-stewards move toward common standards. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Unit_Nm U.S. Geological Survey Loc_Nm The name of the protected area as provided by the data source. The 'Local Name' field is not standardized. This field may or may not include designations, different formats, spelling errors, unit or area identifiers unique to parcels; however, it links directly to source data files and may provide additional information not available in the 'Unit Name' field. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Loc_Nm U.S. Geological Survey State_Nm Location name of State or territory by United States Postal Service abbreviation. U.S. Census Bureau States and Equivalent data serve as the common standard to apply 'State Name' and to integrate State jurisdictional boundaries into the PAD-US. See domain codes and descriptions in the PAD-US Data Manual Table 16 or the 'State_Name' geodatabase lookup table for details. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . State_Nm U.S. Geological Survey Agg_Src 'Aggregator Source' describes the Aggregator (Organization) credited with data aggregation, version of PAD-US when the update (or data-steward review; if data did not change) occurred, feature class name (except when source data are mixed or split into multiple feature classes) the data reside in, reference to the original source data file, and a reference to describe the State location to manage boundary inconsistencies between agency datasets (from State data-steward submissions only). 'Aggregator Source' is attributed in the format 'Aggregator name_PADUSversion_featureclass_filename_filetype' (e.g. TNC_PADUS1_4_SecuredAreas2008.shp). State aggregations also include a reference to the State in the format 'organization name_PADUSversion_filename_filetype_StateUSPS'. Aggregators may not always be able to define the geodatabase feature class as data may be mixed. Organization acronyms are used and underscore replaces spaces and periods. A data aggregator submits data in the PAD-US format or is a nonprofit managing large regional or national datasets with required fields for PAD-US translation. USGS is identified as an aggregator when data translation is required. More information about Protected Areas Database of the United States (PAD-US) data-stewards and source data files are available at https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-data-stewards . See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Agg_Src U.S. Geological Survey GIS_Src The source of spatial data the aggregator obtained for each record. File names match original source data provided by managing agencies to increase update efficiency and data transparency. This field is in a state of transition to fully meet standards as the original 'GIS Source' is not always provided in aggregated datasets. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . GIS_Src U.S. Geological Survey Src_Date This represents the date (yyyy/mm/dd) GIS data was published or accessed (in the case of infrequently updated files) by the data aggregator. If month or day is unknown, the date is yyyy/00/00. The date an aggregated dataset was delivered to USGS may also be assigned to address data gaps when the original 'GIS Source Date' is not available. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Src_Date U.S. Geological Survey GIS_Acres Acres calculated for each polygon converted from the Shape_Area field using field calculator "!shape.area@acres!" rounded to the nearest whole number. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . GIS_Acres U.S. Geological Survey GAP_Sts The 'GAP Status Code' is a measure of management intent to conserve biodiversity defined as: 'GAP Status Code 1': An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a natural state within which disturbance events (of natural type, frequency, intensity, and legacy) are permitted to proceed without interference or are mimicked through management. 'GAP Status Code 2': An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a primarily natural state, but which may receive uses or management practices that degrade the quality of existing natural communities, including suppression of natural disturbance. 'GAP Status Code 3': An area having permanent protection from conversion of natural land cover for most of the area, but subject to extractive uses of either a broad, low-intensity type (e.g., logging, Off Highway Vehicle recreation) or localized intense type (e.g., mining). It also confers protection to Federally listed endangered and threatened species throughout the area. 'GAP Status Code 4': There are no known public or private institutional mandates or legally recognized easements or deed restrictions held by the managing entity to prevent conversion of natural habitat types to anthropogenic habitat types. The area generally allows conversion to unnatural land cover throughout or management intent is unknown. See the PAD-US Standards Manual GAP Status Code Assignment reference document for a summary of assumptions, criteria, and methods or the geodatabase 'GAP_Status' lookup table for short descriptions. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . GAP_Sts U.S. Geological Survey GAPCdSrc An acronym to describe the GAP Code Source or organization(s) that applied 'GAP Status Code' to a unit boundary. This field also describes the methods used for assigning GAP Status as follows: 'GAP - Default' is assigned when GAP's categorical assignment of status has been applied, without more detailed review or inquiry. 'GAP' is assigned when standard methods (includes management plan review or land manager interview to assign GAP Status to a protected area) apply. 'GAP - Other Organization' (e.g. 'GAP - NPS') applies when the measure is assigned in partnership with GAP, including review. 'Other Organization' is assigned when another organization applied GAP Status according to their methods (e.g. The Nature Conservancy). See GAP Status Code Assignment section of the PAD-US Data Manual for more information. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . GAPCdSrc U.S. Geological Survey GAPCdDt The most current Year (yyyy) the 'GAP Status Code' was assigned to the polygon. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . GAPCdDt U.S. Geological Survey IUCN_Cat International Union for the Conservation of Nature (IUCN) management categories assigned to protected areas for inclusion in the United Nations Environment World Conservation Monitoring Center (UNEP-WCMC) World Database for Protected Areas (WDPA), the North America Intergovernmental Committee on Cooperation for Wilderness and Protected Areas Conservation (NAWPA) Protected Area Database, and the Commission for Environmental Cooperation (CEC) North American Terrestrial Protected Areas Database. IUCN defines a protected area as, "A clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values" (includes GAP Status Code 1 and 2 only). Management categories are not hierarchical and follows as: 'IUCN Category Ia': Strict Nature Reserves are strictly protected areas set aside to protect biodiversity and possibly geological or geomorphological features, where human visitation, use and impacts are strictly controlled and limited to ensure preservation of the conservation values. Such protected areas can serve as indispensable reference areas for scientific research and monitoring. 'IUCN Category Ib': Wilderness Areas protected areas are usually large unmodified or slightly modified areas, retaining their natural character and influence, without permanent or significant human habitation, which are protected and managed to preserve their natural condition. 'IUCN Category II': National Park protected areas are large natural or near natural areas set aside to protect large-scale ecological processes, along with the complement of species and ecosystems characteristic of the area, which also provide a foundation for environmentally and culturally compatible spiritual, scientific, educational, recreational and visitor opportunities. 'IUCN Category III': Natural Monument or Feature protected areas are set aside to protect a specific natural monument, which can be a landform, sea mount, submarine caverns, geological features such as caves, or even a living feature such as an ancient grove. They are generally quite small protected areas and often have high visitor value. 'IUCN Category IV': Habitat and (or) species management protected areas aim to protect particular species or habitats and management reflects this priority. Many Category IV protected areas will need regular, active interventions to address the requirements of particular species or to maintain habitats, but this is not a requirement of this category. 'IUCN Category V': Protected landscape and (or) seascape protected areas occur where the interaction of people and nature over time has produced an area of distinct character with significant ecological, biological, cultural, and scenic value. 'IUCN Category VI': Protected area with sustainable use (community based, non-industrial) of natural resources are generally large, with much of the area in a more-or-less natural condition and whereas a proportion is under sustainable natural resource management and where such exploitation is seen as one of the main aims of the area. 'Other Conservation Areas' are not recognized by IUCN at this time; however, they will be evaluated to determine if they meet the definition of Other Effective Area Based Conservation Measures (OECMs) for inclusion in the WDPA following recently released guidance. These areas (GAP Status Code 3 areas only) are attributed in the 'IUCN Category' Domain along with 'Unassigned' areas (GAP Status Code 4). In addition, a few areas are included as 'Not Reported', these areas meet the definition of IUCN protection (i.e., GAP Status Code 1 or 2) but 'IUCN Category' has not yet been assigned and categorical assignment is not appropriate. See the PAD-US Data Manual, Table 12, for a crosswalk from Designation Type, GAP Status Code, and size to IUCN Category. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . IUCN_Cat U.S. Geological Survey IUCNCtSrc An acronym to describe the organization(s) that applied 'IUCN Category' to the polygon. This field also describes the methods used for assigning 'IUCN Category' as follows: 'GAP - Default' is assigned when GAP's categorical assignment of status has been applied, without additional review. 'GAP - Other Organization' (e.g. 'GAP - NPS') applies when the measure is assigned in partnership with GAP, including review. 'Other Organization' applies when the IUCN Category is assigned by another organization according to their methods (e.g. NOAA). See the PAD-US Data Manual for more information. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . IUCNCtSrc U.S. Geological Survey IUCNCtDt The most current Year (yyyy) the 'IUCN Category' was assigned to the polygon. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual IUCNCtDt U.S. Geological Survey Pub_Access Level of 'Public Access' permitted, described as: 'Open' requires no special requirements for public access to the property (may include regular hours of availability); 'Restricted' requires a special permit from the owner for access, a registration permit on public land (e.g. self-permitting Wild and Scenic River, backcountry Wilderness registration) or has highly variable times when open to use (e.g. seasonal Wildlife Refuge closure); 'Closed' occurs where no public access is allowed (e.g. land bank property, special ecological study areas, military bases, many easements, etc.). 'Unknown' is assigned where information is not currently available. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Pub_Access U.S. Geological Survey Access_Src An acronym to describe the organization(s) that applied 'Public Access' to the polygon. This field also describes the methods used for assigning 'Public Access' as follows: 'GAP - Default' is assigned when GAP's categorical assignment of status has been applied, without additional review. 'GAP - Other Organization' (e.g. 'GAP - NPS') applies when the measure is assigned in partnership with GAP, including review. 'Other Organization' applies when Public Access is assigned by another organization according to their methods (e.g. NOAA). See the PAD-US Standards Manual for more information. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Access_Dt U.S. Geological Survey Access_Dt The most current Year (yyyy) the 'Public Access' classification was assigned to the polygon. See the PAD-US Standards Manual for more information. