Detection of Desertification Hotspots in the Algerian Steppe Using Remote Sensing Techniques and Google Earth Engine

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Abstract The Algerian steppe represents one of the most fragile ecosystems in North Africa due to the combined influence of climatic variability and human pressures. This study aims to detect desertification hotspots using remote sensing data processed within the Google Earth Engine environment. The methodology is based on integrating the Normalized Difference Vegetation Index (NDVI) and the Bare Soil Index (BSI) to develop a composite Desertification Susceptibility Index (DSI), enabling the spatial identification of degradation gradients. The study covers ten provinces within the Algerian steppe between 2020 and 2025. The results reveal significant spatial variability in land degradation intensity, with critical hotspots concentrated in southern and peripheral areas, while transitional zones dominate the central steppe. The findings confirm the effectiveness of spectral-based modelling for early detection of environmental degradation.
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Detection of Desertification Hotspots in the Algerian Steppe Using Remote Sensing Techniques and Google Earth Engine | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Detection of Desertification Hotspots in the Algerian Steppe Using Remote Sensing Techniques and Google Earth Engine Fouad M Fakroun, Lyes belaid This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9680091/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The Algerian steppe represents one of the most fragile ecosystems in North Africa due to the combined influence of climatic variability and human pressures. This study aims to detect desertification hotspots using remote sensing data processed within the Google Earth Engine environment. The methodology is based on integrating the Normalized Difference Vegetation Index (NDVI) and the Bare Soil Index (BSI) to develop a composite Desertification Susceptibility Index (DSI), enabling the spatial identification of degradation gradients. The study covers ten provinces within the Algerian steppe between 2020 and 2025. The results reveal significant spatial variability in land degradation intensity, with critical hotspots concentrated in southern and peripheral areas, while transitional zones dominate the central steppe. The findings confirm the effectiveness of spectral-based modelling for early detection of environmental degradation. Geographic Information Systems Desertification Algerian steppe Remote Sensing Google Earth Engine NDVI BSI land degradation Figures Figure 1 Figure 2 Figure 4 Figure 5 1. Introduction Desertification is one of the most pressing environmental challenges affecting dryland and semi-arid ecosystems worldwide. It leads to the progressive loss of vegetation cover, soil fertility decline, and reduced ecosystem productivity. In North Africa, the Algerian steppe represents a transitional ecological zone between the Mediterranean and Sahara climates, making it highly sensitive to environmental changes. In recent decades, remote sensing technologies have become essential tools for monitoring environmental dynamics, as they provide continuous spatial and temporal observations over large areas. Furthermore, cloud-based platforms such as Google Earth Engine have significantly enhanced the ability to process and analyze large geospatial datasets efficiently, enabling large-scale environmental assessments. 2. Study Area The study area includes ten provinces located within the Algerian steppe: Djelfa, Laghouat, Naâma, El Bayadh, Tiaret, Saïda, M’Sila, Batna, Khenchela, and Tébessa. This region is characterized by a semi-arid climate with highly variable precipitation patterns, combined with extensive pastoral activities and limited rain-fed agriculture. These conditions make the ecosystem particularly vulnerable to degradation processes, where small environmental disturbances can trigger rapid desertification dynamics. 3. Data and Methodology 3.1 Data Sources The study uses Sentinel-2 Surface Reflectance data covering the period 2020–2025, with spatial resolution ranging from 10 to 20 meters depending on spectral bands. Administrative boundaries were obtained from the FAO GAUL dataset. Sentinel-2 was selected due to its high spatial resolution and spectral capability for vegetation and soil analysis, making it suitable for monitoring land degradation processes. 3.2 Pre-processing Data pre-processing included cloud masking using the Scene Classification Layer (SCL) to remove clouds, shadows, and invalid pixels. Spectral bands were then normalized to ensure radiometric consistency across the dataset. A temporal composite (median composite) was generated to reduce seasonal variability and atmospheric noise, ensuring stable and representative environmental conditions. 3.3 Normalized Difference Vegetation Index (NDVI) NDVI is widely used in remote sensing to assess vegetation density and health. It is based on the spectral contrast between near-infrared and red reflectance. In this study, NDVI represents the ecological stability factor, where high values indicate dense vegetation cover and low values reflect vegetation degradation or bare soil exposure. 3.4 Bare Soil Index (BSI) BSI is used to identify exposed soil surfaces and is particularly effective in dryland environments. It highlights areas where vegetation cover is minimal or absent. In this study, BSI represents the degradation pressure factor, where high values indicate severe soil exposure and advanced stages of land degradation. 3.5 Desertification Susceptibility Index (DSI) A composite index was developed to integrate vegetation condition and bare soil exposure: Weight Justification: • BSI was assigned a higher weight (1.5) because bare soil exposure represents a direct and advanced stage of land degradation. It responds more rapidly to environmental stress in dryland ecosystems. • NDVI was assigned a negative weight (-1.2) because vegetation cover acts as a protective factor that reduces desertification risk. Its influence is therefore inversely proportional to degradation intensity. The asymmetric weighting reflects the non-linear and unbalanced nature of degradation processes in semi-arid environments. 4. Results The results show a clear spatial gradient of land degradation across the study area. Stable vegetation zones are mainly located in northern regions, while transitional zones dominate the central steppe. In contrast, critical desertification hotspots are concentrated in southern and peripheral areas, indicating strong environmental stress. The spatial pattern is highly heterogeneous and follows a hotspot distribution rather than a uniform trend. 5. Discussion The observed desertification dynamics are driven by multiple interacting factors, including overgrazing pressure, climate variability, and soil degradation processes. The results demonstrate that combining NDVI and BSI improves classification accuracy compared to single-index approaches. This confirms the importance of integrating vegetation and soil indicators for reliable desertification monitoring in semi-arid ecosystems. 6. Conclusion This study demonstrates the effectiveness of remote sensing techniques combined with Google Earth Engine for detecting desertification hotspots. The proposed framework is scalable, reproducible, and applicable to other dryland regions worldwide. Future improvements may include the integration of additional environmental variables to enhance model robustness. References Borrelli P et al (2017) An assessment of global soil erosion trends. Nature Communications, 8, 2013 Fakroun MF, Belaid L (2020) Wind erosion hazard assessment using GIS techniques: El-Mesran Area, Djelfa Wilaya, Algeria. Eco. Env. Cons 26(4):1555–1562 Gorelick N et al (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens Environ 202:18–27 Hugueney P et al (2021) Topographic controls on aeolian processes in the Maghreb: A remote sensing approach. Geomorphology 375:107542 Sahane VV et al (2022) Assessment of soil erosion and land degradation using Bare Soil Index and NDVI. J Arid Environ 198:104685 Sidiropoulou A et al (2023) Monitoring desertification risk in semi-arid Mediterranean ecosystems using Sentinel-2. Environ Monit Assess 195:412 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9680091","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638285101,"identity":"2837b495-db16-43f1-8c94-a7236714f195","order_by":0,"name":"Fouad M Fakroun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYBAC9gYgwcMgxyDBwHwAyJSQIaiF5wBYizFQC1sCSAsPKVp4DMAChLWw9xh+eMNgIC85+8znVzdqLHgY2A8f3YBXC88ZY8k5DAaGs/lyt1nnHAM6jCct7QY+LfYSOQbSPAx/GOfx8G4zzmEDapHgMcOrhUcix/g3D4OB/TwenmfGOf+I02IGtMUgcTYPD/Pj3DZitPAcK7OcY2CQPLOHzYw5t0+Ch42QX3jYmzffeFNhYDvjDPPjzznf6uT42Q8fw6sFAsAxwsAmASYJK0cA5g+kqB4Fo2AUjIKRAwA+BTv5ap3q5gAAAABJRU5ErkJggg==","orcid":"","institution":"University of Sciences and Technology Houari Boumediene (USTHB), Algiers, Algeria","correspondingAuthor":true,"prefix":"","firstName":"Fouad","middleName":"M","lastName":"Fakroun","suffix":""},{"id":638298183,"identity":"dfb7e21f-19e3-4c03-8858-8286a6757b52","order_by":1,"name":"Lyes belaid","email":"","orcid":"","institution":"University of Sciences and Technology Houari Boumediene (USTHB), Algiers, Algeria","correspondingAuthor":false,"prefix":"","firstName":"Lyes","middleName":"","lastName":"belaid","suffix":""}],"badges":[],"createdAt":"2026-05-11 13:10:09","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":true,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-9680091/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9680091/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109273803,"identity":"a83b562f-95ce-48ed-a831-2590c873fe64","added_by":"auto","created_at":"2026-05-14 14:31:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3728922,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy Area Limits.