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Access_Dt U.S. Geological Survey Date_Est The Year (yyyy) the protected area was designated, decreed or otherwise established. The date is assigned to each unit by name and the current designation type represented in the PAD-US, without event status tracking. This field is not fully attributed and data gaps are difficult to address. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Date_Est U.S. Geological Survey Source_PAID The 'Source Protected Area Identifier' (Source PAID) includes the persistent identifier (e.g. numbers, letters, or combinations of each) associated with each protected area, when available in source data. The intention is to maintain a reliable connection to join authoritative source data to previous PAD-US versions (to transfer attributes not available in source data) and support links to other data. This field is not fully attributed and significant work remains to ensure persistent identifiers are provided by data-stewards. Several Federal data-stewards provide 'Source PAID' for PAD-US and the FLWG plans to continue work to ensure this field is operational for the Federal estate in the PAD-US format. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Source_PAID U.S. Geological Survey WDPA_Cd The 'World Database for Protected Areas (WDPA) Site Code' is assigned by the UNEP- World Conservation Monitoring Centre (UNEP-WCMC) to all areas submitted to the WDPA. USGS maintains these codes, assigned to overall protected areas by 'Unit Name' (includes 'Designation Type'), between PAD-US updates. Areas identified as 'GAP Status Code' 1 or 2 meet the definition of protection by the International Union for the Conservation of Nature (IUCN) as primarily managed for biodiversity protection and are submitted to WCMC for the WDPA. Other areas will not have a 'WDPA Code'. A derivative PAD-US product, with all 'WDPA Codes', is sent to WCMC for the WDPA following each PAD-US update. This field is incomplete in PAD-US 4.1 and has not been reviewed by the PAD-US Team, pending additional code assignments for new protected areas by WCMC following PAD-US 4.1 publication and development of the WDPA 4.1 Submission. The PAD-US WDPA 3.0 Submission is available for download ( https://doi.org/10.5066/P9PSRGH4 ) and display via Protected Planet (https://www.protectedplanet.net/country/USA). It is important to note statistics published by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas (MPA) Center and the USGS differ from statistics published by the UNEP-WCMC as methods to remove overlapping designations differ slightly and U.S. Territories are reported separately by the UNEP-WCMC. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . WDPA_Cd U.S. Geological Survey EHoldTyp 'Easement Holder Type' is the general description (e.g., 'Federal', 'Tribal', 'State', 'Private') of the easement holder, following the PAD-US 'Agency Type' domain codes and descriptions. This is a core attribute in the National Conservation Easement Database (NCED) that was transferred to the PAD-US Easement feature class. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . EHoldTyp U.S. Geological Survey EsmtHldr 'Easement Holder' is the name of the organization managing or holding the easement standardized by NCED to Proper Case with all acronyms spelled out (e.g., The Nature Conservancy [TNC]). This is a core attribute in the National Conservation Easement Database (NCED) provided by the easement holder or data provider that was transferred to the PAD-US Easement feature class. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . EsmtHldr U.S. Geological Survey Comments Comments from either the original data source, aggregator, or the PAD-US Team. See Online PAD-US Data Manual available at https://www.usgs.gov/programs/gap-analysis-project/pad-us-data-manual . Comments U.S. Geological Survey Shape_Length Length of feature in internal units. ESRI Positive real numbers that are automatically generated. Shape_Area Area of feature in internal units squared. ESRI Positive real numbers that are automatically generated. iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzsvW1zI8mNNYqsF5KSunvaYzvWd18i7rf9/7/nfvJG7D6x9tie 6emWSNbbjXMAZKGSRVFqSd3SPM4eDim+VGVlZSKBgwOg+f9+nSb5Z/vqVlX6jFEcx9OhnKokIqNM YZhTSnzUkmQaj7KTSW7SJLtqkBZfr0T6lKRPk2z2X6Sua5nqjRynJLfDJLeDyHFqZKwaOewHaZpG 6jpJnSqeZ5JBkvWlqioZpeL52B+eW/sxoi+D92qUKYmMSZ+91WPzorMjjeiTyGD96aZJjuMgwzTK OI7SykYGmTCQ/B6GUa8syZj09zqm8yOPfbgdcfwXr3l/zrfRBmN5rND/r7/0kwN43+M1PHX0h9Dn ahqlsvtfp8S5m+plNyq7tjTdf4E+Bmk65rnl89ofaG2cTM/QXnY2/l/SuIjOiH2VG7iBKtn09qkA 62WSbZWkkgnf8KPlRQnRk9odpeKYahlGLNJJpjRJmlQIVcMeYkVkamUy4YSz4DWEVT9iReOAtsD1 FH4qCkdt+cU3bTYs4nIDC6bFhEd/cQ0jFkUlYyUyjbiuWWhhrWEseBxbiL7Y8R3+befBCHuLt2p4 aD9NWJavn6tFIfXcx50mG6v8nm1axTldWGHneMjl6fimewXWgw70iPZPgfXEdt/ExU2b/DmpSMBt nCBsRl0qbZukxe6HJUVhJDJMk4zQlKAx1a10U5JurGQ/THIckgzjROGD9q6x2ZhG6XlSzJGGAgsn HPmh9xXCcDq7UnTto2/yzZsLl7ZKksZaKqmoWVVDlQV/1sTCBuHje6JdheOeakhBeK1oxcuOzb8v hWF53K+67kJYvYTgqtjHSWqaA5NuTZiPxTjyusJnaP3YLwRS+Yw75a/z+zoJX+Ra/imwntjyDQ/C IO8uaLUKApqMnBCT1Jg0plnsEiYQbvG4OI4eaZLDWEs3TLIfRwqrjhqTSF3jV6N8vGllTJX0UyWH PslhTHK0XRXfrOtoEmBV6/Fd5YfpudhdreW/X2jn9+ayMZ9uEmkqCCY1mV0jHPI1wPQW07hm1azU rrhm8H3XhorP/DWO4+1EmPtmc0ZYPUc7J6zy6ycKxMquVzUhbkfUavV91eb9e2llLtRZ+PAIJ5uD Ww76er4XL9X+KbCe2HySr012tNYWFhWqcZAqDdIkvF/TZNtQsxpMn5hkmAZqVpgkmDiHfpJunOQw CJ+hOUELaZskdSWyqxK1sb2M0pmWUk01NbApSARocDAYkwk8/K39bma8QubzfqsGnIr9cNNCZarU 0fwygxXXNJgQomKEzcCOU2pXLpggkFSrte8Vr2sbH96/dHo/YbDHFocGX3moSXmuZcyIHTt9/dSW wthQw68wbFN4TwfAdSMXXHlc84awFFZZgLuqX5zzpdo/BdYTWwnmLrQrn5CjThZMjgYGWzXJrgbo OUkzDZKoUekX/WgVphXtyCQjsBus4qqWpkmyqZPs6kHaapTucJARGA/BHVUnuCumjS7IvtPjEfea pE6D1JCgptkF3cZEmk6JbyWzBlvywKxMD7De+Nj6OzAS7X21bE5Ad2+K/9nvo/m3BpzbgnQzMWvK 1KzcRpp/M2tauujHJy5P3zi8xfnD4z/5RkxZ7FY15uNE4D06gjgPAMTbswPz3MiqU80pPq9171md EkX7p8B6hlZqVwvB1Zt2Uw0UVNsKoDImBwTHZDssBBUeWLzzjg4NTPEG+vP4HiZVm+A9G2Qz9tL5 AgcAPyUKxE4GaUcgWg01uJrCCX0gukXNTBf/IFMHUQkPXCVD0h4M2IaT7r0vDcUv8ZB5BXAM+cp0 GLfvkopZaFfn+uYOC/OX3vMtjPHSC+gOFBdI2T9xYhY+P6hcCqtnOeZkWlZtUCdt5DHjV+q0wBwJ JqMJK1p7waucWxirqI2vWhnPbB/+U2C9kLDKNIKu48pq20q2dS1bCqteEiTZCEgcwkL1Kz6obgN4 1mMAFNbJZdgWTEbYlyM0q4M09TUxrAZetTFJ3/fSjJP0YydpGmgyAmdo0igNhEKa9BmdqyrZHzpd 2BCKVUOtpXIxYabpS7aFh8mFy6he04WToBqzqWuKgI7vpfUw3X/PgCW6MNK3lwdc8wzq6+cC+dZx s+dsqTKt23trF+MmuJ/T74GD8tGTeNa58I1ZURcFFm4MOD5f9ge5vt5Srbw7jLLdVnI8+uIM7lDH SCB9HVl+wy1hN2rUrU6w9zhIMx3kXSOy2yT5xy971W4qkaaujd9SUTCgXV0XNzR4ZTBwEBfaMKVs WlGLV61ri0ct8r4uvTQQOde0jxqbVZtqkneb2hY6VP6BfQKXaBhFengfR+hVvTTwH6ZJ2usk3dAL FDLe62onaaqhZqkHjcSw822YiVyrrencSwp+l9lwMHNdqxrdKxCWbrY58N/s5UTjjv4gk8NWnKkA s8B389ve69V0do1uNkWt/2ensJ55RxwOYzsSz1GjXs/9ELmDzSa/DtrlPBT3H6Qygau/89/Mz2M/ Kc6EocjcBtcqB9kEzCrjXUF5BK1k/sXaMLywV+axAgsX07Yi7dByQI5H0V282fAZDcRGmi/U2PUG YGzwcngqKvmdG7xoftOwyuokssFCq0aadB/e3wTvi+5kGZfA4hx0jJ7avnbX3UNYGQdLIIiqUdrU qg4FbY9KVK3QKzySoFJUyncirnThtMmZh+da45qjL0y1s/jXN9icL45b/vjrxleFi973IYPVSmcp ILB7z/9URWUq8LkMqgelgZo6AACz+dTD9x04LC8psIZhkMo8WsOg/CAIKAixvtf3vfkNwk3EboGd 57nV22/dsO/CM4X1Da1kU4+yS4naDDSUna1XBdVt+4fZht2b2mZ6Zmzjccf7MtYUWNBugFWhjwO8 lEm9ittpoFZYVxP5Xv04SA/vV90o7nFhPl9aZwuiPI9VLXEPedlW5XmpQoRgOsm5uqqd1nCOyT5e WNAq1FWbUsXYCCpmxl/SQHwsvpZJn7DGVgSea+rYYP0NhwGVnecm4EzFWVhL397aez6BdTzW8uXL F76mmthgle7kl19+kffv38vxeKS2hdCQ3XYrm82GV4vvI2zkLTfj3NGzVqee5hm8dDAkMDVH06BA +oQwTzE0Bne82byIsMoY2YVJtaf2hJ6C/qCaYD9O0iZoxJO0lMY6bUEx6PtBjiQ4YXI3rnudbSDB 3te6sCipgZt371tSJ+ZhOx2/dZ7WPLbn6CreYLarKVXzWOC5wkp2wyILjDMNm4f3cebxhfNelFgp 92TtfZiBlJsUbBr1QFouIQbjiryhdlGaQIM6HocssLgrySSfP3+Wv//977zxd3d3FFq7zVbaphHI KEjwrnvbwgpNbyec/YNsAFjzhmuDmQOMyxs0FaxEgMNTgn8KGNUz9eMrtSy16lRYkTdErEZVxpo4 mc5mYo7YeaFBT32e5Dl25ly75Hef+oxX6cjNu/hLhLiUbW2kFuNnmE3E0ONrRBXc1+CZ5bX5MGnY o1SDaufEje5rUSgWgmr2lF6+vsm1xuzA0OZUBVLsjPIC6AK6NjWzRViNvPp2UaJsNg1NwbZt5fr6 WuqmkWPfZVMQ75EAudnIpmn5zI9oDr5OtfIxrRlBRwDuM8qGQghBuZX0lfGwRxVJwIIQ50eToNJY v+e49FI4lYLr0jm2CSatet1GE67wUrbkZfVSN2ouwsu4hQBGwDVMSMqiQboL8koh6/NtGjoTmoiH xKRoaUZBswj47ou1h86/c17A5kJwtHopMZZzrGbGb/H7Cxeo4VRBW86v1Zy8tDmlGBBezI3gu6Bq 26TahJVRGAKPrDzNa123D9Cw8P8kV1dX8v498gqIfPosst1uKaygdb179464FtRfXDex+GGdSPnW Wis9uVMbA9lBKYBh3EOxrhupJjUJie1ht4WkHjT0hdd/aYd9YS1rN0LDgWcwEXMnixyOA5pDtVQt vFtwf4psG1wn+fDSdxDMnfxceOnKBrrEfQ3jpoRULE4w+XvyvBCkDfmJQOeXbJ61YvFeOOclWsRF T7ddPjcrzHmVDhQAD7Ev4uHXcKyHDE9yoRU1rCCs8Fo1KyOJZm/o8hyL0KZX2h5Aa1jeuNvbTv76 17/Kbrej0Pr111+JY3348EF3ld68iKki9+itewmb1EmbGtkY4a6nC9sA1qqW61YxKtensBThLr43 hcMT22M2gZYGvAksCqnE0J5N5TusseuTYhvYeIBlVQDlqT3ej8FdYD3IFQQgwHzTPoH5QHBB28P7 GNtv3Za4VLqfp3XpYE4rWBBeLcQI43vBaXHe4l7XfM63de0KmxG8gTmkJgsrZbpjDutv5E20y6C7 hQfAFPz85Shd18kP7z9QKB33B1Uv6RgbNb2JBe6Olar937sdB+dJ4abVBvZ6hLnIwQFgaOB8jPZQ SfvDdWP8HdxkaFU1vYRUpoc98Z7YFkvhASr917QFT2eFHzDzAcFiWqdVEMUiTqVsesdAuuFg5sgk 7SbJH9NexqmWw1jJEbGMk+J4V41IC40sKe8LQi7u8DreYN931KZG5PcSkcM0yR2zTkAgTtKnDwvQ m6aKulz1Oo7d6jg6p6oiRcMzOah0GKED29fbUT8/1+Y4ymIA/TwXBI7PcXpaMSaFADysegHD/Qug 99pMgWDx30wr/Kw5Q0I8wExquwFW4S1cS46RXLm+b7ls1zTMOFbZKUG80APHHnBQSOmq2hDLiiQ8 CDDiV9iyi/YgHsoLt6pq8uLJfhLru2JQpnlw0oENbtkUzPNnkQt2QfoUPMVvvsVg32jCa5YCA2lh QjL2UZMU4j0QKsGYX5oh60KFeb0gvOi0qOQKdImUZMtEhLox0HIjXoRNj8yQrMWeekbnZFfA5/RN fsOe0NHXYdes71dpncKQviKcKcmbbpcMEcfa9DVI0hdaD/snuoEZ6jGP0nbbZBsa6i93vSwgvn9r amhI+lo9ZVPOZonXMElw05FFYUNS6EhzCV5BLDBa/7Ywn8KHeq3tXEqV+Rlgrfr3Whi+wOmmkYHX FGDDadK2KATBAaO2ZB4rEpElybaCJ1XktrtjoBsxLamkBw+fZFc1v6t6c+oRiwHNnsAvUycc9n4d bc0jGkH9xbWsanvxWOnkNTDHe9vrkNtnW5ml92RdZYeC/vlgAGEe4OV7TaM4FSkPC3PgdWhY3qBZ O9cIdj0wlGHo5N1Gd34QJ5GbqqkGe1ZN6whvXwjn8JYzLb7yCXGpYTzOJWizL6iwIYM0maBn0uWF ORU3KTcR+TqQ5fF9N5lUcYVJh9idkUD8kLhNyH4apRuQCmeSwQRWuRPPgkAZ294XOhX4Ql9fglBf GmB2L+E5rlc3XdhEFnGL2uLm4Gl4fgttPfgbyoWmUMJgXBRYSGeyZl96xHrfq7biJ2SIThW0re8s skbXrCzDJwig0KaSBQdftztNqke37ygbLkZ9qDBqTzSHl8KmXkMrhRbJsOT1OFcLHlIILccB17Xp +b3wuTsjPExkSnJVkyjCdMigPSAsHI5HJB5EqMthBb9ZbhgIglTiJvC4BfgchMT3ak5MjR64BQ0s SP35Gs87BVKhza5icKE9c0r1Z2/rc2d+jUSV0IXGYVBn3qUDll6O0gXKUAtTS90T4S5WMt2BRH7H pumG4bYH9wgqtCEd2L3TJNcNRZomLgOQbv2nOcIUG3NOzPma5xzsb32DW9WqQkMueeUZqeOBGpbl v50gJIJ3zNu54F1N/6wbR07Tawg7oAZyswxQhJkOL2I9wqdo/4oNA48Rn/N9QO6WF4zP8IzeG718 0tf7xucpbclHXJ4POKD24wQqVU31nmOKceXua2Xw+GtrJZVidnAZD65V7Zk5unK2tnvagDD/e26e Ylrz365ZOZb1vVufOhNEIIAi8R1SvCA9HjJSTbKFSZIHTIF55YLX0jN31YxflSmQ43u/NYHl1wUz jaldnK7BBQVtqJJUtdIw79a6F4uPMDzU1mz9wGuIhnhU/m1xp7hX2FjwALdpMw73eiGno248fCC0 KGlxD2dwWwbz79eCoyYy13PyvNpSMMdQoOwAKc3gtNSu8PkFYuslDex7tyicyvtMp95+o5EY4BQ2 9UNMwmqBIcSJqc/r2IWahiT6fNcGM4PCKo1SV7Vs6yTXTqBjlk4sOCVLsswVn8lVpkBDorzTve+3 0y5qEFWjwXG4t9R6TAUCnQEaVrJA7yKnfV5YkZ9kxThoJyEagJCCb7EKNOrv9DN4EttaJzDu43Ju 2XnqJAO0M4RBjRWzTbAPHrT+CpMRlDyveXZZlofHzLTqwv175TzIRdofkx9RaH053smmrmS3qWX7 EIHl6Y4WbJEF5z+OrifdsfYtJktjZiv7oCQ5T1yJrqdPSa7bWj5uKnmPtMJARUaRrmqk326lmeZo vwzYKvLFwbEleEYLebrJEDVR3CgGmFtGDE/b4zcRLWsWdoPxff+uv+/H8OOfA9Xx7M6Sc20j+0Dr QWiH5uwiw3/oLcfVHGSr51SnhhcvWIyd3xgj2KSTdBBLmoU3/N4D6eOY9/Z7jOCm6klzvQ7xeH8e t+uanz1+mPan3DF75qM7UPAhkwUcMHtEAVRwDmjK06tRy2Wwz7Y/K3VGH0uD7ARPUaGa++bXNn9+ pMWijP0RyRxZU1AxPsr9FyY7XuJJrbHjHRpCqwetBIX/aVJIS21taxS1Nquhl3o8yA5RJQ0iZjSj B475f369lY1Usu03cp3at59xNKvT/GvWBunTQrKEOklTY0eGMFOMitxuE3CvxUvHpH9B6PiCAdDo n7swQvNFxSKrqHFo3/PHGq/KW2ni/pbbNTWQU76YjwfMjDhG0dvJZ/DPEFvJtDFJWqqZSEY4ydgn GXJZorBxR7n0DEOseaw81/rrDFIuzVd3LnTQmkOBEQ32duhIMWIG3ZPrVzMMDtANs95Ok/w/v7tS KkyloX9vX2C5zMkg5Ly9YZLuGqQmRpUan4h4H6o3HOiv4/JLDSCqx/6eC6yoefjigrAqv6uA9ExZ KIWTf/+31Nb4cu+b8toVG/KvIGW1vufSRbNs2FepYbDKDLNwYOfXBVgNwMzA1L8+MTg8R9VzeCix SCdTNxJzqGuydev2i7dyT7tE8oz0EzwPWVv1L2ktSGjgvC+grzCrbiXbZqTXGOR8piEagTGb1TD2 LAr8OlbsExoKkk7BDOWCHnulL0yj7NpWNmBW0+ONdMG6FSoY6TPr+zVoSOyJ2e2lUHINKvLcfGF6 xtfy/WjmxUW8xB6X5uJvpZWa5HVVYq5LWkrlXrbopQrHAygOzR1OAGBr+DshrAgE1zTK0b+3pE5l BvpzyBSIJ0MOBUUkLsFWz93uE1KnNI0lkJ5adSo4RqmUIaQ2skHrJ2lrYRUpCC1k8tUybpoifN+1 1LRQmxNhXW9eYGmdFy204DmfYO+zKk01yq5qybHKvCKmWbHB/JZZ5M60aOq5AIkYSgQio9mI77tm BWwHD3/fv/savLTfs+H6UUatFFgRW9OUlHM71URRC1LTBWk9P+VetOAHTSJ7S6WUf5bLp9mJnrgj MqjecCs00Evc+/ot5Bau/9KmVgqtuOkS82StB98cBuKM4HfC9EMufA3GV6I2fnPsoU3pvL+t3nGF w/sLtPnNCywGXmeOj7Knkcq4qSfZVRNzWFUA8awOWwyF4G+/s4JRmn4lgO5CLOfNL4RQBOi9+e/x jFhP/959ptNvpZ27phOh5d8v1JXy96BIeG43fj4B3LeU01OSa3hJKwXEyf0idQF5fNw58rTribGC yeQf9S3nrH2De3iOV3fpN/wdjACDaWpsrkzVpOXugC/3KD0H+hDT0Y7S9Vo0+AhHx9jIwNSoLDfA 9vYFFrcanRiuijIJXZVki+rIY0/swTOlMveT7YKYDM9TIuLrW3ThRuwJ2hMe+AwB5x50fjgcqEW5 QML7yPZ6e3ur4GT4LoRVFIaxRc/kb6WtORjgRItzY5HRwJj6546DxmxeLFSrZGOFE5BeWoGwm3Tk dzCPOs4qhBhpRcfnGtnMZ0sRJ/s21sGljW7p2CkJoJMc72DiYT0ClkmyQx0B/A3TEJZQBfNQN+Jh TAxVurPsID1Q5l6zdSBdlWb8fePN3Z+cmHjDQkagbm6aStJRS8CnkQq9EfOs+N4raCWuwpt8PDLt NIQTXiNBIhIoQrggVTXeQ4YMvIecZJ8+fWJeMjR8F4kVXWDh73KinSOL/hZb5DWtLfElrWAGnvIY