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9680091/v1/40b37492661d92c1c24e102f.png"},{"id":109273804,"identity":"779667e4-b238-47ac-93a8-9b6e2df0b038","added_by":"auto","created_at":"2026-05-14 14:31:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":457453,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGeneral Study Framework.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9680091/v1/069e7b8b867eabe50a753e03.png"},{"id":109273805,"identity":"c25a5288-2651-4146-acd1-4cdbab478309","added_by":"auto","created_at":"2026-05-14 14:31:06","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":623180,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBar soil index BSI map.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9680091/v1/68becc83743aabb72b53f4aa.jpeg"},{"id":109273807,"identity":"c866b00d-9725-4134-ad42-250699f981fa","added_by":"auto","created_at":"2026-05-14 14:31:06","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":699858,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDesertification Susceptibility Index (DSI) map.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9680091/v1/361c1c24f39d74e37a11c750.jpeg"},{"id":109296596,"identity":"98a3bb3c-716f-428d-b80d-b26533d6348d","added_by":"auto","created_at":"2026-05-15 08:48:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6600193,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9680091/v1/d3ab37a7-05ab-49c4-8868-77c45eb2a2d3.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eDetection of Desertification Hotspots in the Algerian Steppe Using Remote Sensing Techniques and Google Earth Engine\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDesertification is one of the most pressing environmental challenges affecting dryland and semi-arid ecosystems worldwide. It leads to the progressive loss of vegetation cover, soil fertility decline, and reduced ecosystem productivity. In North Africa, the Algerian steppe represents a transitional ecological zone between the Mediterranean and Sahara climates, making it highly sensitive to environmental changes.\u003c/p\u003e \u003cp\u003eIn recent decades, remote sensing technologies have become essential tools for monitoring environmental dynamics, as they provide continuous spatial and temporal observations over large areas. Furthermore, cloud-based platforms such as Google Earth Engine have significantly enhanced the ability to process and analyze large geospatial datasets efficiently, enabling large-scale environmental assessments.\u003c/p\u003e"},{"header":"2. Study Area","content":"\u003cp\u003eThe study area includes ten provinces located within the Algerian steppe: Djelfa, Laghouat, Na\u0026acirc;ma, El Bayadh, Tiaret, Sa\u0026iuml;da, M\u0026rsquo;Sila, Batna, Khenchela, and T\u0026eacute;bessa.\u003c/p\u003e \u003cp\u003eThis region is characterized by a semi-arid climate with highly variable precipitation patterns, combined with extensive pastoral activities and limited rain-fed agriculture. These conditions make the ecosystem particularly vulnerable to degradation processes, where small environmental disturbances can trigger rapid desertification dynamics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. Data and Methodology","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Data Sources\u003c/h2\u003e \u003cp\u003eThe study uses Sentinel-2 Surface Reflectance data covering the period 2020\u0026ndash;2025, with spatial resolution ranging from 10 to 20 meters depending on spectral bands. Administrative boundaries were obtained from the FAO GAUL dataset. Sentinel-2 was selected due to its high spatial resolution and spectral capability for vegetation and soil analysis, making it suitable for monitoring land degradation processes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Pre-processing\u003c/h2\u003e \u003cp\u003eData pre-processing included cloud masking using the Scene Classification Layer (SCL) to remove clouds, shadows, and invalid pixels. Spectral bands were then normalized to ensure radiometric consistency across the dataset. A temporal composite (median composite) was generated to reduce seasonal variability and atmospheric noise, ensuring stable and representative environmental conditions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Normalized Difference Vegetation Index (NDVI)\u003c/h2\u003e \u003cp\u003eNDVI is widely used in remote sensing to assess vegetation density and health. It is based on the spectral contrast between near-infrared and red reflectance. In this study, NDVI represents the ecological stability factor, where high values indicate dense vegetation cover and low values reflect vegetation degradation or bare soil exposure.\u003c/p\u003e \u003cp\u003e\u003cimg 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\" style=\"width: 187px; height: 66.8339px;\" width=\"187\" height=\"66.8339\"\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Bare Soil Index (BSI)\u003c/h2\u003e \u003cp\u003eBSI is used to identify exposed soil surfaces and is particularly effective in dryland environments. It highlights areas where vegetation cover is minimal or absent. In this study, BSI represents the degradation pressure factor, where high values indicate severe soil exposure and advanced stages of land degradation.\u003c/p\u003e\u003cp\u003e\u003cimg 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zhlmtbrycuXT537b386/Lhj7rzySEGiVU9ElIbG1+pyoeN0LEDC3FD08KpaktRcJyAikL+dWU1oFDRmzgMQKBWB4EqECpQLg/SRs0puCYTiGoHipmkFla3fhBQsDmx9rwlcBuDVahkj8cxjNBwkQowXtF37+TEFLtBwFbmmL4YWCnOHB3KpbPaTDuReGkBlDHtJxAVgoegs9i8laGh+mNPu80gjSFAURaRHUSVxDpLEZ+gwkQMtqQ4OZeOgVoOZSRSJpn4ISRKukkz6DkEaV4UeNLjlI8Z3/jUJ40iMKgcIcVmEXxIo7rC6D7/XwMymKUQKOQduspHDHF3mRhgeNyFJukMydn2n0OD4gzmM05tTp1ulNBcGENP33grIAK16hHCECcqNNp32YMhALozIfSQVGb4OP2htLYwOUlb4+KmtFrlL4uHnMGdUw+Ic+3hSNNIaM5hmlMXx7GsnkM6NtRiOW21IvLCtkkfGvvV+Vhp0bU6r0SiX1d1DB+BgwuizfYXI/5zyddgAaAYSYORnRjAQNzPeqRXCMF7G6MjNT1pDuRCD2cYxKAAbepMr4LldHIVQMaspNTHiU8XLDmMVq+VwpuFEIFCMVE6Ke1yGR8TuY8nKA0GMqw1OqFNx8bnXhztxZaRlTjvPfrEgiY4kv3t1YE3wcMyLmmRFpuW6+v+9lQiAavovCFr+lhATfF0xA0kIngbAMldN0oV0Ib4v9u0yPFkKTYMUrSgVF2PAmljoDQZICh24chBCQBAq5wEfJRDkNDABWEMOEOQmeSlFNcfBy44SLFA8tGKN7zjOAUpvKku/ynA6tMacGUzDi1r7nSFxokoZFgglyvpO5NCpAV/6lYDShpbRqHX8wBvR3i/BdAJUnDRS+U8GwqSuNkAYLodsN7jkUytC9d1N6rngkQEKCxIxJVzJi9ECelNUoR904s4pZNXQ73RbK13hMLGSaZ5nxmIciYRaw8Z8HJJxWDLYutMhvdofzrOe8BfQgY44YMxOUBldT0hDSkPMwowLEhUCY77QoB0Bahln6/KzkGseXD8x18vN+QUwDsXjIMWfwBYDSoyEPUhm5EmaxRDm2PWLoMCFvRpxLMB+bRhzlBEPrZixKoLdhnqnDtaDdgvZBehB6PJGAMjw7Lix6wwmWNBDLFIaaqfd/5m9wYXifeVqOb+qh30mwdUKBIGnBFyEEG4fGASBUdPauwpAFEPNy+5TL4RASiMlGKm2Pevi7haHxwJQReYYwcplcKDO3pEQs9irC6j4R80xc4YDWlVBTCgNZHON/rVsASIywDPCOLhIxoeMAJmOxTF+8EtG9OFeM9kySJNBAYUmE0XV1ivVqoSQJdIlDiTUybmnNqFuwTtj2nAgTTFFsXCcwVVbRmXBAYO4nxsiEu92jqqz0s9BcHk2pqSD3HKMoJEQkllyFGwNCYhex3AoCxzEIAoQLgWJzAgkw9odO7VnYsyRyw1MRNkmQBoYno2Z08yVHrrkRqc3FtlAIgDQNlk/IETWzbRGlxyGmEFgxqRTwKSuQ1PBpdrHRi4W3ixADLxHuH+R+JINLMM9NS/hwuXyOayS+g1JBFN5JYDETw9xeYcVtFoz7g/ag0UjMe8hjz8IfgQRteb0cpSAqBYnxgXsqanmUQJxwDba4PgODSXDyDq1Q5oQdjgi25SK6D828SFRlRSkovERNcAqIb3CsIqwa3bBzZaF8NrKwK4gLpb7SamFSJyRq3piV/yOBMqYMWDRBwHeHkBht5hBEJAGAefmWCDH6Z7idz1GB+ztJ97Y2gwtrCUjXhRlT0AtxRnpiftbHoeB0v8rwxRuBaEJVSJ+MmRWQMf7KC7oRUxx8tc/b6M2MNjF4q2YQ9X2ErKg1wNicfS3kZQ+9OY+IeZsAkAQgEUVinr9GRmXUvCQoozXlvFil6gRHX6681Lx3wHhHBCIp4ZGXfOh8UsoYk4WGgRBSU9CUP0Fp0JFnmDZyvvV7/H5FLGSHWuRHQmCFrgCi3JPn6RvHo5NGkrAgBv3KzE0jWkRcIonThbwxndokjWB8UsUYxT9trCIeS2LmokrB7VdBcGJKcLUNiCXyuRhBHsms5NrAeK0hCEXJJ0hgZvkVgtYsr1yphAqB4srBrAOGcfh2It5GFAYV0yRwY3cBF5uLucb2T8IJKOBGojBlRNFAWSMcu/BGaFKtztSByGQVAOHkFpSa4BR4cQXfKRa7diZREzjRFa6xbfke+8zyNSyYtddbwlnN21IbBwYXAtCFXqnUoxlsFPouHEyYmgdZWLBiLmExGydgYwihlcn/+kUAcg6W+7LCDptSodRhxpoIw00sIAJj/ZAi7h8CIxExUmEw5MlQR6G8wGczCzVFLrJYt4I0jWgbS00AkXpZgEJBQuuVfOaVmUb7wRRViCxnRrRN0bFQ4FDHeSGeSHtAme9Vyw05rTumVBkas8fIt/yrUGbKknLhqyy8G4GcxkGw3GbhaYNl34CFiE2JOx0WcsWNw0QKvnUjiGsw+lHh9gzDH0D6odCkEom23YKvK8cXMY+oyNUy/lUozUBD0ZWDV9hQR5t3B0WERx2c32F8EpGkAQSTG+6lAc1QGUzZ8LtgMlC4RDM7SAfuAfvl84we6WDwjuObggDIU1yA4dbmEkA+NnFiNQVKY9KQzpmavDA5UODeOI2yjvKSc1TSgHnZgBvrlj8OzEMzCsMXMGpEWojwOfE3yZnyRogCCMy4KnLcJtsDlVg/rEplZjraEQIPBbk7aEASI1Y1Ac3NubwfThhiSiaQQPoJjAhx1WgA93CACVmTwohe+VdYVgSIMyJzdyZEjeFUFTH3kKOvzLxKQxCnasJIqOTs1uK7fsYIxng+d45lzGZ4LBSKDaKqyC005/MT13Xm8IuFAdwdVysYEIOLAquF0UhIBgdXJpZHgcFPVVn6G0xpGPEVxOrzJjWV49k8fUx+QKWg0QSthTw1cn+ZGrO4Re1zjLZB18fkaq1wIroFyHv5fN/clGsWKUOSamE24qRngrmPdGGRYHX40/ggWXpVot/JufB7hi74CD+ngeZhT5bnh8AtAoaRkkfA/KkCpSVrMCqFdd87lRPMMo/jEXYeekYg7RAMXHc0y5QKw4SfoQ8mbF2QE3/OS/6+Ei+wjb0mbyASLHlOg4iGoKcF+JQL0BK/PjczJGxOMDpiREW4wT8YPlFWhnoFsiMkeAjLhud7OD7McYLAIhlcr69LYIZQsTrjNfvtBodysQZaegXkUXcSOb+C3gw3sUh5WIccm5vTkqHK3t/Hp0KB7Tj2H86bdQUM6SmFdTEO6UcMDlG14FGXIbyFc/HpoN8wtXc7v/izXBtKb81gpOrNAfrXRjpyhRVsK0keLUxe8IDDx+VtHwxBHvP8mxOswuScAmLKrn9N3Mdn8++X4WJ6x+W+ySMAVkXZp8zUicI9FQUgSeG2ukAnkVAA+M5vTt4UnAE1iCA4bOyzArCGg+i5DUeEY8aQWSKkJBRulCstRWi/EOZyfB+Ph/74Xj7PudFiLN/jTFta+kRMqQSoLIywXEDaZkbezzmycqcvjGHIiG7tmucIJIWyEAUkeqjC1mNtZBx+fVgtmcXgVVg+YM6Ef5bM7ujkUNygSI85MYtcLWTrRMJVuzKkELJEPwKrsICy6EMBaDDvxddgERyrWhXHvViIzwwfBczbBCHdx2hOZ7AEPAwMrIwscat0h7gXysIhBiTzDowBIaxS1QjuTyCNkJ8sYhBgVXlcGJWEyRHNrfsEQ05O+1TXpGNRQVBuvBfHpRhNmhAXgWnfyM3zFlIBYhGSNsTz/5HjEkjEm8LgYMKDXUYYCQEI/GDeZUBA0ISVimpl52B1JedouDGvX42fYR6sqhW3qFfGlgpdodyYTaIvvHQKdxds5DG1MFhU5tgouJxGzfs1pRNz8gQLL9wILbupiG3ih4DVw32GL8C5URj71e/BkI5dbsBafpG+qEAA32xO/klg3YKC3WPvYJWqcZcqveYix4ki3AijBTXvOLd0jPbh0/mdYW7Sh2pEKAR9n4xAYl6MVQ+6fFUKfUYVvKMRN5IXtGjcWxhIfTJZwRSKr6/cA1bmzYIwFy1mTClgio2RA5dRCnveIgiUgawAj0oZ7u9xXPB/xv8BRd5UPZrikaIYkVhayvFRQDoEhhACmIxj9p+gdUu5WGChlEjUDI1GJCm9MZi1ZdERAqHPSkoCA1cORDJA37vsL9+Lw8k6YZVWnFvRHl7xrhQeklJTCAorhnACNNJm+fDqiWJXHGISjHH9PoAF62nnjCDsviC+F0LZs5GeGi1c1WhgobAQ86Tge1IkMJdjjFKWsWshVPkqMgiibQmAExUrAkmg/BcrqjgHsbEUHAPBiY/CWYJTMg0CgeE+knioqDmniFIpRVMsbi17PkwV0LzEm5A6SS82Emw+OThPN4zcYo2RTEH8WZVUQmYmuXt4jMzm3QWgFoq0oiMim0okiAlBPk2GM8EGe6eHeKnESMccpoRjkWryzaBiczNrXIwG1eeofV49gEQS6+WiUMmgyMwyDVChnhO19mRFWA0mtCi8CUgL8ZhCdsgEy1k5DSloJPjGciNt5rNs75KqIvEwHoS5QwFzggzQES85K0mDhcZpiBlWTUBDlZGnPl3isgIwoS1ca5SICDM8zKDiECwmccOq4En4nkIaXQryFW271d/hf5B3onWGoXB1/WMv400JaYefGVwAhEDaBmLBd1DKSg/1xZy8HV1OKf9iC7rV5YfEEp4w2HALAhBCSlaEhdxMRnKaBlBVFmAJ802hb5uKX67IEw/BKvk+WieYcvuTyzqL8Pg2AWWtBISpBIDl9+y4w+1NattXJAaGlZXpHpbeuy7gfj2PhpcGhuOT/2bXppJGeXEulAVW/WpRiGjyX1E456Uyc+Gsala4UGDQgrAwhlnSUljVRrHiYShDToxFCTDsXvS9/P/bpWoxZtvvVrjNfVdSELELSCKYAs+FGAmf/zPBolqEwlYjLKHlh771+1xcwXFsI8L+e2xOYu81kQEB3WDCyFrFmJLWQlfyH45YY7nV1svX9FXNKYm9IAALjwhBRiPVdvYrzOmDManztSkax69g9RAPimpLE7SwsLEzis+ddi1/m4dIZio3R/LVvjK7rMDAcRBzengljkp4AxSkfJ95XXAvil4u38XiiJCYZnIB7rmLvssNkwJmrniLHBqFM609WD6Yxh3zt8Q1aQG2skADi2ZgqUTt3cGMHb/ICwZX7eNEfst5WMUt4eseAzVoHnO63tGsYqN1wNZla3dacuMA6KMdm7laXoOw7+cBKsjCuwIFIWnAYNyPV88BmUHM3DDHElsTw7GMSqgpM2hfhyFTwORpz8vSCAxiaRnfAmL8yHtdhTtNGU/ZWgtYGJipcGn85Dlb7nlqJIAh0mCFL4kVKkQP+YG0AfXIiKn5UCnu8/d4JMZ5JwRajKGvA0vBHyYjCX8wFGj4dCXl/BESL8qhgR6VXi3vL9f8v7/5XZkLBbSQyx6CdBiWdMArwB0DM+zMqPJ5+P1Ofy5X/DOY517OnzRGg9rW1deVxvXEavOwbSQAjIc5B/TRYaHMogtXtzo56+I2NQQVAIt2oycg1RP5FOoFU/kL+pBXEAcxZ4uhgPRn/bdbtCHQ8wmBghogA6mWLOfaGu4RReb0YNUv/n7hg/YUmUFsfsRpKRB93sV6CmIwzxDlfEwC0gq2eSQmtCiwUShVwIjClBLNUGdLQ6IL1cJw6FMSYs8BhcdHnPDiUpUeqdJyJT/53AQi1gWiYAQnZrvXDJVgYUCbAYLlEERAT5NvNE/e4EsE8jv34uy9vJtrCcXnbjVSIILGOn8bVJw4FcrPCxhRiFAgkC6cdktYw+hCzRPhx2KWK+AhGgpEMdwUpc0mwMstMS7IzPBzL6q0z80DpzAW3wRvPfYiEWnhW1NwAoN5KQQBCk4xeNCL5iQYWeA6qIzdazGHMTB0WprFDjMKkgDLi3h4sQgxMhRYDl5a1P38X/BEZBhSNULU86J9dA56BtKnLNU8hDJsRmXiYV/ADDKfh8HRhR9xbvRPTUucmIDm5/3/Kg04RHuHWfl+R0kbFpq3kwhCQSPlcPQW7Hnnr0KClXCyiogidO0wKWFhQwr6wu1eJOTr678cDzS0RLk2V7b94/v8fNQg/R2ZDF9Ca8F5QoRRBdKZwRZUqtHmRQVW4tdpSoRcwnC7kZ19Xl6kbzeWKAc8AqSFsRsj92xK4PtCSIwPS9j5Dw0FlEfAtBqLzTLhwzCPh8AoL3d7jSSBoIzHl9JhNUIDqMHJJCVifOzCku27VG2xFvqImrOrusJKZ10x9ItSCqLieWMeZyJauP/zHvstSSgUcTF/gGPY/PoJDxBamMoYMO+1b+w2VYUKO414uTkJxZCoFmsGSEwKpAnLyLu9rn3hG6gZl2fOhoKPS1SrcDOhUE67EACIAgQKLkC42dYsUEgAywFMMRshA8rYtpXXstzbBAIsV7NaxWjfVSg5FMK94GvSvAmOjMfs+Ab0SLrjPDiHYEloVT/qhZ5qNCbz9xMOVGguHH0uVMS0YguBJN78VJifMHpymhOlIIArGDGYMU3K7RfF+s2zVSJfzJtmqNijBubpW85IhMIe8DCeS2/SShDex60HruRomPDf3pew3DMpYJgvBNOrCssz0uoW8L1UUlyb6RyOWRQ/mNIxfsk97K9Ujpyn0ZiH+ZzwCgHICj4xazqpptCoyDNucYig4culeF6U8yAYqRJyD3GaF9QvJ4Svt/1IRmfOikp+EmEHC6cT9xjJm9HSA6VS6Yut2P2cBz0uXU2RANblAr5eGs5FlBIEWj+L8G3M4XItHv4jBC1RUSLQ3l/6HNaGzwd0eAhxzLUJoNyc7QrO10fjwULUDgdEQFImEDRaikRMQYqdDkIajOAeRCocwJ0Gai2HkctdjkMZ6bKFfws8wpEwAtEnX/kM8aMRLBKJ7MBEBUu49V8igurgpNIzIzG51WZtf2zCRVjKacmJ3v6kdWOE4BMnBwGrVVqVISQYwslA/Ju304J1besWhHoXCq+ktH8LbIHF+VIGDFNErkhdKfe/vwBgwexcg5gC7rfy+gEOtYR1JOPACkh8fW61CVxYEJZu7dIr5UxMpKFar2PJsuV4+dXZnK/mDCNEIM+JQBUm8bWPAWPOH3p4fKFIgNpvosTCEUZvav/QPLOiCQo6wrmPWKyU2I+TgYL71sSLMwzWhZVuIWklU0UAUcrSZHo6sczDWFhZTRCJ00M0CxnKzZSWZObapJirY1PESnuL4GeJr1jsCwKgPActRscyMZBHlqbnOaj4jA6cjlTNQ1NFiJHCW4X4jzTScvCeaNuoaBsFlmLbcUa5hcCYa1TmfMRyWxBkMSLP2fKJvUHdFzW6DAKVgCStYtXIGFauGkOtPmQFT5xfHqmcKcxYFGLLYUTEoCZWBamrFQhR+Yh7jF55aCSh5tk4PtSUFYW7K9tgoT8gSVNUBwYxb8FCLF85CkkqyKJAc6MrO5WCob/c9pQSd0WEBYI89wgNN2LTauf3RRs2e3+esRhEAR7XIwIFXVqVBCophbemZqCVssppxOmZLECc8e/Ad4pQsbnhJhFAZLMBAxbhXjCc0VofLxbUS1rgrVYcpYKIBCoJt+247FTii7xseFXzIP00ERErKHH6Bm8qGhBYNEh5H6RqxWh9raiUOsAszBLXSIu0TFS1Li6w9QoLBhGKExmiAhEB0QxpXpQfnU4PS5ctR1qtIqQpx1NT1gElbsxwhHVOAahUKTU4D8dVct55550HALHX4qtMqIhbDfCKl9I+oNUGWlhmFTK0ZNB1oW8IE0OiRi6Lg1DA8X5ucoZNrnBPQY9K7Z1iQrEEjA0FEpdvoLVRi5BEoYRAwUflYuJMSgUcjTgdgU6Eqz3j9xuUiiHcRwz8jxQhIY6hBVyYUOW7+XC9PoDbbrsDJ514Ch597DEcc9QMs84j0rSK+tAwJAR0ej10M3ZHkBBQrw+gWq8DCqSVGkJagYQUiVQQkop1fTfFpdyQmIQEtdoAKpUqy7SjbRxWWkFJUkWaVlGp8Hc1rSFNUkhIUanVi3FDUqGxIII8zxAkoFYfQLVSQ1r8VBCSFElSQaVaQ7U+gDShp60KemLRwg6u8IQeGeHlRF1e7t8HC+UGiyL8L024MeR0RmHAHB1EgCRBkqRIU841JCl/0oTrrtZQrdUK79Afc0OvklZRrQ4gSVMklSqSpIIkrXDMpEIYVmsGxzoqlSqFcJ4jTStI0io0EDYhJAhpBUnFnqnWUasNIK2QyVWVaARxWK3WcdFPfoovfOFL2GjjTbD1VlsxT83EhBnKpThzD9FjLC5yGdIlnCSYB2K8SoVl9G1CBvYMHQfyAHmMljrz1eSTam0AuQp+cvEl+MQnPoUNN9wA06fviWqlgkq1jmp9AJVaDSFNeOKG0bRNEJVKHWlKGkzTqnnw7CoRjD5ZZp4iTSuWiykrH6vVOpK0itToOKlUEBLiqVqtI60OoVKrIeYZclM4XCK9aPKqG3lGZy5XlNLF5Q29nVAoMsLTBDOHsc8C1OQYb+W7atU6KpUaKmkNaZW0mFaqCCFBWiEtJtU60mrKbUcGq6iKkKSo1gcQQkoaSipIKqRBGo0uA2mUuWNCmicdpsbT1UoVSUissxHnm6YVziWpFjySphXSogoqlQpCavRfsfenvDetGPxN1lQqxFtSqeCqP/0ZJ5/6cUAEu++xB5JQbgWAwCIhpQNR8DPc4TIa90YblcEyzNhpLuPDJoBdQ3t4ToyZYlGIQSvbQzeuHRkTNQtGhUrGXV7T+CGQIcR686nmSMSqeIr7SBhJEpBrRoZRLoRSxYRfUQBiCsbza9ETMrE4s8cBY4akCQgKOr+c9gqypCQsfpOJy2cojC3cYRzvbriGaKe40qr1qksqFgrgam0Af776GnzmM59HWknx619dgqOOPBJZr4dKWkUvz/GfO+7AnXfdg5deehErV61CtVrBpMmTsdkmm2G/d+2D9x1wAGbeOhN33nk3enkPiLRSB4cGcPbZn8bGG2yAbrdL5SXAVX/6C15+6VUcdvgh2O9d+6LbaSMNActXjODnl/4Sy5evRK1WQwgMA77vgAMwbdo0XHbZH5FlGTuDCNsO7bXXHjj1wx/EgnkLcNkfrsRoowmAJ4pnWYYsyyBBMW5oGOuuMw077bwzdt9tNwwM1NBpNw3gfYLXLGGYtcevI0ICboUA80lqtAUFc4XiRpbl3Hy8Au+kM1UgrVRx4fd/hNlz3sDw8DBCCOj2esjzHvI8R61WxaRJk7Hl5ptjt913x3bbbo1ep4Ws14NIRLU6gGeefR5XXf1XwyvDcfQy6GclEEjKdmFJmmLttdfGiScci6lrrY3rr78et8y8jUUR5tkFESRpglq1hgnjx2ODDTbAVttsjZ133hHjhobQaozRawBQqdXx8iuzcfonPoHHH3sSP/zB9/GZsz6NmHcRY87ONkav4uEhpbKRaJaUeJcKUnuuSt4yNk68LZgZcNFKyiUyLC9CeaA55UMIoei4Ua3UMDLWxte//g385re/x26774y/XP1XTFlrMv509VVYsXwlvF5nzz2n493774dupwOAuZm0OoC77rwHN918a2HEigAf+MCBOOB978Pdd92Fv//92qJgxHlqjz12w4c/fDLarRZ++tNLsGjxUqQVeiwxz5BnLN8fHBrAuuusg2222Qa7774bxo0bRqfZtDAkAeDSjCIlL+QPQ9wudEMRYdE8QBLnbwtdu2BWet7oV3cGK0XA5VdchVdmz0GaJFDleXd55OnrIQkYGhrEOmtPw/bbb4e99toLaSVFr9tFmqZYvnwFLr745xgZHaVcMe9lypQ1cdanz8Caa0ws9rtCqXyrA3Xc/8CD+OPlV6JeqxGOmiOkKT7+8VOxw/bbo9dpoVKt4eZbZuKmm2dS2diRUaqK448/Bvvtux8u+8Mf8fTTzyBNUyAEaJ6bl2n1FCEgTVMkISBNUrxr/31w0PsPxEsvvoSPnvYJPProk/jEaR/Bj374PQwNDiDLOoCddMK2cYKggTlHiwrkpnfUvLkkBNSGJgNqV2t0kbbHlmi7uVjbzSXaGluirdHF2m4s5c/oYn4/xu/aY4u1NbpIm/55Y7E2xxZqa3SRthqLtDW2WFtjS7Xjz48t0cbIIr6nsURbjSXaGuV4zdFFxX3N0cXaHF2srcYSbY4t0tboEhtrsXYafHenuUw7jaXaaizWps2hMbaQY44tKd7H8RZpa2wJx7Tf7bFF2mkt1U5zGT8bW6TNscXabizTbnMZ39MgPDqNpXxnY6l2Gry/NcY1tpt8R2vM5jGySMdWLSxg0hpdqI2RRXaP38s5NEcXqcYxvfXWf+saEyfqQL2q1193jWpvVBs2xvLF8/XDJ5+k1UqqAHTixGHddNMNdXi47lynk9acoC+88KxeeMF5xWf+s/tuO+nLLz6jMWtoa2ypxnxMX331Od1s0w0VgJ78oRO00x7TdnOl9tortTG6XD/5yY//n3Eu++2v9fFHH9QNN1hvtc/HDQ/q97//Hc3aIzr/rdl68sknrvZ9rVrRwcEBNTtUAeiaa07Qo446Qp977inVvKXt5nJtjRl8xojrdoM00RpbpK1Ro7OxhdoeW1Tgm3S6WJujC7U58rY2Rhdoa+xtbY0uJN2MLdb22FLS8BjprjnytjZH3ta8s0K/+51vqtlk/BHo5MkTdc01x2mlrI7WTTfZSH/8o+9ps7FCO83l2hxdqL3OSn32iYd13332WG291UrQgXpF65VEq+bA+Hciotf+4y+q2tV//+ta3WXnHVd7dqBe0zUmDmutSlwD0EmT19AD3re/3nLLDapZW5tjy7SxapE2RhZr1hvTV195XrfcYlOt1Wr6xz/8TjVvaWNkkTZHCYdOY7F2Gou1NbZQmyMLtN14WzvNxdpuLDa4EqbtsUXabvC55tjb2hh9m/TdWKzNEX7faXKcdnORdppLtd1YrO3mIm01iLfO2DJtjS3TTnuFZllTv/bVLygA3WP36fraay+rxp6uGlmmX/3aF1db97bbbamvzXlJu52V5J2RRRqzhl537d906lqTV4Pfz3/+E+20G/r0U4/q/u/ad7VxhocG9Ze/uFiz7qg2Gyv04x87dbXvA6DDQwM6VK8Wn00YP6QHH3yg3nPPHap5WzuNZaWM65N9rcYibY4uJMzGKLdaowu12VjIz8cWabu5zOiWvN0eI7wao4Rnc2yh0TZlXGt0sXbGlmivtUJ/95tLdfLkNVebLwANdiCG/z1x4nj94AeP1wXz39A8a2mvPaLLlszXY44+4v88e8QRh+jSRW9RZplsb40s1vboEs2zht511+263nrTVntmzz2n6+OP36dZd5V2Gks0743obbfdqLtN32W1+/beew+9957/aMybev753/o/765Wgnovgf/9efd79tNlS+Zr3h3VV195TnfcYTsVEf3cZ8/UXnuV8fxCkwUl3JtGq+TnJdox3h4beVtbY4tV6RXx6pgC6DT9h4qo21peCOHWqCkUExAuWFqjFOytMVNKphCbo0QuFUEpyKnAFmtndLm2Rpdq05RaoVxGTaE2OJ4rOldmVIKLtdVwwbdYmw0qLf9xoiRzr05ErbFFXKOva8wU8dhSjt3oW4srIptfu7FUO80l2hxbqI3RRaXCNviMrVqojREyJZFgDPA/P73OKl288C3ddpstFYBe9OPvq8amNla+rY1VC7XTXKFnfPJ0BaDjJ4zXX//q5/r2gtd02ZJ5+vqcl/Sznz1LkyTo2lOn6AuzntFer6M/+uGFGthwUt/znv202VilvfaIdlsrtdNcrqo9/dtf/6S1aqIi0J123E4XLHhTs25T240V2mms1F63qZdccpGCASO98vLfa3tspTZHl+trc17WnXaiEBYR/e9/btVOc5mOLJ+no6sWaaczoge+/z0k6FpN77zjP7pk0Xx98YVn9Prrr9X3H8jvAOhu03fRBfPnatYdLRWZw8vooW0GDBXbQiPyxTSKxpboquXztTGySMdWvq1jq+ZT2I4Rv83Rhdo2QdsyhdcapTJrjizUmDf1t7/5pSYJe/F85KMf1pUrFumSRfN0zuwX9KIff0+nrjVJAWgIopdc/GONsUUja3SR5p0xnT9vrk6bNlUB6HrrTdNZzz+tb819Ree88qzOfvkZfe3VF/TKKy/TNddYQ0VEf/2rn2ueNbTdWKbz3pqj66zDZ9eaMkUfevB+Xbl8sb7x+qt6331369lnn6VrrrmGAtAJ4wf1Bxeer71uQ9tjy7U1ukSbI4tVtau3zbxRq9WKTlpzoj7z9GPa64xoY5Sw6jTIR1RKC7Q18rZ2+pRUc+RtExILtTXK71xh0SBdRBofXcTnxhb2GapLtGljdZrLtDO2TNsN0ti//nWthgS61pQ19OknH1XVnrYbK7XbHtMsa+snTqfBlCSk1dNP+6j2umPaGjMjdGypdtsj+sQTD+kGG6ynIqKXXvpTHRtdpsuXz9fG6DKd+/oruv122yoAnThxgv77X//QXnuljq1YoM3RpdrtNvSsT3+yoNVf/+oXunTpIp3/5hx94pGH9BOnf0wrZiSut/40ffaZxzTvjZWKzAxYKjQa006f5PfFhMUoDdhli+fp2Mgik3muDF1OmIEwZkqlX2GOLVbNm3rlFX8oeONTn/qkzpnzsj7//FM6a9bTevvtN+uMIw4pvv/IqSdrpzWqvdaIdhvLtdse1c9+5tPF92eccbq2myu1PbZMmyPmYNi7WqOLtTm2WHvdUX3s0Qd08qSJCkDHTxjSWS88pTEbK9ffXKaaNfXt+W/o+utT8b3vwAO00xnTVmuljo0t1aw3pt/+1jeKd5915qd00cK39OWXn9YXXnhSZz3/pD7xxCN65JFUuLvvPl3nvfGqtsaWaq+9Sh9+8G4dP36ciohedeVlqvmYzdkMsVGb/5g5Qf3KzOR2c3ShqnrLDFgBgYcXwXiCWsWeBeeK+DFdaSvUsJ3gzGrbcJGdLkLfrnEPQ7Igg6GBCJZiJ94sti+/xWMB+FwZy7ewkVU3BWFxAICic4I/79ANVjrNAKkVO4AlXx6eQIzcx+L7pcAQTBFS/J9QJJP6VioqDB2Ydw/2E7WxzS2G7V0KlqcLCEirA/jd7/+AWS+8jH323hMfPuWDaDfGEDVHtV7BY48/jr9f+w8AwMc+eipOO+2jmDA8iFoqmLb2JHz3/HOxzjpTMW7CMIaGB5AmOU7+0ImYtvZaAIDXXnsdo6MjCAnPD9IQkGUd3HXX3eh0c4QgePnV2Zj/1nyGDiCIeY60UsHoyBgAYIstNsVhhx2CLO9CNWLC+HEYGBgAANTrVUyatKblcRSqGRIoJowbD1hAZWhwEJMnT8ZmG2+EGTOOwDXX/A17770HAODpZ57DDf++CUmlDpgZR1yBbhIcP2Wu1jL0qNVquPbaf+LkUz6Ov/zlb6jV6xbrVxRJesBi/9yrRvozJEEhmmHjjTZAvV7jemp1jB8ehzXGD2OjDdbDF7/0NZx33rkYHKwhRsXvf/97rFy5ijkuCcjyHsYND2Pc8DAAoFJNMWXyGpi61ppYZ9pUrLfeNKy7zlQcf9wx2GOP6VBV9LpdqwwFhgYGMTBQBwCkaYI111wTEyZMwLrT1sa+++6Nn/3sUlz3j2uw8UYbYNVIE9/6zndxzTXXoDY4ZCH2iNbYKuy3zz446qjDsWz5Svzoop8ij4o0VIuQO4sDuJ+S+S7SawgBElIL9QvUGhnD+IzVoqGoBlVlyCgIk+eqCuRWtWnFMWlSwejIKH7yk58g5sCZZ56JHXfeCa3mGPk95kiSBNOmTeN7cuY+//Snq/DPf16P+uA44/EcIhnWmLgGhoaGUKtWseVmm4FHJuaIWQdDg3WsueYaAICh4SGsvfYU2zemiDFDpRKwzrp8DwBMmjQRkyZNxtSpa2GX3XbFL3/1axx/3NEQAea99Tb+9KerENIK3y+s1qX8U8oKK66A5fWNUJFWa/j3DTfjpA+diiv/9GfLs1pKIgJBE3aEgVc/Mo/lskuVWxt8LQCw1pTJ2GSTzbHZJptgs403xoHvex9++5vfYvquOwMAbrzxJjz19NNIUtJhpZJiUt/z66y9Nmr1ujXB9mIw8hKFakTMuth0k40wbhzpN01TDA0OWkhSocq9wlnWw4QJ4zFsdL722mujWq0DUZGoIgkJNt1ss+Ld4yaMw1pTp2DddaZio/WnYZMN18MuO2+P00/7CCppipFVq9DutBEC0G41sNuuu+LTn/okVBU/vfhnmP/2IqTVGmWqVe+yotpoOEmg4D7kAHbbcbYu5AQ7A1ggO5IJ1EqJidBoFTBENGA5CimrgggEz7cZV/QpAh+faThrfir8IVItX2LJZenrlO7HQvA8JWc6MhJbtfgxEj4HS3wW41kRiTDGr9aRX6OVbgR2KOezxtCuGH0Pnm3EDVb5FAKAaEUFsE2ILoCtWowVlv3zAtJqFW+99Rau/cc/ICI46aTjMWXKZOQxgwgLEB577HEsX74CALD22lMhAmTWsqjX66BaSfCxj52KGUcehvHjh9BtNbH21KnYe6+9AABLly7DY48/jpDWSHiSYNnS5bj9v/9FrVZDmqZoNdt44qknqIGtcqnTamHmzJkAgBlHHYWhoWE7/sXbJblCAPOhlu/xbu2+IRQK5L0e8qyLbq+N1ugqTJw4AUcffTQAoNfr4dlnngE0R2LVThy5rzpNaSwwYcYWXLA9Jw89/BhuvHkm7rv/IaRpamXmpA0vM4Yp2sKgKQw10iuPbnEW4IbkXp6h2+0gZg0cesihmDqVxsGc117H/Lfm8YgWJbMDPL0BZnzFrIcs66HX66DX6SDLeqhVKvjylz6PGUceil122dlyajx9oGKGnggsX5ehl/XQbTXQba3Cu99zIH74w+8hTQXdbg8XXPB9zJ+/AGm1wnfGHPV6Bccfdyzq9TpuueVWPPb446jWauxlKISq2J6uaEKKVphfFBiq9j1gRqnlh1W4/cPSa9qXM/acFas0BUltALfffhseefgxrL/+ujjqqKOgubcGKy9jK+y+x3SklSo63QwXfPd7mDPnNVSqNeRRETPyb5qmnCVLR62gwXjaBsp7OXrdrpXFKwua4urv7fV6ALrI8x667SbSNMERRxxelNI/99zzyPMeZYTS4HAZosrcFwvh7G+zjZJKBU88/Qxu/88dePjhx5BUuA2BFoNaZx/m/ETBSl/bIgOTLf1rgW1J0NhFr9tGr9NGc2QVJk+ahN133Q0AsHzFKrz15ptQ3xCvmRnrvJSNU42PKOR9LbxBLd9c0m9AUTprRQVUInwH5S5AmefFbkIyKb7zS/OIvBeRZzl6WQftxhje85798aMfX4gTTjwG48YNI88ynr2W93DcMUdh/fXWxbPPvYDr/vEvVKo08gCwQrI4J9PlTUKaFcoDy0KWygy2YG86qdGOAYhUIg4MJ1y1zaUAE30waw9G6CiEhlUoGhGI7aERA4ILBjGLUYuiE2MeE3HF/g21VjpWGupzc6bsnwccN0LtXRRmOBGVeKPSts+jHbDYX/YZTaH5D8DxqOSp5FRpQQgELEgxxQjf38NxQqWGRx55FLNmvYB11l0LB7zvvciyXiF0/7eC78YbbsKyZStRrdWdjNDr9vCNr38FF174HVSTBFnWhQjwgfe/DwDQarXwyCOPAKBSTStVPPnU03j9tTdxyCEHYZtttgEA3H//faaUFNVaDS+99DJefvkVDAzUccB73s3jJgojpYSHgAzu8Cg+t9+qim6ny+KILEfM+TM0OFisK1o3i2gNSQuDwS1/gMxk74Lta1EIavUqAGBgcIC82bchlYULtr1DWZzDi54yk+RlBwQAVojhnj1pu1arF8IUhALynKXhpD1vvOrPl/NmFWeKJUuXYe+99sL1112L3XbdBZ1O2+i0L2qB1WGoZlz22qtw2KGHYvquuwIAZs+egxtvuAlppWrbAiK6nTb22G03bLzxhlixfCVuuXWmFVfZHiCY7DI+8n8Rl32HOhaGXh/t9Rl1hLEAfa3h+L1bz4Ks28att85Et5djt912xRabb4ZetwOaif08x7+POPIIHHn4YQCA52a9iAsu+F4hX/gKRl9IA2DVZ19lsTO8qiLLelYl6zC0CIxdme12VzXPCorh4XEF/6epVUJLGT1y+HkRClB6AapW3CGs+AOAwcFBQG3LCsotK45bOgakL85TeW+JGsC6v0QrwY9G/91uF6PNJmBzHTc81KfMOA+/inn3K98++ct1+PaLUmaTHsu/xbdp2PYYG90MCs4dCEiSkkeKzk+2ukq1ikarjWa7hc+c9Wmce87XMDw0QB4NQLfXwbbbboXdpu+KPM8xc+ZtGF01amOagu27VJWwNQcByh7B6FdmXGQZluO/S4C49xQCy3m5cLVNnrCpuyIxq7g/TOeM616TkQfnG4sQR+BLSVQJNa/Y516OnRdVVqUC0769aAVBm3DkO2k9i1gDZAXSwCNcksSJ1cgrCJ0VX5Uh2uFS/AYbkPYTOOmGc3CkBmEnhmgd7TVGPProo8iyiI022ggbb7ABet0OYLDOshzTp++ONddg6OCBBx/GmWd+BgveXoxx4yeiktYRQkCv00Gv06bFKgk05th55x0xYfw4xAg8+/SzaDVHzYJOcOcddwAADj7oA9h7H3pwTz31NBqjq9gjspLigQfux7LlK7DzDjtgx+22g8YcifWPLGgBoBWg/BX6BKcregV7CJJn2VRZFZg16wU+LoItttwCSAJbNAmMQfi8mFdNw8vopa/VmiuCJFi7LXibnH6jqiyD5rwZGWA1ZMHxnK/yQEDuFROk1Rpee/11LF+2CgCw4UYbYp111kGW9QpaI9ydAIFqtYbBwXEYGh6P+sAwzjv/e/jM2Z/HkmXLkWc9O6wyWkRidWVK5nblRtqJeYZqtYb99tsPMIH8+JNPIMtYERysnHmtqVOx2aabAAAefvhRNBtNwsAiJvZGo0szwkCRy9AsQ2KJVMo9a0WZtNG97dnj8+Z9F5uGFWmaYOmyZZj1AvG7w3bboTYwWPCgmGcDAEnFhF9QfPnLX8LUqVMAANdccy1uuOFm1OsDq/OS8Rbge6WsetXGI94Ml+Y5ABZNsYubcwEadwFAihdeehF2MAa22nprhJDQ6IreiYZGM1wOKBgqtB8XEE53FCHEndhevUI22Kb9EMxFs0pcPlcqSYD4SdIaBuqDqA8MYWj8BDz5zDP47x3/BQDstOMO2HbbbdDr9Yp4Rn87qGLOpuxKnu0zEgJDzv2XG+ACKsQCu6404U69OTMkHR7fY1cIASGpY2BgAOMmroEHHngER8w4Htf87e8QBbrtDuVmwvPdVBTVWhW77U6D7Yknn8T8BQuscxK1hMM3RjdsDfAKi7bYu30Svmeif+ECCl7mHfi5f+/hGrUNpWJlN1meWzSIOSJDW0FY/g4VFPteYAjot/LJeGygSwImYPl+U4huLfwPUpxpVluPjRNV2RDWNpEyfwZfkREcARlAhbgaQdg4ECvQtbH8niA2HymbABP0ZsFC0Gm38eQTTwIAttxyC9TqdZbtA4Aout0O9tpzd3z6058o3vmP6/6F97znA/jhjy7G/LcXojowgLSSQHOHVY5e1sUGG66PnXfeEQDwwosvY+7cN5BWqmg1xnDXXXdj3HAdO+y4A3bfY3cAwIL58/H888+jUquh02zg/vsfgKpiv333wlrrrIU89uDKPE15HIpfwRSJ2UrEtSsJALWBOioD4zA8fhzq9SHMvO12XPmnqwAAW225BY4+5ij02k0KO3WP1ODgRog1gwYi93V63NZwH7wjLmwTs+dYi5ZDCRBsMydQbGT9X9pI0wpqtUEMDI/H4LiJWLZkGS666CIsW74caSXFZz97NiZMGELMsz6PzLgZQLvbw8OPPoF77n8Id9/3EL73gx/hop9cjOeeewadDg0VD9mQVspTx5F7L1OOKQqIWjsfATbeZONinosXLUa70+k7XVpRqabYeputAADPP/8cli1bbsLNhLr9OGqUkspCiwEeYKFHy3nyDDR6b337Z/8PHyjAnExIsGjhQsx+9VVUK6nlUeydbtyZQnL+HBtpYLfd98CZnz4DANBqt/G1b5yDuW/MQ6VaLQwMolecrYyfHPLk0RgNr4oiJ95/Vat1INRQGxyH6sA4PPvs0/jDZZdDFVhn3bVw6kdORS/rAiY3SioGcmtOrIgmRzkDEU6EpxA4bHKG5P0YJGv352smKZPWXXmUK+I1+/XX8eBD9+G+Bx7EHXfehYsv/jlOOulDePvthdhkk43w3fPPw7RpU5Fn3YLv+uwiuwivAPAdduZYIvybIowOAS+jCSjXSbFW4tDvUuH2F8vBok+2A8C8eQvw+GMP4c6778c/r7sB3zjnPDz44MOY99Y8hDR169f2k5oXG4FtttkGaZpiyZJleH3uXCRpyuiYK33HicLytKQF6nBOsE+ZETkFgcZIl9/dTYp2+KPBNvWSSG0vi23ORD/BWeGDEzNVhjGUCXdYD0PAdpVzQlAHVEGX3O/C87qsKwQ1Cfc2FHOgB0mhwfWIdwOJ1vXb5l80JrX7AcoAkaSw8IN5CQCK+QvYuoYMz/d5n0Gx70srxhjMlHGzMYa5c+cCANZddz2XEoSHCICILOvinHO+hvO+/c0iSfvGG2/i6984F4ccNgMXfu9HGB1toVofQIzslJHnOdZYcw3suusuAIC5b7yJWbNmAaGGZ555GrNfnY1tt9kWW265JbbeahsMDAxgZLSBhx55FJABzJ8/H48//hgG6lW878ADuPbALhBJErhnyqyw4L0Giy7ryWrhwTzPccWVV+E3v/klfnbpL/H5L34ZH/3Y6RgdHcO222yFX1x6CdZdZ210ux2DWcnsDH/x7zStoD4wjFptkBtt60OA1G1DOMN5kEEMDI3D4NA4DAwNY2BwHCqVeqnwLLcTbGM8BBZyogAEgDlzXsO///lP/OPvf8cvL70UJ33wZFz3zxsgIvja176Ck086AVmnY7RFq9LxCctRzphxNN77vvfjgAMOxrnf+i6yXFGv13mahNGlmGHgP6DoQ5ZnZrCzAbPnqhUR48aNg1+dTpebjM06Bgi09dddDwCwfNkKLFq8pICPWggcSsUE22dXHxrCwNAwBofGYXB4PAaGxmNgaBxqg0MYGB7G4NAwBgyetcFh1AeHUK3WyIM2N1+7gHvqlixZgmXLV2JgoI61pk4FIoWi875JIp42AKDb7UKzDj51xhnYd19GCua8Nhc/+tFFyCPzZR6NYfKZy3XpYq+nzFIFIAiRhkD5Tr7/jjvuwB8u+x1++fOf4dyvfxUnnXgiXnrpFWy11Rb47e9+g2223hJZp2PixOhCyMmJ5eOTtIL64BDqg8OoDQyjNjgOCNzwDKNVyCAGBo0O60OoW4MC6lpTyH1RHobASw9fRHDNX/+OffbeHwe87yAcfOiR+MIXv4I335qHyZMn4Uc//D4+cPAh6LZaSG0cCWVukZdJeY+eqLBYRym/xDwiwoZPlPh0Q6eEH4NlriroGblhRuzbW0Xw5z//Fbvtvg8OOvgIHHPsSXj0MRrtgwMD1CVmEIhy3xrD4TnWmjK5WMOCBQuBhN35YYYfTI9wPta9pm+O6FdmrhjEhLyY1R0SHoltOoPKxRiDmt0BYMk5krZ1vl/d0+IkaE2HIg5tjysrCUPSp/hM/YrNi4tSZB4bcKvNLr6vzL2IW+egcg42X4YQDKnurfUxp6odydB3DA3AcIKY4HUQilARxdxDZQVqCQePIbulGARjjTEsX74cADBh/ATC0zGgtNbyvAtBxDfP+Rr++5+ZOPGk4zB+PCsFX375VZz37Qtw7PEfwmuvv4V6fZBEaQUYe+6xG+r1Onq9Hh588GGoZrj3vvuxarSBnXfaCRMnTsbaa0/B5ptvijxXPP74U1DN8fzzL2DO629ik002xF5774O8l7GSy0M9feG9EMq2YyFYLlKA3JgkxojLLvsDzjzzLHz+C1/Gpb/8NZYsWYpPfOI0/Pe//8G7938Xup12n4wy5hKGExEZhpu/YCHuvOs+3HPvg7j7rntxz9334oH778Frc14HAMyd+ybuuOM/uPHmW3HDzbfixptn4u/XXo+nnp2FNK1x7tGOJLEN/EQUlYYXQ9x99z047eOn45QPn4qzzv4C/nPHXdh4441w043X45xvfBWVNCk3z9qpyiIwhgaGhgbxpS9/Cd//wYW4+JKLcPKHPsjvy6UVZhCMbvzcqGgnRcA8IUod4xvNrVclr5IevaqXfLCGhaRjBFauGinwJBZhIa+RQ5946llc8/frcP2/bsS//n0jbrzxJtx886245daZuHXmbZh52x24deZ/cMvM2zBz5h247fb/4vbb/ovnn39htdyMmFFDGApWrloFVSAkCYaGhoyvGdmBG6p+6C+AXq8DaMTw4AB+cMEFWNuKba686s+45ZaZqFRrhRHYnzwRoRwpeQ0FR0YpDeb+6+qr/4LPf/5z+PwXvoALfvBjvPDiyzjxhONx15134OAPHISs03Fzs3xIletVIE2qWLp0OW644WbcdONtuPHGmfj3DTfj1ltvwsuvvAKIYPac13Djjf/Gtdf9G9deez3+/o/r8de/XYcnnnqmyCup59DsFeQtylz/fueddsJnP/sZfPqMT+DjHz0V++67N+r1OlauXIXzz78At95wA+qDgxBJkIQUCMzP+kXcM38PiyCx3ZVHUSib+H7DZx8sqR/MwAYgIUGa+n3aR9BqeDEOVsUee+yOn1z0Y/z0Jz/C979/ITbeeCMblcwgQuMexSsZ0h4cGipodsVKFr6J5b1FKXc96uO6h3KnnHdBmf9bih48pu+KqE/QS7kcasbAmTEU6Z6IL7Qc0xEprgRtEFcyGoEAekREMa0EgWnSPoKm9Y6yCCSwGjMqEK1Mn2tnzg0mYIvQiwPErGaYd6XwVEN/vo3zIIINCWa8UfErT7NQtXCEebeBypakxYFFBN2sZ9VVTOZSIBqi7P0SgDzroNttYvpuO+Ivf74Sd915Oz51xumF4LrnnvvxxS9+BWNNy5EAyLpd7LrrdKy99lQAwJ133Y0lixfhiSeegohgv/33AzTD5DUnYfvtWATyysuvYMGCefjPHXchRsXBBx+CoXETLWQcLFRnxNOXH6ByExOwdp8RXJqm+OpXvoiLL/4pPvmJj2P8eHoXd999D958802O4ZhJtDjwk33lGIKu1ev4w2V/wAEHHIR3v/f9eM8BB+Hd7zkQ+73rPfjnP/+FSqWCG2+8Be973/txxOFH48gjjsERRxyDE048GRdf/HM2epbUaJhje6UeTMl5McN73vteXHzpJfj617+GjTfaEACwZPFiPPnkkwjK8ulivk6HVq4OABMnTsCXvvhFfOVLX8PnPvtFnHTS8Ua7EZU0LWiCXkMZ8YAzofGCgvTE5sZ8T2OMreYAYNy4cahVa67vCjr3LRMA0On1bGyjKVW+RQJCSPHjH/0UJ570YRx9zIk46ujjccSRx+Kww4/CoYfOwCEHH4mDDz4ShxxyNA495GgcfMgROOigw/GBg4/AD374Y1TrNYtKlPLAhV7HunjAhFaMuRmKETFnztALygAgyzPkMUer3cTue07Hl770eSRJQKfTwbe+dR4WLVqKtMJyecoVi+aIRQzMGCDdGE0GMhzz7ZwOAJx6yqm47LI/4oc/vgjrrbcOAOCRRx7Biy++aIVoDicbzGWSEu9pbQjXXPsPHHnU8Th8xjE4YsaxmDHjOBxyyOH469/+hrSSYuatt+GII2bg+BM+hONPPBknnHgKPnjyR/HTi3+GSrVayj0LrVGueF/Gcq6HHHIQLrnkEvzskp/i17/5Be6687+48orLMHnSJDz73Cx8+uzP4flZLyKpD7CaHIERCr9MyTBIR5ixAp1RBXpDVBZFqFuo6ARC2e+wszk6MJPA97hRxz9KUO+77774whe/hM9/9ix89atfwS477wQARRcS1TKnzTma0xDYOBvmsTNywnkxRN5notC1M/yUudFCmdmyi6aWTjwKd+NNCdlE+uOq/pLgZZtWESTecsrGAIz5ioasNgnXsB4GAj0YT1Aq8mJ+9ASEM7DnRRRqp9Im4sceOlGatWt/Ahw3Fkn8UqjEvvZcDtlo+QMk/HdJkOWlka48hb2BVIFQNDple2A1X7+SJEUFVK+XrVYcw4KXAEGCSqUGUUWnMYZ2Yww77bg9fvXrX+G3v/0l1lmHe2j+e8ddeOqZZ5FUUkSN6Ha7WH/99bH11syhvPrqq3hh1ouYPXsOhoYGMH36buh2mhgYGMB2220HAJj7xhuY+/obeOihhyEADj74YHbLRllw4Z5lafE7MdPiCynPdCqIPgk45pijcPbZZ+NXv/wFPvuZswAAr7zyKj73uS9g5cpV7Pko3kvQaDBS0CtYGbXdttvg8MMOxkknHY+TP3QiTj7lJJxyysnYYYftkec5ttxyC3zwQyfhpJNOwAknHocTTjwOH/jAgdhhh+0LJeECv2QIUm1m0QMA2GijDfChk07Et779bVx+xWUYP2EYY40mzvvOBfjn9f/CwNAwYGFuL4qwgAUvUXTaTeTdFnqdEey84/a48srf4cILL8CE8eOKHnVqxh6sVZs9TP6yv6I1HPaGzQsWvO1vwbR1pqJWqxk/9ueiC1ZGJST2eV/o3Fctinftvw+OOvoIHH/8MTj22Bk45tgZOO74o3HssTNw3HFH4bjjj8bxxx+LE088HieddAI+eNLxOProI7HX3ntBvZp5NVkBQAKqFZZU53lEnvXoXdqZdEwfkAd8ThpRRF067TZOP/3jeO8B7wEAPD9rFn7zm1+jVqsyYmO5Uv6PObpCKIogBJ44kQTP5dB75teCvfbeA8efcCI+//kv4kc/+iGqtRSvz30DX/zyl/HGm2+hVh+AFynBeFFVrc4XQMyw/vrr4/gTjsGHTj4RH/rQCTjppBNx8iknY9ddpyPPMmy++eY45pijceSRh2HGkYfjyCMPw8EHHYh99t7LQsMlDYoV1xXc3idTYsyg3TYaYyNojY6i1RjF8ccdizPO+CQA4I0338QtM29HktbMuy+NSL7DjX7uoXWFFEKCRqONsWabPNsX6mbluuGl+K/xh9BghRdu8CVm05VjAKATgAyt5hh6nVGcdeYn8bOLL8Jhhx6CmPVQq9UNttaeyg73da8dAGqVqslfOjyhLzTPV/NzVW69cQO7mIW77VxQ6RKWIC5L5tUIhPshfGOm/Q1u8WCS0JSEaTQxZILLsDCfjW4GXlFRlqspmj7gihGDaWR+w/kSX1RMZDAKVjHvQZUUJNbElo9bLz3rORZtroXVCRRhKfeeive61+ZTM0Ucc1uoewJFl23LsUWWp0+YwJDhylWrDN6cL8dnRePKkRFIsBJVcJNhpzmK4447Hid98HjAciizZ79OOBWeL3Dwwe8HAHQ7Xfzlb3/DG2+8gZ133hkbbbgBsm4HyDNM33VXDA8PYdmy5bj55lvx6quzsc02W2KbbbZGzLhRmrAyiy14JRhhV5Zoi539VEEwy00VaIyMIWs30Gk1cPbZZ2KvPblh+uGHH8Gvfv0bVGs1rteBaDRAOhZ0Oh0cedQR+Ps1V+OKP/4ef/zD7/HHy36Hyy+/HEcddSRijPjABw7ElVdciSsvvwxXXfEHXPHHy/Cv6/6Oz551Josq/tfrNcaG7zPkCtBpd9BuNdAcXYH9990b3/rmOQiBW1G+94MfY+7cN5kbEUYrYDzgCXSBhalVkfcyrLXWFJzy4Y/g4IMPhqrg2mv+gVmzXkZarZkXaz/FnGwiVsFFuk3R7fZw/wMPAABqtSr23nMPVkQq5y4iQBA0WizbhgATJoyzdTswQe8oRvSyDk7/+Efx56uvwJVXXoar//RHXH31lbjqyitw9dV/wp+uuhJXXXUl/nTlH3Hl5YTn5Zf/EX/9y9U4/bSPodPplArM4KBQIOaF953lGRpjYw5x82opwLygCuCRKVwnoxP1WgXfu/A7mDSZkYcrrrgCTz31FGr1GtIKLfcQeKJxglDkBUUAJNwEnljzZkiCNC0r/NqdJoAuWo0VOPaYY/CRU08BADz15DO46KKLTDaUBU6+RDJWRLfdwOGHHoKrrrwCl/+BtHjl5Zfhissvx/HHHguNioMPPhh/+9tf8be/XoW//vUqXPPXP+G6a/+C00//mFXBct3BiuNguC/kiF8iiAEQsZ6kyKExx7v22wfjhoehCrz88issGrOQYv+l0RSNRcryGJGmFcyf/zbe/d7342c/uxTVWh1JkqBmHn23m6PRbBYpl2gHLNOwytHrURnX6wN9cgqAORX+F8OREUBE1u1g3332xGfOOgM77bwznnzqadxw4y3o9jI7sRqgjA5oNpt2EgIwYeIEQC0tbXIBzifFR6UOcGegUGYiDOuJ0LtwReYMiuJYAQ4iCKhVB1CpMsFZSSsYqA+iVquiWqshrVbZUTwhgQVhs191IaKKYFUxEQEIDIEM1JnMHxiegPrAIKq1KmrVGipJpSg2UCt4YGd2Wrz1eh2Vag1Jhd3cEVkJGSRAwSoahXWs93wPjKgsT+jVNWKegYCVSoIAzZRHGwjzb3APtAhHONB5ZAp886MrZw12zLhicGgI663HhP3b89/mOwFIZGipNjCA/9x5J44+5iTcetvtqA0OF4jLrUBmi823KIUKUMTEgYher43999sPAwM1ZHmOv/zlb1i2fAXef+ABqFRSCLgvZ7ttt8HUtaYgRsVvf/d7jIyOYb93vQuTJ0+yfTsZcmQU2L7x07wJCnI3HsrYtVtP3gUhCQF53sOaa07E5z93VmGc/OKXv8FTTz+Daq1GL0KpGCSUIWCAx9QgZtC8B+QZkGcsQrGj1UNQpKlA8y40diCxxy4LmiPPu8hjr+/kcpO/HJpCxBUy2GQ7BEW328YpJ38Q06ezXPi552bhT1f9md3D/QjGYMLU1y0JcturBgno9TJ0mmOAVHH9v2/E8SedijvuuhNpbbDw7IoSeWGIg/47PTJAMDA4jIceeQz33/8gYBWgBxzwXnTaTXvGcSBYvHgRAGD8+GGsNWUKG76SW5js96OdFBDNgawLZF1o7EGzHjTvAnkPyLvQvIM844b33O5DZBm4BAaGOLbRgSrymGHNSWtgaGgQnU4Xi5cshYRAXFrlpUcu3HOImrNZgUVyet0Odt5pR3ztK19GCAGdTheNRhOJ+S/sYuI571AWIyWkQ4QEijKULCEUVX4SjPBijjQRfPL007HWlEkAgCuvvBr33XcfKlWebCBuwIkgKAsWokbkeQ+IXcReF8hzxNhDkoAVv+ROpCkN1qAZRHOEYHQF7p8MZsCz+IHFGxLKVAjHUVbpBg8NJ5AkRafbdT8RSUpl4B5OEdECPWa/XM2klSpuu/2/ePa5WWi1W8h6GdI0wbrT1gUAdHpdvPHWmwiJHctTVJIGLF++AouXLAUA66rC71l9S+UpRhC+58un0+120el00Gx3cNZnPo+vfO0bWLZ8FQ1DU0ohYcNkD0UyRWK8KZTZ6JM5CtYWlBf/XSgzLoDAUTuUL9pBg1II62jdi4FVY2N4+tlZeOrZ5/D0c7P48+wsPPvsLMx64WW8/PIcvPbGW1i6fCW6vQyVWhXVatUYgISpQSgckxS1gWFkKnj5lTm4/vp/43e//T1++9vLcM3fr8e99z+E+W8vZvudyBDcylVjeOmlOXj55Tl46ZXZeOmV2Xhl9my8NncuOp0egoUFGY7RQlkHU4YQ4ftNcVOwsdVMnuc89sI8NRId83iu5XwnPwAKldAfc6KgLJhdqAhUgEwE1Xod2+3AEN8rr76KTqdDIhfLQyUpXn31Ndx//8P4/R8uR1RhpVltALXaIIAEc2bz3LM0TbDpxhsX4SZVIGY9bLjBBthpJ5boNxoNVCoJ9ttvH2jMAFH0el1MnbpWsXl6+fLlqFRS7LPPHkhTYdlvdEsaUBVavHbxKBPzGs1AQLE91mCSCKRCg6bb7uDQww7FAe99NwBg0eLF+PFPLkGuAZVa3WAnLAOHWu4IJNTIE4yj5mb1sfs9nxBjrhx5RuMh18xaEdlcDBchqLE3z0eKkVWEsPUIAmIOZL0e1poyGad9/KNFKPCXv/wNZs+Zi9rAMGDGWUgS27cDQALqQwNIawOo1vlTGxyGxoi///3vAIChoXGFp54kJaxUFZVqFUmlivrgEIaGx2No3EQ8N2sWvvjlr6DT4YkHX//6V7HGpDXRtcYG4sUECrzyyisAgM022wyTJk0qDEf1YhrzrPk+U6DwELl5rwogV2hGPjDpj6g5lVueUQqbp+55dggQsxyTJk3CeuuuizzP8dprr5nssBCW+r4qUzwgfxbelXFT1u3gox89FXvvRS8ehnEaIWzNBBGEhN3YQVJDkqQIdqYXhXnKfWMWcatYWbhIQLvVwE477YTjjj0GADA62sD551+ATreLJE251Qhi2zAy0pP2bfCP/JxbNNjdHi5gY4R64wkyjp3oyrZhjJwo24SpQhHoVfZ5kYxq1TE4NB4DQ8MYGj8RnU4X1133T4w1aMjssssu5tFSi/TpL3aICVXUBoZQrQ2iPjAOGgZw5z33AIAVjwBAxPutarnb6eK6a/+JECqo1QeR2BFHtcHx+Mc/rsfChYsQQsCuu+wEzTp9G9S9Wp14qFQqAKqoDw5iYGAI9fog6kNr4vHHHsczzz4LEUGvl3PuoAbSEDD3rTfR62UYNzyI9ddfH7A9wQUc7YpG9zADULTchlEqs+Ihj2+7ArOwnllSAsXA0CCu/+e/MH23fbDnnvthr732xZ57vQvTp++FXabvjV133R277rIrpu+6O/baex8cfdzx+MFFF2H+2wtRqdXNGjFLXwS1ah233HoLjj32BOy863QcfcwJ+OQZZ+GMT38WJ37wVLz7PQdh+u574ycX/wwKQW1wEFdeeRW232k37LLbnth1+p7Ydfoe2HHHXbHn7nvjqSefQqVWMyHH9anF7elV9X9mhCgUim7huDLyf3P9NpgBUg02fpl4oOVqiHDPDQUiWMK79957QQLwxptvYN78+azcEp6xhWKrAnDfvffjBz/4IZ597iW8vWgJXnv9Dfz615fiqqv/DACYMeNI7LzLLsiy8sBL1YjhoTres/+7irltvtlm2GKzTZH1ulBlJwtAsc/eexb3rLfeeth9+m7otdtm1PCkST9Uct68+Vi6hFWY7XYHs2fPAexcsyQJaDVHsWgRPYQ8j/weAWmlAgmCwaEhfPZzZ2N4eAgAcP31/8IVV1yNLAckSQ2eVFC0jm1bhsDCeUqFZiEzvicHwLX0Gw4x59l5wcajkLEMiPK5OXNes4NPgUWLFqHd6TDcHCOazTEcc/QM7LIz++EtXrIU53zzXCxYuASVeg2SJli2fBVGR0YAAFnWw8svvISnn34STz/9NJ566mk8/tiTuPrqq/Hkk08bnVepICRg4aLFeNtg1csyvPjiS3jqqafw5BNPYebtt+O8876DI46cgaefehYTJ0zAj3/8Qxx33LHotJtlNMByGKOjo3juuecBAO/ad18MDw2acnbYWTRFGaYDaFDyB8Ynq28CL8OzhpM+ow9mEriIUQXyrIu1pkzC1ltvCQB4ftaLaDZb5BO/UwJUE7z+OitR35j7JsbGRpFW3EhS5FkXE8YN44ILvsOOGvY55SaVVaVeQ6vTwdtvLwQANMaamDt3LiSpEP8hhWrEm2/N49OqWLhwYXFqMmJEnnVx1pmfwqRJEwEA9913Py655OfIoqUcItdPD0C5Yq8wDUxVxEgDmEaWFTlYYYLN2oXCanIiWscXETPmJWDu3DeK72e/+ioef+wRPP/cLDz5xNO45ZaZ+PjHT8cf/ng5oioOfN97MGPGkcizLiQkyPMu5s71oipgyaIlePqpp/D0M8/gqaeewX0PPIif/eynuG3mfwAAlbQCQJD1ejhqxuGYviuLNP7y12vw7fPOx4svv4pFi5fj5Vdfx08u+gkuuPD7UFWcfPJJ2GevPdC1LjYiAd12Gy+99BIAGkZLlizFCy88j2efnYWnnn4Wjz/xFB544H5c+4/r0G53efZcCGCuLYXvCXz2mWcBAFtvszUNImtO4JfTntMfX2hw7RPyPALGO803F9vRK3ZUythi7TR5DEJrdKG2xhZqt7VM5859Sb/1rW/oxDUmKOhQ6PRdd9YPfvB4Pf64o/SoIw7VvfacrkNDNacGfde79tTnn39C86yp3dZy7bVXqsaO/u63v9AJE8YpAN1k0w3102d+Us/95jf0jDNO1y0237R4fpttt9TFC9/S1thyffbpR/Rznztbx40bX3w/bdraesH539ZFb87WrL3COi/b0TJjS+yYFzsdoO93q+/YGB7hUHb698/Ydd/u86NqRsrO+v58q7HIjqZhh2p2AWenbO+gH7OGvvjSLN100421Uq3on/98har2tDm2RFutZara1T9f/Uet1yvF2jZYd23dccdtdfPNNymOLjns0IN1zuyXtNcd1eboEh1btUDHVs7TsZXzVHur9B/XXKWJddE/4bhjtTnKbt/NkQU6tnKB9tor9O47bi3ecfhhB2uvPWId/9lpfmzlfM3aK/XRR+/XbbfdRs2gUgC6/vrr6C8u/anG2NW5r7+oxx1zuNaqtjsT0ClTJuu53/qaNhsrtNtepd3OKm00lutxx80o7qlWK3rSicfqm3Nf0m57qXW153E67Jjd3+2e3fLzXkO/8uXPKQD99BkfV80bNl87pmN0obZWLdT2qoXaHV2knZGF2hlZqM0V87W1coE2Vy3UL37uU7qGdaUHoGma6lFHHqoL58/R1sgiHVk+T7XX0D9ffUVxDwDdfvtt9Z/X/U3vvee/usfuu2pquEgS6LrT1tIN1p+m6607Vddfb22dtvZkHTAcioheecXvVDXXF2Y9rQe8992rjTtx4kSdtvZUnbbWmlo3GFZriR500Pt15q03aa/b0k5zpbZG2S3cT4OIWUMfefg+nTx5kg4M1PTGf/1DNbbKzux+GsHIIu2sWqSdsSXFiQ7lz8LiiBK/37u6+ykX/T+8Z4m2R5dpe5TjNVYtUo0tvejH31MAuulmm+gLs57UdnOpjq6ar+3mYn199vN62mkf0cHBgQImBxywvz768D2at1do247oGV35tvY6I/qlLxHH9VpVb7n5X6qxrVl3lc55bZYeceTBq9Hieuuuo+d9++va64zoyhWL9LSPn6prrEGZAkDXnDRRP3P2J3X5kre021imzdHFmvca+lU7qgaAVioVPeyQ9+u811/STmOxNlYtsJ/5BQ0WsDF+zrJR/da5X1dY9/+YN3ns0xhPK/CjpFzWdBpLi07v7bElmnVW6E8vulCnTl2rbx6i60ybrBuuP03XnTZF67VEAejAQE0/8pFT9PXXXtGs19BOe5WOrFqqH/v4h3V43FDx/LhxdV1v3ak6deoUnTplko4bJrz954Lvnqe97piOrVqkWWeVPvnYQ7rv3nsV36+77tq64w7b6frrrVt8duqHP6Tz572mvdaKgn66zZV64fnn6bhxw7xPeEzVJhuvrxtuQD5Yd521dPKkNTRNSdM7bL+Vzpn9ouZZU9uN5Zp1RnXpkrd1rz13VxHRL3/p8xrzjnYbywu4OQ0W9NpPi/adqmpfPWe0kASY0PcwgOWfGB6hpZHHHOutux6+853zcO999+Luu+6HKnDGpz6JU0/9GGLWRlRFlkW8MGsWzvj0GXjqqedx770P4/zvXIA/XflHJCFBWq3hrrvuxte+dg5WrRrF/vvvh8uvuAzrr7eOdUCIWLF8FU446UO4554HMG7ceIQkIMu62HqrLfCtc7+ORx95DA8+9BAA4Pjjj8M5534DvVYDWdYrXW9zTT1RyBw+La88mudk3lfhRRXdEMy7Ak8BcG9MaJoU0IN7XsKQCQy7/VdiB9x1Ox1steUWOPzww3DJJZfi73//B2YcOQMhSaGao9McxYwjjsCa/5yEe++/H2++PhcLFyzAaLOJiRMmYP/998ehhx6CDxz4PgzU62i3m1BlCx61uXc6Leyxx3R87uxPYf6Ct3HCCUcjTQOyXg5VWuS9Xg877LAtvvXNL2Pu62/gox/9SOmqW+5QrNBHoNhllx2wz967I0m4QbvVarOMPPYAFUxZaypOOeVk1GrcXNtstlCtpMhjhkqoIFegXq/hu9/9DtZdZ100mk20W00mfKHM+0mkZyYw79BmY6XeBK2iUqmy471yn4rEMoJgD0BF7NBJq/oL3LUU8xzjxg3h4Pe/FwN1VuBlPR4i2miMYuKE8QghQbvdxIwZR+DHP/oe5syZgyRNsGrlKixfvgzrrrMudtppB+y+23SENEWe8yBSt9jF+pyK4aNSr2H77bdHnnNv1bbbbo1NN90YScKTljsdHqxZrVaxxhprYKuttsJue+yOzTfbDIODA+i2mgxtGZ5FouVSEtxw441YunQZDnz/e7H/e/ZHr9umBVvQKcNfUVjMUHoOzPkCtkGV4QZWKTocwYI4IJabZxWMPqh3+2Ezgl6nheOPOxa//vXvMWf2a7jl1tvwubPPRLfdhqRAp9NGrVbBB086juG8LEOvx3B2VOJfoRBE5FmGs8/8FEZXrMDyFcsxafKaiJHhqZGRUUyZNBkf++hHUKtWEARojDUoM7IM0Igpkyfh+OOPQ5KywrHT6WD80CB6vR7D+SrIsh7OPvMMxLyHhQsWIkZFr9fG6NgIpkydDBUwPypSBLGYiQdTLha9SSspJkwYbwUnTGn4xWcJTSlkRClH8pzdSY44/BAMjxsHKFMAmUUeQkgwbtwwNt1kE+yx+x7YcovNUUkDOu0G0rSKdruNNddcAyeccAzSNEGeK3q9HtunWURFAdSqrD2oVivY/137Io89SCBOdtphe9x8078w87bbcdfdd+G1115Dq9nCtGlTcdxxR+PQQw/FXnvujjQN6PVYACQiiJpjaLiOY4+ZgfETxtHby3pFn1IPa4utQ1Wx2SabYPKkNaE5m6on1QHcc++tePrpZzB50po4+mieZBAjozJitNjvkTlte9TQxXBx0nRrbBELHexmCn6WS7J4gzF3VetGLTz+/LDDj8DMW9kz7LI//AYf/9hp6LRZySQKVAcm4PLLf4dPfeosdDoZpkyaiMcefRjrr78uFAGf/dwX8Mtf/RYigksvvRhnnvkpNEdXsPIPwMDAMG6+9XYcdvjROOigA/GPv18NQUSaJuh2gSOPPhZ33nkvAOCb3/wavnv+eWg3RorwSSwaDFP5MGlpCV4ToZqze3QkQArhV4TtyL0WF2Z8WMFN3kx+8h7x94XAUJjHdEW4adsSvdFOmH7jjbfw7ne/F4uXLMXVV1+JY445Cs3GCBWvCOq1QSCtUOl2u8gsT5VUakDM0O112NE+cq2qWTk/S97W63VISNHrdtDr9VgC3NfpRUTsKJKAXreHPMsJe2/DpSzISJMKagNDtARIOvwVM3TabSRJgrQ20B+5tntydNotSMyBhEe9V9MEIfUQUgSQod1sUmoKg4wiDGuzzRPLbwVS5O7efHMennv+eWy+6SbYYovNodpjvkT5ThdADEtaPiiAhpkI6vU6Q24STIiD5fWdDmLO51WBkFZQG2Ce0gANzTPkWWbrhYkLv+xd3nLBP1VFu9VCnmVFFRkZsS9X4pcJgWgndWvsleFxY2IFMDA4hBdefAUHHXwYlixZgn/9+1p84MAPoN0cRYxUdrC8N7ehgHlno3yG0gIp0pQUYHnbPoGc55wST9YoO+kEUQp3DwFFxcDQePz857/AZz//JWy88Ub47+23YN1pU9DpNGmADA7z/caPANDrtKmEiuURhiGtoFqrAYGl+4jGd0nKz50GSalAjGi3WhBhKgLo74oRgZij027augnHJAmo1qpA4H5EQNFtt5HHrIB5IENAwcpLFkYAMVImzn/7bbw253VssMF62Gij9cmHmkDM+DWRYjQJ5Jozz6OKJElRrQ0CXvJuuOFVFnUBObJuF1mvg2gndXjRS31wsA8WJuOU8uv/jqns6erGvvL7NElQqVaBEKwxeIYQeFK6VzNyXKvKNoVSrw8ACVM6Pn75Pn+/XxSi3VabMqVSRa+X4fAjZuCOO+/GWWd9Cpf+/OfotseAmBX0YU8W8sFbXLEJNWVDbXBSqcw6rSWWfC+BLoFdEoKklsDUgqFDkiKpVHH4ETNw6y2Mxf7+97/CaaedhlZzxIhLUR8awp133oXjjv8gViwfwfBgHY8/+iA23WwTdLMcJ5x4Mm666VaIAJdeegnOPPMMNEdWGK2zPLmXRVz0059h6623wpFHHIyYZ0jTKnq54qijj8Xtt98FAPj2t8/Beeedi/bYGJnP4txMDHM8P6PIfyDWW03JXFRi3AhOOx5EontwAMSO9GYxDO9JTFFG7bNqgyIBlaS/L0n5d9AE1YHxuPzyy/Cxj30Cm262EW6/7VZsstFGaDZGzJoGoGyGTP4vN3cG0OL2fVLENmP3FJBlXsmJSiQUG3G5Vq7f4SAK1uoJi1FgXlkIlsQmCxkTuEDyeZkfWlhKhINvNfaCGgSvRCoJNUNEsJyOs4SIw90qOO09Yp3zK5UqKvU68k4X3W7brGEqIAj3zBDfnInECFhj3hAC8tyrUWnAJQiIsHxIYT278Cr3CBXrhNNHKDakihktypvJdLZ2fwICeuxmGFFxBwBKpV0wsBuPWggBjsthqrUBtDtdfPCDH8INN87EF794Nn784x+h124Ve7o4igkAVYgKop1DyCo4ronvtC02ISHM+r5nrovGGkBPDFAW5dheNp93kqTodnOcdPKHcdNNt+KYow7H5X/8HaqVgF7WZVViSIv5JSiP5Ob7vFk4iUDFKmmj4SL3+jzCJIjNyvZDeRNyltiTlv1emBFL8FMuRKvKCzBlbuvgmnxWNP6Y4/G/AVKWIk0rSGtVxF4P3axjsHHcmefq3pjh0U0+VS0iYf5uPkR6h0FdLKfpdGKLMGPM+Zwf0bNWbvlyXlQ7usuMXPh87Dcf7vPm7W9VZdWtkHZC8CbU/kLSB9dAnuLH5djBjFDA1hi4T7A2MIgffP/7+Po3voWddt4eM2feislrrIGs2wa3SpNHiDMqfwDseavEL2kzR31ocr8ZbWGlQquDSAms2OKiyMgFE5YPlwa7w88TqBKwcuUIWk12B1h76tpYY42JiDFDEMHkSSyPVQVuuvFmjI2NolajpxAkQPOIJBF8+9xzcMxRRyLPcguLJNbOpbRsy93sVqyhWm5G9A3ZXrbrG/Fgfwdbl3jlogtqUGiJCR0xL8ySmCLUArlvBhW6xwoAsVAdfQRjPT+h6HVHccopH8LXvvZlzJk9Fyee9CE8+czTSFJLjIoAwQpyom1AjZkh2jwWDk4i4mRNUFmCld15DSuKHAHRdtVzw6WVPVvnFQQnI46biIWe4cxtZe6i1H5g8UDwDfPwY4MyRM0g5qG4NwDv59nXrLfYq9XPzAav6EpMubnamaTX66I1NoZur2sE70zp8wPXSMCwbNs2jkal0A7BGp+Cla1wY6YwamAVru7ZGFO5J4IcKiw+AZSVotYdg6FpvlrJv33bX1h6TVoj/fQzE+dsRRmGC8MIFECSVLBo8TKcedZZuOHGmTj5lBNx7rnfQswyg085FuEidgaUIAkANLc+onwtt6dQ4MYYi0IJEW7oJT2ZYjahQv5wI5GGLwDkWQ8DAxX89Cc/xG6774rrrr8RZ372cxhrtFFJq0V0ArZVhjYScRTt8wjyYFQq2GBnqtGAdHrhOhlpodmgYFSEPMH/FIVMcJrlxnye18h1BPgxMwbr6ADkhhco72Jlrwt4ECbCNbfHmuh0y71kfjQH5QPn6OP3iUoAjIL4vfwnQ7hQpSzuK4RAAWszQK2voxi9BeGcaewSvwKlAoAZIoYrvszwarj1lbvCIoZJi87L/MTu8+9RGlC8hWsWkzU8200LY1oguOz3v8f551+IDdZfB7/51a8wda210Ou2jT44E48gFQrN5+rV34Vs6YNrf7isALudzeWLcUECgASihYkC2E5tIEFSSZFWq6jU6miMNXH99Tei3aYye/8HDsTENdZAnmeoVBLsu9/ePgX894678KUvfRWLl67AwNAwQlrhzDWi3Wqi2+0ipAn3rRSnWJek4Z1BOF+1Zfd35eBcRekCcMM3kOWKXq7cJ6QBMQqynOGVLGdfVLUzYqN6B3av7jIhVxxi2rc/wpBQEDhgWyAEuebct6IR55zzDZz/3W/j6aefwde/fg66nR7zISYsglV8lKRjl0ujopmynRrsHo4wNAI3VIT7bviYlBadKXDA9uI5fss3FRfljgkUIbPBu6mIh65c0ZkCtg4uAD1Jr/4SWGzc6CqqMTW4nwmWoSBdmpVXGFIGe7t8veg73TwI9zS5R0ErjnRK69877JtyUjYGYDSDzWVhOKRQMm7wfCpM27rVyZcYBdpJ62rvMk+r8C4jMcN9bjQC3CBkiFj5fiFHFgJLgGqthttvm4krr/wrzvz06bjk4osxPDiAXqdV4MI2IBQCQGlH2J5H65xgdBPVYG1VxjBYqxkFgtIad1pena5LGEREtNtNbLzhRrjyj7/HwQcdiKv+dA2uu+561GoMrRZP9eEV3G1q3gjHD1bVq1GR57YiKUyt8vIzBH1OvuYYCxKPhXFgnocrbpsH+c0NDB+YhoCA2xvUBKvLQJigVqFCEgE9FDvYWEEvoiBT5YGpPv/itxlOQCyVoNFB0Tne7iYeS1osrj68FOsKnBuMdhwujiuuwzxcryoDSI/BcOxyzN8jRjv2Lsen0ydxyXD0/1XbfHWlkuDll1/COeecg7XXnoqrrroSe+y5O7qNMcD2tzmsXTb42O6kwKNT3qUE6M+ZLUGweKTSru+bHOlVwDAKbJ9MpVLHIYcdgVtnMmf23fO/jZNP+TDy2EbWy7FyxUr8+te/xVVX/xUxRuyxx2644o+/xaYbb4But4MkrWK00cTHPnYGbrr51mLBm2y8EU4//WM48fhjsdFGGyLrddHLekiSStHtOSQVaASOOvpo3GJhzgu++22cc8430GqMIFjeK0l8p7kBH0CSCBqNFj73+S/hiSefRlKUBgNBTaGbhetKs2Ay4pNjB+Bb3/oGDj3oIHQs1BWjK5ViyIJoCE9ngmgnLAMhMGT75BNPQqHYYbttCysQduiksacJ5HJwtvlxj9MIMFqxg1AQMG/I9UREy+MZYZoV6gzKOVpIw2idX/DfIVg4zr/jgopyZWcUhXXHNsXiNOjjkxUF3CbCEJgorbcE5RlnmvMZRkQpjPgFw3siFn5whQTbpOpenAlDMt3qAqBkRn6joHIJwlCbK0Oe5cc3U/DzEmGPPcBzeoQ1QHj3v0fJ/WWRg1CqkZ5M+VtuhqEgMa+RL6aA9BBaBctXjmDeW/Ow/Q7bI00Csl7bX1bAwufIy8bTyM3TDIrb3kAqSeKa1k4hzABA2cU/JLwXzh9YXahSctA4UQTUqwNotpp44slnsO46a2OD9ddhlMG8YecLPsN3F1BTzi0EFhrQODKLvDgWiHOIJpOctog3H4kKmnik8eqhZYEbDMSFoFSEMLwlTtKFsVWul6Runqp783TZDKY+B/IMbFl2Cy8L+/XzNF+gfM5g5M6UKo2UIKRVp/8Cz/24D5z8akPbWolG8guXzYIpyhoz1ixlQh7x+53nSKcRoGzsnwOImyK0yBfzl+Gw3e7hwYcfweabb47NNt8M3eYY7eL+UKWb4kLZQpQrDZ/AfCKVW0R9eK1SmTXHFjEOGRS5KvNIXsWYBERRJHBLkkKtWqnj0MNn4BbbvzB+/DhMnrQmJLCZ7sK3F6PX5e74o44+Ej/+8fexwbrT0Ou0yEwiqFbreGve2zjjjM/gP/+901bOa/PNNsGHTzkZp3/iNEydOpWWpy8wJMgBHHP0sbjp5tsBAN/97rfxzW9+A+2xEWtFlFkFogHSciaVSgUrVqzC+w48BM8+z8ME//+9fv/bS3Haxz+CTqvBDyRYpxBXQmx8Cnicl4qMtFQKf5GAtMJN5Vm3Z4xDFnAiiWAsnpdblexVSY/PiLiQW8bsxqN8n1mnQZAjWhcWJ2JjocBeaTQcGHvXImTBPJTxNRneFIWH+qQwAi0Ma55AAENHxq0A/Dw4ei8xzxmKoGwqllnm/igJFOiDg1/OxBTEnpfjLxdAJpxNqBuLlrkJdQVWGpUEKRksRkUU5vZgyrLI2RieSqFkCgpmaxR4DO4nlCFvm5eI/dsNCXGI8zebMQtUebpvmlasGpDJcsK+hG1w78MJIgTmDuFehgkyg04hZMUUCECBJigVupEs8VoaKoQ7oxJi8pIxRCCtsGLTPVoOyGcLgS+ggaJq8O7nW0GuEakZJg5iCmADrhkbpQi0e4z3tMAX8+PkGRpM0bznYEYH4wEU6gqw4MPyp9qHseItfXhXcIxgTcV50YcgvGlGwAyaGD2kS9lkgCielRCovBRFJMLxXPJ7uV4UI/BSVauiLqiUK1B6jX6PGB1rEASLGoih0FHEtRu4jdc8wsEbzFey6IqakjRwAoYDscYQteoAorLjDvrCvL4eGm9Gg4GyjDlzgzVfAAFQG5rc75ktBsAjWHJr7eTegXs3jpJobmlaqeOww2fgVlNmEyeMw/hxQ+j2esjyHL1ujlUjowCArbfZCl/72pdx7LEzIDErcmoqAbXaIFauHMFvfnsZfvXr3/A8m75r+q474ZKfXYJ99t67UIQSEmSqOPaY43DTzbcBAL57wbfxzXO+gU5jzJSJJ00t5+WIC8FO7X0GK5avdEPRhAnvyz1vqKAQUOd2IinPMiQQ7LDDNlh3namIsSz+8IonXhEhCUhCYlZ5SWoEvY9JCAO0eEQEUYisYPOI3sHEkSmwnBgtzn4LiVWnNgV1tlQWWlg+SU2ZQcicwazcglG8wM0MGIdN4REByFWtEKJcl0NRoYVHS4HqUo6Kg4RqxOtzhQtYDhk1ByLolRWFHZ4nLRVGGWoqcenSV9W5yRSP+JoIK4b+HAL0/yisbFJmVKgyBE+jjhAUAKLCQhebSwDJThJbiL20OBHAaIuMbflA6XunmOcTSoVBYRNXC1FyYMKf/+rrK2pw5ZjeFcMUnm8e9hsLm0qoSPoRUKybfVeTgpeY9IdQeHEQPhfAKl9VKjdCjR6Ih/L6y/8NZcXv8s1cnQiFcbAYeSE8USrX/r/LL7TICbmhFYReRQGbQmny7cQDaYckpMwHRQ/FM+/KKTA3XXgO5TTsnSye8JCjCKgw/W7nM3u9Oi8Fo1RxmvYbaORw/f5DnPVDjmty2JhxaTqfVGIRKEuHOykQ7c6j/pnxcNGwnTDg/8jTYrzE5zhXfxf5i5+T3v1lLN6QYGObPii+FwAWfvUtL5ybG2I5Q9CgYV6t9ymzdmNJHyDKQRWmYe0vWu38naQ1HHbEDMy0MONPfvpDnPXJ0zHWaCDLM6xcNYrr//VvXHzJL7Bo4SKERHDuN7+Ob3z9K4g9NrJlrFZQSatIqlUsXLAQV1x1Ff52zbV45unn2JYqBzbaaH385c9XY6+99kSv06LCgOCYo47GjbeYZ3b+t/HNc7+BVnMMASwyIIStmAJmrZoFVqsN8OiEGOGRt4KoCgQLEeHfef5UASDycEkvI7UQJWCCpBCmwMjIKNqdrGBmKe6x1/DFlC3KIga+l4LLGbnUAIFzNGJg9VSpGLj28ioFgHXRMHoRn7OPa+sPpvAgHkpzZoNZzmUClgwtJEYroYd6UY15OqCVWfxRXAZo7ecqfqBq3oCAFqzF0p1hivwcUBgC//cdVugiZFIuk4o6WGWkDWeKxPAiVHj2WCFAIgBEht0ILD6nACWGCQ5RN2mNDQNzZeKGBGMqtjj2tJOgFHwmkamk+t/hwsEVgePDBa0tBChh4MK+H7b2nUY2qvV8WFTbj6bsp0haMOq3sCNhZF6HUtGUCoMA5nclLQmAvPAeYfPlVFjoxDlRedvnNl9/DwFry/OleBi0/zIFCmsX5cSr3gAcHKvgE+njAZ8PTGAaP8JC5rDzDI2wLZRuJQ1mkHDaTkeA2Lto1JXjudepYiXkahWnDj8Yzgx+Cik8M98awAFKpUtY2rgkPUY6hDk/OP1b+LEgbphRxX+S/mFKyHBqLyvgr2Ckwtdd4NDmSjD0KzOuRywSJGL52QIuJS1H5IYv4m/c8BAG6wOlEWj8w8Ilvq8+OGX1MGMQj4nzARvbCBpEavAO6YK0WsNhRxyNmbfSM/vFLy/BmZ/4ONptdvAW67n429/+Hl/4wlfQbDYxPDSEu+64HbvsvD061hYFfVZamlaQ1Abx5ptv4qKLLsIvf/EbVALQyYFjjzkSf/7z1WB/UUWugmOOObbwzM4//1yce+43mTODeScw4vM3GAOICEJih9sZgdCq9c7zpaJxBcQ/SKAwSyPPu1bEYIwgVERehFCppnj0kcdw9ue+jLFG24S9EbmFzIIRhsIYEX0d6e1y5uPTfULN6aFQGi72XMA4Do0Q+Slsyi5/y7Wa0OKcODllworWtFr4Ujx86oMSPh52I81YibSDzpFckhbhaJ+JGCO5IDHaAyhV+0NM/LRcEwUpX1KWwjOnSNg5/vlG9dyGC2wBYSe2hkCDV80jJuPyAfbu6wOa/zMY9B3o9kWRRxHQ4PHijuIzN1ZMbpvQE+cLNy6FITenghKCXvzkl3GvV84GW4/DCWVBQ4QYoksahMNFfGEGQ9pNvGze9Ph8vZw3Q/t2n4m2ooDEt6/4dC3EDKPp8uK/WawsZc7IflDAmXhRe8RzpVQwBmeh4jbg8mmxB8SgVcg4X4/91xbiKwwOPvi2D0JMo8BJXcxppbC1hubBt0c4DBx+LB4TsSiHCXkqQZuo8QNTCVyfOrkr7zExXtA5DR9OPwTi22khQvxBrpnExued7oo/S9lc3OCPmCyNKNCFADtLzqbDSZQ8JQASC/Oq8aaBoqQ5RHbQt6Kl00/7CM4+69PodpgXjra9hoaKUpkNrabMFkJghyw6kQQrjTXBHPvP+wIQKhUcdvhRxT6vX/ziYnzqkx9FszHGkk4RhEodq0abOOCAg/D887MAAN8575v41rnnoN1qoj4wAI3ROoE77wjqg0PIo+Bzn/08fv2b3wEaMWHiODz5xJNYb91p0JgjV8Fxxx2HG2+iMuM+s2+iNTZGYBXl3xyTVrsl9UPA4qXL0BhtWD9Ei6sXDG1UW9C2V6XRAlKlVTt1rckYHGAnCtit2ld4Uq1W8fhjj+Pr55yLdqeLYMeB0xoEQ4oA8mh7xoyY0qL7NIM0TpysjmUOKjGrpiiyMNTCBDAJ1Trdq3O8wYL/KISOGFPlJmglWuWgKfXcSntZVBIJG1PMcOLnf4p3Cdyo9gM8+bzpCT4bWTElIHMQ5iUsaQVzjoHSlexln5EPvbO2PY8+oWsbVzk3hcRoAtjutka9sLkWb7Y5abQgWW6VmLZ2FlFwIR5+4tz5vpibFxnVtmuYkobDicojWFguuLEQ2BmeSwws0yZ12hwJd1dGtlozGvwv0giddjblhfVWhHtXMAGp3PsEoYcYYfgwoPB7q6ezz8SMGpNTRcWb40bsOe0zAtQrXk2AiYRinVAe5gqjdQM/o2p2v/cqhckhv0QEyIlT5RSMBC00XFQZW9rAvA53AoU3FzJO+kxBsbk4fYvBWbwYpO8ZXwflA8dgPslgDZBYjZ4UVK6FkVLgznBp9AhhBEHUwrnKvqPsylOuQe10DoF5PCCMHcRuMKg7aUrvppwT7yNd8A8qXC1oRoWxAj86yfexqR1pE4Ig/d8entF3W3JsgPQOWCGwahFO5fzKpAXAblOfOO1jOOXkD6HX7RajeHGW89TAcJ8yazUWW2jEBFhUIORmcXjMnZNLhGEClYDDDzsK/7mDHTh+8ctLcMYnPop2cwyGB0hSRQgVHHjQIbj3Xh5lcfonPorf/fZ3GF21Eg8++ACmTZuGrbbaksd8+BUCagPj8NRTz+CII2Zg3rz5qFQFD9x3P3bbdWe2bFHgmGOOxS3mGZ5zzldxwXe/jebYmAlOS/IaYZDRWNAy2mziwx/+GB588GFUKxXziIzsHJLOVIW14gRn96ng/O9+C2d84jR0Wi0yj1knLkD9ubRS5ZiGQKEcJyPZ/DxJmxRKxr0cLTbmwvbHoM+SDYHH1ES1og0j1mKunDAgFlLxv4uFgh9on8di5AWzFnPvkl3kAQw4Yn9bN5T+vEYwpVrAAeSsYKl10ojYNgeaYWrvZMWZApIgWuFDACiMfP19G3b9E2cKCnZ+Stknts/LsGf0gL4tJ2JK1gBgYGEBjQsLLSoNjcmVc+LU+j0Sw1uMpvHIL8R94SZRV9szYhWhPIqIcCrGE/5HCUB7xr503PYJET5Dowm2p1LMO4ByMzovryztM4i8yAWWH3cFrbzXBT9MiPr6y7/5l3KJFMSWY+SRL3Ygq4ERRsOcu+8lE8C6DnFt5XJjNCMBaqeH9/EsUVbkrD3C4XWSxB1X7PwDE4ikRULZacILaAh+kwEF7RMuxTiOI3unh34FsLxZRHDDwPKfPnFuxXCD2XAH92YCEqV8IP5QhicLUjSloGbw2IToVNCwcPpUGJ0I1yoqiOLRJY5F/vRWhlTOKJQis4Wa54QBIhKPOFm40lBVygnAstGlUcJZFbMEhJ85F4O2KDQqsrxHuWDFQAFiISm+Y7VN00nC1iWJbRhW09AUFAy9uWDiJEhMeZ+VxGolMg1DGwFJmqLZ7mB0ZKy4b4011gCQoNVu4zOf/RwOPfwoPPPs86jawW+e91DNMHXttTA0bK2PiC/bh5Ajzz13wcs1t1+5Ml9Ca9dLOSmM8izH6EgDvU6GRqOFRrONRrONVquDVquDdruDTqeLdqeDbq+LdqeNVruFVruFZquNZquF0bEm31nsA+tjDLeEwQ7t3V4HvW4H3U4bWbeNXrfLFlW9Lnq9HrKsC8170CxDr9dB1usgyzrIsh7yvAfNM8S8B40ZYt5FjD3+aIY87yHPO8hznvsVc2+BlPHfWa8YO/aNFXN7Z+zxc80BH0N5zH2MGedm4yFG5HkXqhli7EE1Q55nyLscK/a6yHsd5Db3mNu5WN0O8l4XWaeDbreDrNu1FlttZL02ep0Wer024dTrotNto9Npo9tt8bmMz3U7LfS6bfQ6hGW320Kn00Cv2yJcOy10Oy102k10O030uk3kvTaybhO9Lu/vdtvoddrotvnOXtZG1uug220j73WQ9brIuh2+p9tG3mvzsNLYK85Wi1kXMesiK3BBmEB70Ohw7bKjv+Z98IocR3sQ2Fltyk3medZBzDLkNnaeE34xJx7zPIPGDJpl1nvPv+si5jx7TO3fMesWcMt6HWS9HtsYGR3mOWku6/XYC9BoMMs6yLod5FkXWcaxsh7HjhlphX/z/hhJR372Wcx7iFmGmGXcqBlJa37GnOY9SM6zvkiPtjZ/Ns8Qsx7ynq3P1pE7vXS5njzrci29Nnr2b/IM5xd7PeS9LuEbCS/yBmHjdMlnusVxL/652ji5za2ARdZB12g7y9qcR7eDLGsTbj2OmWddZF3SFbcWEfZZzucKvsg4T8K0b33F7y56vTY6XdJnZjSa93rksW4XWc/fw3PoouExz0jbBY91jbZ7bcLH4NnLjF9tnDwn/mKvxK+aLMj76FI1Wju9DDAZQlgR3jw2qIs87xCP/fLAZBliLN4R7dy8PGtD7b6e4UDEw9fMFzIHbcrSrj7fnR9GZfugYC1YmA9ShBD9tCBT3wLVgJ6dBwWzPoIkqCRVVNIaavVhVGoTccONt2D27NcQBKikAQe85z10+0NAu9PBvHkLcPWf/wxJBiB2BApCCpE6nnvuWSxZvAQAsO5662KdadPQs+MBVBWZNdMEgFarRcvDvQtbp8CMY2VfuZj3MG5oEFdddRkeevhePPQQfx555D48/PB9ePjh+/Hgg/fx54EH8OCDD+CBB+7Hgw8+wM8eug/33XsP7rvvTpz0wZPYSNWsFrdiHchuYWgeWVptx9Cw+tH25Fj4KlrnDIZIaEB4B4Pie7VzlKL1LcxzaKTCi3luJ3SzSXO0c5jKUI8Z5Z6fQw7ABCTK92hUKrVY7vin0cD5+JwBy/HFyFJkFc4XbjmTTogH0hItMSdCWt8MmfFV3MhLb8a9JVbVWtjI982Il1GLhXLMAzIjS/iL+T0GCq283P6N3Dx3sKqngI/Fn/xHiLeIjOMrbC8m/yfoK6Cw8A+MnSIYGioCLTFamyh6RmrFtpyPeXGaF4aFquEFPDcLah1gXDnmhl/4QDmNS/NKVD28TAWqmjOsavQnMHiolrBRwolegK3TPX66xja+PQ8Pj3Nd9F75ThpVBr+c3wtI41lG4UjfPUP0Q2DBd9CI5vEqGnkwps9V1fbtCUq8wDckm6epLDYwogEsZKVGmuSnku4Ir0jjLJIzouHRv2Oja4ZlyadGq9Yij/xh8tAGpumfQ0AeQTRX1S/NDf+8CAOvHS29wxI3Ti/GC5IzcgDmJbOYsYemtdvz0HgpS7iGPPaK7zRGxIx8rxZNoHflsCYNUP643LKwrZnxMfbn9NgYoeiL6uMiFPuYNSp7QNraRBRB2