IUibsWxwYJjQcnwxJblKPbUqhhAhHhIpiCDgnmloozBI/p5Hjb3yhjm33++JTaUNYAt4+5QUTOfF iFAb4FazJorEmBBUxwo1KBvZdLfSVDXX8oN4WK+99XXLu0nolLFuHU1CVq4ZkhXM0A8hsiKxRH/z fW+9m3luGgKLguYEIfTnP/+ZiRH/8pe/UGu6ubnJOfShfeG9//zP/+RxfvrpJ36OY/zP//wPhRa0 Lq16VMkPP/wgf/rTn/gd197cdHxqWwO1/TnicGtM9UsaXrmbo8Xf+HVE50TEAqnz4LWZzFhAeLg2 ioZklB4Uj/d8fLApoMgIzW71Ly9Kt4Otv+NmiWSVytNqxlHuhjvpWP6glsOXXnZXV1JtWzmOA2tA ok8tTHxgr6C5oe5lM+ddx5zEcbAZM9Lgwrg8pTFAHIkALNzKExdgCWGYW3AWx05GM32RF6+uW5lG zFmRHpl4MY8Q6saEjwCrRLrhKMfuIL/fVbJpGrluO7lqK9W0MubVqIBKtRynRm475EobGLFAbaoa 5Y9XuOdW6OUhwc9vtTlT+rU3X9QOrDtgDoHz448/Zk9gxLrigoVmBQHmKji0Kmhm+A7eRzbYkhaB 5gD+JeLoS+Ifz8EDc+rGOcHWdSpw/HOMp5vUGAMXWj4+3s/s+DgTgpWPh3tGVElxUlQjQrgMCpQi fOlw2MsEzyJB5VEm48tpvcokmxqxFKMWurVCrFTkvknGe6GwQn+1ArmPqV1jbbGOKTHh4tgP0qEM XAWMeKeRLAd4To1ozXRNik2NmFtNKx+utur8QAiSAJ/yUCudi3fdkXn+O/ybYBZq3cSmqaVF4oVp Od5vXmBVoWyUzykS7N6Czlw01xCgZcGUw98w+bDIcNPxGjcOJqFjW3jP01W7BgYhhmcILggsP6b/ 3s/1rfCrklbxnKD/wiMVsaeA3bl2F72sxEXMsxr5aq6hZQFm6V1K5n3WKrHwDAiHeIMHDCRHpqQe RY5pkKtqYnZWvAdtjP3STtKTDdEF7Qut43XAFoBJ9PK5TgYrT88AEfN2zsQO40TxXy2HrpPj0TDg bcvkmM1Us3YlsLtq7EhPQDXsBhEabSW7dmM1EJJqmFOttS+tfuN+D0GpabqJ/NWivEnmpWMa2cV9 ffMCC80pf7gurQiij++d2uaxGkL0DEK4uAbgLHZfYHjP/4ZGheePHz9ScPnnfhxoahBwaB7acs5j 9hY1LD9OjA6I49g2c4pkXL8WBFbqR9S6fGx9rLP2SXzllB+Xr4lpml0Yq+lYQ5sYE8mON8gIgkUI s4+mklETLK34WMGFj9OoIwiVINX5jzAtQARPq2t5qSGVOQvGDFpcFXgS8N/OHD/jhLGpZNOCZt0y 5fWRmx0010bSVuNDQaRF5SDgfBByqMrESj0o8zaqhoYq5HBMwAQETQHB9H2joVOuWYIYy+y/qANa UCo45+WtN4uv8kRxetFzdsvXHn1SmmkladR3/EgU9cXm7+Fv4C1OYfDPILjcq+galWsYvngj+fQt tkjniNgVmntb3czO2BNNxY7fh+MCAj2OB46J8aTACgH/qwKWxzVtDGYe5iEymNg5huOdTF0jE1J/ IETMCcBWGh0B+UwdjcB8CMwKizvJvh8sh9vLCqwEeYVSbF0vbVPLrmnZ/2nspOv3rJxUN1dy1Wzl qoZpV8uX4yBHKx+H/mrGXhSe6YgTD1UjE6slTTIOnfRDJcd+kv3UyLFWkxnCiiK+ak0D1gy/Va3Y FeMlg1f3N2MSejOBnjUrf5TEwNfYonZQmjOxcnYZZuPaFBbGbruTrlcaAxYbBBV+6xjVmpfwpfGr c+d9TqZ9GbI052azDaugdTjh1nEsNIwfxhG/daHv30UpNG/lbo8GXAcYFfHDoZfW6v4Bxj6O+xzQ TnwSC9iD2HMqGRQ8QYm4SZq6lV2FwiiwzXp60Z6rEO+5hiSWWCUI595OIlesXYgO9tT+IICgLYHT CLMQ2FOPDBmexro7UlkgfQhaFzcQxFpq0RcWHxkm0hXw4PUzNrNjjrreygHiN3BEkI5UV9JWSAfF UrSL/r55gZWLxthc8svLAuCVq1hxwa3RDrCASlAZzX/jZqELKTRoCHiN38C0dA9axKywiBzbeukW BYlf13PhZ9FhEc9VeiyjxuWeU9dA4U31v/EaY4nXcFpsdtuT88WHC30XTEw+WE0E4w+ooG3aPwmo VhlekxcwIlHzgpHxPEoDc7RB/BxMNeCWxxcXWEO/Z4GRa5SsQ0Fk9Bm4XD1JfVXLdtwwJRNoCCM9 A0j/ibxmev3vmLpJU0k1UyVXAq5VKw0ViImFeAc8IAUnjz4AzQj1Ow80h31ckZ++rRtpG80AnJBJ JfDkfhsm4UrTSfrdU7c9qJWYShRWnlomUh+8RRd+zPjAm1prqA4E1efPnxehPpEx/y1A95fWsPw4 kTaxeD8IFDSaacNAgYSxAK8NgsnNb6eCQNDj/Ri4l7HRMJ6OeVEYwoSD9kBmNkyjkVoIwGbEvDIs zO5n47ULgVmhAnePvPajAHFDkl649b9FSZxxOErbbOV608oVM04fOGabTZIN4nCnlniSdL30RzyY iV87WVfyY91Kjfk04LoamrUbVOzFcA8iX9JBOtbp1fI3JIBWvQm0JJ0rGhW8gqBAYG5iHK1uYjEE r15ggQPCfN0hxN7dr8zUgMjmQaTtDnKdOnnXaJ5w2NqYP1U955MqFzz5NaZ9oJX4h0+uNZd2pCPc 1y6IXsk6AAAgAElEQVQtSBc2EYuJn93HSPe+Y3FBU/BjHDslluIzAPFRQEQs7Dk5WGvHcxzNcaQy kNuv7b7xx+8jQA6B404EfAbsBw+YZsfDEW/KzrylTu8A78rP77+HFxYcNzglfv755zxWjgWiz8C3 bj9/IYfNj4PPm0adGtAY0Adw5pyK0iDhIQJ6pZFd2sqvCXUemWdF6xZicXMc1DTVVKsifQtmN1gC vaTeKBf1Vv5Qd3LsevnSozCH5nEbwYNS951c96pV8xwMGfKwIF0uPms8mSHMzA2rmSN9ucjH6srS Xx/kgJTUDWobaCUp5MLrLecZHy3SvwyyhciqjsStcBDwHuFoQIdgYP4DdIVplEOa5Hb8IAMSFIwH aca9XEkn120l2x0oozdykxqOaz/cyS5tWAAGggyq6DCCX5felsDKwiq+5xQGcw8SA7B0xhxoB6TN G7N+3POlqX5Lbe26npNW8NRW4nZlP6O5Fz/P2mSB0+E1BJJrrhAwaBlHMrMQwgwLBQIHgipy0igI myZrT96XGMtZ9rf0TkYKhb9GDq1ZI57z2cdWzj+v6IT4O6EjCZqbfocVyEMZNPbDs5aGvFP2AT2B MMU0U7zV3jTaAjrEXzKMbT4aTL242fummNfO2PFIEIgouLtHwPKAB0B22IDI+4/EmSJbaGxgu8P5 wPROWm2EWj/8o0gtgzEjY1YtgZMc+PLK21qwL5p7BCGJSVgDYMcCnapGwu2Km6V16k6bT0Q3jdbM ibckvKLwicLoUizh977GyM8q++omV+RRRU8gJrd7/DyMya8ra5vGWYsLDcLIcSo0p5DgGK6xOg4Y zXE3pyMeiO84zuiAvtMkvN9ZGwdIjdi4EX1fr+dYmsvtCG1SM0Y0Vc1NGGltYGqCMT5WoLhYnKGT LEPsJKwrx81QT4XUBRQkBVCOVOGQWEjpwpA2T7an6Zpj9tdoCcQxwJrjvQPpExoZaAsA2bE59Kj1 eUeqBMy9mybJboNUPej7ZNXiFa8anIaE/O2TVlJS0fvGNKyYqcO9CbrZmLdlrFnUE14MehfoYQFe gOh5pT3EBVDuiGta1ltq57SkcuKfA/W/9zWXizVSL9BcI/LvRE2HWlTXZxPOW0y5Ay3KKQu+6Pwz vAeB5manCx4XNvgsEk3jYnUvo7/vx/OAcx/bhWYHrx/oFL3IZqMYY2W57f37UTjz2EzHogTOHr7H pMVmOwjHSeTzpJUe53AXCV5I9APai60jYEhAUYyNDrDd+WMq8EywGlVUYyexYaijQsfCy/gpjwoW DbQrEkMRA8hwIvV6oojIVa2gPPKyXzUQlEjCpxIV2mPX6/gAv0GA+dQnXmeO1yygklcvsJaOPksA hknrOxBCAqyUOiK/k+cTJ9alUfN6nFldLz1XpdkUwdV/tpdtJb5WCtG1fPbxty4oXGjEz93x4GYh BJALELxGRID/zgWja14R4/Q+ZSEZ2PDAwjwY3Qm9LjAfshnEayuxVl7XCPxI3fs1jg3yKc4Nr+II jEghES27poLJ07xBWEWLypOqLjZrIGeWMMBLqeXityNKbEGQgBxEaifVN7zGe3h0HcJ1GmJWd0Mt RzDYmY9OGf8fNpqjneYezEALyYHZR1MUDgkA7NSssBlY7cqA374pgcXbaUa51g6EKmtCqxLZkb+S TM0cZcJkYpkneFnUlRo9bjxcIbjio/TUfW8N5FI7px2Wbv01k/E1XFu8F+e03RJH8t8Qc0KGhFC4 A/fYzUO851oSmmthEC6OWTmdwT2HrjG5p3DNGeLj58LQBWfUwPx70StLQB7Lvp5NQiz4eC9cy4rF Rjxmf4QZZ0HKNEGrUa4nYEhImwSBpSltGNpjQgf0CpYCM0I1VhTyrCO4GqRPAOgURsy0Wi0KRpB4 Ecz0UgvkmE4ttar9VMmdYWGuTYG/BYBdf2saNJjvpDVATtpGg++M8NpC6bAqzBi3pbx9GwKLypIJ LGQXhaoJyA5CC6rmFhcN+x4Dj93TB6RuyCJGOttyIUSVPT68xe9/C3Llc7Ry0l/Cqs5hW9+6RZwn 9ieC195Xz8rgWhI5VZNqTtGj63nEXHOKXkYIIXj/Ilgf8cyoQeF70RyNLXp2nYMVSavRbMybIbAc CEWkW0mnGSzWAP64ySYrqUexB4EmIh/hYQSZcwB9YpQeWJLC6dTGRhOMTHDJ1Dgq9Lxkm55StScV KPpZmkD6BKkV16UZfRnszNLxrgFqNgmmg+kRzgM8CqE9ItdNkncwuS2YGQRcZnwYEAKO61ZlBOlm IJkm8LmozfLIWpiigsb21gSW4W5Lb5/GPUECQ2gx0xVIZlAnAeRpiL3UTa2ekTPgZqllxfa9F/Jz tYhflQLtNXgK79OwosbrizhiW/zcsE0IDwgjN/cieO7pY1zQuSblIL1/5gLMvYOgKUQPZOwzmpui UVC5kIyaoB9fr8G1RMNurMVr9N9TYzRmJa22aWZ+A/tCu2mBA02yN3MOAhxhP2Df83uNgujUvCB4 JqwcqFujTI1njbDrol7lpiyzyC2usxwHjuEgsu9HueMDlAhUIsJn5uFDqlDH4xCGg7N7Gbq4sbqw piBT/W6tvbzA6g8y1Y2MDSSrxfr1ozRDRxPutr6yiz99oP1w+CmU+akY7wRvCSS55vK5ZUwTmhLa 1NbnyY6aMyrGjkWvT1ltJqYn9snti6HMt+S/udRKczOq+s8hMMoFvHb++357ySyMQiQe85wJHc/p 41Vyq9D8PuC+RNDaF3cpXPFeBNAXwHir2NWx7xRX+vA+fwdOF9e4PD7Qw29cW8NvIdQcvFeulWpg eN/7Gx0AzunCcV0A+nmi5xlkSjxmeo5rK/i7ZgEGCjUwyJnlAAscxMtJjvuDhr0EfG4yQUdoBGO6 P2oiQbDUN0luRqRw2dMUHLpRfkHdP/yD0OG5laeF/FMIr4GQQRrxTTryWSokemlkn2pBzfQWOFbC elNRAVIp76nd733fksVft7XstqqdfuI41nKTWnkvnzQ/HXrL3O6DJu+zLBEgrjo3l/NFR5eaIoaa JqLl2PJaoS/aeJMW+Mms8tL7Act3xWPnxusGHBkLZGY0uyVl81pnDCO4h0MVd9ZFn6yVsWdrzXdJ f33f+b5HO9eP59KeooBew5a+5nilNyyaclG4x3qLaDFBX6l5xcKz3mJO+2geRuG6MDEDM96PGa/b N67SMZMxNftO1EruG6s1KkccH5iPfvy0ssHkv41/CA0OXkAWzRhH+WCB2XpMjB0S5MGEFCWosiAs nFnYmMHTIiJm3CxkW1VYBp4/NQjtZKYgkcaBca0HYmiEZQ53cgCYXlXy4eNp8PZyLIpxmUyLzkVl 1WCdBvpIv43A8iEmj4wY1ERgDqDcTf+JXJBS5c8Tt7nOx8o+A6qNAO7Om3URRyh39tjcmxO1nXOa ytpkubRov5dQuwTGP5cwjGO3ZjataaMRRyy1rygYoiByrdfvp2taEe+J5pm3eNxS0LhAdCEYtXDv R8S/4nWU4VJxjsW++298EZZjem58yvOdG9ORZqI2rCtEdjBJDbUVxAaaMEYOKnj1ILCYMNAF4gdJ wyRH5FYfgDdBkkHrHKldIU0xKzWyEIemzWG+ejspgHKEGVGDhflJ0LyS1B+lZZTK9v555FWzV+hG 81yBkD1KPx5fXmAhVEDTb8w4FIhiIJztEFbBSeTxcsYJcRPHPBj5gjzVR7xAy1e0Nqmi6RU/80ec nGsL2z/P5185xpPH5wEm2df+fu36n9LWxqBc0GvfXxNWl8xq73ckfJZmb9SoIrN8TUD5azfv/buO d7kwjHGCaFHDWxvLeP3lcxwrzjPzlJWCM5rY5fiWi3c6gRI0gNrLf5EbZQQgvtcfSTJNlr5YmfK4 TlATJtZVHEhRQFwfYhmNIyVH9RKmnXkNIVpSNld9LbNuAoB5mI/MtFBLandSw5w7s3Eu5oMFN+uq 1jWvlDG7RlbZRh976abDt9GwUCDCusfEGxUEFAdjlKHa6EBj4sUbY4XXktn2enFrO90pmBwnTjmh SjU+4g1rC7tkNp+blN+znZvsaPcJlIe0hwi9ctzj99cWW/zMs6lGsmhJIvX3YmhMeU/LaywFA5qf J2piToWIAs1TzZQCcu2cUchF4epCMM45eN3K6/fzRw0tapWai3O+prHEKqNVwsXtFAVtDFxGzvYR JM8h04GAI0GQId+Vygz47jRxIPOdukRCIVo7mgstZGpQVjZAcPxC8+Ej8yjwOoTINaCOoPzZtL5+ Tu+Vmqv8DthImfCN31tO+ekbmIRRyPD6Wd5HQTuAbX21Udk6K1e5ocNIdzEfa352UzNO8lLLeogm dG4hxec44At+zDO0l9awyu88Vnjdv7tf7ks5hlGI4OHs8vK4palfmgxoZYyh/12C9uWG5MKkxLMc qHcQPab2Ka+5ND/XBGZcpOfmYbl5+vOsfS2x06nw8KpJ5UIMggPf8Zwto9TNjgn6IKBopBAtZ/oE 0hM2dW9FWVXYIUQGbzDlM45fKa4FbQwhMwkCH59a/M/1ZksrqTc8DBblYAoIArSZx/4eTzCEuFKR hrmIBTRmD10CZI+UN4DjUctQXriZJad2Ns1CTVivuwECTeedLN5gv2lI6g97WS9ayXNoXr05modx UNZMvKgtRJOvDLAtfxdd3qWZeIkN/y00sYdoP96X+wTOWoshLaWmVY53KSDjmPvf/tq1nQhyx9/E WMHoOYymaNQe/TtoJb/KX8e/Y8xfvFYngMb5US6y2BxLi9dQtiiw+Ps494Ylx6wUtKQirAjDdBbb CtoRlnkNL7kWmyDVh2sRmVF1PYloAj7/vepLFquL60PFHIbOGPMc5fLo+NJy8tvUSNWC84XqVRvy rlC5eUqNNGMl76rTQr7Lphnfxwlpf45a4ZH8L+WIVXJNWIj9/xZVc9hR3izjNGAuUWUlJ4GuWMQc QWX1kBrfNxiYaXFRxl/XGCayFhzDmkMg1gblnICKZkf5eZwMccGsHfvS4n9pgXVuIjzXedcW62M0 tnObRAmSl44R/8wFS6x04wLL2emlII0CNuJEsUJ23CDjb0vy6JpX0ZsfswyrKaGH+8bJY/Siuesb JD8jO15Wtdwp50IH3G4pe/I9U87WfkjSsygpsiZYOBvSMrMYrBqCOAZzCCKXFzEs40VNgG+OXJd4 1CibR5Fh9wzB3HslG1Rpq+sSVZuhZREHS/Ie2QjPzAkeA6Yeg7kZIcm4RQX9NXynGhGgDrY+ROk3 0LC2yJGTC51WxvLFhFQPw3HADSCypVkY3d4nSJmkQ4i5XqaJMovjtHfLXa1Uv0Ecpb3pNjFeu8PG 3LLe4qTxyeoYhfNy4oJb0zhKDcG5XjHcIk7+KAhj3y9pbrnPOXd9iKi3nZuAsvF4fMF7FR7P9+QZ CeI1nFu4fu2x2gy4cTlo2M6zv1O+FOLscB7klPrdjz/Kr58+yZfPn1nJBxyj7fsNf48kevgdqv7g WPv9Qdr3jXSHI4/5t3/8xLg/5K/6/e9/z+thXCBMlV4rBzMszftIfBR8vEo6BO8iFAWmnoXRMP8S sDPkKLeMrXgfY+O8PZ8XzUb/ztq/ET859+Dtputfw8Y2NTZPK00FWgFL1kNLxHjvaeYg7S+T/HWT HG4HqXc1Ae+cmpTTUq8H/ZsrVC/njffv6ko37AEluOw+0KTFuqPZ+4naEbN5Br5YmlrZtFvlqY29 HKc7mSrgWTp+mnMeutgXqaqNzgVoT0fUdBSG06AWo8h7Bkgfhk/M24UUM0j1vK23HKsOZbyCCc2x YyVt3CuYm2qhEioyK4rriKYhNDfLuTrq2n9xgYU8zhhyEHbRQdYEgV0c3Lx+Q76m3bf7l63EqErz Yc18WQPty+/Gz+MOG1vUGtZ+u3ZN57CyBQZ00GwD0TkQhXjUKqKG4td4ToMqd/J43nIs/bx+Hu8L FpAv7rvbWxVqTZPTuPzyyy+5TJmTe5FMD68hTPH4r//6L34Pi8zJnfHayjEuN4zb/V3u59rmEAXw 2hiWWhpa3HyOA/oTzDMtVuVleqWfeulB0mT2PAYDKlsdAo37J+iZEFaVUQZss7SMmxR6RZ/Pmbvl hogWtb/Y74c2KhOeh53ZHOAM8ESQk3Rypxs7sWbQKoBzaVl6UBxSUQJbxxCC1MaZr2cMTvtmyslK P19eYJmPQXkfmjbCQpqM0v408DoKiXLBrdn5a6/vA0UjX6gUWH5+f17DGko8xfvmoG/U6EpBUr4X /45CM/bPyZf+m7ny9aw14jsuTMqJv4Y3xXOXQjSScqM2hhZTt0DoQLOCcECGTrDJkY7YC706C901 BA9g/t///V/212sqRqETSaLluPhuvrZI/TN/OG7lnLwYAbEIkymwNLx/NK1meY650hGA5HEEcKxm GPvn5GeaUD7GjhzNWNS5gvSpmNdRQMf7iP56xle3FOK4PKQxT5Zpf4gHVEwN19bL1A9ymHRDUDY6 wuVQWQf8Lk0fA3N1OZ88CBogu3LC9DN3lLgJ7nSHZfsGXkJVnT3rgnbOjDrazMtdL//ugV64+zQs 3sxQpsm/Xx47utXL7/qEXdMy/PPYF//MdzQXDNF9HgWWJ5ErBVIUlFHbi+eNn5eOAU8mB4FVmp4Q Bq7leLaBEm+J/YgpjcvxO+w1Ra8vAggZPLJpb7+H2QeTDg0mmYe8xPTF+A3MQowJNK2ffvqJx0BM HwQbPivHsdQqSre/Zw91oeSkU5rOtZlzwSsXf08YwMJIIr60uFcAgvLzfJ/o+XINgqAx0iH7cawA BTM32L7tGEVwUPl6WRPG3uKmF9ePj7vf35iZYm3jOddAU1ChCsxLxxE2XI8c9CyMqmak1iNEyTIN 7K4BnCNL1mITtKBny6/FhznhOLeJu1n2Uwos/f43FVga4W1kPtqviCxC+mKQ0fC32rhfaxpG82Xt BpT8lvt+FwXWmuZVniN+379TYmD+vfvMqfheed4IEsdjetu2m6w1RcECoQENZnu1O3H1R1DXY/ki D6qc+LG4qAtLXyieZtgBcteMXBDj7xhy4/13QYLfsdiDCIWaV63529/+Rk3sX//1X/k38DAILprB liSv1J5Kc861NT/XGmE1pqaJ4543GRQIPUORWf5OmdETMTPcCxVYxK6pPUAYYuw8FhB9gfmki3JN O2c/g0mIVmrEJbUjCqsoXMv59dAGk5RreEL2kyanyEEqUy0EC4hnzh7IcyEEyKtQZLTZ+6DCHEVm qX16V7zs9OIav0OKZJyAym5dMQ0GshriYro0Mel9dCKUC+YhO8B9N4QmUoFblDgFQhaiCh2DnuMi jeeKeE38rf8dJ4RXZ4mLPe6SUeCtmbEnRMGgReABgeXaVOyXC6M1zMKvq0yxEvvk7/nEj8eIZmCk pDiYHzUfH1PHqfAZsCk3TTwjAvoCs/G///u/+Tm+C4DdNS4XgGilwyOOX2m2eWB0HBO0rKkVnr14 D9fM/BMsiya3wh2ZTwQXPTxexm3CgtaUKqYVegLiwsJYazvL2V6ujRToHXGuxDnpmlV5fec297Wm ZizmLgRWqwUiSC6tJdUbOTA6Zc7yy+KwRM4Vy2PximD2QTCpAMc8oX8yTMzLCsvLCyyA/aoFa1ns CW5WCCtNtreBvXsGTHxIW3NN+3F8wfkCjSZNNssM3IznjscqtYr4eTYrVsJN4sQuU5D4gnYvnB+z 7IdrE3HXjxM1erO8lThSVP9jf9CguUBDWhPI3vC3V0OOn0e8KZbPiuRLNDzjHBA8LqxhGrpgi7UA fWG5RvRv//ZvuS/Za2emnb9X4oCxxQXr1xFDbeJ8KL245cYUKRf+N8fAQoKpOTFur1OiI1nbau5o Om8DRjjU4FdpQiiExcT+xvt/bl6jxWsoMakobH2co/MlenxnTvx6g1BFZgmYg/TlefwuM040kqBp QauEEKY2itxWatIB89Kx13z2My7HHDgIY1l4QV0byxsR1K/qW5uEdj/cTgfg3hOMm+MEva2pxZcE 2NpOUWIaUViUExIgYcSwzuFV5zSeSG7030SwN3537felphXHIeZsKk0W/9yFSUx/EwH9qIWsCdVy 541apvcvekpjX/GAoHEQ3zUlL+rgAgnNv4f3Ibz++te/5t/hNT6HtgUh9fHjR5qSEGxOeYgaY8Qb Yz/jIl4ztbOGY4uc312JPfTv83pQUqu4N1FLh6ufdEsKLAjQIbOyuUmDYwSBxhL2dt8ZG+N1CcO9 dwKns8zPWBqpMF3XNEH/rMQfz62Zc41aIGRLo4HPA/LNAcxhaUKIj6N6OOlQs5hA4k/qUQRetVwD M7juVzt7WeeU5jomp1mxXlxgHfwMo7DUTz4tMxWK/NQj1w4Au5HZGzZMUq+AHd7v6406KZACliA6 8rkrsQ2wge/M8RFv6PU73dmxOJAviXgLgOhOZH88yJ///Gf5j//4D5ofjsO4ZwU7P8wTmDPAU0pz Jtb3K3frNcGJVnKeSkwifubni2ZXaaruu7vFQsYERb9xDf/yL/9CPhY8tMizVFk9PYwbKuxi97ja qqmWj83gdM0uyQXZ9bLbWFWZOwXIeS6ynie5ur4mBuXCKgLX6M+vXz7zHjAtsNWg+9s//i6fb7/Q /EP8GQTV/sut/Pi730n6qNVqtjdXqCDFuLURSebqo2x2MA1x7E4mVJ5pdtINR9bOQwQFaurVW/XG KWaE4FyME/oMDhr4RJpz3AHo4U5zj6N6CzAXZASAs36w2LWu60mKbOobPiPCoh/20vWfZRj3ctdp ZlOSMetG0oA6mbqJcdH2f2c2XMQMa1l2zU9VT61MIHVWnzMID5xI4E2E5oJipMS4OBvyppFgioXS d7gPXXdHYdlaJhfW40yNXO2u5ddPP3EOYY40W/0duFGsbP3lVt7dfJR//PJ/ZPehkgbJAJGfqtrK 2Deybd7JfsBmOMhQfZap3suUOubJrNO1jCNCpZUHQG8ipa8GYA8TnDod17hrlczlxQc0MmDaGPt3 2VnhsYSM7yGMZJpOWBPfPeMoyhYxHdkIFXKUDgsBxDTLToiaH/DksMP8f0jTodvTqmbCzy2nd+RA uUaE97HQsDjgjcKkg2eKpMbjkTcZQupPf/oTsRXfrfAd9zpBWLrwcu+Lt4ir3NdK7cV/G3GSEnMo tQfXYlyDwTV4f+MO7N6xSGYtNQrvt19TSQEo++jpiaPZGwF+ED4dhMdxoTF5hgR8/8MP72WDeLTt RpJRMJi+d+zk0B+kcSInAF4UEmXxdgOBm5bZA0ggpefJNwVcA7BDvfYZgPZx0EKj6s3T4GArrcAF qNwgFVjYNDXCAgxsN3Hm6/MxzRrPIrvEeVoCx51DX/KpjHZhQsmjPRS0Fi5mXw/QRnA6FWRcDKYh m7dNRm62kdrg8ySHAbm5SkHjgsNeE19yryzCbXrWNcSq9PEgxzVq/VaqS3M1+Fxxs9wysBDjwj2w 4ro5FtLXQ/CMF3P9+wssaTkICM+BNEYo9AQNyItMYJZavh1/djKxZ0AsQdKobaFFWz8uXggcaFZo uJl/+ctfOGAQYDBL4KlC1V+YLBBcEG74joeD4LMSS/DCBM6avtTO4RalkFozTb15EQUXHDC58B1o WhFvcnzJrxe7bqRV+Hf9OsrPYpEFz84ZtalYfcaP849//CNrqhCkaA62QwNEPUm0zQbC0R0Pjs8d ZLv7HbPsOlA7g+YjKxcD+IXqwvAROlAizwrVhRW7WibX09zhxJucB2gLFKEiOA4InxSq3FB1oWLB Zk3XuFYxn5off94UtHQ9VQlboFzSXOQsKri4v4CnIaBoblnwL1J+z/c92QPHVXIq93ew03kOZDyG Awbv6z2JlXzK/PR6Lx3zBG4+cVPImVKSaoYMmwMWJr004FrRZFV6AvhWuhEo9UGhHxdafnzLSZcF /bqC4QK+tJhelcBCCA62VE4X2sujDH0lQ6MBljsCeRopjgavizpMNVk+vr9mx7sGAeERTTUHdbF4 IFR+97vfZQ0AQgoLCy50/A67E479+fPnvAi8/DkWoZ/HuUeYIPjtjz/+mLWTtRjE2Epcyt8rTdzY onkYvZVxcmZQtchiENnhLnjiMfz92A8XEm6K4jh+zRij0vSNGha+D+EEPAoC3o+DcdZj9bn0PLhK PA7d5BAe+K6aSDWgARRYmA78DRYpQlqUKqDgbblxkBJgtfkgLKKwyRiW5T7XPOKoOoqipQhNMc+i lmeQcTpqOSoKNsS9YePUDLgLRwdMwwVfTUPReF0ckoDb0pWv15jviZtODCVz09JbNT/ztwCzVbPS 8y15cxTA1re4EcVnFHZlEDiEp9UJ4/3kOFocL2OfNXp38pAh4lUOfXiu+fnZz6+BzarJ6rwMMaEE 8dUZ4RpY3Aw49wuO2XcXWIrPJdtIMOha9nroUTWjkgMLLiJKG2Q0JAuzGw1VvaBExIXuAit6R2J+ Isdb8F0sKNw0YFl4749//CO/j2cINjyw4PB7CCwIBpiJ+B3OATPHsR0PNYlZAO69/hVgP34Wd5hS kKlAbrMn0dni6I//HT1DC7DZrh3CGC1mKYh9iQIw9iWalHFDiMA+zgEeFZoD8fgcr9Ewhu/eqTZI k475lDAnkPcbwhj3DFiI54VHRgDzyDE+D6aiusfpajctT7UcrRHlWhA0FoL8/YHaQoPaANCO7Frh rePC9lARky/uqk/0aLmXGAsxpDsi92gmQFJXykKfYfwFmKzAPIUSVJj8vh2DppeFOfEwnmqlzsd0 kxJmsN5PD0rGfdXip9AgYR768UsCMzUubAzQJscNzVDNl9VoPirKRVUY9D4jyFnBdJI8rULz3Cz/ OjJqeTobYlz22tPelPM7jGPZSg/wdxdYVjJNzYFBpTOBTRBLpyS/VpO04yQ7LEBMSrs4XeTLpG6l sHI1OE5k5yz5sws0Lz6A30Dg4Dj4G48//OEPqqlJohmD1x5mgu8BSMYDx3GQ3t+/ZBZGTtGaKi8k pVYAACAASURBVLx2baUG5NiV98eZ5mVhUd9p/fWa56jM8OnjOy98Lb7g53Mu15qnDQ0arN8LDzqO QbhgOkOzwqJBvCn23cHZ0w0CbhHkjI3GvYM6tgC8sRhhNqqmhJ0fWkPgxoH2kzVDCKdBul4FHhwR 1B5IbVFzkFoTX6uSACWryaElTDNiV+UAeChHb5+U6XIUJPcxDlwxaB6U0NEEMooKtS59Pdj5VUgN im05VkTXP8amDgUvVDPC9cA5gMqDfj/jWnFIoGlVBKgjRTcE3nsTeoC5dS5Bw9XUyXn90TExa1MK KWvmCDzrSJmXkNkX3GlgQq/A7/JaiEkLw+ecg/KdW3YMIC7UWPE5ecw0ya/TIFv+YbT/INExqUti Z9zlywUezZXoyXOzCAAxhBHAdic6osGUcbPFtRBoVy7osGjxd9RIvD8Xr78I1Sk9jJH/tIZreaYB ZkkwThU0GP/bd9SSP+TX4gK1pGX490u6gDe8dnO73MHL++AmpQtUN9Uxrtih47GRbK6Hp4o7MmyS g3Llhpl2goXlAqSqERqkmMpcOgsAPbQGVFlys9g5XuAOqWkC7Q0CUzUrF1ZmznFxASqKHDYPvA58 rUwEDnPQNIlMRaFpGoTV2BEHYgAwIdqSyGlYl5EuFa9CPxHOA7M1OGpMY8PaqSo4GnRT6TGOPcrE qxd9bW7p/FInhHrP4blEuTw1c4+yl9E0wEwVgSAfQAdSrZc4FoWJKhAa2OyalpvaOKfjW6qaRghh jic+xXNLTuArEFgBNOdNx8RSlzlmzJ3GLTDXNKo8qw1pv2FF3NNy8/ERSYZeqtyBcV9c8BZeX10T IAaO9fe//50CCAsNj/fv3suX2y/Z9MIgQpOK2o3THPw7bhrG7ALnmguRiP1E8y2P1Qqb/9gdF7iS FwrFaxe8jm+txS06Pyoy5aOAilSK+Fu0Eg+LAjbyubxfGFP3zKIxyHno6B1kpkwU5hwm6bigWUpB NiAmUriMmcDIhcmF0TN+zTNuuuDmLo8CCsNEgaXeQ1RxsdL2oBj00PbwnvbfNRam5yXp0a8f7yoJ 1K9RTSRlgGdMxoiPCFeZv2dkrDjfs/dLC5Iq+yGGjkVMFstgqXVMKupyJkuG+KDogwmI7K0lHAcz W+dULLbhG5WuAdXE67qVqm41bbJZH5S7jW7mKrCSTL2GRWEs1ezLOpBpWTAX0SfHnD1KQgmoXubM f8bN0wSWAvc6HqXm/2oE1nLS4/8KHvqNfl+/l24c5fM4yb5Ocg3iYTPJduqkhXCu1W0N8NClelVr mATUN1TtcA0jxpT5IkXDYjocDzTzoJVg5/d4NXhbvtx+0ptEj8goaVNJD48RyiIBY+EmUhF3QT5r qO3gF40HuMhnwHpN+NTDtaQJ2EAtE/gu1DA6Oe5v2b+b9z/M4Lmzy4Op17yviUOp4Grk0B9l/+kz r/Pj79/J51/3ihlVIodOY/ZqVLuEydrdSVVdk3szTHfUPDSZImLGtrKtb8gd4txLI+vdjV0vd4cv PA74Wc1mK8fui3THQbbpSraoMwk6wdSaowTkUTDfGzoqcC0ff/hR7u4OMo21NHKUz1/uqHV8+Phe 3r27ls/7pDGJ3ShtXcnI+znIcdprbqt6I6m64njvD3/JYwt6Q0oAx3XTwNq57QPdZIxCA55obDL7 sDmY4LVslwDZq4WrPzLMVVjUEzhaahpjjiAYWDVY/d67ditbUCxAQWh25BWyCDBuSJXkMBxyaSvi QeCE0aFkAulE8xotGaa+04/g1yFvVC+H6TMFf49/TD2c5DB+kk1q5frDDeMAYRKDmY55fHO1ESyi d+8+yHBA8YpWruudHORWtkysCSIc8Kxa+hEcMVx0K9LeSV/diqSDNOO7RbhfTnRgJNlGPgQrZ/Za Yn0RumhiaI57DddzwdE0lVfeoo9Nd1BYxYplNTrD+JmqpaaKehqPgs7gxzgHbJegtr6vrlm0bGpS wwPor0Ups3o7WEkzgKEnqQbnWabHtUIF0BQ8Ds14QcjWSFPEyJsx/Abncg2FONK2kqsrmKdNNls3 G8Uyjki2hlCDpDstzQ/+DpMGphV24dkj48AN82xTQ4LQPg2Z8tc+tlysOA3Lr+t1ILhVF/kcQ7i8 jxAqEDhqxrq56CbufL8sxMWOPVhFEwfWy37Fv7WdRvyvmdfnWjlXTj8fVx++8XKjMU+jA+4jiKGW Y2n9mGou8jrPVECe21r23DksKM59fq75xmctO+edcn7ZLDSgLYHKwcYp65HB+BuKxmXaDs1dq4bD EjRQItTvmrXbx7RXL7AyHlQhM+MoHbAZsJqZsZTlNbIAMPhedyFGmS/Tj5QTNE7waN8vzSYJnhcs ZOcewZNVywagpmuynAszCY+clgwCz+f1iczXFFiqWelxNfYsmlduVnpuKSde0rxprqRtb0ikPB6V +0M8JQ1yd6eMdxU6EH7KgNb4MEu3QmFoOIn1X4cC2AQoHACrtdKwssdnygTVfEs5oljEaGC4FxTA uG5CeIaZbaO60tHcMdGi7puowwAeO2qVFtmvgK0KHnoF0beqZdjM2oIv50/5nSiwIp5Tfr527Pjd KChizGL8rIdGCJwHaYqTxtwhQ6frCqo9h7RBPk7zCe+9PrSIyZb4LMwwmM08tpFvmd/XsDncPwD8 2RtMNM/NXGBmuI+lxMe9b07eXmvwEmrAs25iyZMNUGDFmkC/EYGlE8doCSxtDTPMTa9GWgwINSoX Vpgo+jfyT69NvHKSRpxm7T3vh1bNVbIhFg3MuAb1q/075urmpGU6HaSAnStfZ2jRquay1VrRFp6x nNPeGNN4xD6VAch6sFa6I9z7OvlgVpArNh0ZggF2BTJWUBsxjw+vj9qWkhh10VRW4xEP86QNSYac EBBY0JKwGkmp2DxINRigISle5N4mxU88M6fFO6K8lGWdhMm63bWyP2qY0YTkb8CPsibmoLayuIfx IInYxxwatfasY67m2WJOhX+X5l6cM+Wx0Zxgmu8LYwdNI7dx7EOcHQUwvHn2HuLxXKvJvQvkykta YMphLYX1YNMOwoo4H7zuvKcIg5uvDxqX4k6a7oX54+zeqUbl2pp3SUmwql3heRl8f9o8O4NqnTj/ 7Lwps7T7OESteXxbAkuiM5ne0Zom4QEbOhjBlopHBx0Do79Qc2HecaK5F83FGCwcXavePJEYj+rk NqbJgHLXy5i27JN7SrJJQODXCIoxhW5pjlSakoSesFxaSUFfNKTxcE6XCyzXtJyS8fkzYskAbO/A VpPPn3+hpw2moeIpqnW1TVL8ihlgEY+XpGrVvHXzTjlIuqs634h9I7l3TkWDv/sO4wIcbNZgVcBo zm/2lwKm08VAHhG8lnNwtUcFoK+Hbn9iqpVFGlxbQ4UVdb5cTvm75jSIzo1Sa1pr5wSWJ6hUeoHV EXTPotZ7sT43yqJnAgJghTFQ2+e5c7EUxGdfHqiCTCtao1+fJiqc6TM+Zo7NzWsBm41SLTS2ES8h kHwN+GtflCro7mvnLBd/7xFx2G9DYKn66CRcrTwLbgpKbks/yRXBPbtBvHoHPNfDXXwAI//JBVYZ vDvfePdiWtWfLPWTdIMWcVCGb64vSVCXcWBGACz7kc8typwHYIyGJGnuWkdDqEUkvqLFgG9W8sVE E89eCuH5helpd9t30vW39ruZlYygVEbdG4ah72uFbk5cCDMKq7k2HnZGaGHuNh96M99GJ4X65mB5 5KutbNpGjgibMTNaM1Eq1ohjakDyTCj1+60ZJ9UkqaDB0iS36P088VW7i06bdcEVi5i4sjubpwuK wkVtZk2wRUhC550eO2xyOWuDUlFH4kMz8bQ8h2uiujFcSmU8hr44hOH90UaNhhEDWsw1exIDo17n hZqDWhlHeWM6r1W79XNox807f8FiVe2xXI/xR9UFDSu9QYFl+cAor5okFdJcjFoabNrEwcANdtrD erCuCyP3HJYCK2pZ8wSNIL7uqPo3+nBHcp1OAM8vpH2ASzoGgXo/Ik9sAvPawNBsqiJDgc2P7tBl ZrgTQp2qgL87VmPRndLDLyCoeD2sSTfI0B9pAioGZyRPy800jtB4cHRzW3MtO3dpkO32Sqajxqcp 9mUEVVRaAZYmSMOLcVPTZhw0cBeZDSC0RDyeEe5xjcFUjc+LPyhGNx7VdOTYm0kCU2ZbX2cvMGPz PCMxXeQPL7O2pkGV0MCa4DqHc3lzi39+2Hw1pwoEhKdNoVNCf6WaO5nqMyHVS2650co+XVgfU9BW zo2Fz02f21lgMQxuEiTu4KYLqoLx2AA16AZRn4QS5RzOl6QVoYc5cH5di32civUmBJZfEyYH7W8u NHBeHF/xQZ3NN/9tmUEgEugWZlDhKcyT1EzNOGlJYK20Ou3h0FPFR+oU1QZxU5SPAi0nBq+uCc7j qLnVSYvg7VCAy7EJCAU3Cb0kV9RK+sOd8YJUoCnHRvOMKDCP0J05h7aC2VrlkXQd8nVwziYnD4ga YNuCHGuxawx/cca5mdH1jFfxHoFPxbg0gLLA9+6WWqUXPDczFM8qeA80n1wLUI0WPLEdr3vAg5sM zE1ltD+sed/8/i7vRZwrlzSs8nuXgPn8vbmC14nmr3Nxxr8UA9Vnux0Xr89baVHEZ18LPrbOMZu1 w9Omn5ln0K0Kfz7/s+IgoYBFHpNgli/Gb00De2MCCyaYIh9zAkfF/pKk7VZG+ZlgM0wpDRZttKxS QqLAJC2tKNOqiBUCgzoSLKUWIkdp2o201Y1sqo00004maDg1ktz2UlshxxEcpf2e8ic18FApeo4c S7lxF2Pn9HwDavXtCBIDc2EALQXeRmqYb1Mjt18wgQZqScCztKAsBKWCmlcfQOhTasPUAPBP0qc9 6zgO1UG+fL5jnCOOC6Y+nvPfnz5Js6ul3rUiQyX7rpPDqCFIMO1oKA7OQ0I/lFJQNcjXDbLhKHfH Tjr0iVgN6s/dkfNT71Akcye//PxFjqC8UXvQUuYggmJhgAB6GA+yfbdlfBzKu5G8Du3qZpS78ScF +600FDMjOPeCHnFlug/TrfSjcsiadlk7EOatL8DVXRyaXzmnXBsKkAOEoX42p4hBY94vv72L41pM qr9nIXGOPWrCFyuNpZEp6tRwWgcEOwsJ6wbiHmiPC4KLRM3jOfYPLRKliWMixY61xXXamq8bhODs ZdOCLI00M567TGMct9dIz3OQAc4OBJRTqGAj0gIUIIqq0nA6tvp8P7Wh3gAPhRsCLvPQN6fGBeJ4 Hl8jhHNzBf8rKyFYr2+8IXQAmAAXueEa1KagbgP8JTPY2LPY3cl/QTpXePAgiACUOgCpgaAs9GhJ xGjXW6S/7nrLrSWd2SEUfzBiLBnRGPzTggJq7mkQKgDMrH0ZjwmJ4Txth4PbMdUsBB3i7fSAJEPx b/U0qhalWoZrbbowXIOLnJw4EUvto8zI6uOM9eL4B1Yl69LZ3wh9gTsfYSP6ezN9GDZjmoSFtJTj 6ZM45oj3vpUa8SWz8CntIbjWU5pqORYGlTZGaZmvzYOXv/bcySwUHTeLJSVuJRRSKMmF2oiMdCCN xGkgyiSsL43FE8v0PfQ6vL15gdWl1qJ4kMXRyHJMQTNJg0U6tFofjcAntBLYQRrOYYH4TBEwB6aC 52PkSaa8ccqELXjGbGlqEbToASxVWuyoCH1QgTXH7GnKFPUE3myQrQCUhs40MRO4Z4Jp/XUO7G40 AybNk0p3q66H5w7M6vVFHc1SEkHuIVG6kIqeVRdYwJ5IUkXlFzMbcL3E1GDgMXOB8qVgWqLBe8l0 TgwZQZGCZd3G8txOJI2ZJGLhjPjd8rcPMfGeu5VC/2TcHeU0FW+uyoMYxzk8Ry/CPXNL8zM94to4 b3Jc5ykfjYLKqRkBE3TT7T5h4lrRU9pjr+nNC6zbIQkqZkPAbE2jIjDPvNqknKuAYE5tDYpgcCfT CQHgxexR5jf4VRQcqLlm7uqN5TNiHi6z/3NcV8g5PXt3+JftbLHQqS44j0NTT1pD8xLHYViJucZ5 Dn4/SXeEEPPAZf2875XkR57VDgLKMngC4AOWNRwyHYLalDGLdfemo1VxJ2Mf400Fj50vZo4G0+g8 gDoKPgfNYWa48CMuhezX5KkpbaKt30kLgWUOAGrCI6IUEGyLjOBaEVrH8zSFTSwxVmqCa2D41y7s 59Cw1gTUpYbMqBHP4+8yR2pZHehrtBIXWNo3S8xYW5EQzCHmoJ/NzZwyR4Mqgzf1tC2E6zO1c1r+ b0ZgHWHoQdUlaAnhhTg29RJCR0JMH4xCCgwOPnhcMBchlKpMrMNih0nJAGZWpFUTEEKlQnUTBs/i jEaI5FFZWXHRouCiSg/+kZFcVZPzIGEs+EoOHXa3wMXK1Uw0uLY/aB51Px7PHcvRAxfxFD2WYhie HucDDZ0B7QX/LBdyCP3ODgfT/srF7y2G5HieKe+3Hmc+X1PtFAei51F5csBGvLJO381Ve0q2dtRS Svwkan6voXk/H6JhzTFzS1M5g+852d1KFYZHtijkHbNbmNd0vwcg/IwwLIXHc437Y036Ny+wxgrp gQGgT9IhDIJaFfQrrZN2RWzLasFBgHBhoEYiTMla3kO7gpnn+A5yeoOdTcYvKBQDg0apoUDjgNZk +fYd+/LG/cgDZw07IDBaIfuoUh8yJ8q0LzV51CTEIy9I09JAwERbeC5NJjYmGHzhRtNtXjwu7Cw5 HoQwzDYzP9yJWWJHC8/eyk43CwuP1dNwH8afMeSjlrqppYX3kQVGkSJm1Awb1HMVjH7MhI4m6X2E z4WQe6KGdWkxrWlxa1rgbA7OQkivJ/C1DENyciyJuiGMK7aHLnKOk2frDVBAbzw6Aehvzg6EznCO o7/GFaNpYi1e09yeR8Mqx/E3q2FhBYIHdQR+MiHpiGqyKCUGDGWCZw4+F8t5TS8I4Xeov5Pc9JVM LbQzLALHujTLKQIWR8T4MS+sLn7Nk2QA/MlkWmIAKnTcfNoo0AxtzcBPpRZoReAZGHVCp4YZIef5 WuiQ786o7whPUeacWZEFx5lcm5qHq0glnV8Wk0O342ySuYDwiRRxJDgTlMZhHlMqd8hFtWEYVcYG PeQEpc5Z7eaommtBA/DzRU3gnGZVCqxSq/nW7ZJJ458xlZKlGdbvOj9Oi426FzNHYH2lqZsKnC9m pkDTEKhlSJoSTdeJ12vHfUr7v0/DUl+yho7UFek/xslTd/XRMig6M9fscy3rBAAXHivHbixnNc13 qjAyIr+KsX35NUVM8/njRJpv6GweeF4l4kC56KZWIYEbf0OSp2jaj141LBdcbCSRnpJd0dw89Nxe jjP5ayYXJG/KsRDvt3nriF/cT2hyNnmcWDHDKGgbGnAd2f6a/bJpdpI61raid1a1XAg7gL2am2zY zPnV/Zr8GiLA79ccBZl/vzTHnrM9ZjF9TT/UyWMcQcs46hq63t9nwOCmeexoinODw9zuUWeLGztz g5EvZRsCxh/chkAz+Vbtvk3nuwusNakd+9pgUVHrseRlRrJkGydpeyecWEwW1gfYu+aSrYdebqpW dki3IqN8Go4IhpGrqpGruhVQlDBp7vYdtSnmQpJK4NRCgOrm5g8kLuIBLKZl6IpOMjgA67SzC7GQ lJBDHer9tvmgfyP/L1grDXAzLHINrznc/UysqgY3q95Zhks1GwmMV1dSN0fTdOAt04DlrkO+qL1s wStgmI1xhqBFEheDl7Qip8gsNit86aAuBHslKVRCLicJhZzWkaIQyhgIBJgJE7Ck6wbJ8nCNiBfc yKbaSjNdy7RvZGoOdAocByTMAxcN6Y/hENES7k2zXbn/HpeoNA18z7MLaMpd/94kYz9nxHRuVBRy CN52vCznFYt1GIP2+ZUTeOZz2WvmXrOoic9f1POL+z81ahIi4wRqGG4a5GHT/Pt6PXMqIjezFymJ 5TRQ/5I461mgo5Kxv5OrtpZ2C9ywlx7mIPP8faalgYBz1Er0c3FzYQEJxxZ143O+o+aTG5Q4nHO+ FyE4wImH2VkS7/M550TckDVaI7MwX4fAutQ6j/+0HNtzvJZWo72EgzA6yjhZk+8yVix0A8BdtOCj ZhPQwGIUHWUYa57cSIuh2pLCQprPOwKYUSvw99WTp/nPo1CIWMyuvdayUyDgTWb+GUOWZgJM3RzL qNgThVELL9529ijZIi3P8ZIqOzEwlmtHg+ajuzKdGCSIItwzpF0hF26Oz3wQouzhIPMb4fWckjmC 3J6sEa97ywCL5s6BqKllwuiZdklbOjc2CxPVv8fIifkSzjk1nlNjTCbU1oTEQpNf6YP2Y842iuYp qD2uc3YY+O/4f/tjaeavjc8lDbasDv9qBNZysGYtq/OiCPEC1euuz55fLIxbvNkozNoxxbJ59rCY EMSLVLtkZoMXpDmWNLfTRjZMuO84jfOmPOc87oOmrdH0vDM7l/mvqMKHyWCxe1GYLTCbhHxaXlXF zFZqZxaMiqymPLdfnKb7VYXC6BmFV80XYwwqfsi4r312btFEIQBBDsdCzeKlG6mdRgLzr8dmAEHh JdNVs8vj9lWtoI8UAsJNVp6v8NzFzB3P3dYWpXLdbIMyL/Nsks+59sv+lFkOntqv6kwiy3Pn8ffp oMkFZKHMK+lXj7mMIpjHeXH2s2OzDqcs5105Lt9dYJ3fofR5ABuA69RCHIrPz827jLcg1/oETc3r GOp00VxLkySGDsA0UAkIouhxUCLflBALt5cEHhG8fB4PZTeTPCcYmpFmUCwaVLAuTa4F6E2ujWkb 2JGIEcFsUK1vajx0RtZNAgPrSwzI+/HQe3AOxF7bmRffQRl4BjojPKpVk4EjqlkaEJ7DXF8WJ6cm Hn5t+dDlkY2rft6xUBFaMcI5mZ/fjzJmlGmhDLvkgoPAl+P9p7swhtOF36iAtCwgrN+nhGKWyILA qk8xuJdyIKSVexn5daUw46ZM8x9po+dUTLpZq/c353rL1+w1GN0JtOTvleNzaUPM5etfi8C61Hg5 CneQUwWOFf8h9xVSraSr+w8AJnxCkQbFYY5WL60aJ6kRrY4aeGAZWyK1O0g34FPGFZIRQkmLuio/ Sm8Cd01iRPMCKblSvOkUfkvKQbTpNYOBOg1mKwkxhaphAauK2tlSVcd5ZjMwfudcts3HeJRcWzs3 qWheI44T/2poWBDwyL2EYGstE9VPR40ztKyWql15qmlznV+eAfbStdBZYGna5GW2z7gAO8tsGsN5 vAjJcwqDsvl8KAm3aLxPSEX9DZj4yUxRNJ038kjIwMfNx1fzdXnq42Womif3w/Ftc7+QL+ux7bsL LL+P5b3Lu0yn3ot2Qhl7jBMWATIk4HmUqVXQu5x8GecCAoTJwQBX5U4hexSnPEMTtJoMtAM4BPdM IztJsxm1yEUPTUCkQTYOclrU9vOiroOlK/bFHSvrUtPKqWjOpC6xXYQkCGcOO1NcjguTgeA8dzZf sHj/dnUClhlTz49/OW5xcp9qXaUmR+KttAsOlub30oBvJAOcF4qaiZ7PXjW0hwiNuCjwp4OwKiiR ZhmFOFBA1vPae83Eq61WLsJ3PBc+0vOg4AiqC9283z1qfE56dqYydwkk580GdzrEhK6ZPv7d5xKo 0wqnzucnS9yH78U+LDdXze9UguJICFn+rkIUA69Zg+D9u2vjcs4knefcq8Wwopk3X1Q9dLJJtVxX tVxVgLobLuUDU88m0fot5WKaj1tbtLxid6guAv5VIggPbItFEgbgWg21GvC3RlTigScEvxh0ITLT A6PoNUgUWgOsyKGb8SMFxC1Cv1Cvy91sBso9l7sJHcbhIUeWxha2myu9qVOVMTYILY24mIsMRPUe 7T7N6LHAenlP1hppJaFceq5uDFPQ+Wmkk3jxDc3ucNlHZzu6XlVI+Iapq44Of/hYeOpm/uJqLl3v hS7cWRCLezxHW92Q4mYFrTmEwYDafG7BnsO2vhZ0n+fH7Jjg87B+nvn87qjQTRImLDYMPR42biVB 65fhCPINe2vXrfMbLcImZZTCOQdEOS6vRmCda4D1tpXIVY3yXkkrPyeR/YhcUoN8uVT2jzF65t0z EifvhRfYGTZyBFBOulVFN76qsiLIAMzoQ/ub9Aq45J1IWk+5aGk0OWKIiW5MS61kYboAw7B+snox mQkQXMhdbwKIYS2anLAyYJsJAgcF80sANYLuvnC/1iQ8B1Dna3Hhy3zlZSlyy6tiPz/1KBWa04Ob p+nVNNTbzU62P+7k9z/+4eSb1ISDQI+aJ3f4CxjWQzSsc+9HgZXfK/JXkS5yJgzq3Nh/TSs1rDxH vO7hGZMajHidV+qh1opL8L7G3yzn9xzcr6TIqEX65u3j/5j5uRBYrrIrdSCk7yhSojy6AQaiJ0ur dcC0YtlHYz53xgCvWLylY/gGGrMqTEn+3x/AUu+lGsHhwQ0GKA2wFWElwJYixuEqWjh/NckRyfZI RJjkPeIHIWuIp4xyPAxytWtlt62Zze7L8Va+HAY54sY0W3JnyDfpkaQP9eXQ10Ya5LqSRlrSiJAn 65BzNnmxTyyoutosKgN7vqf5pkFoTnJkVlDNJtq272Q4JrndwzuIYqHIvIAYbTDtOwEXE5mBprpF +gMvHhbMYB1w1XbAH2uD5jHHK3q40Dx8p4uD3DSMFRP8wQyGdxW19RRkv9t/IpdpqlC+SpMRAl/s CdJuZBxUB07wKIWKQOCI1Uh/UzsPy5KdhQwFeD12704EoHKTDJsKoOzaDo2cqMAhc1Y1Rn73NFWR Qqi6ML9LoVNilSQYu0DSD+x6qW5LN23krutl2xzI4UtyJdWAWpnoGYqFiGwb8NYa6Y8GaLdai7FH QdkVgZkKiGHNdPdnpgCqkSF2ylk8dttrGfrE2pDb9oZZa8HTwnizMjYK27JoBebmjdTIlYZ8cCxs oveYKbA3u2VoERe5FlXpUSiEAgVecAS8Q9moLH0TMp0eLeD+VGe6T0jnbw/B4+rFd/DDF8dtTQAA IABJREFUB1Qeu7dBgGbJCslsuXhgXNFU6CZpwfhOg7TtKPVG481Ynw+fM3slvBThZhlJVBOk3Q8c 6qeWsxq0Qzu2GwNps9FJ3cE9rzfspmllg3hDKzeFOQ1X/aZGEJDarswmWmESHJQQaTW93GMFzxmB x1B8M04kN9+8Iq/vNF7SC58xoh5OBqYn1oAiJGQD2K+5FmASXrjhtoNqH+aMANow2R6yIVnGUSpL ln4HgoKAv1ZE0RJgc2C2BjojYLzcfWcP0jwmIe86zQvszF6iPfb1YdrYw/AfLRH3Ne0x+JJvVhr2 ZWn9Mk9Pcaz43ZdoU4jAmLUijTrQMVYeoKYnMvMjZBopjzXPX68AfRqG5PMbCgrXKAFfq4CVeXhz DYSHNtYidQeV5rZDnJwKBNzOpwoszNdcmEHfsTSwqi01x8/S1El2bZKrepANdlDjLhGjGd65U0Lz B1mC37FGnTcwnS+cP5c0AmUhkgy9oEPDqsl3XSdXTZKr7YZ4GUu/d7201UYzaSLzA4iKWKAs1YMO 9XLskLNcXfg6EQHg72i68eZYKXPtg3ooNdzCsj7QG6hqtOIqWm0aWNX1dZJj30nX3UkHYuvQywaT HiFDVkAAhc7WzI4Z5FTF0+fTY7AtNC3H7t/XCjw0/SCgkKAvBx0MitG46WVZANxbNAvMebKWKa0z RuXpJ3Iz09jTr+QxPU0/feogCCWl4trjIorZLNdbecy19+8fv5n9HQVWLmziZeEKDek5TcGRghmO KkAJmtcfR1clUAumIgMt3iDnyjKlYu562puSwJmFVpA4cUOeNVArpGqplehw4bf8vjzuOiEAZ2Iq /heImdwcn4hLItmA5frURHsGrnsdF+Qf1x1oYMK9BgndKtW/CNfiwrm566qDcMVvjygoigVyYc4Y 7SbT9TT4uZLBJjyS/gH8RFYGmFrbPknVIC1NLwil3qDWn2UC1atAEj+9fR1c6uM+xyKSb5M2s7Cy FDTeyP0qcRQS81SID9D8EJc3QttsZdvsRPZapHQ4opcA4vWaYB4jnXJDWocKA79SCkaC8uhzW+yW swB9UOMO7LF8Lji0yg9NA5gbsS5frPJsmCHvg5FsNUd+DGr2WE2fgC60TAurrJ5h1gzdBPGMsKeL fSFgrL96vLjoFDx+SLaB+4TWg4ZwhSRZ9jt6zTy9zFNTy6Bxg/QsotwHdHNVAB3EXvXmafojx9P8 xHNFbsacBrwrzqnyWuJ1ap1KnTsl5qVffqTAEuySOSEqFs5Mq356YEegF3BeaOFGXiiBLZF0tVEB BEyEHjhoNY2k2gajL3cLzX2FhQvSYCzqsdam1TzeFh3N5QwbX5nawLho9/dH7kUt4vamI8UOesY4 Ra4nTVkDjEGv0YBGYlfK59JUxFCZrTS35zkKea+0iJImCNR1rRgTnFdk1pMvtKMnse/35oVzDUa9 NJ5UcDFGgTjZtJpgjxk+DVtZ5F+6eP8iOdUnY8hYCuEdgrNPfx8ClRUBtL80G4WBEfd0oDRh7TkX Q1gXVCdCOX8/8LioZV3y2shXa1fsKccmaCTMiBvNKtNggxYGTZVjiZ3piWZioobgURVegflgmq9S drLW6wVIAhysTh38Ruexa+i6jvU7ax7w+fqXGs98j/y6HmeWNzXAP3YSGhCA6IZ5ovAcsxJ8bes7 1SyYC8lyJiBRHsA3EDePx/dW3Ajeml4Qy7pt4IIGDgR1tSOlAMB0bhR4WkRV0yKfb50tEDdE6GVk Qho93geEuSB5H0Fy9BMl6BGcOklboe6gYmlZAKG2TYVCFwCEIZB8h4L3bptLkEPIMIwhmITUlExg aZ8U8wE+prialmlnPvcB8YtIoXwVXPK4+TFuzvRQlkGbQ05yUrY0SdvsNDMCNC4EHlu1nAevA0zy rPbrtZJvhVFZIW2uehwhqFRa5uPEawhfNNct+j6cYTyrsJrNj3u0q3jMeA5oVkjr8RDa6hNNwksa VvyOF7zAXLdcsE9uyWyVpQDFRoOydoyAzw4PxR0VcsEY+QalsMXSgwhZEcfeP4talzp3wu9CdSvX 0sCpfExrrlvtUA8WOEJCMKkN9FBT52koFqgBsHMVSoUQQJl5m5TjJLfTXuppkFo6sJ0IzKNIAcvB TwiP0b5Adqq1nWQDDRD4l4q4e89/5MRUy5kCEyk0oCLb5z+kA3pFzRIZSFExhxkbGEqS5CjApphw mZodYhIhlHAcYEoa74EbgU+s1Bc5SGB6H7O3JAqTWOEZoD3Ep3aypzeGWB3HHwn+7izDgdEzSH5F mngIdJxbNQTfFefdWhXltt1yN+v7L/TWqhPAeVG4D5dA99kLRA0SbHYB+x+plxsZ4F3KeMwSYNff zderk141Ky1CgeuIppp7CoNGZPPPx9X7EkuwXNSuwnXMGh7UCYD78qIm4SqGZdsnn02jihpWPucz iKzKArznOTjHWRK/opmoNwNKBIveUlHgzcmauuZvi3ise6HjsZcE1QgjuDfQNUrNB/F4nK652Wo5 c+BBEPDdmKRjKIXVgn8G7I+5pJENFOA6NCgSQPWG7VCoAe5/VEo217WabGou3GE3MJe9q6SIa0qN xggm5qs63zRzomXF9EBCj6BHn2ASIB8VYhWhZQHVY3BzLx28dzbhtPKx4l9uAqIfWihScRmvnkzt gPXAgItpLKBPPgpgtUtlIg+IxqZ5PzV9DFPI4B6g0ANcztTUArfLRDfPOxxOFk+c+JrtVDELX+gn OMLF5hiQkkM0lNwrB98FEHnOVZW1StMw1bEgi8k+f8+xJE/Xa/cUc5Bl1qwP/t7KnHyQxsPN76Ge 0dPjf01bE1jELM2rGo9aOk6eA8RKZ+MHUakJ85YqHSMrtEK3ZQjhHFRMLfMM6ZWO+OO8SZZCa3b6 4DcaNwplZDZRrSjGIy+x+e99EZoQzdGH3KPpoDF3VS0dVVmtMYf0T8Bi+sOtvGsn+dBO8nED7Uq1 hOMI7aKWXWvpP2zB+2BQKx0HuWa2hmqu8GHVgWEmbVOSfwd/yrIGeHoVLb6gCexaK0SKdL35GLb4 YQp21zf224PUqdfYOJRit7p81JqTyAbFSW3tsMqIjLK5wg1vmaWBhQRUNVIhJhvZtVvW8fNaigsv Ea5vgE0Onorz1CwBXpbBtXTpC9cXhgYo29x6JKBSEz4CtdxV3ZWOWoR/oxe0J+9HC6vC0eGTaxDF MFl5mqo/k7bMp6mRAwy1vLTw5tgfpWYwLLZXHVuSXJGZYTrSewsmPiz442Fkn/3a51zmxpjm61lD Vnk6pzLhe+N+rlRsGThjDF4UkOXC1N/7YDoogPcBPxxVyRrhzrdvBC+kHyOa8/HYfvxYt3BxIfZg fQFo9HgwLZFpi7Q8ahkQ2pKS3E693B2sBFeNGFmlXehpLWYveWoSdeqQLlBtQtGK080I0IKP+9G0 cdzeAQDEAQkeUZdwDmrmvTGy5wRYAxgu83thM1YAXrUtXQOHXmN5LeuaWkO8dDUZD8g821pcrjsV AsGZ1tc9PDJ5bqb7wLS4ntDX7FrghVQwOmpUwIIoqGCvUsDqzoKagGuTzFsKKXr9s8jixsPLt/tO EAsukCTXQIBp6AYFFl3+pwnr4jnOaSurZsfCXe/XoemPn8kz/aRWYg9xAeqEUHyJAs5WLtNJ88cg +uGuqulELlGhneB40OJIGDRnAHdkYiCBZxTZDPF10c/T5lk3A2UikDdj/r3y/j0GZzrXIi5THvOh Wlc51/w9NMVFaxJpQdjUwADgl2qqqVfVBVG1PDCEe/bgmgslOuDIWXr89Zbrwq81Xm/eQLLp7udT OoQTmRFrCDiDuCP7h1hK18iMO/WI9mSBBRiXSrZWE1JQlw4OdLqTdygFBZoCzCQuAGBBCXUiFrzA c6AtmN9ZqodBK/M/LXCiEGMHBQwaAR4OAo4+mOYNXVOZo5pbfmf5nuJs+tqzEECFVpv/W7a1xRkF fTlGmt7EnBsk+SkGx0Ib7llCnGUIb3FMAvicejWRQnlm8nPToMIMTRXBlg+jDay99muKfZ41gdOU KP4cX8d89ufOEYHi8jvPIfDuM1WwucHpwnhIZA1BP4AocKi18pGmsS7H0TZJFM31cy3Oace/YHPd tzmvjWk+u8ewGj6p2DqEkaov/psGUSZkpSib0eEYn1PDhfF/doHFbCxWXGFCOloEjbQo0c7Llnck o42sHajfR30/A9wAxIX7sDZJWHarmwMoXZtyDco9aGj43kmqEaty7JVbQEpFlgZiCfxKfbLjlXnT 19r8vi/W+Xtaf++4INW9ZFvbFUuNYC29jQos7ByKh3kIDzSseQxBhK0X1Z2Jr416vL7TnO+4fFAy GPqDtDOesWI8rGRcmF3icTGvTViYl/63Pma8LFImTsFeeZCgiiFNa99fG8vy9UObQwLxb85BUFPM iwpnDijKNXFkbOrY5DVF8ZT9DH4MNbFK4b0UWPc3H6/42zXLI37PHwroWxk7FtXQdEEusNAG0w5L TT8KqXPjuPbZkwUWqAXQqGA/wwQEAXRbtXIF9bapZeus7hzxZhfDhRFIhiud9WcPXWH6YhNOale3 8uvnXzNutVCzz2hNpVbmgxi/Fwf2sTuoqujGfLc4q2/R1jRAtIgXxJbHPQOfrm3CD+t/L3N1uxsb r3MqHRNcrAZkGRA0vzqeNbd+2ae1iXhud42B5KX2tGYCPsRMW5qMcaOcP3+ouff1ZpaNMteBbZTc zGEWwhsLyGOQHvGO8MYG8mUivqWFbikiqIhFFv3XOQlKwfdQiGF+qEOMm6B+ay5Z5vec2rdKA48b LpWD+8b/yQJrw7p76EBHybWrhBWYt7RVYRqa250hP672wTOIDhq3aWWg4gS9u7tjLqOYPgTPEGDA sN69e8fcRuUkLlMSx0HJKYR9aEvNYyX9RWzzZ0FdJ2fJSI3kEb28hlWq9OVna5qiTx7VjOZQJXqt JjDX5nAc8s8YsGobQTCzMEbbLXhiYN0fCdxroDs0Ma2Wc51rTJTaTe712evhZtVHrWaOQyRxMYLL Z0zJ8vPHaGDn+lSO40M3NL4Op9C/1WvpVG1WrnHaA3FFo7EQI5QwXhrChMIR1HA04XcmKfsD4Ppj TcJonp1bA1EJ0DXQKAwATiLpEu4M02BpX480BS30Sn8bnS6X18uTBdZ22hMw3MAN2lTSpkk2XAed TJ2Wd9fgWV6+3STlYOGS+iAcZk/QzJxGYraff/6Zz35BHiCMrJEfP35kihdgXWsCjyiSp0FxhzlL s9v5VrQxfy4lfnkTo5BbDri56L+BwPJ2Sa0+t6AV0dNQGw3bwdR3wBz358C/M+ZFT5Gz+RMr5mh8 2rxJIEMFq/WQx/dwLfOcYIhzozRNzo1FueGcP9esZUUNK57rPoH1WCb6LBDsbxY3UY8103AzhS08 ttDUwQ3UYqpLwLfKcguphuL1upmrtIHL4T3l9ZUmsL+HFqGSPDacK4HyAi87E/g57wrZOrTqkWvl rnQofKMmZbne/Lns/tNNwvEgW5R2ajYsEw/bu0ow4UbpDgdpd4pXaSCweqDU1cttcnUCRkFwfX1N 7YqMcMOrGHLSNBRSt7e3ud4aQbyQm4rUhkwZ0Ni6DCuZBCsh2fLmnduZ4+RYtiCoHhkn9RItTrr4 2ie4Fps1Dy53xiXfBmEcTOsDIHiAduUasY6c8tOc8Q6trZXtZisVmPlIczF++eo+ozHzRcjkWm4c 6F9sEV/xhRGPe6ohPawv54TW17YIX0BGoVIT6Tep1VhV0AOJD2GBu/OmKo6hXECNCHF8TIVVrtqb jg/uTyngS7wpXv8ssEBbgcQllK7ZRi1ETZNOgnZhGj2uEUHWXPogHuN69o8at6fTGqqtHLAjwDsE bxF2bGQiBEenHuX2oK5nujbhsIXmhWtrMQkbqfbAvSBoAK7PQgmDfnv7RT5/1gkPk88nYtxN8H2k xsXf0LbwPfxNDlbbylU753zqGOCsNnVlhFWffJg4nl7XC5Py+piAD+YsAjk1HxCuBVrddruR/qC8 IrK/GePo2UqRs8vwHL/JPhEiM3wuvfx1rdYkaBo5P5c9w86N9262H+XQ7ZElXjZXOhbdfpDurqdq Xl9dyV//+leOG67Zy5LhGdd4QNbTqmYQK0y/H67fSZUO0nVHEl2rGrGOGqbDS8UmBE4bSLAN8h5p //xeUeuNf69cUlwcO+Qko2mIHFvD0tQHAXm6kX7YM+oAMXpc9CxIgeR+tRzG25zVFaa6ZifFPML9 1Q1shgLmO6T9QB6yWO4t5InLxNiQKvf0QiQhhfW0k0mume3WYxkbuZE6fZB+/Jvmw0eGDxAs6XkF 4F7JCNJvj+rjk6Qe/CadM22zlU2zY9gVrgnpn3tivMC+1PkBYUdBj8wekfxZVFWCx55B8pbZBwH4 HoqFz2/STdam1UzV+MBhOpCjdVP/wHWmcEGiloi5c+jvOH+QTQQ8LygeWFdYY/jutm7kOBxF6t9Z mmUlSdNrCsoB743Gv0YB+WSB5SEtSFcM7xtph4wfUQLgFcwDLGiSxpDiAsRIZVJWmATZ2+PBtZ7E XhnkP/30U54ga1iUTlAVLhgQLy7AbAfbLQev1Cwegj2UeZgivoVFqWYpFOJtANuXJuJTANCHtjwJ CQ1qdtRZy9A6i4iGZBI100CBCX7++Vc57jtpthsKLEwojCMEvT9j/O6OB2lbmIS97K62Ws8R0RGI BYUZgKSLAROLY1zm8V7TVi5fn3t9I9VkJsdCkGWTEVk1SCnRAh3MxsG5YeBu5nL5AoB2c/8SQPLG NUjAPZROsly7vmg5zPPNy9BrBgqMbSy+q/2bPZg8h1kQYlQAeE5nbXMeY0+BHPvrSV8186rKYo6X aWXIAaJedO9bdCLpZ0R0zJPsebTUeab9iJaN59J34rY7zPzz0qnFYsSKxMuEFEv04hsuPCIkzsxC G44nC6yxBnYEYr8G4KKiDfQsFCbA5Nkm0MNVk8C1N5SaGqsEiXwMxLPSc4cL//d///fFJCibvw/z 0HdwHxSnOcQBKpnREfQvw0oUo7A4L+eb0JU7J9yrW2X66nmNAWyawKJuwj3geNkeLkwNCPcdkTnO W2KKes9V4zj2MOks20SY3KxmDSEDHIXcPn3G7zGBMJGmPSaaOie6emQwOI4L7JFZQ3MesBmf8H4p KfLUde7j8ZCNw8d5KSzmBzRzOncstTSv7f+n7k2bZEmOqz2vvXq7yywAwe0lZTSKrz7qi0z//09I ZhKMpEgQBDBzt16qKmuRPee4Z0ZlV98ZEJiFOWh03+6qrMzICA/348ePn1z/6X6JNlj+/bm2OM+L 2taXDt5j2fchq9cbq9wAvMmedyq6BB+cP2DGxfNDlQKlcy/vP+9V4fnQuUgh1iTx3gZjLG+1fjbl ZMi+UXVRlQOlZVDgv6doUzJTd9nMf40v/LDsz9njVVJqHeoS+V7rDaeBA2+qmtdWBrkSWuNnOtSj Zpa6nnFf9WCj+qd7WJThqJ8fIZfgWVljWXSs8D45U0S7yaYmpCLzqQtyD/q+ZMHkMld2z2fL+Prr m2eTqD1KF7p2+LLkZdVr92ozW+33S7vguWekVhS5q/s8xdSt19ZOR5Gy0rgFNJfS4ujaX1qolzCE l+67/7fSxl6conqoCYCxDS64JgqTh7WJx4VxjzvIvHN1j+FcNzceZ17LhJO0rki/K33fHruYL2ex Wl67VIhnPrHe2Rjkbr0rSlf+JA8rN7TCQaqpRWnIs0HWvYOl2QN2iAEXrB3LnlrThIF1PeNrG57v 7MLzKAOWhe4XnuswLxxyeWE7AlHNXtaDKgN7JEowBjTgn+5S08rnRAozDl7dkH3za1ovNDE85OXy 5/b59BtXhsntvbceckfxvtrepYJulWhRRXSMeNo+9U1AynjW2murVMrj4qs0tjQn5+DeaOI52SOe X/VRmLKBnlMf/nSDZQXjofGpyGMI4/GvWdyr+PUUcyYvrbqwklJecEy+vrB71qCXazk+2oXckkpb w9WCrmM3dGwY6vNaD6uuCTWFM2MmbpE6ctbV5EQxWdR6V07VFmA6Dina+/0chjMGyi8teNtDN+uk DlIE0EBRwcmO7XbTkGmH89eOWLtijWOF0D2fqmk3Xu8lowXWQQMNEi0vcd3q92MDNd4YPnuUxHKF 5SXkmF5lFY6fcoF7LuLlE7a6/GKMPVVR7+d0nC7NifHh83pRtq9p3/NE0qIyYjUPwU+V3vd4I/Oi BiR5bc+eVV+/d8hwDs+MTeo8FHcCJCk7yYU6xfMsYo/JscnucSQM3BM5VKkZ1yrGPcB/zuWjDOt5 tpKkl/sQuF1eGaIeq8omLRU21s8cePho2fv63Z2qisMtgSRA7s9ssBpjJQGXfgL7d1tib1VqH2Mh L8TGa8qF0/Fkvk7Qz+6gGA+ajIQYLLruexmseigVQ9fBwJXVr9e02abv8rDgkfh3xYivzraj5gTa 3bssjH5ec3dp4V66p7FBfQkHGxag/t+PWp6shJwTrJw4kYAntKCphq9hu93Fp0+f4ttv36ny4OP9 p9gdvPsxnkxAvmux7I4xXy4kJre6XsV6v1QhOI0JFmTwkgg8NlaXvMXxfb1ksM+PtlZtuO8yWG5u wSYx1K9xrfxOCZPGmxr6AQ7UgpfHtTbO4bPHrznXJhuM1dibcdiOXFGGTxOQI4QhAavNrwIPgsdo w+xzj49Tfx+VofNrBqoAG1ORehPjFWRz7qmXLhsY57R7EpdL3XOyxlYYGeaRsAk1k9QfG+7VIar4 d7nZlZfF+0kCMO8qeTWE70PUU0kuhcMpxKmoQM81Q0NhXClrnmP9pxusVhstwUQZnX6MUqImy2FY TpBNpSfVKDG2YHhrgDpkHy5wYup7eVOXGNF1nnaH9XUObmr7+4s7bj2sNKIM8NniKyJj9eEjROvB zfPhrfv7PiHRS4ZqfDjir5HNlmD8ITWo24VaXaJVFL5ei3C7vrtBWESgu3b7rlN4WFy37dNGuzn3 t1zNYjmfxRKwWwCoM1rjRXtmfC94VJc82ZcODGp/LgNGOS45TspL23sx9OYwiseFPA/ZKNOlBjD5 +3iB/ecfNmceir8GSgQYyyWPeNgIB7yp1f3y5Tg8qsSAiLtnYonDeV1rOMl7bs/5nKfWzs/npU2V dCgMi6TYSljfceJNihIt44+8lggDyguelvHo1uhjlNjoMFJ4U5WwKSGCS9ytOgb8eEi88efq/KXx TcNbXuefwcMaMjceTFvIfqdCoEHqoJNYzGaxDhqi8m/cT+qkzmv/xl5PuZm9GzsCNWthjQ1SueFt Bqb+dik0HP/cu6DzjNmzV1mBrG0ZRI5EypL4/n08lx75Li/rpev43Hu0bGsS1WdIq2sYU9x9KCUs kOvrm7hd38QXb76M4/Uy1rc3vZFismHICgvcd0/CxXYdlQYRN7dX8t92O3vI2254VjVBz+7zGSY0 8iS/4/5az7h937BhlGdhSSIbFrA7k1lp2NFvaBc8jZeeTc3B/d70AHBCz6XBaF3a5NrzjI1WT5po OujI8x0D6Oq+BDbF3G+8tmmNafWpPO9zOPaChtfaSHlMhlZvfp27Z5ekko0j14Qx6UTNsYAmRGDg ArexA6flnBipwqbKy2qdhfGYnj375PiTvFGiRwTmgliSHJsNcVxF8WfwsNz2qvVgzws81Rb+tIur 6SFerzFWh9h329ghLzyZxcN8FRN2GRbBobrHJSi36SJm2RfvjB1rDo9cS95Dg9VUrqzyDVzhFaU7 cn13cZjeR3d8iB2Df5zHYnodcwivq4VwDmJ1pW9JrWqTnsVhOo/l4S9iH0/RHe/jGJvEEa4NQgYd dQ7CSgSpQvpDblluPw9oHwsaUkgmpFLZlbp2e6zJ0bvSJdyNzB734ezKfmhmKcwm08V0oObeZ3Dc drHd0yLeio7gGA8PnWswV2RR16Ij3B821oJfT+L6FPHqhqxOF7Q5jMU84rDxc1BCiFZdEHiNhXQA +NqajTfM1IvQ0tGKxkpxILX7CX9mFaLnoq1/e9pwbw7Zea/Hwc8fe7Kee7dXrWrSGcooG8hNjFE4 9SSOSvI4FU5CAHno0m+fTjM8Qtl1xuftY0VXpCwCZ2yZB9A+/D500IpGsFAyyeqgbnEF7rSdwTXL eZefU0KGdD6KeIydwutpLFa+P0ENx50y6ZykLzwXH+lcehj+H+PRzn8OSSYtIOb6fNvNNjaPGydV lqaogBFtugf9TqFZTGKLcekMk3DO13evXPp22PS0oBPlUKfQpvbttxagXDSUIRX3s5EkP7KqUMp4 8zo+k++cG6NWIWCLk+LlSzpQzVRCFBs6gwtXZT2SyHvY9Uadz/zBOz8vFhgbbhRiHw+TjMMiJovs W6ZQMfkixDGQ5lIhFGd/mwJ8Tv8ObnJPfpNBc0hmY1A7oGP9OVwOics5HX868bCYCDupiR73A0fE u02xdvOazryooVV67ZB1vOQJAcT3Ui16Ybq/+b12oZfCEmEzTceYUqIsFVJ3rUEXbK+6O4VoyPto kh9jNj/FZE7I7TRnvyBY8IDykjh++RAg+x1lLkP4mt/LWKmRwmdP/+J926v67i4/L3nKw3drhytz Ws2C+wLSAYowzokBrCSNDdhcTHtr9vv+MqQS3yliBr43Y/74/o3BelM9Hh1Oco7ZkkWfhhp6CQRj MpmzlPTpM51DuHWpkH/sHTJ/e2+lETpsEyljBZMKQ6s6pMcTR1hk69nW+erfQ9XJAHM4gTDvs8wt XtWGiWV8C/uqv5cn3N5fXXO97wc3WKIvaKtGcJ5OuGQkhgtf9u681RkrZ6pdSNXrA7dleKity21k VcuvgFgxcl0XJ7VMuzsxkXtLnpds3iwmdJAWsG43ufTK7Z6y3RJSDGlid8MYDI0KU8d92SpS0TXy YNhNrBtU/Qftl7qT8qXeeud4Q6bqM9s4dHROIxtXun5CNHZ6T6ahV+FizSQWAc4gCfbGAAAgAElE QVT+rppcoCQ5jOnnjt4rGV3fYBDO+xy6ftD3qvttC3+bc7QY3fg62nNb3vryOXx959SFSz/bK/Vz G+ZOGZX6sucyeDDeJLW7CzOauzxJr0t1TzwtRQUYtGTNay5mWKPpbKMIO53noM3xQDcoSNRTkac9 l+qZv2yM26PWRJcbemuIasG3kEhrBPhdZfXGhmJs3PCCij/F9zowSl6LJosWjaFUVeT1Jc+vjFOV 13FPZQCBH8qAcbRrvDhdbdndD26wXBFh4/PE7k83GmgO0BpYULU4s7rf/BOnXOXsrNYXM3v9RM+M UAnmaXLNshsx/JEgA+K+g85WpnywZIdhSu9ix2AfKNo1pVUt6RWvDPiJNdRd11agZ7voLh2+xn0u 4jJ0TG7e7/KRY1Dbk75TwznRf1JcdtZRv9e4NOxmwtEjJUD83hsDYQgTpi8knz71IShdfCjhaJMN J3P8XjzG9zm+12FBeVzq57rGS63W2zHzRH1Oc+g3iQbUvnRcwpDawzI/cAb4vGpzlbWPsdeiGjZD bygKTacs6tSvl+HkexrRXpIHLM9egr2MMgjuSA5HjM2kp/zs8UKwYtoWz7oHDZ5NUxjdeDg1ZpML Y9Fu5u3rZSgznGo3+Rr3InWOjUR7PTc3ruUtY1U4ZxkftcpLA8V7azzHXlPdT3litTG0GF69poyu nJb8XEFEGOf4oY8c/L28E3aVlCdRc1IbKS5XpH/9oNSAcCkNOjH16KG2A19kOg0ALn7uoh4kLDIa 7kwdg66UCMWcWHkljsqB1lqTRexlPJYyVgtJfLgph1NtPFDEBs1XUbg18o6eXVc9g6wdMwhaOFUa PJC7UpJoKtPPPCyFpfVZJhqqiWmGzWB/xP1ojwk3oZ5MCyYXwDSxLgwW2ETqkPeu+QXaSHu0lQDj e9VtymOslucN/SMxre+j1tCHJT2xs810vZwcGf/7YkidDRemUpjI0EQCi9Uyzc/GzT/IcLGYUns8 tfq13bj2qTEiyELTnICWcPDyDDn4mpw+l556xsTqPC5PjjAbDBVKCOc499DL46tj7EFORhnBwVg+ Fxcsxnk7ni0pdFzl0YaDtabq7+XlFBZVQDtjx99Ud7rd9gatxWLH7y+DNc5stuNQ1wAGVh6kSKfx YxxIz+BTAa6mUcI8SLAsBeCU6tWkwH8/72wyJn+2N3rAvS4egfop1k5vlu9+AggNiAcPhpIVBg66 6lXsTxQs74Vl7UGcKSM6UEB6ijW8sSyZ8GeCoQ3YWTuwL4WElVGp5hJcm70rY2zjDjDt+Xqjxfhk aUZJLvdZlH5BGoSVtxn76PYD2x+s0KC1cZmqQ4Nkqve3siUXjjHHpsXcOEwuNUm1wOFJ/wx5ts+z uO2/WwylNVh1tJ/5xxzDOCapV5jfJL0r2qYZ15uLZT1UMLTNTMADEdFzS3fPqRhl+lbzpRo5aC7u DCZXa3Y17NDYpRfBBkPzlOUqVtOVPC2a8Z6XpJ1zvtpM5nRU+F+/G8/B8n5Y6BA72zGuMa2jwsYK 69pSqDJKfVibRc4YpsH4DYazsCvzqwYFlfKa+F7nlPedRfZjL7INL9uSO44f3GCVDaLfH0xZkedU sZJpWaVIh7lgcl1T5jGqMm/1dGxM5ubCsEyk305GZKmec+yNyvDFTiEX5brsjHRKORzncTgymdZx miGBATPaxZfoeE0XlHYMk68MTTthTFa8nA7v7x/j2HdMrlZlCQZTd1j3XWFf+11zfN60Y1IuNSU9 /DqyTZ7IblpAZrHXkxfGluVPMlbZgWg/iSeyidxn06Hm0nGaDxrqhYe04095jwmbOT69QeY76ZOh O/Zz7zjHqBasKAouYblktJ5d24XzvfQZtYG0Cx0jb7G59AWz1tIelxco2UJjkIldpQE0AbHOBSXA BFDGniyony8bUi6x9NKNZy2FX3W7Y+xTkVMimGa9nhmWMVfw2SbeeGNjoL7wo/b9BczXmBfO1BqN MlpjD6w2rrHX1oZ3bajJe1oAvjytOneFh4WH1bnKWPF3KDj1+x8Jw3IrKrcEZJFXXzIMFl5VDkDt 3AmIViDfqg+0mkg1MNQbqsUWk0GNJazHQwGNvHSxik+xRx5Gk9ZV5t1+Gt1hEterZRxJnUtCxfOQ dHeHh5JNVT0ZhgftB+aHckkhrfW0qrlq31BSb6+/P/ewnn/PYlOFWm7k4eanCRLTDEK6SJnBQr4H 7C5DnCeyw6qI93mY491mF4+fHkX2mx4+36Pv9S+vz3bxlwzPmaeUYaLCjO9wjNr3DdStISSuwuCX js8Zq3ZR4RHBDCncsxYgTH5/tp+Rau+kpLoSmfbT/XbkDRsbRUKJ8xz2szgoSzhAFn1Gaz4TBcQY 5vn9HjpjMl22SmND9/s8ay6FanW0IVsN8Njzb41WGYH6fev5lAfXY55NVpLXFz7V4sgtIZuWcUVT KIWUChnLK6ssfHldHAXCt5thez0cZVBrDHTt8QMfp5UbTbBQYS3N4GGdjrGFcrBexnybO3BmBEud UBODkhIIkE0YooE3whST+TpOLDhxpk6B6hPF1nCDlvTfm8/i8emdekp303Xsjqs4xhXtW51mnkZs Dkj+Z6pWnhD+C3kfZ4cO3UcbSmEZTOih2JWygU4ia6momAxoD256YdNqD1+F0N6tq3XV9LT6vMcQ D85CiUh3NEVBTS+906/WX8pIHY6bOJ42wgmFwB0WsT9MYqXQx667y4ymElW8ma9isbMmWDtBatLU LjfmiLWeriaSxoPFs5UNrUqAaj9FlrE9f/vdP+f9V6uxsyJq7rP1ps/Dmtp5P8+kbxQ8eLZE/lIQ MaMaVoIzrtbiR21mOYMbNxegDjYIefKQUr9nWAt8t/khjoSHs0msbvAwZsIUVdcBD2uyi27/FMfd LE5z89X2PKcDdJtjTFdbNy8GiD+RoV5l1MDrqL91lkxZtc0ON0aGlDD0/uk+pjc8c68HmiG7vIa2 YXz2JHZ7DOIiljP6bzKO1DVQ1PwQx8M2btZfCZfdb4fnLSAc2sXuYBHO/Pz7jx91/1998YUMybtv vonXr1/r74z5fudQ8fb6qi+4r/CxvD0OjFp5VxW+lndWnlTroVUY+aN4WCnFpAmpTs3HqTQGVdpx Uonq2QREsdQFmAY7n9JN10JXy/hkcRej3DQbeQ7I9ffYkRql0gySBaEG9zEBN4CxmwW1doRy55TS hBUlaNBK7aPraZ8vsrNDCwKMqDhOSZosqmjDivZnDm3J/e8WlB4SCXW0O5/rFc/T/NWtRJ6r8MBU pciM5HnH6OGcVTF/s7ruf9/urL3BylT5JdzO7P/2mpI8KeY98kJ/HO50cXgvYF1jD6r9++fwwPZv bfg0PIMm3C+6zYXH3l7Di/OiwZf6TUxky+T3ZdmUvKTi5qU4gygOmexhQ0yRh5AS6QRjwwZFIolq gxJFzOdwxDiwSRFttJuhN5Yy3Aguco7V2jLKnFv34tyQvqYLohDtQl6TtXERFuZ3RUZm9NbgeENr OFPts2s9OFdd2INvgfzCw/jiObTe44+TJUzsgL2fHROPppPDAK0hXVL1BqnkODu/3fj76tzLLiJF RBuCAXphwiFqkxyWlEG2bA0P/CqOk7kygXTJ5VMY4EPia+6XeFKZCYnJNZ1+EL4TUDvI745313oQ CdA1331NhVhVnVhN3GceQinRjMKr3ovLnckGa3ye8taGziRFnB1rcRV+M9bWLsPVXlOdXwvuMyVC Xojb3kibnGlagK8BVYfdnzZ9XsCy2nFosUWNfkM+bI3GpQMQfvDM6vlVlvkoGs6lz29/115ri5G1 GND4uote02XFkGcJyZCKJvLahIEN5W9HSqz23RAuHyFv7p1gwoPSlj7TZj09nmK5ZMPhHMZ4wZHB FsFvgUZ8WblI+5Znrp6A1gE/EfVYzxl7UiLSStLZpUNVC1j4X2Vda84NAH0RdO0VFwMeaKIduzbB U/LoPT8ufuDDYVIpneMGo6OU+aBjxAYlQxkPQjHn04RAWZAxttkfnodpcJ5FMDghp2zfbS+O97Pr 5AQ+AKKnNK3CAHaGfKuKla1KRGzA26l1pPEqBisOnaR+/T5/YB9a9BPVqgxWbCyjZbe/Jv94wfgB DuNTbdHHx6WNe5j4Q5jUdU+mbQgnGHAfv34AsMl4+aETSg8AeisAN9yXf6/PaJ/lqAsRX7udeVTK ziZVQ1mxnFoHZHD/hOP7eDJjo1DvG793bJh7jFUVDilvIjkXvBVvBOMs3EvXd+k1FQrJQ4U83Tfx rS7bEJfLM0lCZQIe4svtD7FKpQxJwQSkU3UpdmZvKfW5vEayubzOiQEyoVCHltNXvaLosGEt3JqP zU1GzLQXzW9xF71OKCXaExZhGNP704xg48TILub971Qorc8lkZNRQdPXqMWhxlnM2liKJMpR3lbV CjM2+nv8wEdfJJrAppygKj8UxcFW2trabii5B9AU7SFiV8SyDP0qo9jjmMehcl1NJxNYVoYQHECa AgR7hIJDeMpxyOyMsVSHg7xSrGUeHZMg5S3GpQJV4K0C1bwYL9j0Ui6Us/Tv/SNS9Ofh30BQ7LNE gOxNYqCKs+voSzh6WeDTiyS9Mf6jna0pYq2J1YaHVfdHNqwvl2qUKf/U5tffZajan1vvsI5xwmD8 +iOKmsWvKnUNJVScaW3Lqi4ZxZZrNA47Wy9QCzY3av0+e3VOVMBpBQaXhLlxijyp4z7uVh7fg/hj nZ8BYgJzg/rdfpCTgSJ0QB028Tg1gqHrUQMruKYwOxplq3v0+lv6wvRgyEDYUtFfjufYkhnuQ7mT vdIBXK/xgHPWPosWj6wynuJtVQ1iUSMM6mcbsx+rNKc9KlJJ58RHuo7uX2A9LNe8OI53engIcVKF YjCExToWV8a7FtQIhY6AidKKxoAMOgptOHkQyOlyIU04PBEVNO+VWUTHqF0Mz1zc0nFR2GevzZMa t5dwrnEH8xjOM9AYXgo1LhmZnjkN+Q5sVdph5Z8myTQJiRYpeI6j9aHJ7DzzM/4CwxpnqdqQiyxt +p89fmb8ZYzP/deOcX3Z5zCr8fvG+OMlw+OESVUv2HgPjP2B/9eOf3uuVkZlfC0VygDE85+enUJ7 zzEy0BT+13LQPebiB1MSrjSDIU/zlJ04W74qS+rY+Hkt+BrmqiqBm1hJH8nt6D7KmJgKxHzB4ea8 HQZLJFcnIlREHgcV7mvz1sZlL0zPIHWzSDT4e+JiE5pTWAFXFBoZs8XZmmmpMfyb4mm8rPKmKmTk u73Twdj+KKC7RNTOQhyDjhx4UAxsf6QHdRQ/weUNU2lK2wXtZTX6gCN5xKntU90AOSVmBHLgaWY+ kgH7BhaWtciMDgOjc6NZDgvan8cjdFJgiMc9obOhp94D+xzmLuJ9FvDTuSlK1q7TUBqeFToPMiBj fKsfkkbgX2qn8oiGheRWUJSSoGvEbm3tqhK1axeuxqvlkakJyLkiZ/v32k1bsHTswZDMcFspZ6is W8GYnYea/9WjHbexUW3LPsZGvfUq6u+XrkdZzQKck8+nc/C7zMd8Liyt9P3YgA7GaqANyOuusdJ4 8Td3W2JNkOnGfFFiJZoqoSCdnjoAaRazPSTNU/3Oz0ULO1eEsoSYx+TcIT4gY6VSNcJEb2il8Nl1 7jDF0StJyNsySD+VGkcjxaOaydS2m+LhQVuyioM8tQNsR0Lgqme9Gjh7DY9rwA3PDRJHy9kqD/ZH 5GGVprvDLaXmk8+iVlSH5RDeDarDHnxULZVFyXhbM8j65TC05QFwj8ThVQSSs4z3ag+asoRYSDY/ 1TzXnaeVI7QnnufUg0rcTd9Hxc1j8Lx03MtYyWC5ONCphARN/ZCGcfF5mGyfJ27WazWp+k7ZwyKi 9ZjgEZIHma6vcedacNvb84wN2EvHGMtqSyxqYpfRLw11X5JT5z2tISfof/VoMcCx4RiD2e2111eL 0Y1DNr3mgj5/H9oLO/q80b1E7Kxr7ed+sb4TkpDCprLKbOjD+5mT8LEkn6yIYaFWWHyRGZwq9ecC a34nD1dtt8y1cs3j7Ezj6nQyaA0Btkiw2qjh43VgxDZIeq5gYilrJAPBCpraiLReZO/p0mIMysbU RhtPDS+MMFBUnkaNpMb3EiZYfK1itVc9oqgS2bWo4IsfXl6mFxIzrmS2th5PuoxNEU7dh+p3/Jpj hRlVye60VSnAxG6REzE3APAT4ejZ9fkgHgtqjdn0k47TaFYRKhJKbfdq+tnNI572x1hMDnELZwww dvsU2zkKDkU+bMBaSmBO+3javnc4tqTIeiUDDHZg1vYspocn61HNvchda1WTgNo1M9WdGSlcpDWI NlTVHy99Rxk6KZou3ERC5UfQEFJ5VM0oZldi9GNMSGqIqmH6e+Jfx9jJQ2vSznYlLxIQ63dtjVkX 25iv4A+xaDBULkEqI6uUhULDytiBG/Fewo1FnDC4lQDIcanMpagVnRdDSf2W8ewNmBZ2eoejBqoK 144UgheGJOEie5+5SclD1v7yFEe4SW0J2GytBVKfWZ5ILd7iDtUiHHvRuu7VXKHTSUkc19Iyj+Bu 4aSr+L+kloEj2DBbnttxH/MFNaLOqLnZibs5Keqa28BQ8QCOiKFazNaiJPAz2Pt8sdRmvN19ioNq H6mWeIrtcRPX1yuFZJvHh9jvrOCwwMOTrntI3qktUG49oXpWNWYFpLcbXTffx3yNlhga7k/yKmlt hiLKcQ8nzIX6vJ5sIUYLMUnGmjpCj7Gfr9ZR/Dc5ngPYuUuK0T1gNLXeCrc57vzdXekrtBgwBhZU G5VWqyh/Jos/T6j/ZaayAWJJ7Q4PyCEwh1O/TNSX78cLy0FqVekP9qKRtelf/5yRjBvuX2TomYXW ZWxMiygW9pDd7OvAvgNmugRUj4/Bg/E1OGw2+H7sWPhZ20nxNZI/qkZwFxZwl/KCKFkp46V6tOPp rIHuJYPVnRBVTONV7jPXiSdeP1/KHjaKp+Mwtz2eGcjGkPs5X/ZYh7C0CVkbz7htpTX2INvzt2ee jDxBX58LrAuHq8/0mG5lKCUkkN1xmJOLBWPvEH7fnWK5uInF3O3RNpttL+uC4dh8dBZvDFm0XlMf AVxg3O92NLLNzXpb9Bs0xLKVfeFgo3nWcgV7+OLHYLr/OY4hEzEs6BrE+8ehzRBHWx4x7HzZG3GE iXiHzokju+FQwG4zpT5oPWQWrtLPWd1feu08aKdgcdF9sSoPUsF3qkOMeENtJm4c0oyJoS1p8zIO luGyfiosJfW61Chg4IE9H4PsXPziuH936EjOCSzy1FjrIq3KIEnuxu2btMMilT2Hqe3mI+zm7KR4 DsvllfsoqnGIvbgqOh6wzqyHTE4acjo9BaPnoVWJC92nm9ZZF8D5eiaXwkWOVgNqnAipMpdL4zaM XcORS8M6fN5QitIaq/HzvXxeH13njczP28w8jwX0bLyYp5juCa2Q0rHSaNf5mgi9bq5fJ7VGQZzb 683NkVqvl3F8f26sx3O23UTq7+1cPsajq0aYHsLq3OziUFm/kYpEnbeijlaf67+NwXqO/wy70G9/ +58Zcg2uaGuwXr26y3dl+jgfrBcvk58ecfZypE+FjpGaaKAUuQx60Zv5VO/Fhc126DGNrSR+bTQM UroQWddJGPQC2XAAjs9VEEZ76sjDamvLPA6SvREWWuVF7glZCgHGMWpBj6/Buu/tJHwJE7r03T+b wuBEgDOjYIUij9JpZ3ITqxVGpYsOPS4MAPXcTqRaDqcvjZopLNo+bRXmKOW921+UVimuI63RyRRD AQBYVnF5b4St1VRE0PJKqwmDPNBmtMdeTrvJjBdqG/aNMbJL46T5KuB78PDGc2I8N8bH5MJ5PR7t RpZobs6Hw+FJeBk6XBgolGn5+G5n6sDmli43j/LU1+t5XN+sYrVaxG63iffvzaGrtVbeZJvsGF93 K9DnUp+EcHKNoitGwTwyThU1FCba9hRt768d4/82Buul483bL3t1yLG1141mK/X2qOeth5wGQmTU zETyM1lFdu9TOHTx68vt5rP88PbbQZZZMs7pESF/a1D0eZfb1mMi0zI2Ej0mM0rNjyeMfqbQu8io vTy0+yb2jQjy6K+h//n5Dt7+3C7Wlw41PBek4kaYfGdHnU9Tx+ywCDLmrgk0jsiiUReWCX/LpgtQ UDpLlzw+0KlnHsubdTztLUCoSY8nnYoHw/3sqqXp0DC0WcB+re/DVIKxR/P8nloPqx3z9jmNPeFL 3lC91l9V/J/Z1qzMuBRyX/Jixued5HezzcsgD/pbRYKt68bLPV1ZFQFGvM+xsob76RCL01wGC69K iSDp1Q16W+21jK+vrTct49J7Rkq+2hMlFJ0egSjczqvvSF2F6Ll2+xZz6cHWORUmxn+TY8y5rIfx 5ss3PUZVm69lPrK+cOtd1lX/NdlKe5u4HhDTXK7MbMcJ0B8PYTaNq+lrZx7PiIKQ+NK9ZvEBgNLE lMhH5SypeMrkRKL5BQ6QDzcHyLvLxXZuoBySpvxwMt1lOJXlTKa/LpGsq78j3OeQ91xipMXwvJDP p8BLC6X9W3sQDsqL1Au4l0Uspiun2XWpc0kE8VmrBaVRlk1GRHC1XMaOzsH53FB/3W4e9X25wDjx Nrfwcip97mbafesqyXH0xrJqNPt7IJGvyX8ps1je1MvGuBbJmWd3wRhdGp9LoWcPrieeNR7bS5vD +N+nJqQcb17+fTVr9Xt3m2olRtH0Mq6uIKEOBne9uovp9M4RygQv7Cm2uyfhj3hap91zdY5xCFeG auwwyAgRvku/vvBiZywt989iM7t9HAKOx7cwrf8WBqtJXPVHDdg333w443nU75mouLx//Rdf5WAO oaQ9opwMZm/KUOkhswNkobU8qUMaFLVIJ3xksCG57ZJ5PHTa5XXWorLMs5R5R6U5lybg+KgJ0QqX XSIwVkhZ3pKxtzqvPRqYgC1wrL/1eM9Rlfaf86I+510Nr2HcOS9jBqBenW9MPBUpcWIdcMYFL4qS nfn8OjZPVgiQt7q3cVkunVV1Qa+lUXwPNnxVmCxweE3lv73K8aLnPfcPH5QV1oLM+M9eWD2A82fR Lpaxobo0/mNuWHue84U+wh6b310696X5chrhbf5+Dv4PYaGN0nZziOMCuZyIxbI8e4sZugM2mbuJ kiOA7uCJkh2SJ7ZS89xzjPB5b4Vad62WVZXabMHPWCP7Y2wnO3lWu24nvFPPRHPmXGurHc/2fD8K reHPdYx3sjI4FSu30hi8tqQthknS7koMshd1ZfXOPywX/mSmMMX6SW1mxyS8I6nkcLq9GkHqwbKv qB/eYEDa46Ud+vk9Pgfkxzt9n0kp8TnqKBP7qvEZc4UGT/Ggrl7j66qfLy2ml44ynsW45kuCeIhQ q/t0F4slE3AXDw+f9Duly+kcI5Ij9aOnWNKCXRghgPFOPCNV+PRNSuzRupU6hguDpSvo22sNhsSt 1CniBUQWVpbUlF5rPnv0fZdhfmksWmxn/Pp2k3lmDJv3f24TG/PYTs88N8Z+wGw14tn8wsSerHHt P8+bbRGcX9290RjRJoznR0gItUDvP54L7vXXPoIpLnXqqbpAyuP0ey00qB2EfFsLD2TCqi2/qfPW Z7ScLNNbjo9xZHJRE1cZMzqBoFSAtENc9wmyQp+rXSgDMu8VCn7Y4/lD9fe/+fqLz79PhsdFndOZ ZZIJCQ8780zoJah5zIthCBw6KY3CWaJ/ItX6cJucSKG0gsVzjG56iN3iEDezVzZM0j16jAnqBUzi IGZHAWyltDLGYddJWEfNWbFv2jnm7krCIK+XS4dNGNIODtIhDnPvMC3fp0BJ/r3au5GlMj244AgV spCn6IJBEHyUlngRC+VWI7PTLJyzr5G3tUNtIXvuUdQqwHQK7yqxpOO8L1BdJrAqdvYuy0jwkNBd IkW+2cTV+nU83HexXtFp+hCPT9u4EiOb1m+rWC3ddKQaGlxd3cb+4SE2T1lbtjfJsbCOm4mNUXWp ZtOSXtR8ps9DF42r77a7CBVqGzpwr75JbHKjE30PL1lNZwlBff1X05umDdxzEUmusZVI0Tiklro9 FUTt1sq8dZtuaFuHNDOdeOBZwRMcCdj1Ydaob8Bp9GXPw9ngGpPKAopCcsV8w25RV5ieNu+Zepw/ PXKN81irN6XnZCuNPD/ggeMI+JnwOzDIIQx8nkFsqTdT+jjkXN/k+xYUdPNMjoe4kjS51VbIKQJx MJfpnci9LKY3vSNiDIv0MRYJaV3RaD1zMWCWfrXTmdBJXw9oz+HHMVZ/yiHh/5TNMMZXEswOAbPv qiw+/4ZwucbMMLASJHatIGS/dnOrCQuQqzo6tRVrgXFP7O0OiZrWkU2XoZeINnA+tJNnZ3uZ5jAG 3wcPbgywO1Xd8q/aEpLv4z1pQSQRV1LCNPxsusqUQkXLfC9vtwxsGZdy62tRl1b8F198cVZHdqlz cBmKuvYyZny15TH1/rr2c9qDGybguVn6hIadJzcjzY42GKl9Eue4tTYkH4/L52oW6+ifZ4Z/tch7 ryQ13sce2pl31pRXTUcNJAae3fGZEav3Y8zHnvrZ/E0Psx3vIsXWPbTPlKMF2Yv4XPdaxupSwmgs z6xnq4XnNcm5wM/8fpNSK4NcxN35TG2PXG8HwxwPxAknmMGoHg4uK3+pjOy54fr5HtonYY6X4SkP wtlgG2EB2ic1nUC8z8bKbcHcoLWROW4aXAjUFxPdfeVaTMkTkh2buJ0HOY+lmmYO7bzV645FJq/H D0aV6wmK9ynwCxmkfhEfmuxV/zDOkwRFLGzd9/r7pVDoPDSdpTGHRCvWlf5fs0HV/uedXSosqOPh YdMbKLwsMBLIoGXA8ELoHIwhw1MhHGnbQBnvGmrLWmCW7+/fv5dHUyxrGyl/59zw6fad222VhK9C lf1OPf3UBanBtqgpxUvVQsk27+34j8foEhhfx0BBGYxu34U5eXDj5h7t+S5TVQEAACAASURBVKsa gaPN1nG0eFLrdbcbU2vQ2utoDUbrDdXRzpV6XUks1zOov5Wi6Pir3nPeaWhgw9dnG2+zQcRY2St1 P0Sx3NEvbCgP8yXgpvABq0dSXsjjKp7ecYYHptuwjG16Vd8Di/1ZHKpWRyerirCTDa60qtLLDuEo OCe8Xc5VzhsT6BBqX/9Ss9P0uLQ7pDFrwUjVJSpJl80xmLBu1Fr96Lg09KzgEmkh7ikerdqpy9mn 1lsxj4iJ7Kxk7jq+vmwD5tee73AtU3880Z6Nn9RTs2mIuFJq1KZMKgu7jkuGsJ34GCQ+nwnJdWNo mJQPD499O3MMGa+phIlJpMZEOEqJsjUAHz9+PKt3ZJKXF6dFeiC8JsSgzyWS1FAuaDhyjAOJk9PW IdqK7jdzyRjbc3anoVZN45Kn0hqS8d/9jLIRbpPp0oZFMf64CW/zOWPQvQzY6YK33WbWxryl8kxa o9+SXfE2Kwwce7Xn4P5AP2ihifZ17fMeMLvntJyz+TxBItrPDzUKKBDT+SKmwCZI5mwHvpeufzVH bWASc1B7sBncYvr1KYXufmz9QyuHCtyq/8fP+1DnaSFKZmRPkwsDCKyGFLNOmBHUk/VkGhJUlkQG E3afqgup5dVneGrg2S0cx+shSL3UXC6/h893Vx8MPfiPylWSFK4wq3AhMiLiKVF8DeHU19+rBzQ7 aekHcbDhlIign0mpTg5pdI7zcDDP/Zldp39f30PR/CqXKyWNQO7VecjGcYaxrYyxYajevXsXv//9 72WQMFj8DXxHVfjZ2652X86ljiud77UWe2EZVSxbIWerOFCvd688Qk+639iA67WdsR4ZUT1Trnen EhKFKMIw7S3TTfvSQnvJwzrLBI6O1ogrE90QScf4zyVw/jQKRdvrGodfw3Wcd3J+Hm6f66G1hqU+ t8XuKuSuML42kPE11fWqfvcCGbcPa8OYW70ekjHPrTxpyXk21zdXrHqg6DdifjzE8jiJ3alTS/mj RNksNWaJitRSl8REZuri52+wCHtXs4nuDcPA7ilwGtSOxgSkvfl7hnYG6ff6uzWuSmBwcJ1LCjiJ xjnpWyKhPZk5/loWM4uBzc6+a0Dc/M9SO+h42VipIPe4lybReKGUh1UTTlhSSvrmq3KinocZw4Jq PKsLY9ZOMIiJCmNTBaCMVS9aSCJj5A2UAbFheidjVV5U9awDu6JN+c3NrX7HxC/wvFLiGCRJXjce VruDF8DeZqc4anxk3NgUKHiveUtzBJQLKP/ZH2KqJimuczuSkaJX4QJg2ATKntc0Lul6NqbD78e1 d5cMWC1a9zx87u32v0vqw0ve1XHU9aY9d/2+SNX1+wrZPYbnXW3aAuYxp6oNEetvLSu9DSt7GCl7 VbbX1GJue6gOKYyAEu58uZJqhDDGPcX8w/s1H4VHYKymp1hOaHR6iuVpHzsyVcifHGkecYgONUM6 5+KhqH2TGc4/d17E5MCix3s6xPUCZrnZ7R0eDZ5Rd4glk5R+hprs+9gettj96OJA64o0VC7p6DEh YVHOQFbpi6Rz0vOyrvlMjG+5zlxMKjy6e7NDtcmJdPugIiqjIzWJk9jydFLRfVwoDh12wpxI7S5W GvcXwowWV1BjhM94WjJUyZoGcBeGl7r8moS9PLMnI8bn06dP8fDwoIXx6dNHfcewMOl/9atf6XXg WaIaTGcyZm3pTFFTKsQbe4lloIoRXcar9fB6hvT0EMsVnhN8Irxq45KM72ptmRWyg+565LpLPPA9 BpCxeaGO86UQcWxczhZ5elT1OuM45x7O+DxAGGOscdJsDIUFtb9rDQdGt/fqRhpd43CujFWNcXmt refXfqbD783Z+VsDV+Fvna+9rzpIdNBLtCd9szZULH05MTRHmVPVX+rWYa2dKYvpiFonTTgzdIlT bFIZFMxLH/xjS5b+Vw7kUzL7txSfyuKABHoyWtuDFuI8yZdMUoiOm8kujtNjLHuJ2KrfG7reiDbQ 7DZDRXzJBM8k9eHux97BFI5q0rruzpMG0t6wQ3lyXC46rcnT74TVdOL5jfcNJNrDIe0wycf4y9nr esVSPNG5WMpmJxeYPLQeLwwE4/PhwweFfPz8l3/5K03WX/7ylzJQb9+8jfcf3uvz4f+s124JVZm+ ujfOiWcmmscou1mAbmUa6z0VihRWowVF5+OgRMqcOLJiauW2xKAt48PDfazm81hfGeQlifK028Zm axXM2zvXol4KCV8yWC8ZtWEjGb5aUHz8Wm90581M62hfU7hUzcXCtCr8r6zeGBvzuA6/b1/jYumt PN2X8KxKXtTm0AL/1fWmstctj6sOGTI2ZWl3ueEFgoA4Q9psLtA85v+5O8j7uJke4pqJKQLfLPaq R8OKPab6fPEAhk62P0Y8+CjKAUJ+21gct+ptKG5KapRv4i6Os2UcFjS09HvmAOj7U0wPu/jlqjoj H1Uhrh6H6o5sg7BYkrFCCM/0Bww2t0h4TD+5R4n7u4mAiKbqUpNhC2UnieY7/Ur44R6CVgCdxSEo PWl2ODAROh/OnS2aqn8cnCsyWk/aLACzSMHTznyS17rPEEx6R2h0AX6TgLymezTcGut+FyFQnrNA f7Oh7VW42UIptyKlG8iKJJVCgZ88Q7A1lwLxbngzGJuHT/cGvufzePfhnYzJaT/tKQYqpt1s4tB1 8cWbN3HzV38VyytKPFaWUj6d4t37dwoz/UysngmznS8bnMJcWHh7cYaW8sSmsd2Ym8M4q+/ebBpf fvm6/2xhIMurxLlg7JziSHdndnDNixXgi42darfQa7uO+WQR3WYS26fHmC2mcb26kl4TXuIO6kTf 5QbunhVDZSQvFD6PvY1a/HjjgMhFWC1PElwQrPQErYJ5NE+ciB6JUpoc1CKiLS/KX7UAehmp8pK4 DjYNY62WG2ZcaoPha7WywWw3AK5rMDgt0fi84Jnfl3ZVm9ltcazWiBVVYvAup7E43YjjSAJCvDFh wibDMglnhEdV7UIbPoBeNDJ3qglTY3Sl2ulYy5DFZKWGjkwTZw/T/Syy5Q98iPM2iVixUKaLWOga m0lyUFtRi96V1nScFAb65p8Dpe0u44ecEiQSR0O7GvVQjIYpDMNDGzIf4921za704VojH1KvbQFq Zwbtmfk8XO+QbWRTAHT2zgy25Z3MO9oAfvYhaXtk+FnhXBVwnx9N6NJ7EaYueIdDo2oIz8y72ceH d+/iX//1X5UxvH3z+izc4NpevXqle6tdWmO1GBIVNRbGyAZZoEtjxAaBbDXa+mSTQBQ1oakkmEyl AJHtIrI5CRk+aztpQ0INoiUyKmM6PBfVJRJ+K7vq121FWjQbnLrI9vouzac6LnmrrWcoA1Z/ynFg vnmrzCxv9STMBTs+9/gYh4vjY4w7laEYq5u0nvtLWF3bsGTAo56LPLZ0jtZKjMelvfbnsIUP1mJp 7GNs58fTzFwlaZkTyjBg6J/TcSbiwM4okN2SK66/teKnPutP7IryXceMbjZBaEbPQCBsA+U1EAph 4UKRLMiBW5Ihol1X40aPjVV71GCxo4NzSOwffEtkzqaRaRI6B70pNwPQ7y6EbXhY242bCXjMXbQ8 /B2eGyz3Mb7knZBtxdSBKiexdI0noV+NS677SiPu+y0OTxUEl7FqJ3aFptnII8F0TeZSe0iVxwr3 KgQhlPvmm29kTL+OQWSP1/Az3YDlTb17d7HIt56Dz3neXr3FY2QghVMBzFq+2r+3QOJA7Gxbm3Eu rjcFDGUoh892iDQsrtly7t531DGqndVJFQ5ky+n6PF7YrT5ZS5Rs728cDtZhHCufs7Kr555YnbOd p+NzTF6gULTzuJ3r7fxvX1uGiWdZ7x1TEtrn0Z77vNxr2GCfP1t3VbpkwMf3Mx6n/lrloRlnFQ8L 4yR613HhpgVqEe/278fpTOB70bBs8FPq40dKD873GxmgxeyoUE99B7MVOgtxRekMWSAkMjAMsHun NEOdqg6tsizjXbIfXGrv5vmAMVhHiIqdyngk5N/QGcYg9vhoH2xruMaTuH1/37/wlO2Xcgfw55E5 UdGj/83GQXMMvIdST+2zWK53VHPMVHFsXe+22YW4WvmfGs42ZTnKA6pBwUBkLU/p/bfv+kmNYdqc nnqCX52bv1XGjq/b17cGX6eWEx6PXYVydYw9RTaPI4x0lc+g4OBQsj8HHlNKYFfXItrEGbylTrF0 l6ptmRsy1POiLT2v5XOqbZW9OEuyVHp9bLDGuNOleTCeE+3zcjNltxmrom4XQ7c0hJd5Q6eRasNL x/ha2gxd/bv+fgmMf4bBjQzfJWpF64GNDepL19a+9uz8gjTMoWKcVFuq9qN0RxYfCY/AeBXnMlc1 35y62T8maRTvSpSLbG50UliQXoOM0t7UBfFJauBgrWPQhprD9jj3smphg/+weKpo1J5OAe0FMo8f zncdYE79J50pCehKsk3WgD0V4VQAcXa+6cNQhXjDNT0HUIshP6hEtPrro1HQFxyx7INu4yUHzR4j RvFp61IJ2Oj/9m//Jjzqy7dvRUkgJMSbqkVQuzbYTxk1cBBnI4cdO5rre8r6vwJu6/m0nscJYixz QTVzfQP0s890ds9UkOqOrEWTPLFanC3lQJ7sPFVhy6CQZZIyxzEm2em4zay1435pMY4NVfuzNs8e VngeFrX3fmmuTi5IE7dHaxgvYWv1mtYAj41MPaP2q8ZsTK1waPkcx2s/b9DeuqxAcclTbP/tOZ2b N12FeoIirjnMUi+njLXJGKaByizicMKaNj/sgZoAVnVmolLqTLmKHRdevCmCGQEbycKv3oAUMDcb 9thdlkeQBajoWwnkDUIQp5ufD95z1/dZS/g2C6SW3+fEtwrv6uHD/xqkUQy2Gn/yQyrWNn+Xfrww rpLLKRa+XfOeVaywM/lhPa7nRX2+c3MuY1SSOZaX6fyiUvDNjlpp7jIQAmQpZ8qQkaOtG+TvYFkP m48JVhdu9Bz5LExlXEeo51XeDGOidm+VnbQhhmojBEvt13mO2XAUCRUSEak3JmOhzTifAc9RX2QM yRITnme9VY7X7tDFamE1jnq+tQHUM2mPz4VvygaeqCo598pEVK0NQnOmmtGVR3T6vLE6DV70JaN1 yYtpjc/nooVxeNh6YLUO6jVjz629lvH52zX40sZfv3/cZsiaONZcHlcm/cCoUonNnVYkLFxwYF1E 7YKe4D90+bN6C+aOh7fhPnwW0ydE6LvlmIQ0TK4ch/EA1u96r2COxEyVL5h+4K465e0MLrpyDaN2 R8pLpCvXGiydXwZ3MFjjkLDCvuxL1l9jGS+Msf1JNgtoBX4W1cyAf2HMfZ5x3VthZTWSA6nUY+Dz spwtaOhuOvbqHCoSvSA9TIjHPf/iF79QCIgqA+cmQ8RR2aRWWqSKbnsj12B3HPweY/zSgul3+MlS 4SjtzCZoNkmY0YaP89qgl6gi3pXbrZlGop2413fvvcocF752yeXiH0cykNNDLJZkd33t7TOpZ956 Ic/m6wUQuTVYygKP7rPm5NiLqd+P5/GpndPfsX5aSKJ9b9sSfgy21/Xz+9owXzJ+raEaQy8+z2XV 20v3OB5DnzMhkpy3c/UGNIBxdoJJLQgxr0vSwAuTh1kkxR/axzKeNImOnYn0r3ZWPvVgryu1q3xz Az6Qd978buQZnXGN8Apqog+g+jBoz7lQrRHq+VnNQ8TLY9wuudLjnamyhOPJwn3VxCoD5Ou1jrxA yGWqb+JlJB5lnfc6l8mQFhGuo5piWvtbbncmFKB8yHMD6znQ5ONeqXGIn1999ZW+P3z6ZMO0vupD v2rTVGRPFgCAbs+tSvC1PNeeZ7VaXpz4tYhUGrWjOzHduHcx0waSWcRAr8w9EB0SJh40SVKuCgCY rRVG5MTnuchIQWXYuvhZHY5ZvLCtlzFP2ZSxV9N6gJcM1qWjf+ap13WJET6ely+FSn/sMTaIrQEt vLH1cMfE0yoDa5MN7fmqZd14XfS0oYWzrJe8vPr5pYP3XN/eDNeOPtexaeRZXZTtNmTadZxYOk9U xp96QDM5sD7qy3On51nNunVAuZnP4Ih4h1TvjNMyDvul2hjpms56BqaLRXQ12VgETSEDnlRTtT6f xvbwzjjR1GqXtnaEBwzQQdwmFg0FmZghMpGzw1YdocHW6LwH78rXTWgKu32hGr8FQLNkaRzGlPGh AQAHId5xBvDcxW7/GHv0yRMwZ4FTFL3Z3HpCIYsytwQHX3iGV1er2HYGbLlqfqdM35HaROrslvG4 /2gDPGVyVdU9ITZ1e8tYnt6IY0YzzN3OBmcYh2N0j9u4WV3F7fomrlBS2D7pdXd3ZAYtq/P49FGL //b1lcIsQqvHA5ymWVxNXyU+hZxLJwne8rpub6/00EluHPdDyUgJuvE78D0668Czk/dEDaigi2Ns uw9xtVhbQlmGn1ozDPCg92UYowXywUFPatGOdNAJAF9lIRHra+v307SB7+s5z/EmNvvHmE+hu5CA AHPzBvHh48e4uv2yX1zaoHJJFFkBhQ6yqdvFJCbLSUwW8zhstnFCMC/2Mb9uNdnPwzS+uqOTKSYd n3qPAzxvvqDvpfHHPUXessVLYW82qPM47T/0dy6dr8Li8uvu7u5MPqZVU+B3i2XEenWlf4uXtuvk PbsCAbb76tlzs+gez3gooRpn68vgl6zQS1UcQ9ciO0s/OVF93GXKRjO5NnLgwFfO3UdNVxYWO+IL qdH+tdkN2V6QQ90+MzK5YO2zRrIOv64NKc36d4iDQJnxJomusIMmV8r4y+CBPsct6oFsBfZjNH0Y k2FxcD2EYKUoadG/Si17gVuK+HQWkrYPneuTkefBK8sqUXRLw+xPMVsaD6qK/hoHJt3T5iGubu8M nC/mse0wamBDdEEZBN94hgDwahIBDpVhjzEYFoPxtpaFriYTFM6i+tAspCItcg0KMU8DIdGZwixb 0pNvSJUvHmNp6UZ9Qx2QC4d0R3GMZ3UcEga2oziezQBW9yn2iAAe6OW3irvruzg1uNs4C20vesCk zjAeRS3P6QatsRI5WeH2UIN3FCZZHkfehjxMnmzSJlRUbKUI1s6lMPV8jQwef5U9DQbMG429LArU z4ubsVVtbWudu/eQR95puxYuYVjjf9d5628/ucFqDxso7/AULGcVjdWXsiyITtB6JuI/IYZz+egH TkC2/bI+7CgJFpjeTNqW1NeHuZk/lUads0i94VLyHy+FImr/zMUC/FvP3DpR7GiDlmc9oDyNslFm 07uhhcMav47wZ6tpOF9cJVBf1IXqDDNk28xUN9jNeMGEGCYp2EkngbqiiBaeZLa7jRVeU0nRcKCO Skj3F7/4OpYUCEfE0xP1gShkLmOVbc27I5UQyYtSfVc+J1UNpJTPmdpA1u0pRJzJS2ipDVVS05f7 kAjRPCDEy2JzMn94y9mM4o+eZ0kUZojwFrQ4DwP2Zw5bhvOH8/CvvGNJANMGTiKXpdJh8rHA/DYx dYFkrMzk8fJCbqkC1LmWHNFB45yeo0Q3sZ3d2Wbq0jnDA4wbMu4vYUQcZWxag3XOC0NXbHu20ZRR c+h+jm21GeO2XGh8jy2J9ZLROtvgm59/coPVyi8L98FQwVSXQcBgkMokbMCLQaplnwRW9UR5Buqd nVtZPO9yZL16t7t3iM0eL9lR7VSNh9XvhGIdV6NJVwS4VIMBXChbaVE7H+xy5TEpe9lfT6l/DsD3 4bixIZOkSduuPrlMZ62QvLtW6QUsdAQWa1Jo4cja53WkXhbeFd7U4J4D7pgGQk86GR7tqlnPl80z 1ABVzyDLN8CPWORXay1YeUDgVilvSyjIjm7WOJ1xGJUhjBna1dtDRBN/vRwUGuqZtYvGmWDjTaXL NunLOuS6fXZ+jT2KvtlsfqcPC0YJa0BobFnpAfPaS4YID/UQ+10Xh87Y5H7ne5xfD3I4/ZwZKRK0 87EWqcujnisctN6VPPCGljKn7VyPRaWx62xMTul5IvymZ5CJIFpqXcogjjHa9jVFMeH7w/2TOhuB D15fu8lqbXL1LFuNrbGXOf53fX6dA/yzX6ufiZZ+PgaL/0vSnwTWZKyOsdJmnS769KjiZe1aCJ9l 1TtaOqG+gZdTt/45mzOmSJg+7oy4mbsAWlapVq8JW4qhqYLg11sM0KGfybPzmRdcHWUU9ycbnKs0 Lia+JTM4Ca7usGO11+qpp4238QTxwMrQtPda1+9waQA6q2eBAVHGp7S8HBJn1j49tKGKvtjxUAJm ArUnAtipc6RVmcy1PKNZbzj5G5QAGZhs3+RkI7WNDqkm3aYBnavHnK9bTSoOT2c7d8uqt9Fc+94s qSdJGHBBsdWnC2UPv2uGDUYrvUvRGqpTD8Y65Yan9pog6zoEWsT9p3fyPgkHMbKqtZuvlL1U95fE b57xlkZFyG1YpLmjrKFJvDUn63vrYXU7MLOFmwXPqrlHdhvH6KvPBAKVxK1p1EUAdqhbvK+xQa2j NbDn4+7P7JbAAxhq8FzmYWKsCv9dkTFWgq35V5toC1G0n9WSVi+t3zrHz8pgOUNZluuoUBDG+pKW 5nhRJIq4YZYY7royarxUqlaftci6aVQXJIFSKWoXw9b72LWcYWLnzvR+ejnG0hreVmJXbo6Xu97U WI70wtKbEOAqHMHGrypjwBQKfXF3kzQWMoyI+7n+UKUoVHhmkasfnNnbrk+sO3RtX02imhjFZ8ID Ql2zevf17b1qgeGdEsbl9XTgaYd937ZLX7wdUaHJIeZLVxgcgKv3Wy3Y+Zq+HW4CKQrGCSa+sT31 FuqqE/dcoepSKgk2HLxuA06WBNPy9HRnjXKDaQu0i0JznWha9TUv1EdenAln/8KvcsZuHqsFRdKW wpEoIQ1Kiiipjz4INHfmN2K9XMfN9U3y0EiYPGUCJ8+ZzruuURnXZq6nd69mu8krG+NL483XbZ32 CodnqIxgsGSUmIP7CArks9ejQsxZqgeXIRpRasbhYWtEyuCUkRDoPr+K9WrfS++UR1UbQUl+9/fX GKySVW6NVQH8HPW+S8fYUP1sDNZwSINRYSHJQBU9y6NyIOYq92JmSwVaYVNMrz9rtAi51IhCbcy9 K2Ck/ADIvDG4CxdZosOTAKZj1ZHVz0yFN7HsV1g4hCaHC2914I1UWRA4mVram0um8wUyNhgmZyXp 6RdKEPB67h4KBxMVMqNxNTVmTYVI3lO7VHWcrjBRZM7O3tNU53INoxd+ysssUg11luFXljw5HPD9 sojX0dmTUJlETuQMY1kwR4WWQvNdVCxvcWhMS7lLz3E7MfbHlBMR2hJPj8OufPE5HpIdL16zEyhc bQqDfveR1A0PeiYcZNgtm8IXnoOwKdEiSOVn2zhtbGPP3KB838qMNnBNNqttXGEDcS4bU9JEGDdg jUsGq51z5wblJNURVoe9XQzodb9RihjLxqaNr/DQ88TEpTEeZyf5GVyR399coX7hsK3bs1GhcJLj hjcu4nUB8IVrOVRsW3i13Dv+1iZXXvKu2mv6+RisFEqoQ1oB0l0y4I7fYrFIZ+EKH/lcLRdHb+nR ckjsqAqBpxNPOLedNw+lH5jmWmqCVSMKDWDJ6lRJi5jhWRZSmBk8IL6zooZ+DL1hEMkzhfdPWA69 zWxwY27oydv1LCPH/fdDltSLmhhy0fMeevc8u/vyX923s6tMaJ9Hk5MWYHguWnDFoTLD3jIsVABw //5bH7KCRyHpU2EPn0+xcOIudayvlrFFumXrBWBDUMmHQbmhjEKLpXD08iR5bv2sluzfj6PkBXhp 0jl58u0376QLjyd4fX2Iq6tr3482N9MtNNoJEYB3kTkUNohn2Vx/61FU2FSJlHFmrNV6vehZ5Wsx +IV1HVIfy0bLEcdyvnQtpMQLUK4wVmr5p+f1fOOjDePaOsl6/rvtXlQRGeejaS/zbGap7GFmi+v+ 675rTFpAvyULWx575UYho6MNB6tOtcbpJzdYm1MXqzjGHSQx2pmjgaNMR6519UVLop/SufLBaIgu D8F+O3fDYOFue7eZTI0h0QdOkwTeCi67PBjSK4kh7Zk6cJ5uYhbL2J820Z3oyWgv4qBwLYH2xJtO k3lswWwYwAN6W8xoduidmnsy7didOd90DfHNGlr03WP9KfSSlA07IcoQaVgz/MRAdQdAcJqPnhod rGt5a9u921vN1/O4Xd3EibArprGar2IZq9jT/+5pG5NuG7dfZKPMrS0nGI17E85UFvS0YzelRGgV C/VIxGslfY107iQ+Pfw2lsvruFrfxnS2iie0p7qdCsavrlFT3QTcwflkFeupd+LjYavnsUZHa/Im jtOnOE7d/WbzuAn+IwyEA/T06KYRbeffCgXl4a1uY4cnuqM5gSZEdMcnhWqzJddYoUOl/hOkVqsf /r0WGVaZzflSntT2AS3ySdy8uon3u0P886//Rbs9ss3Xa0KgldQo+Pfq+m08bb6Nbn+ML754q+v6 9ttv49v397qH3dY6T4SRr1/T8n2quks4c1u0wSprRtSQ9ZTISiuig6ek9mPPcaQK73d6YRq8+SFO M5791lnUwz5u4iYmrIXZMmaTGwlRHg5bZZ5JaiyXVnStrkQ8+76PpMJab05ScN25R2OF7MyVXfcY HXF4z7MaCrOXizWqQU4moVS8dAMbku9sYIur6wEbzUQKn1leF7yuVim2dURqHrRlWpq/8RMf7lLs GNytGzL0Q0teyoPFKBjqGxU6Zt5YD10FwmYxoxjqSn1IfjYGfYGz/AKqyyqsS00qlaIUVWLQvLJs SavK6Gv2gGZ6W6FF9j7T3wfulR6ACqrNoiYs1MKyOt7QvGJ0jIFLUwBchKvgToKCuZNJ5M3hq+VK 3BzZUjjm0NROVw++PAGD+QOvx2z4VDPAptNUdu3i5SIrVJE1k9QNYM+rHfqwohZgqrBWMwqV2eRO y0Ji8vKd31c5T91/60Hq3FOe7zlvbvAeBn6Vft9L9frZtEaBzsP2eY5ldAAAIABJREFUBqYqL/r6 66/17+p47G7RDq3HhqQ8ifL8riDUXlk1FaPoBYYXP3Qn6jO4I8xI+GOG3y95WZfY5Rxl0LxWzO6v OUs5mwrlpXP5PEtZn6drazpft5vG8Az0aVniVPSagshc62isWK/We5Qb7pNU5xUe45/b6xn/zZ9/ nuH8yQ0WNzcvw6RFd1TYZRjE1AUbnKFPXwnsYZi2hacIAzNmwd86pGIU1/t91Mbt6YZcAySlUHUI zaLqnIzqlpMtrDRAZMiMAXkRZj2aeh2eJCTn0pohDBpCHEKnp8FgSf6kGrPa0yMB0LOPL0h4YHRQ GCU7VyU/Cvuks8G1ui2Ejf48TmBKSFxP8MhssIYs43nbJ36/WrMrmv1uChY4jico/C0Ikrr3Chvm k5gdXMSrRZr3PJ5wFcZIVvkMQD9PebPjOiRD3sWAfJutKv1101dyQyGJoIWexd0JZlUm1x2PckHI 0zpvm1ZJjO12E29evVaN5B/+8Ad9HsYTg1UqFC0wfGmRLZd4im9kBG0A6HVoI3/CUw+PtWx78ug4 +u5H8wF8vrSQiQr6zzvmPE9FWSm2ZqnSKWW4vQgwxgN9pjXW7YZgQzp4M2Wwav4W1papx/6zfe7M oEMk5nfC/HvimZdVhqRtMqg+qzeYF5potHOphX00HvETH5Zktgwy2IabYhjExdrgMdVRZFEWi4pd T8d4miSPKZkIlrAiw6No3yoUSovbizqo9bzbtvMKletQ4HvYWdGSHQeMJcmVfcdVbSHjXcJX1e+i qvHDi4J6Yc+Gc2XJ8mCw1A7sfFf1In2OOVTdHCFbVSmUsWKRxAEmvLOMda0wkpUJnZ8UPrYPvLI0 w04/FH1zjl75kkyfykcxqNV2nPeBq0zjREnIBXyGQ0ZHHtpBvYfaBd43h+gJheAlDnHZCFzOYaxN 4wJojBcIdpaaZJ7sJBUKD0ryoRZIKULkc6FVehpczsv8WK3BDWGRm5KCZ9V2nyZUefPmTR+qthmr Nmzh/sB4mCuUqBgHpITMnbH5jHo/1AlgA9dH2hP2NV0uCK7DOJ+v/SQ6SOF/6VFDHOVvh/PyF3nz 6TmXcWgNRM0FSyg9b3JRBmZgsJfkUo53/ZfvZ23aSHE5REM5J0Z0jZof9btLfLW6liq+btfJT26w 1KGtPKpkuo8t+uUHmZkW9fGxdATeT9/aOmu5NKCZXZS3JWKjmdIiOybvR1K7hJMKsgDMHYfHPikM iusHPMFdc7JYFOMkA1WLk4mbaeC2NKSXQn6erfHiOpcJNpZgPlBLzDMmthcb/Wpxk7zWxpAmmxsP 0I0CLMI3bjcu7OVghvsZfUNgr8tCTgg7yqAdrB2lEhw2GSF1Gsc2zGlDT2GEE2ePKotWXZr7jBEe CNkmhbkZ9lVmS/cFTuln2Ku7kik9ogwKKFut2LNoW8MwLC7fk2WvVehPxx8JARLymWVf11eyOISJ hHntgmmzf7WQhck9PcgrE8v/AoBewLvZ8JkhFm5qXfuzUrELIZK7lieKcMqFXfNxitH2/akdX7aT swJIZUUHHtTYMAjUTn2x1pjV64f3uGvUuVHxhj7XuOBE4HUThu7jqGvx5jGZuVayHZdLWcFL67v+ 3h4/vcEiVUsYKE/EE9z2x8ETA9ovcpUogOeUsJsJiq0gGR5ZPwgYKefonTRJxjQD3FW1OaUfFbIp DLVhq5o7t7mSyrmvIQfcMruTDCGbrKW8s0aCpx3w9NLa8vF2x7aO/PmOZGKrPS1S2b2XpHIeQqq5 Uv82liwijHNCBxAdl9araseoJQbuHglZbRT5KszLtX6LcONdG0hwQRsi4z82qGBeQ0ZvPClZ+Jyr lBxaj1IeTfLNCi+qOrbeC4M6kfeC+S9543o/tW1+3jaQOXj9hleYopn6pi049ULn5Yh9Z4PKdYKh Yay4XvVEzHuSWGHjbfDvkoV+fHyvmkuuyx1m9FTNt4PWJYOSEs4Ny9tVDY1iRzMftC5KbyrJy9qc T54jKoUS54tCczcb0brpFTqS9KznM7Srr6P1uIYQfggT+82ykhdZclSYXM9/y3kDtQXg1GuSTlve XC5tYpcM8yUct45xuPyTGywPRIqfyKdMQ6RJxQ3hthdGlU0aUj7FzIKtqTbqslLaUZ4MzNldkugo zi3dGfk9e6fZ+5icsgwRWTPhLOOA974UwN0OdIuH+PDCUHlNxed4BcXd6o/nZUR4Zn141Ouyl9HC sKBKwY5FeOLdSjru9NVbURZEJ55O7ZG4LHGEIGUivdvtg87e5WGVsTqTCkGjaQKLmqwrvBhnoBaL SSxpsVXNZMVH4pwJ0irssZdg3bDB8A4eiCdadfIFWK86tB5HCxpX0KUZbw81B2NB7lloCWG9qoqs leXECB+i26UevqgZDueN4wyLhLFRYbbUenh20FmGVlZFIv7yS6suVANXd5vxcy8wHqPL+0rvi2ta rWDo46UdxenTfR+3krzGKd6IFpBeWapzsslxvShzFChdm0k9o/HGVUb+MGLP8+y8AFgXOZ/ZZJO2 Q8XFJaUEzb1RRm4I0wehwpnkw9uQNec1w6yOVo4CjM+ReqepB1GT37Mf6Xt9H3Lo+PWtUfvpDZbc WLdO8gJvuU8pF6wJVsxgl3ZUHK8sB6EHW9lx4CTVokEOQwYkXy8QNjEZT7hVj4EJIK7u1j0PZhDR H8K74e9tpu/MldYEg1x3ekGeovjuziLWvZ9jZClSp7DVDPSeyzSPbPNOQ1HaXIHVFNu9jKpfW1/t 9dWualY75RUYH9fRHfZVwuNsF81IKYPSRE5sDiPQA+MJcLdM57oHUvxWnJj0i74MqAwj0kFNaQ4G i3PyHi1+SJypJmGmaGUtz+v1Bg+y8DkbLXGF8t6soZWdq51r6XlrUCwA2wsMh9bQkhv5Hb0WOQDk q4v19c1anlS3Z3x4LdfR2Xil0gFKD8IhF9UElvnKXHaB/6VkS6X7q5i+5kOkt+hnabY/5NbJ1J6q vV6+mLeLmBwfzzyqei798ht5VGPjSXH62N4IuZDjw7MfxPXAi9XDMiGVaCodxkaovZax59V+b73y n4WHdUVn5jlV6a78Psi7cs2gPZWBeekmnljZBMHl3l9JdXN9XtLXH3cCOGlPvpECwl5eGZN3FfPF OvYUUFdVfp4bwFQ8JRb3cqnwaw/fKPlP7nO3lnfCLj9FfwitrO1G2l7qNAzp9bCNx47wip2KSZWG ck8NmLn8p725KG5J5rCo3z3pxded1GRBQDbGjcRESnxs92AGj3DmhRuo3+FiHsv5dWw2u3jqdnEn HlcREJlAu1gsrmO9Nkj8+PjJDSU21qlSzRpcHfpVfnEdk91THKaz2J5msaEjNl6MipyNfc3WeEbw 5lBZmKsIt2NUj9s4TnZxO/sUj4/fige2kxYZdXTzWF0vYz1dxKmbyFjQLVoGYnHtTtCHqQpvJQ64 P8btzRt14bn5koxcF4fNJFZxFbtH0yGACijyhpt3RCPsMI3ru6vEvabR7S1Gs1hM5fHI0ONN7p5i tp7F0+5DLJZw9ebx9PAQ99+4ldk//uP/Gsuvv47NdhP//Otfxz/84z/Gf/znb+Kf/rf/GYeHQ0w6 t3qXczeZxTfvfh9v376Rl0Up093NK2NzaSrBdFbHWWwIsXeHOM4P5iWVWB6bLcabprT393Ezt9cH VjcVFEE/xqoLZeMAy3yM+SIpKifWwl0sZq/Usel2OY+PH9/H9fU6nrqHeNo+moZBJlmS1hhPY7/C 6dCNSwyRYnA4WIvZMhaEu0d76/DawDARJ2Cvgs5xQJl0cor18koYJMZcm304krHqBXPZ4pvqNcp6 UIg/KEWIpZO1nMIUV9bbQhlWBdnxEx9LJHdn1m6fCUDn4atK0D7nn3h45yY9bMNjnGquiSEjkKQ4 PAZATNLI8tAUUp43LhhjTxKM46GU5Efu7HZ1eQAGr10478ybDZGbmTp8ctasxUiGY+jPZ1C5xAB7 fUW/qsLaC/0Sq6U7R+tZ1e/bcgm+8HA4DMhX2Y6zpipHUcceX4v/nr/Xbm/KSbVKI9x9gBDLGNJ5 ew3VAuFAwjAb0IdsdV6ZOoxVXQveWQnMFfMaCkTJzzA2r1+96dVOuTdej3FWbSDctQ4jTCPXlQzf /cdPsUerfT2TAOJM90lpzk4Z1SXFzzTX+OJ1/G38ra9x86jzs9BrLMkk6vqu35554hhmiKUYqZsb +FnMPQyJFVK1KacCKw+yozi8WrsnrUAbFQTd7TauptduQ0bT1wVh+wCEn2FNFUEcCyPr3Jx0pOTa bob2xp4XGLdZOkB79XiEDZqecYU4rn8tSk+TMR4lgargvTK3JSqSjSTLPxvUQpPHp7rOwy5pOoSh A43mpzuw0lILdVmLGA1JiMPLEuX9TzjUTYdUvHCYzPRQh5XyHoZg2fXpx5cV95W+hWQpoLZ4PfkQ ivIgZv3wcJ3Jw8136Q2LeImHRyaIh0Tfx+wYDFkVw4zhrLCkdd1rcqFa6t+nRE7hHIL8SPs3rbwr vZ9HGyr1DObG7WfxscDLYFabef6N14LXo3EAxyAbrx2YYmFLvPDIcPlXaEOtoApMYieFiArNF7FL 8BcBQDpFLwtjI8zd27sgFOPcAN4FuhdOVIZJdW2pIQ9jm2stMqqUTDcwv4eMHp6kQkoJepsyU4Zu g1zKI/hVxO36Sj0JC7/pJp2M1u2rm1iuVz1ovIxF/PX/+Gsbp+Wd50waFrBLDG4LQyD9DB/r2D3E REbQLcrYaJbabfDwmJOD4GM9B4U+JXCYdX2oSkw1d0qhtDoGFQhu7THmhw2WuXU91PJSpj0TOTVf 2vBMYbzmXVJy9pCOKRPzWqWagZ4FNjClsXrepGPAzwzrVCbd/oDn73eFg60C6k9usFCx1E5wojV7 KhkomefiZMKdzx2fyzD0r+kNU/LTRQx1CGhAdjBWZTRUfyhMzNchPCcNQst+H+RZ7G2150AWBz0l yjpK4sXvy1SwcBYL2VXDyd41FveGa08qwZTXWLVAGAMg83F48JcMVi3e+l2l5tsJxaJnYrSLv7wF vAoZU7VQxwNYiNpA/8YsWosPH+9jcreIGaFnZkXLWPG9O86U6aXMgyX1uNmpFo8vGaHr1/H73/9e 3guGiIWPAcOD4T7xYvhbGQ4MKgv417/+ta7t7vUrLWykl7e7J72Pxau/3d1JplmfNV3G7d1dXC2v FM7c33+Ih48PsQyXE1XWtK/bk3zyIdbJYl8tVvH6zRfxH//xH3k9FB5fxX7H39ZxdWUPUX0QCXkX K5VHEZrzjEhidIhjoDGWmx7e8oK6VmamKhRcw1dZ3NXNKg5dGSxvnBzlYZUh0thoQ2VhO5kxm5qH VfPqklFQNnjm4uUxpaFeh8fstLPnLR6idbbwtggbneyx/I/hHG2qmYktz48dz9iY2fGS7pLo5Txm WSfbd3huitU5v9aE5KF+BsTRnQiCpGfdKLVoDQLiv4cx+q6jdNbV204ZIlLlmfaF8Je6SOfsWzS/ /RCvViWN4VILjsoaVvNSL6YKjQZA2CHSzg8n+/6BAygUBQdqbq/dVdpDuYcJmu5MPLetCmFqJn1O F03X6SYjWR5fMcfbQtI2G4RRKkC+BbH5t3sKWv9KEQwMCsnwEt26HRlCDlAD+Kow2EoSfAZSM2wG koYQ3rd5eIrd08ayw6mhVJ9NuMfP0Abw7jBOLFRAbi3gzMxx8G+M27//+7/3vycUlRLoAg6ZPZSb 5ZWyczbWraCcuVx4aqVyWm3KhNXRUFdehbElwlhGHwNqL2ovj09dhMA5D8f4z//8T53v9RtkpdcK DSX6t8Djc0b0eHSDDkkzo+bZbc7KgIq8yjhgwPFmbEif85Jqc3O2kyqH7PSUrc+k8d8kWcaUAo3F 7HKjlTNjSISS3DV5u4eB5kLIxlq1MeKWMDDPy6uG81txNldnrptqc3eesbRR5v6IBrIxbvzEh6q9 yWrhmioOTj5H9UP8rvd/x4vU4ECWORsbWA3K4SYwdYXNVf4DIVGLje+VoUhj1XfTMUYlL6rniaQ7 nxpVYBcedGuCK53ODiVpW/ToCetMdlQpUNKHBk8sJxkNJShE1fuTGKjGopbLaYmpvbGRwJ2JoUyu Im2Wi11V9SwOFl3LdWHxVZ2fPZ7rmFBQPt3HARxBk/QQJwwTBb+vfiEsCNyI3Xie3uiWIuPNNv6f //v/iqvVWjLLlHFsnx5jv9va4BDy7f41KQxTZeHozPN3f/d3Mgws+Ldv3/o5Ji2ipHcpp4GN/uXX X+u+Hh7u9bpXr27Vpqu6wey6B9X7LeerePh0L0OIJ7ZeL+Lu1at4ut/GLtVdpah6OqgfIYKO06Wp NbPlTKAz1RCLlQ0hBgulBJ7l/YePMvy//ff/iDVj8fat9N43DxtpFFPehFdnIwU3jvCRObWPj5++ kZexWC9jsXYhuMiqzIuDF69pFYPGVInn9fy9vp1i1dXyhRErhv9lWKXdpNrfDRt3dlVK/BIcWFlK PPFMQJG4KKoGc5c148iI+e2sXhlWoTFZWO3PzZxthsVSFmllv3U9KwG2rFcijJ/cYIkTJUmWFC7O Upo/14FXU2JpEsgTuc1pX4eJpU+VnkfPOiiyqB9AhYZ6bZYqYIz4vb2EgeTGM7OnEeJDCZzM0M9/ H4Tdxjta/W7gSlUIWZPIrnJxoLrUr7mUFldh8c7yMLXT1mSonbntT1dhF2EVxqH6DdY17yVj4h1U rv50GrfXX8mjge9DqZSSCPQSPG1ju3mKD7/9Ju51L6awqA4UEBV9q9ksNo9bLUgMDPV8RWv43e9+ p7///d//vR/HdBr/8i//ouv87W9/q9dj0K5ubvrQkfNWn8JNNuB89epGgPvptImPHxxqLlcYgatY LdfxFNsU6DvEDO9ghnft1mGM+9XVQpgWHlO33cugvrp9He++ea/x3e4f48PH97HvPMav7l47HzhZ xGp5HdtZJ7hBG2AHD43wmBrCRV+hUImPMsZlRLzReBNhzLcUjp+cyWU+FQt/CKcGGRfheeBd4qfh EQ0lOMLCNKZ4S8+bZ9TzNn2GeWv32psugpR5riBzfG9oJI1bG7bagxvmGgYVhQeu3b/zppuVkUPv 077055TjSC/MDGHjZ4BhYSUWlEygR50CcJcwov/K4fe7DMegYAKRyQx2Y4vz94hEKpZiPeT8QzYr VZmIdpSB56TyGQm7mckugmvG7YUJ8SBaVvvQQ3A4nG30jiaP7TQoBgw7Vak4zqM7PF40WONiY36u tvFtV5QC2YvUaaqDuTu//OUvnRVjUs86FY+ryWpltRQnLmNPG6sD+NdBtApka7rdSeJ8/+f//n/k /UIA9bMg1FK7siMu/rwP/zBcf/VXf9Vjaf/0T//UK5GWkgNjyfXVs/3Nv/82rq5X/b8xSOasOaQy DkdCYBePjw6/3r55E1fXkE8HY+9GGojq+VrxsiYHY3yHmcccr/Pt3Re6Tt6Cwbi9vol3k29jebVU GzQIqNAxyEZuHp+EYZlTeBCtAAOg7PDiql/ENHkAqEczzOFfwQP24M26rw7Yg+bUmFdnXGwgmBqu qGzvgF9qbmQXHEkdjaSKWw9rOV37vFIzyXZ60gojkbCPw1b9eUyFgFqS/RKa1TYYv0Ze2SHu0Hzk 0uFsthMwUGZ+FiEh/fFYAds0BLiSC8TikH+VnKx3cxUZMLBqPFDgYER3SO9MGRf+XgA5Kfhp7KfF 4ypCXR2q94jdEezCCi2w3+GTIGHCjnq9uI7DvjTJeZqefPQqZMEp3X78qFQ9WKraqav4uSRbDrFe fpX1YmhgPVh9opfooNNM4klZq9WL2mmCULPnnZ7aM3TI57MrKX523VNstg8qzYAz5rKlzArOSgvM rHWn+gf6RBkmZeBOEVuVtLCI5rGazuIv/+aXnuyTbZwWt7pm+jvGYaMkwHGyjm7+Kg6Tm/j9hJCR 0P5KygPHp30coQ5s3sdy9m18+cXfKKx83Gzi3bv3sVgt4/Wrr+LbD+/j17/+5/if/+Nv42++/jKO 82W8//QY3+CtHE/x9//wD3rt0/2j+G2//fBt3M4m8dXXv4z5//IP8bA7RXeaxJuH9+aPLWfiGpEg oLEGz0dY1uRahgWDTMMLQmB4RY+fdjJu8qLWN4OhOEVcr9/qnBi77nEX+8kuJtdI0VzF/fZdfNr8 IeZ3s3joHmLa/SLWtzfp2U3i09ODKBEyJN005utVzNcLeWrTx1n84Q+/Uzj5q1/dxNsvvor/7zcb eXDKBj6dYr/da4FWqdCHd+/iw7e/i7tXN/HqzZ1IwvdP71UZQAOM7XvwxYXUSU6bB9V5LtZQ0F0Z 8GnzO/VDpBRNC/+0kKeo62OObl0Pqg3otIgJNB+yt+ootIgNIoHiIpKgOsX1ailJ7G53jOvFjRyB x8d7ZXznK3wikgbo4jvD/ri1Wi0lYsr2zY7RoTmHaCTwz34pIoDCZhX476VhR4H/1Y03nP1xKxhB VRHxEx+Q12RJUbbEpcflnWC0LJonSbBeE9osdb1PmJfJekpZyfKfA8/f65DMr1tyQfQk9nfpjxTJ P4uRyWimm1z/HnguBfBaJKeUTIdOzFVuYczOnLPUpBJdwWxozi+Z3UaLSueHZkDmBnE7vAJ1fvHg 7Kp2bm+eFTs0k78NN6pebkUIJ71712VO+jFPesmUEhXqLOlWZEFDtTZTax068SbzWTwjSJkLhYST NRvG65hfX6v57Gm2ipvXXxhXSn39L798G7d3r+N+s41v//BNfLh/UodvDOybL7+ML9449FrdmGJA Q9Wru1ex6Y7xuNvElrrJvbuUkwnckLixwJRB4ua5cBT/jEN9F5+e5NG1YXEbToty0X0w3rfplCyw ThvG0qHr+/v3fTjXNhLld4S46/ldrwd2PFm7vjhm282u9yDrs3kmhSvyO7xEcKGioRzz+XH+DWRo mgmnZ423hBCI9LFoNIuYx+Goc5QgYiVfuHZBAjDZSV8mJqvMXaOUqk1NjOeIDtHKWcp457gi+jif e/N29MFnOwng1pH1Wv6/1bh3GZW9QBwAQx/2vvhCOw0P9al/dszzn9xgkdE80kyTGBn9bryiySEO ai81jRs8rVQME6iYkhkQIFRBnjWDKloo+eJUSLlcqTQ+jpaXlcH0ZBZfRvP+vOq/jtYw+W/mdFX4 aG6WwX0yV3odTPRsumpcyq41u0eORPP/TNAUQ4PZrKuwUSlyauvamxfjySJFU1XDWqaFDJsyZ6k0 SThVNXFMDnbyhVLGVbNnjEItzESKxVi5/yJfMNqPsY4jocJsHYsEfAHkCRfFxgaknn0Rs9ldHCb7 eLp/iONpFusb1D/38fjpo+7pL77+RTzuuvhE+p9avOvreHX7SlnC6WIS7x4f44kM6dWt+GzyqGcY kU1s0eOaTuJO4dkpDni8lOEQPkJQTX7R+4+fzgxCW0dZYVWF9a0SZ5XlxMLG48OH9wrdbm+vrbe2 7+TRTZN/VeVFvexMqkBcsfM22V9vUjY4ZE3ZBGozqfcUlqg2WBkKF841zY2EuSmvcb52cuW4j83W fQ4WWdUgQnAmg0p5ogxWJV3WqLB2GBx3PcLLKd6bxqXbx15V3KYqbGYbJYDIJLHBLWZXMZ9toyOS yajIYoIWMjxvQvwcupA6x541aL6djCUbI5ttinEOGcufgYelSg/BQyy+Ver40A8umzLNttLzphyG w/0FcwKogbJ736VCu8X3k2hZNU6fO7R5dDvtTixwN3TgFFYheKkYYDBY7EYDbtDrFyWr145TKamO yadMDOsp9czflEkZmgcUbmaPywqS1bbsJNeZjJ3kRUqBUgbSJUS317c6C5MTj4Kvlpip3RZpEDpK C1CfxjwbHBh7q6TIDHYTjePjOLlGkFnvW7K5BH3rCHm5H8idC+FU81On8IeM4RJcDuby7hCbrRcV O//vvrmPLYmR9U28evU6Xr1+rUl7/+lDfPrwIVaA2OoPgWXcBxs8Gdjjch3r5TLu9Cxgqm8k9ULW 92aFksIpuq1Z8yJ+ZgKhDEuRdcHPCqiu17aJC/iAhJBE+nCuyDbq9V2nnzcbh471nsriyftoPJnN 5iTCqjFNh3yw3f/w7hsZ6CK18ny41vKKKhnCHN9nhySVjkHFmCxiiad8BR43CaKvugfmVmVKKyvM UYZswDc9yzBWjJk1/eE6GPpQGVYW+2NU9nt4ZuZNSpFBHKrSI0sCuHocuIRLOGcvoFE8rZRd0kbI /HJdJRJP9LYkYYDhZeOHkFwbDqvgJzdY1SdPXB8FFWgw4XLvlfrf0NxT4OMkF43BSPAijpNSnYDk DAg1Sqno+EdcQ8s9OudkndMmxlwVkzVdMGzRZAwWXwWsl+pjypxUJ+TE2UoGpGScy1vLG+s/y7tL ySsPgoEy2qk9VPIzxcIvzgyTs7wH3lc6T7Vgd1uXKxE+wlLHI6zaRRP2buI0WcRhsooDHVJOhKio AWR/2cPvMmykFIZg8in2h2XSKTbR3ZOMoHoM0Hob++2TQ0m8ArynaxYrrPdJ7KnjU40zhFuK6Nax B286gEs5UXB9jZ7WXHjZhHAKNQbCWjTGRYTEUMxl4JDGwcOsexk3ieAor4OjML7CAvk3BonnS22l xxisC/a8y6uq3KTl0TG2hHUC/e+Hpimcu6giXBezHbolr+U1xQUrbhfX9vDpk41c6m913V6Kr+u1 u/7sD8g944HhnRmzFFyQwDbnK+WJCn2Le6a+k/KEzgX87JHxnMlwRixnc3epgi+cDUBmGBh1TndI V96/xlqePhs4OOLtRQ5YP7fJ3i+cFcQAulwMDIvNpRIQZEQsevmTGywt0QKhs/mEOpNkL7jFkUaS M7WjmgAYq+xlnuoLCOyhbkiFOEqiKfiXtdElA/i5Qx2q1EDT8jDeVRmW+WdPUA+BdhjKQI46+bSZ kZJF7h9Uo1lUnqMvpgh03G91dqlFwZJn8RRT2fLALHQE7gadWtJpAAASJElEQVQ8TdKcSkGTuSR1 XOFfieeVaoKybXgu0hTrYtM5qbCcEBYU1eJKxuqI11QChiLCnmKBp3t4H5PTNmZzdmg4dRjVVeqc UVN4jNWSsCFiTyMMwN8Fnp2BXIzKcbaSkYzZKjZQJlgIsOOvCClXMmxdtvqaLM1M3+8eIza7+HTY WqqawvVJxAKPIptR7NXQ2cTUMkJlnAqjsgzOkHltX6tFBvl1h8FYxHTJ08BYT8VuZ9zfvn3de0Mc YFNVCuXDhg8jNF/A5scY+Wu37USTMI/MRfBsKHhcla2tOs+iozxhfHZZqqUGw1Awsl09sAPRW9Ot RleQxneod3Rm0J4UsjjIlLtPZWWfJRWT7fXYBPgPqMHnhrOm6v6YqI3ebmiPpzU16ak9J4r+U2XC 8zalmKQQbO6lN38LEAiagGxN27tgwzXPy0q9PwODlSoUOnwv2fWmDMISEFdCQzJWB0pT5LXYH8Pi c9MUmC5V05TaM6IruMfhd12BJDzIcqU6ozUbhmapl1KvtWPg3g9NCYq3VaEdC8HkzvNzmCxqVdCm jVF2JmbiYGz0GeUq4llRFZDyzTxMJlMm5hUmOFwxYK9OKtNVTJdDxxKOwldYDHwBumMczVy28miV hjChyWuqPq1/UBSgPsU8NrGkcErFq6eYwmOitEot2k6pPgH+5N5+KvxWNhYiLNfIbn2Kxx0ETUp+ 1jFBdSHry7QFKTRfxBSW+2TtVAXDBRNGpzzFjmJiZTudwUKKoYOpjjclzzEb0uYmUi3Wy4C30sit d1XPGMPCjo+cMiRGdZZhgedzL8ypNoOiiNR4uweAP4+sGyqnvNdwwLZvXVbGE6PC+/kqTG2gGhz7 TKYyvTRaUeutIbN4ZpTnK3UcKoxtuCdfq8NDGwQ9Xd17bbyZcUaC+UxDa+9nk+33lvI2cC5QPeGe TMguDlUrD9PiV2VQSbL4s9mkjX/uT9bxetqlRpw4fzaaP7nBEmBcF511f0rTp3Tr66sEVXHf96HM EC93D2QMVvovUh/NbjhMkrbu5XPHyU0p5RYXJyp7Dnp4ngeXfnhZL5iiemO2sH9IVkqr9aUQcOB2 YSz998IALKjHwvbun6Fg7qD2pJLIqmp6A6JuA+YSDsiFnhBgIAOgXHhIeRQqB0kNsZpApZxZonuf BAwDquewnCireYxF3EMbjFPcKSHgsMCJDzU4o6SHWsWrRWzE8ToJb+HR4MkRMlAWtbq6kWgiye8D C139FiNWMpiIF7pjtEoX5TGlivaERQhPahaPp3tnVJH8WNBLcCISK2MPG77AcO4Tz3K41/OOxbWo 6+9SrNgdY9eRDPIE3WShdvVuRAaHo/BAvK0aP873L//vb/rxRw+rTZg45NzI+4LRz/MpThoHv+fz +kU/zXKrub9z3qcna3hxLsLlllNHRFJZ4hqDOm95bDTiMCPeIYkNuvEvJKglVw22mR2VClPVMsHw SOCvyo6Yx2xQ5heaF4ZBbHtDliZ9crowvipKnMZitpLKLSofXBfzBm9zWFc/gocF4VCLSwz2VKbI 2SdO1ZyQrmFzQz487WM9m8QKBYXtR/Xz62IhciJA3noJ4IjHsYt3u9cKQ3ZgYNLTIpOAtd/HQrIm bMns2mBNOUEF8nnmL2ZNcXWfVvRD8IPIWDXLd4ql6xgdYp2bvCpbx0RU4wuHDvy3Oz40MTvdbgof coPUZdw8CzuV7VSoSwYJguEiuj2TiCzdzgZpZpbzYuI6O09IUtvusIzZkKbUg9uwV6YQTSkmNLiJ i4NvY7f5GN3mU9wuZrGkl9zqVXyK6+gO83hEGO60jFk3j1XsYjbdxWKyzaqBVxGrjToyz07oJaVE yMxaS/P5Tew3lPPsZP6vVldiqVNWw8KgkHj11VcRU7opTlUoTYjIqx/VQnoWk/0m1sd5XKFzNZ/E hnW1oH/ldcyOk9geH2O2vtO8uj8c4hOAvp4LRpM5ZymbI7y1BwqkNzG7vbMWFID6ah6rLK6uMJnn K16WMogYbJpXmMDJs1SfRwiNq2stqKpcAF+iEetZTSiKBtmg4t07sCSUHTZqMDtfUrGwVEflzUen 7ykuv7mzpAzX+vrtF8ni75QxXC1n8fDwKR7vH/RMX9/+Ql7Sp/ckHfbx6tWruHl1Z/yrvOjVKu4/ Pcbt7at4/+F9vH3zRayXa6txHG7Fq6J0Cg9YBovk6NU0JvtOYdrHHZI+q1hcW5FDXcsp1IYUe/fL 6Ej8hEvsUMflFQthZpNYHt/G9rCLLV6stL2uYoWXrcbhR/WKZBHZuyOZ1KmLVgD/TC131GOu08UP b7BUE5XCe33op03JJM4DmIUWsOVi3bDUnXTYuQX+qQjYhB9q29mo1F0nJrEW2IsOZV+c4PVfFd/K SjynJVQ27azV8wvHSyFhW9jZur71Hu3aE4pm0w1OHW5L2wx1f5fO3ZZInIH9GMe5vRDwCgzboBDZ MuXtgBXbuwWdywNQqhvy6W4rOWUi2l0qZ5DKAGRHXHGCFwrWl1iZzkUyxAyNNNTZtkjVtCjB4pVZ XbNS9iyelgeE0fxwfy9sBxrDZHYtABaAmexvtf/ObcZPVpkMR91WsqjMq6srVSWh+8+WcdOh4zDH +hojA1GUjYes1PlzbJ8f14oBkKBghn2auYkNMYb12nHYUwbLBdJQBzoVR//mN/+mYfrVr34Vf/Gr X8T13du+0SnnK7kfnmlhWOrWDZWiA1BPmeusgGhZ79QX6hlvq6wn4u3d27hZ3cT24dvoNlsrV/A3 ngMGYOXw0kmtCmOPzwD4Cql5tjX3ea7C7DSvaAk3E/kYYT8gAVFpxPRPbFl9Q1nzrHH31NTm3CuS VF9DXGhXwMDD6luPoS8XP/BBbKpwt4xVUgmkqAGArg5TCTCnYbHLaNCP0IgOSWR9ZgLIwaowV65p u6Uui27RqdudLeosSFrGcmTAVIwsmYzvrwgxLl9oVRlasL1+X6+bSCf9PG4fDOXz9krjn/3eoZ14 hW0UG4sMKMyBkKyyinDIzvWEijBZ4nwl4yJPcfOgGjdV4EvBgIJrQjRtF32t5dBaqhrGZkZsiR+Z WU/VbPL+XPC56Fi0NUYVdtW1YCyF480I6YwjESKqf9EhYjXHe3O1mWVLSs2jEg2C3Pv6RrLGmkZq DWZemEiW3V68oesr3zuhDjSI2dyhbz239hlxD9QrluQLvysSbmXdSq+r3WDOn+Xx7G/QPKxAULV3 +lSF9OBlZBCdGEnQmsJ9KZAOBcS8VudjE1c2LcnLZZwBrXMuwmsrEUsD+KV667m3vlr7/gi7swFx a7AW05UMm+pqE0MThC4HeB5Pj8gn7byRUF7Hw1k498J79od7wRauMdWHJGveunAYoVJD4VlxcolE AolIXHCARKjz/OExrMQc9F2NbLLAGMXKFB3zYrSHZULlgAGhY4TkLSlSdtoFGIunltPiWXqjKd23 8vJv+NmN403Y7AtzRC9gIn335bege2VfWlrDpVrH1kMa7971n5feuTbV5aOlv1bN2AA/qiGsynqq H182hBUYe4xuu+0lZFqGuwqPNxtJ1RCas5ihLwSic7GIDgIvZ2RXt6ujUaw2Z2qBJumYNBya0Ejo 4J1ZFqfbnzecqFbpeBSwwLk+BPQmhF+EFVLTcKhtMYh9XN/d0qHdxEXdow2Swu5UQEiduqxdm8WR hUBfSpRs+Q6utkYhYxXLq7UykgfAZlq6Z6VCYVp93Wf+DsmbFvepLKuMYKqcVoJivDFp+ieIj3f2 N3/9t8oK8h7GQoKF9BVAsWThDlGSo5F3gdywdeOF5UGt6Kpw3HPaJUmWvxYkQKlZqj1IDePqyp3F qLpgw1+s4np9JV6ZcKOjja6liYe1qHZ5zb1aicQKqW0kgQe7JtGhShU0zo6xOe1izqlX+EnuBYDH DF55QvWX6gQKsdE155z7aqpRm3NWeqhFw9DQRLSnH0siWTwr952SlVYZzP/f27nwNHIEQXjWXoOX Rx7c3f//hVFIuAMWv6Kvqss7ODkJKRKW0B1g4/XubE93dXVVc4zaDAWqB8hzz1/BiI/7dgIHMgub jgQMZspGGM3ClJJAZehSWVV+hjaQSwYNHpfRs+ArBQuJh/zPz/ae9d5nWWGzJzj5Iycg+wbsA1Yf HM9BLu9TA9WxB9fuWxZQkufxB67fUQI5UOxrAbMwUwZmAJrsZ5KKKGVca/v1dTti2wTmU9NEaRb4 7HYs5WK1U6rH4Qiqg0aKxPE0nsGNGjnm/J8bPTjadANtYmyvw6rN2uG948ikgYws8r/Fx7Fc8+I2 Y5clU0LUn4SLNzBG4tchzTyg1T5e+UoTrOhmrpnvm9q8f8+962kOfE/pppd15693/wk7+1wy1bXM vKYOscpguFcPDw8LdYXXzM9tnp/PXKkExkj8oL2fEnolEqg7eHL8Lg8AHj7+WvcdWfbp8UnnmU2A 4yeLAwvib/fKHcrK6/WBITR3yuQXA+1QVcbFMTxr4JYuMMezd3eSGUPIn6gIn8KPU/lIYNso8zqr jOo+IeEgMNoTVPLauBDBLwPPUrc5TYpPcM2xwcaxjatD29BuhxQIowjyJzZWTHyXDpXHbKAttPZW HBj9nEgr1cti0pK2ctJESa/sp8rJUtE5t4GPXFRwI9XLFgZUwBOHimP5OH7VEw57nOLyeX3wEdFB WUA/U1XZQmkIXZaCvZBebhwHwTgzm3DrRVOjP5Rz1alxZ5DSwyVYdngv3GVsRC3/7Z2COIGbnfy4 scNN3FzcSWRA1tdCWWYV2j4HHmFirApxweg40WHive7vfykFBZeEvfY6+JANHPhUZBZkRe5uXkva GvoH0c8bDIRSaBMxIuKaMqomn8FzuToIrOVvUXT++TyzcNqJz4ZEy+4gRhnoE0AyG2mCTrLh3jSV jCTH3vs7JhvrKQzhbvEVzO7vp7/KZMTjPu5ujgLAOQdXuPG8PLbHPx59U/5ueeqX7y8qR3/9cvdu FvSgQOiuoGSY4S+FrlGCff0miOopADsbC1wyVFI9cnOUBpcMHjRsDIZYEAdXMmUuND3kjJRh16ao cRk3zujgjuuDHYH2VrtQBqiakAaQCcLCXqVJB0XGjYxhmIVVifbDFASxQSoenFPeg6kXRxDDIp9A a4DHASuWgeZJw4u+5XbyzuB4DohMaHdEBExqoAM8DOchgLssqgkQlZMqnLnEwJjFA9QOtlEcqEXS Ssu8uF3JbrLYXRZ+9NFnTZe4VQ+MX4K3aeH2v/e/iwhgH7D68lO/c/dhYRGfQV0vnoxZaJQI3IOx lQ7YZqFmRCMu0D2IfCyO2wlpX8BVGarK5qWNFth/N5gZWoX5VOyYjHCUwX1NBsjMg8uYEarO1ILg RZaR4HmA4gBNBTY9q78ckcWyi6ECuFrX99AR1SZgSp4NPTlMu9ec2r74YD92pzbID5AZVSsRjMd9 u10d2u1msfm6zJJznq3osOCA4XWl6wro3PO8ovrAc3ltKAqcL7IbMg09B+XZwfIuOT89dhZZmQRI abxvtrqx59cn3Qvb61uNRTELKNpEPAs6zf4cJ5fBpeJOXDI+B7/DRUeZYDClMpz14DsbEyHCVYpx tRKPLL5eg9g9HNsV84sb1hGJCEPinpNsjWAJ0dvUbt2ReGm2WRws4oIVTKmy2IxI6RAgsGxN2bk4 g/4MEwoJjhWHCCuvaw1+g0MRUS17QVZE0cfhcIrUHVf7FJBu15ALp6Ut9jdZiSzlPfi7q5LLd4cK vw7oXKy9hfC8mxT/+ONnYHgwrb5L2GdHPHI8/37PaGKNPw1a/d8NCzl1fsZ/0vlzGVLHRHdvw4K/ kcrm4tlnUJasIKMZs6geBChnIQQo0yVK3UDlGYFhweTge0F5QoESFdEVwVIKq4CpWZwmkUZbK07K EQbkC4qDmW4YkZT22LlrYsAVxVU7qzhwGwddzlPODT0H+ir8ex6KPx3bNN0JxN/zLUP2GOMiIsgx 037/D1fi/lrvOlJov1nlvMf4NcEmgYdHMjHztaAz3Ngxuq2lzcUX2QnPefjN7ju8Zt6/tqtx0759 +dq+i1Jgeehpe1MkV1fECnxSGClmfgyZ63spyk5T25I1Q3lBcWKFNBFlO9jZpv14Ke0smrLR0pK3 okdhZDRbCqFZR1JNUKeaLcHBhckFZG7InFBe4b6XU/jpvjZS+JVOGQhk8oY+zG0Usdo9XlmOabyN AO+u+pvswaJosG7/ALLFVGFVweIfAAAAAElFTkSuQmCC