GTBvXARhQTyqiJaQk7gQUkvknMElsrMv7T4cQRjtRQ9QjVWMLmgUh3AqpEGVq5g6T0ANBpNZJmi0e5h5UgTr819Ez/72U9xzjnfwujYGKICM2Ycjne9612IeRfVSgWDA/S6rr76r7j88j9A0hTVgSHUasOY9cLz+O75F2L58pUAgA+ddBLWmjIFWa+LEAIajQZGrPQfAN6aNx8SKlYZZv63/1g7FRhhBgHWWXttbLv1lthumy2x3bZbYrtttsK2W2+B7fxnmy2w/TZbY5utt8R222zNe7fdGtttsyV23nF77LrzDpgwbpDlloZUhRbdMVyhBbHKPoTCNRZh2Iv/Axv51gfYuNNDkSIUEpR4ts9FrEKQHfjJmAyFMTcDz+eTsCy8RsHPeYnY7nkVdhMwsqTHy7i1asLfFloJEsqcqqCkiyLur2yDBJaao9jo6AROr94VGQnW3+ebTU2RGFO4d0u6IywllJV7PnN6wCyR5twsfCe8g1smLCvvQQyx0ErBqCX+yHgGv8gnAhLyg4VJxd4nInbCMefJ0Ce4YVUocIKkVJgSynCeguGXwvixnoQeSnSlXd5m+KUwqdbqqA8NsULChZnZmfyvQlbbsMeXqoVqPJTGSEuJH8LaQ3EG48C9WUVYrAiFlUM7PRRVe2D+r1KtY2BwGGmlZkYDO9uEwBOUNXKTM+mLVwilgHLlSDonnNjWzStyGbpVE8IKmIKxGBVQ0IO3MoMZQGrVmCzEclgZTp3ug91jJfblGg1msdSGUoQYzagSKk2AhqVxILdiwOjTQ5cWzYKwDR33w5HPRewwWEsneCgviB2QaqFf5k0NRmZkuDNCjJhyNcPCrSlPxYj4Fo8++UNq5LtDgpDw0FMmZJ0uuXoIZasb4AUf+ZzMAI+Rh7IODo9DtVrr42Q7x92qSzVaMwWDLnmCBqjPk4207Q7PmXWby4pFhGA5EdAKy2MEkkDrG4qkUsULL76CT336LDz44CPwa3h4EFMmTUIv7yHLMjSaTYyOsLJxaGgQRx55GH78ox9i7bWnImY5enmOo446CrdZAUmSAjvssD223morrFixEg8/8jBWLB+FiOCkE47BpT/7GYaHeSrx7Nfn4otf+mrRsd+vY489Et///oXYaMP1kWddEpAqhYhDwPYNBd+f48QoRCiRT3VubG+WogscFsZAqRhY3mzvMIUCAHnGfEMIrGCLEawAUjXCiVAF6vVBLFm2HFdeeRWWLFqAr3z1Sxg3PIyYkSFqtRqSSsWOVzAmS1go0Om0kecZ6vVBhIo3cHUmjmg3mrT0jWCSENhlO6TIOgw9xMg2OiLBTpmt2fMciyGvDJXagFnlhBdE0Gu30e10kCQ2LsT2L5hA8qkAQMzR6/aQZT1AGJKOOS1+F50u2KncTMCZpxGNaWNfIRKVHeejvs/KmVf8kEUTHG6wiWKgXmMUQO1+U56F8LeO/Z024RMCk+kuWNNKBbU6e4iWCqO0sMuF+3gR7XYLea9HWJkRRyFgWrPIHTB60OtZiE4IHypcQSWt4D933oVnZ72AU0/9MKasuSZPJrA2Q+ijaSolWx8snyL0LkR8Qz0LTWjEGP+L2FaIWCg3z5VRabhh1H9yhOcEOWZtcAhzZs/Bv/71b7xr/32x2y7TrTu8K3WFZi102qzyTUJg6kAV1WqVnXlohUGhyHodtNttpGlanPRgOhgIgl6HqYEkTTAwOAhIf9d840+nXcBCeF1ArMNIRJGD65cLwbYvUEmw+ACF4CZtRGVBVrRKaBHQEynuoTEgxUkOZU6tNjAAsapqN3aILf+3AlDk3TaynPtb87xH+YFAWCSWO/QnYoZms8lCHuXzAAtfYlRUajVU6oO0fN2QlICs3UbP+p0CEUmlgkp1oM8QEwCKdruB2OtiYKAOSSsGVntXwU80ekRMMUEspZJh3rz5+Pu1/8T7338gdpu+K9rtNntQOrsAiJrzjcK5uTHhvUNVFWzRElAf7N9nNraEwiQw/Cfec04UWYxQ4XMAUB8axjXX/AMXXPgDDNQHWC0FRZ5lyP1IdwHSJMWkKVOw2eab4n0HHIBDDzkYAcIzcRRIqzU89vjjuOHGGzFr1ot46aUXsWDBAjSbbUgAJkyciJ123AnHHHUUTv3wh1BJU/R6bQwMDuHa6/6J887/HgYHBhAkQR4jer0uup02fvbzn+ID738fjxXxYgLhOVYCMMfl3Qg81RkSQHJa0qBniuIeFwq0cgDrgVhYc2pWP/9kMpeEBrOEVSzYFF1sU7BWa3W8/PJsfPJTZ+L++x/CZ876BC684DwkCSCaoFIfwAvPv4A7774Lc16fi26rh4GBGsZPmIBNNtkUB7z33Zi2zjTcddc9eO2111Ct8bTdbq+LSiI44N3vxtSpU5BlOdKkhl4vw3/++1+8vWgh9thjd2y/3bY8fdoE0B1334M5r72OcUPDCIE5xj322B1JmuKeu+5BktgRIjFHlvWw4047YNdddsayFStxy8zb0Gy2UEmrtAxzbtwOScBAdQCTJ6+JHbbbDhtssD46HR7F4YSKvoS7KptGkzQt6ZvngJT98zTaWVowQQ8TEMoybm44BwB2M2H4l+tJ0xT33HMPZr8+F7U6j3FhF33ScQiCgYEBbLzRhth+u21Rq9bYANUEWJJW8cabb+Gue+6DKs+zIu59DWRcEdJVEgIGBgex9557YsqUqZg/by7uuuce5NEqUe0E7KRSRbVaQ31wAGtPWxtbbbkl1pi4BvN2WUaPNVfUBuq46eaZ+PBHP46ddtoRv/rlz7HlFluw8CqhoiIPesWpMniAwJNO3OoNXi1JRWTyzmg+QMT6aLoH46rAPTxhJQobDHglNGVebWAAM2f+B5/97Ofx5ptv4Zabb8Cu06fjn9ddh26ngzStIKpi5113xk47bIfcTkAHAkKS4Pnnnsdjjz9uhVOCTq+DbbfeCnvssTtee+113HvvvchzV6KKTreD3XbdFbtNn45Gs4k77roLK1esQpowV07PhDyaJAkmrDEB22+7HTbZdBN0uk3mflSRhrQ8pRum/E1BA7kFyWy8aMZRAACFRM+Tm6A0z9C7fMDUmVfxifHcfQ88iDfenIdKhV4Kw32uFAVpJcWUyVOwzbbbYL311kXe6SCzk+I7nS5umTkTK1eOoJpWgETQ7fYwbnAABx/0ftTrNajmSMAesxBBWqng9dffxB133MXxq1aclufYd999scUWm6LX6yFNEzz/wou4/8GHUEmqSNIK8jxHmiY46OAPYK1Ja+DOu+/BK6/ORq1aQzCFqsrtFzEqQkLDr5IkQAQ22WQj7L77bnjhhZdw6OFHo9Np44c/uBAfPfXDzJOiZ/LUz9gD5a6lBJwOCzibUqsPTQZ4zrRqp7mMJ/yOLtZOc5mdnsyTlf1U1eJkz8ZSHV21WOe9NVsXLHhd317whi6Y/4YumD9X5731us576zV96805umD+XF25YpHG2FSNDW03+k5nHluirdFlqllTVbs6umqJznn1BX38kfv17jtv03vv+a8+88zjunTJfFXtaLe5XFsjdoLz2BIdWblI33zrVZ03/3VdsOANnTd/rr755hz9/7R13vF2VFXDfvbMnHNuSU9uGoQSIBQpAkLokBBKgBRAKSpSbAgK+tqxUSyoFAuIgthQUIpKlwCv9E6oCYSEACHl5ia339PPzPr+WGvPTHi/+XHIPXNmdll79bX22u+8u0L6+9dJvZKNX+dgJ2iPbJJ6ZZPUynZibnmj1Co9Uh7ulvKwngpbr/RK1U6FbVR604+eHutPOd1snwwm9RGFVf402vJwj9RGNku9skmqZX/CrJ7U2qz2y5r33pIDZn9EAPnKhedLtdIn1fJGKQ9tkFqlT370o0tk69yJr4E61QWQMAzlrLPOkMGhXvnsZ88SQIrFSEqFSMIQ2WbGVHnmiYek1eiTkaEN0qoPyeqVy2XPPXYVQL74xc9JozYoFYPr0NBGOfmjC62dUIrFQMIQuekv18s9d98hxWJBwhAJbL+0c8jXvnK+SKssy19/UXb/kLbrPVeBQ8LQatuAlEpFmbXTjvK9b39dBnrXSbPaL7XhTVIf7tFTjod7pD7UI9UhhZOedJydiuxPAa8M26mzQ5ukMuRPoO1On63YSb+VYTuReURPUi4PbZDy8AZp1fvknLNPT8cYBE6iMJD29jZpay9KaF7DyZMnyeGHHSQPLrlXWvVBqQx1S3lwvcSNQbnvnjtkwvgx4gIkjJBiKZC29lA6OgvS0RFJZ3tBOjqLUiwFUig6GTe2U+78120iIvLIf5fI9OldEoZIVHBSLAYyqrNNxo7plNGjOqSjvSATJo6RffbdQ35w8Xdk/YZ3JYmrUh3plZGBbj0huDEif/zjDQLIh/faU1Ysf1Ua1X4ZHlwv1eGNduq2ntjt4VZOT+/uTnG/arhYKW+UykiPNGv90qgOSK3cm+MDvfqp5u9tlnq512jJ8L/SK7VKn4g0ZckD98jkKROks7NN/nDj76TVrMvmzRvk5JMXShAghYKenjx//tHS179RWs1hqVf6pVbuFYkrct01V0uxWJAgUJwPAic/+vHFkkhN7vznP2RM7mRl//nhD78vEldkc89aOfTQA8RpDpqEQSBh6JQ2igUJnPa/ww4z5aKLviGbN62VpDkitUqf1Ct90qj0Sr1sJ0X7k7X9ycbljYabiqOV4W49uX1wnZQH9ETq6ki3VEe6pTK8QcojG6Rc3pCeLl0dVhwaHlinOFneKOd8+hMSFUKJokDCMDD4OCkUnRQKTsIQ6exsk112mSWX//RSadSHpdUoS6M6IEP9PTJ3zsFb4DIgu+86S9aufkOqw90yMrBOyoPrpNy/Tkb610rcGJD77/2njBndkdKrAxkzql1u+/tfROIRqQ73iMRlue6aqyUMAwkDJDK62HnnmfLaay9I0hqWM884Tfu2U26CAClEoUQFhXkU+jk5CYNAjj32KNm8aa00myNy3313yoQJ46VUKsq11/xCRCp22rnxyJFuqfrTusubpGK8tTK8Ue+PKM7Vy5tFRCS8+OKLLwaIW9XUTE1Tby1d3GuZeKwRoRCGjB7VSXt7ifZSiY6Odka1tzGqo4NRne10dLTT3lYiiAKadc0+w59cbW07wbKPqhQKEePHjWX69Olst912bLvdNnRNmkjR3k+SON1z4kSIChFjxoyms7Odzo52OjvbGTWqgzGjOogCc2HgU4wtpdT5FGC1NDFTOLNtNYFDNeots2UCc0FlGpXXwJy5j33lBuvX3leXrVobqnHo7yKOxAWcd/6FPLDkYRYsOI7fXvtrkJhmq0Wx2M7lP72S73//UoaGhjn99I/xk59cxte++mXmHnkka9a8x9q16yhXypx66inMO3IeG3u6efnlV2nFCQccMJub/3oTu+26swZ9cRTb2njp5Vf5/Y1/oFarM2H8eBYuWkihECFJQhgVOOCAAwijkCefeAYR4TsXfY1zzjqbHXbYidkHzObJp56mv2+QMAz55dVX8OlzziIMAsaNG8fixYv4738fpXtjD1EU8cPLLuWTn/wERxxxKNttuw0b1nez+p13eeyJp3j3vTUce/QxlKKCZpimerMZuzilHDEo+83PtibFYoliRyeBuVyc33zrXTze8vAWuTP4W5uHHnY45ZEKL7ywFBHhyHlHcvXVV3LiiYs56KADcQivvbaMd95dwwP/WcKHdt+dWbN2pNVq0mw02WHHHZk9ezZ333UPlUqdiZMm8POf/5xTTjmVRYsWsXjxYk488SQmTpzICy+8RCtusnjRQnb70IeYPn0aBx54IHfddRcjIzXGjR/Ptddcw7nnnsucOXPYfvuZDPT388ILr/DoI49z7733sdOOOzFr5x01+YmEVqPBfvt9hFgSbr31DlauXMmJJy62PUqaiOXh5WHmvJVhcCLdqqD0USq1EUZFs0QUT3U9fLUXH7u1tXCK7c5iXmqllnjvvff45Kc+xXvvrePqq37O5z5/Hq1mlVKxxMkf+yivvvIay5e/SRgFrFr1NpO6JnHwwYfSaGqNvmazxb777cesnXfhwSUPU6/X+eY3v8aFXzqfZq3KzjvPYp9992HJkgepVKsUi0V++KOL+fznPkPcbNDWpocGL1++nJUr30ZE+OQnPsE3v/ENFi1awO6770Ffby9vvLGCxx9/ktdee5XjjzuO9vY29RYYzBwaLxRznSlNZzzAx5gLUYG2jnZc4GjZYbLqUFS4eZe4LYStg6/yA/PmHQ0Cjz32JCLC/OOO5bwvfIFjjz2GI+fOZdasWby/dj2rVq3moYf/i0jCoYcdQegchUKBExYuZuXKt3jjzbcQgaOPPoq//e0mJk2cQJzogb1+BAK04pgddtiR/WfP5u6776FWazCqs53bbr+V44+bT9xsEQQBcUvYe5992X/2ftx///2UK3V2mjWTf/3rDmbO3IEkjpk3bx71ep2nn3kOgAULTuA737mIBSfMZ/GihZy0eDHHHDufd955h+6NG5nU1cXJJ59EMYrYadYspk6dwp3/vouH//u/HHLQwewwcyatZlMp1fhtaDUxQ5uHFlBWXq7r4gij9swya1T7Mu0q96+3NKojm1SzSy2PzPqoDvdIvbxZqkM9Uh/elLO8eswSUc3afzLNrs80RNXMa/aet3gyq0qtp1plo45rZFOqOdXM+qlWvBbVI7WyWpdem9Lnc22Xe9RKGumWanmj1Cs6z3S+9nz6jv2dzsuPbXiTVIYMFuUetdoqqjn4Pus5GFXNKisPd0vcKssdt/9dwjCUadOmyovPPyXNar8M96+XRqVPlr7wtEydMlkAOe3Uk6VW7ZdWc0CqI5tEpC6PPfqgRIVAZmwzTVa9vUxEYnnx+adl9CjVtg4//GBJWhWDg44xiSvy08t/6PM6ZLttt5a3V70h9dqAlIfU4hFpyd//8VcBZNttp0t/33pp1YekXhuSWm1YjphzqAAyduxoeXfVcmnVB6U82C3lQW1/0cLjBZD29nZZ+ebrItIQiSsi0pRnn3lcttlmawEkikK54XfXirTKZkXk8CNn8XpNrDKiz9RGNkmzOiAvPv+EfO+ir8sD9/1bWvXB3Pr26BqYZVId7pbK0AapDG4wrbhbyoMbRJIRefCBe6Sjo10AOe/cz0vcLEujNiBxc0Qq5X45/7zPq3YCctihB8lQX7eUB9bLUN/7MjK0UcojfbLrbrMEkFmzdpBafUREWiJJQ0SaIiLy/nvvyC477yTOOfn7zX8WkZbUakNSrgzK7mYhb7P1dHln9Vsikkhi723s3iDf++5F0tHRJoBMmzZVnnnmMWnUB2Wof72M9K+TyvBGWff+Ktljj90FkF/94ucSN4ZkZGCjDA90qxfjA1ZtdVitMfW0eAuuR1r1Qbn337fKGaefLA89cJck8YjUypv1uRw/qAxvluqI0qW/Xy/3SX2kT6rlXkmSmlx4wRcEkAUL50u9MSL1+qDUKn1Sq/SLSEN+cMn3BJCwEEgQBDJ16mR5/oWnJY6HUwuyURuUt1evkFk77yRtbW3y4JK7pVHZLIOb10h5sFsGejfI0UcfKYBM6poojz62RGrVXhnuXycjAxtEpCE//tElAijsb/mrMrqkLiIi7727Svbd98Pp71decblIUlfcG+41PtGbWovq5clZasMbZWRovdQqPfLgf/4pX7ngs3LPnbdIo7pJRgbWSW1wgzSGN0p1SPGu6i2N4W4pD6+XkaF1Uh7eICMD6yRuDMm//nlrOparrrrCxlpT+hGRxx//r+yww0zFhald8tJLz4kkDWlUBkRE5LfXXZPi6re+9XWRpCaVoR4pD66XyuAGqfSvk/LgehkZXC/l4Q1SK/dKtdwvO++8gwAyZcpE2bTRLNRyn9QqA1IrD0irPiJJXJO9P6w4dsKCY0WkKZVKn1RHekWkIXfc/ncdO8iPfniJjj0eEYnLIklVRESuuvJnAsg+++wt769ZJeWhTTI4sFEq5QE55ZSTBZB58+bK0ECPVEd6pZziq9J8bWSTNOxTG1Haro0oT66We0REK7CqxDaNxAfMvUWi2TNOg5gm3hVqGhdTD5I9H6g+5y/VQCxDyt7zz2pc1wL7PsbgpTGWCWMvCqppk/jkDK2YodlItuvcZ9WpPeSHYGNVdd8H8RHbTJq4dFSpxpXXYj7wPbG+/W/4vQ8+8C8aEwvSbCdLU0dteT++KCwwUi7z2+tvII5jTv/4x9h77z1pNJsELqLQVuLJJ5+ge2MPAHOOmEMxKlCtVGi1GpSH+vjIvnuzYMF8jjnmKMaNHU2zPsRuH9qVnXbeCYDly5axYsUKihZzkKjAyMgI9953H2JB//fWrOXNFSsIw8j8+JoGe89ddwEwf/58xowZQ7NZR6RJs1FNcSAMHLW67pfxUNaqFxn+VMoVmtURKiMDVEf62W//2Zx26ikAtFoxjz32uFbMxuKTHq7Y2ntLC80mdE4z5MJiib/fdjuX/fjn/OvOOwmt+rbirlXfT60P1YxDF1iA39Yh0dRxtWSgFTep1yrUK8MMD/VTjBznfOYsuromAfDscy+wZu16CCISw+lmUy1CHb4wMjxCvTpCtTxEvTJCvTbCVltvxQ8u/j577bkbkyZNsr1nMc26xcEAnFCv12k2q1RGhqlVh5gwcSyXXHopF3zpiwBs2NDNN775bWrVuq6XJLSaTaZOmcJZZ52Bc44b//Bn3l+3gagQapaX3waghKV9oTTpY4g+BhkEAX+75RZuuuUOnnn+BVwQZfQnGv9M0KoiacKAlVhKnEsLhi97fRn/+MettLcV+cLnP0+xUNR4p3hvBkSR0sfkrsk45+ju7uGiiy6iXK4RhqEG+EUzFjXmZXzJKax0b2MzZSiSCK16E1rZ+XkkTX3erlarCdSpVIapVPrYZtvt+fRnztH3Rbjr7rtpNhqIbThAqcaSDZQ/eF6olpbiUanYxiOPPcXVv7qB2/95F2FURERT62PEEhfMG2P8LcBlp5KY9dFo6HmPIFQrZYjrjAwPURnup1ru5eCDDmTukXMA6N64mVUr39Z3SYAmzVZWcCLLoJQ08ctFAZGLiMLIMkodzVZL4W17YSsVK0OYzls0Nt5spM9FYZSm+KvHR2gZHovf6yt1ysMjVMrDVMsj1CsDnH32mXz6nDPYdpsZFKJQj6SSmFIh5POf+xzjxo/j0Ucf5777l9DW3k5g+JLtOdaZ6spYfBZfwUYXOuX6WXpmFvBMbH8CWAaPITB2rIBzFji295zTDJ1UCPjBmLvN+TIwogHo1F0hGRNLzG3h25FECI14nDEnfNaadmwIYdkthpzav45ZjNGJF5BpZowm83j55+ceBNkmaGfIlm9b/81AK+IsgSBzhWH7WhKroKDMQ/G3WGrnpaUv88zTzzBu/ChOXLwITDkIoxBcRL2ebQB/4YUXENH0/cCC7JK0uOlPf+RXV19Je6FAo1GjVCpwzDFHAzA4NMTjTzwBURGCgEIQsuKtlTzzzPPsssvOjBkzChF45ulntJp7HBOGET3dG3n66ecIAsfcOXMg0H1AAXqatJ9dGGkllexOignpd2yvmIDuKYrrTJ8+3X6HWq1Oq9XyIbW0rJJmHBquoWusLhnFA9A9XaDBZXvE0FMTE5ytlYjhoEMTf0zYgi/7o5fHP3U/JzQaNSaNH09nZycAzWaLkfIIQRBYBrW2G+TLjuUSB5xzFIsFQDjpxBN56MEHOGD2R6hXRuzkYF8dRJWkxPKNQ8BJQrNepdWocMEFX2TG1gqz5555gfuXLKHU3q7pyUlCs9Fg3pFzmD59GsuWvcH//u8jFAoFm7viPOqwtaQkYwyp+1b3XhIEmk4MVq80g41fB08T+nfmbvf04cICd919N90be9lnnw/zkX33JW41NMnEzsFDU0sA+OjJJ3PQQXo47yOPPM51111PVCwanSREUUAUeaHqhW/GAzzPQlcT5xwhmuUrylTS3zW8oant4EiSBjvttJOvSMXIyAiNRl1xx9OwZIilGfgGy8BKTolDXJhmIoZGa6l7W/RwzTS0YjzVY7LyMMEFejKJ71PduYofSZwQt2IajcYW8ykWItuorAqLx6X0ym1/CMJQTwUPDUaB/ubwgln79clXup8u21fmE1JA+VMeDxDl1/7SxBQdqogjDCNK7e10drRxzTW/5Ibrr6WzU5XPKAyp16p8ZL992G+/j9BsNrn7nnup1etpRRiH8QJPY55WjO+Tq/aSjcIYQUpgvtiul/AmqEArfKvw8JqdT033TCfr2Mea/D1PAGEQILF+V0HnD300JDSBpKnW+m8iWvFdh6G/eyHl18QLFD8P55RYnb2vo1NGpD7wDGh+LIrDxoTzgtkLKxHipJVukNU9IZnwT4k7UMGT2MZEIznA8fTTTzM8XGa77bZjj933oFGvW9867p13nkVnZxvOwc23/IM//vkvRMV22to7THsVAnTzZmKWbNyKOeSgg3ABNBoJjz3+OK1GA5cIYaHEg0seotFo8omPn8Y+e38YgMefeErTkxOhUCjy9DPPseb9dcycuT177b2nVfawzdEfUBgCp5lngREHYZBq0i5wVpjILlGWun79en+HyZO7aCu16TOJMgpJLGPU4K4p0bq+GkOzFtNxYJsq9Sw0Xy1d09Sz0luJrb/iifbhcRfMO+D8HqiIKCrR2zdA1bTV8ePGMHXqFPVQhCbQbEV1HEIURRRKJUqldorto/nDH/7A5Zf/hGqtzJjRnQSBCnWfpuzpKVMaxdZfN0e3GlUmTRzPnDlHAFCr13nssSc0m9r2HDUbdbbbdlu2324bWnHMI488SrMZm/DQXF2xPT66aU5h5DMvIWPYnunqffvN04LV33NOrVovoAKnwjcMA0aGB3nmWd2qs8cee9A1eTJxo0FoHhtdK43ngWYrf+1r/0NbWxvNRosf//hnPPvcixTaOkiHm/IOHYs2kVei7M/AfOemNKbJrHap9aCKLOIIggKDA9ke1WlTp9LR0QHOCz7NnvNZec4ZH0t5iyMIIsuu055cENg5e57RZrjhx6IeKZ2PliC2G/53TwpRRFQoUii20dk5infffY+nnnoGgO22mcFOO+5Aq9GwIgliWztyjQi2NzIyizJUxT3J9lsGgcY5QQWY8n/bM+vElFHFSl/pyaE5C+kOJNvw7K84ScBFFIolSm0dbNjQw0Xf+g4PPfiQ5ll0dqSGEIBIwujRo9l///0AeOrJJ+ne0K21XMk8PZ5W9IvnA4rHXhFIn3C5PVcpI3ZCGPrNeNqwg7QIqdhETH6m2pEinA42jn1adOY2ItVQPOMxziBqfrvQJ2Yo3FWLtLZdSOIRJsdYMU3Hf/KMK0UkQ6p0js4ZoaP6orMCq749D3RP9Pa+F76pcMPOfLP3MibhCcMzEP3eaNZ57rnnAdh1110ZO3asbmkwhGnVq8yZO5ejjzoSEahUq5z3xS9xzmc+x3MvLCWICrS1d5g2rxaREyGJ6+yy2yxm7bQjAK++upz3164jjArUq1Xuve8+oihk//335+CDDwbgjeVv8P6aNYRRRKsV89DDD9NsNjnowAPYfpsZNCz5Rm3mTDxpWnaoVq6iFfgjSwwXSsU2CsU2SqV2OkeP57331nLHHf8EYFRnOyefvFiZkAgSasqyZnurm0k3mmp1Cd0oa9VKYq0ggSces8Ak8RZ4plSk2nvKUJSAxSpLeAIIgoCwUCIqttPeOZpCqYM77vgXPVZ95swzP8X06dPM/aJMyDnbeAo0Gg3Wrl/Pe2vW8s6a93l56Qtc/tOf8eebbmLzps2p0HRhoMSvXMLGZkiOlY0zwZYQ4wJhl112tgdh3fvrqddqhIEjsOoiHR0d7GrPPPfc8wwPj2ihameCSJwJ6VCZvBjFWpUIQV0GXhFVa9Nvg8gpo56GPA2bdQdaKHjjxo28uXwFzsEuu+5qdTWFlgBim+lxONv/NTgwwMKFi/n4x0/T74ODfPObFzE0WMYFWi/V05S/XOpp0Y/e8zxAsVRsXPl3dU4F2tra6egYTb3e4PZbb0cSKBQDzjzrU+ZpUJi5INsrKWiIJUgtu0zhRW1e7cN4FM4zfbTyj+cLmL6lD6TnwH1gimze3MfatRtYv2Ej7655n0cef4oLLvwfli1bThDAl84/l512nKlbnALxKkv6vg7LKbsNUGsRddFj83KWsJOyNh2J8WTlic7GKWaYgHoDtCuveGklFX8NDAyxceNG3l+3gXffW8dlP7qcn/zsSh5Y8jBhoZgaB36czjkkbrL3XnsSBAHvvvc+q1e/YwXZnY7Xh6oC5cWex6siYNtB8sIMv/jOaTwqEasAYotrp8AmovtKlOD0HW98aYxIJ6zmrw3WgEVuIvh76cQUEZLE76r3D+Unb9W68+/b/dT8tPv+Gc/U0vc9EuYEFmaRxkm+wrP27dvw73tCioJQ/c+JajFilqIflPblrTkt2CmiQrpWq7Hq7VUAbDNjm7Qrrxm3Wk3aSgWuuOLnzJ13OCLQqMfc9JebWbz4FD537hd5/Kmnae8coy4hUUEexy2mdnWx94f3BuDtt1ezatXbRMUOVqx4izeWr2CHmTOZNWsn9jbLrH9gkJdfeZW29k429vTw3HPP4ZxjzpzDiaLIqonomWb6MZgIqUbm/IZa59JVSRJh2bI3WbnybZYtf4u/3XIrZ5/zGd5e/S7Owbe+8XUOP+wwGrW6ElugzFMEZYJifQXq0gyjUOnQiNHQS4nYaVWCMNL6olFUSGGJCQj/t7dInFmUPgjYbDUZKVcYGi6zYuXbfPe73+Paa69DgHlHHs5X/+dCXJJo9C6wTFVlowD09vZy+mkfZ9GiRSxatIiFixazatW7OKcu6DBU5ce769XKsVGJCiWHVakRs4IN9mPGjLbxq2LTatrBqwE4EsIgYZttFI/WvL+GzZs3K+P6gLJuiEIQFAjCiDAqEAYRYViAUKtxAASRMuyo0EZULBJEJYqFEqG5VEnp1Teurrfezb1s6O6mVCoybdr0VJE0/45V4ElS74OIIEmLb3/7m2y3/bYAPPnEM1xz7W8IiwXIufvxG7RFVKBYGMK6t7HY+gY6tux34a2Vq3jppaW8uPQl7v/PA5x//vncededBAF84fOfY+HCBcS+tqvfLK6sAYd5aMKAKCoSFtqIim1a1cQViSJzdQcBBAUi25NVKBYpFIs4P9ZED8fNK1vgBV86U/76178xf/5xLD7xZBYuOonjjlvAkiUP0tXVxa9//SvO/+IXaTZaKX9RRTxj5SKGQzkXp3jFXKWyolguo5KUz/kxiVKXwSLPW8WMAUnMFZrSF9xxxx0cd9wJnHjiycw/7nj++te/gZ02rlacKeBOMcM5kCRm+vRp5paHd99dgwu16owkJpDRdXB+fv6ysbCFMPMSL1BiFTuuPjWDRYHumZaYYNNJ2Q53M7C8SehxHZPAugved+fNXB1IElvhYP/d+vbA00WzNu27/4hZJyKiqbG554MPxr/sb0ywBeZu9AuULoxfvJzQ9sJNm/bMBt1Ymk5M/0nn5c3k3HjLlQq9vZsBmDhxYtqu1jwThJhGvcp222zNHbfdxi9+cSWzZs3EOdjYs4k///lvnLDgZL7/g0uJEywhQNejo6ODAw7YjyBwlMsVli59CVzAE48/SV//AHvtvjtbb70128/cnq6uSTQaDZ566lmCqMhbK9/mpZdeYvLkLubMOYJmo25u3ryG7JFdr9T1JHrXP9ZqtTjjU2ew9777cehhR3LO2Z/m0cee4LDDDuXOf/+Lb130LVqthipCZgWIZGvk22w2mvRs6qNnUx+9fQNs7huge+NmymV1/w31D7N27QY2bNzE+nUbWbd+I++uWUv/gFaOwbdlm6FJcVhjCIFTZeyOf97O7nvszp577cXhR8zhxz/+GZBw0be+we233sq0KVOJW4kKCZy5VqPMxREETJw4gcmTJjFu7FhKpZImB+UVOKMVhyNOrI6ibdjWYgNaz06tixRrNeaRflP4qKXhmZkwyRJVqtUGm3v707ihx7ls3UJGylXWretmw4Ye1m/YxLr1G1mzZi2DA4MADA4MsWHDejZu2kxPTx+bNvWyfkMP5ZEqYRBZe0o/+XH29vUyMlKhUCgyYcJ4UH+K/exd7Yke1Ak0GlqoetsZW3Pxxd+jWNRtGtf+5re88OJSwqhowl+FO6gyqIqNn5fiYOj5i+ErubE55/jJT37KgQceyKGHHMYpH/soN974RyZNnsQNv7+en/38CsJET4/X99S95qxijtMv1GoN1q7bwPoN3axf18369Rt4f837DFtJvaGhQdauXcfGnl66uzezYUMP69Z3U6nWTGlG+Y5X/hQlTAf0FGXGCDGNep1ms8W4ceMA6Ovr47HHnuDtd95NY4vGmFO6w+O7rVFiHXiaEvvuYeeVUwQTiKZYWqMaTiJVjPzzYsJQYZx1HkURkyZNYFLXBMaO7aRYMkEP2og1puPQNUrimM7OjjT+vL57AwRRJsXAwk/p1/QSoym2EGYeGhbn8rn9nrkHgS6AywkEZzEr/7pgZxSJGED0uzMJLi5zLWoDntGoAPTtJ2LmpU/KSIGXHa8AJnByq+gXMcasrA9YVD7BIL3ngSG2hyQn1PJI50SNeK3Cn4FMG1KtyOcSJE7dNs45rQiQxnm07SAIaNQb1GuqBba3ay1GBZsSu4ia8LVahY62AhdeeAGP/O9DXHnFT9l3n70AGBku86Mf/5Qf/eRnJKkLSWi1Ghwwe38VksBTTz/D8EAfTz+r+0AOPuQAoihk6pQp7LbbbgC89vpy+vsHeOzxJ2k2Ew455EBmzNhaY2loAo5zZmmmzMlbGRh71cu7O8IgYO7cucybN48pU6fQaCqjmDlzJgcddLCuRSLmPs5cHoJmOUmSUCi18fdb7mDeUSdw7PzFHDN/Mccet4hjjz2eO++6G4C777mXI46Yw9y5x3LE3PkcMecYDjrkSH78k58ThFoNBSBwIYIm1+i/pvkZbu0wcycWLFjA/vvtT6Ou+1zGT5jEYUccztgJk6g3m+r6thicXpnwnjhpEv+843YefGgJTzz5BDff/Dfa20vU63WLr1qhX9Cq5Em8JWOwAtRpg07/FzpHvWoZn8Do0Z1W1UHdRs4p/EaPzllvtaqWNnNhruKMw7mQYrGNG264kYMPmcOcI4/hiDlHMXfukcydM4dHHn0cgN/85ncceeRc5s07mqOOOppj5h3DnMPm8Oc//omord0KGLu0KLNnTOWRMhivKJZKkAixmNsvjrWGqe17AkjiFk6gWhnh5MUL+dQZnwBg8+ZeLr3kh9RrdYO10qEqnjn8s7+due9VGbf4rdPKLxiNH3XUPL74pfM4Zv4xjJSrAEyftjXz5h1FGLhc8XJVhhOxGoaJ4AgptY3i3/++k7lHzOHII+Yw94g5zJ0zj7lzj+CPf/wjQQD33H0vhx16KEfMmcecI4/iiLnHctjhR3Hj7/9Iqa0jjaFnMHOZIMjFnc4881O88vJSnn76CZ5/9ikefeQhLvr2N2lvb+Mf/7iVs846m409PRRKmqmsUiF93UsOW3Ol2NBn/DlHYF42NR5y/D2nmJpHGEFoJXGaH6D82RcvVgGT8gTgpJNO5IEHHuDee+/k2Wee5IwzTgeg1UrAipwniYUsEqWDRDTpyONFuVIx4UrKXcTXUYW07FqS+IxNvVLOLJ6J+o9LCK14ZZIkxIm6ACU1EVMwmhMhe1e9ADpgZ0VulVMFJIkSn76f0xAsmSRJS0hpqrf/7s1dZ2cyJaK15PDWgQlCB2mafuA1EdOOE/8s3vdrVmX6nj4Xm5WY4of97rUp5wWhvmQuWLMA43ytOgW4f17nYULVmFZ2hI7X4DWN3DOguNmgXh5gStcEvvI/F3Lnnf/kC+d91mKZcN11v2PZ8jcpFouICI1Gg912241ttp0BwIsvLmXVu+/wyquv0t7WxiEHH0RcqzJxwgT22H1XAFavfpv33n2Phx58GICFCxaYC00/ajD6GIXBHC1DKbGQxM6AkWlPhWLET396Obfccgt33vlPDjtUs9b+9Kc/8/Vvfp1m3FJXQs6VLQIkLq3bHEYh761Zw+p31rD67XdYtWo1K99axaqVqxgaHAKgWq2xft16ujdspKdnM5s39TEyUmFwaNgEpFl9zuFS5Un9LM7puEXguPnz+e11N3DLLbdy2WWXUCxGvPPOu5x77hdY9tqrtLW3K345p24uSwzw8YJAoF6ran3AyjA77LA9X7rgfBaccDxjRrfjnBA4iJstBZHFjPUyxpIkGmPxCqThS88mteIBpk6bSlt7J+KwmFYEQUAhKqQKlWarRZqgoCuFoK4ySBgYGKRvYIje3s30D/TT299L30A/zZZuNRgeHmH9+vWsX7+O9RvWs3bDWtZv3MTAsFogiqbZgagOVHAZw0sSSechSWJHx6hFJnFWyMAXDJYkJnTwzW98lW232RqAhx/+X/7730cYM2aMeX5U2QzQ45xC+w5GSmLr6gdo8NGvjlNP+RhX/PxK/nrTnzn/vHMBePbZZ7nwgi9TqVQIokB5TBzjRF2+ut6WNOMcvQN9bNy8iU2bN9Pf30//4ADDw8M0W7rJuNlK6OvT+5t6N9OzaRObNg9oMXRndRr9OiSCi5M0jui9PHrpCSXFKKS9rcD228zgsksv5swzzwDg+ReW8u9/3UUU+SK9WwoU/7dX/pUvK+OPSkVzI6cLaX+aG9xbogSION1uk/g4GZlL1eDqlQx/JUlMs6l00GrUOeMTH2fRwuM55JCDSCzJLHQhLlG68zRFzshRtDJBmf6rPMih9/yz+qjRoL+R97mqxuOD6dYhWdaKoJaUeAbv/MmzljFovNqZNZOkAsMEjPWTxNkRI56glanZBHICyZY8BWD+SoVoXrilxLvlc4m5IQOLeygg7fecwAKz/HKL5i//ju/Xfw8Cze7zv6Ww8QLUYFNoK1EsaT20clm1WZ2d6L+JIyqUaB892uJWMY1GjVplkK2mT+HKK37GosUnkCQwMDjMyy+/QhBpOrXEMaNHj+Lwww4FoKdnEw888CCrVq1mp512YJdddqZWr1EI4CP77ksYhqxbt46nnnqK5cuXM2XyJA46YDbNRs1cYn4OPhHIkB8vHAx3/P0cbEBoby+x22678+Mf/ZBJkyYA8Kc//oUHljxEoa0jRWZdPrPmw5DEQa1a5fOf/ywvPPsor7/6HK+/+iKvv7aUlSvf5JxzzgTg46efyoo3l/HyS8/z8tLnePnl53l56TNcdunFaYVu8BaE4rZnxp7Jg+4Zg4RiIeCCC77ER08+Gcx/f/lPL6dWb5hVZqnVgcO5nFvaaYUCiGm1GrSVQi675Pv8/Kc/Zvy48ax+5z16NvfjIo1NiWSWLSh8xRRF58y74QJasfDa668BUCwW2HefvXGB1scMw0iLJbuIph1sG4TQ2dmZMrTA6FRMcavXa1x44Xm8+vJzvPzyUl556QVefnkpr776MvOOPBIR4fzzz+WtFW/w2isv6efVV1jx5mucf94XaNa03qmPe+Xpp7M9q3NZrVYV520LhYgmgpHzxiSJT7GGVrPODttvy+WX/5hiIaLRaHDFFVfS3d1NoVjUk6j9JWo6ePh53uJxMFvbbGyVSplWs0oYwLe//U0+/OE9Abjzzru46aa/USiWMn5hVlkiseUHxDSrI3zi9FNZuvRFXl/2OsuWL2PZstdZueotzjvvC7RaCR//+Omsfmc1r77yCq+/9hpvLHuNN5e/zJe//GVq5UpO4OR8GTbW/KXuNt0H2Wo2qFZGkKTFcfOPoaOjAxHh+Rdf0PCGvpEydDxcPT8RAUkIQqg1alxxxZX854EluDAkLBRSN2Cr1aLZzB+zo/86a8PjeUdHO6EZIc6pp2ILN7i5fB0xjXqND++1B7ffdjMnnHAclUqNtevWIy7AhRFBUCAMCkRRgUazmc5h7Nixpm96dU+t48C8hfm+giD4/2UzZlJW9EkSM0X1d0NgpwwZA5qglhAYEoClQzvwJf1zrpkgTRIy1m0CC0sD1a7NCew/XjDlY1p2X7MuM2RIPpAen7/8AijzzKwIf4m977UTMcvJP5b2Yu369l1eCHpCNesxj6bOOZIkprOjg3HjlbFv6tmYvqOMTCi0tfHs8y/w7W9/l57N/USFknaZ6IbK9vZRzJkzhzDU96pVLYKrH0er1WTu3LlgSPr7G/9AtVpl7twjaGsrESctmq06H/7wnkyaOJF6vcGNN97I0PAwhxxyMFOndhE36wSWmCDedZNuTFdFONGJmyWuROl/d04rZCdxi2plmIMOOYQzP/XJVKhfdeVVlEdGtog5AbhAM9IUBxImd01k51k7svXWU5mxlX6mbzWNiRPHg7ndZsyYxlbTJ7P1VlOZMX0K224zna5JY9NsSDFyAE3G8FcixkyBOBZlHq0mSZLw9a9/la230v1dd993P48+9iiFtvZ0346k65+1J/gtDAkiLWrVYZCE1avX8NGPncG/77qftrZOxZgtLAeP89amCOAoltp4f+06nnpa092nTuni8MMPJ4nrlrrs97mpNQXQ2dnOhIkTSBLdwiJOUHIyF1rSYvy4MWw7YxrTpk5k6pQJTJ08galTpjBqtO6pGzW6g8lTupg6eSJTuiYyZfJEpk6ZxLixoyx1O8GREPjYB7q5dvyE8RRMEPX39ys9WRzYicVbLFkpnbjhfYAqL4sXL+L003Vj/cqVK1m16m2KqTDzSC7KRA1nQgea2GLbRJxa/GFOARURkrhJvVph6pRJfPH8L1iMTvjlL3/F+g3duj/P8zXLeBLRs+fiuMWYUaOYue0Mpkzp0rjQxPGMHj2G0WNGgTH6CRO6mDK5i6lTJjNtShdbbzWN0aM7FEZO9/KpYpjxC5dauX6wul7OCUGQ2CkfwqjRoykUVagniVX6t3a8y5WUV+o7fq+YiyJWrFjFN7/xPR74zxKCIKBYjJg0SWOt9VbM4NAQOOysNtsYTUKj2Uw3VHdNmJjxZ1uPlCejSh5ihoUTWs0mjXqNUqmNa6/7LV+84Cv0DgxRKOqpFf5YmeHhYdvkD9OmTwNUWdFmTH4YI/YCzNNKKlv8IHT+mRURmJDxQE+cqCksWaA1vyCKuJIlToilyVr7iWmGiU00ZYr2m7favED1bWLjcPY3ZEkZ/soLqZRAQo0npILNj4tMAHox5YVyaG34eUnOpYpZYFuMwwSyn5tDTeAgCEyjMWIX8Md7JInQVmpj5520Usfq1W9r1XSzTgIXEhbaeO7Z57n88qu4/sY/UGgbQxBGqcsMIsrlcurimrHNVlukxzZbTfbaaw9mzJiOiPD2yrdxzjF37hHEEuMCaDYb7DRrJjNnahbc0pdeQUQ4/LBDGdXZkboWIskO1wyiLPtPtViNdeWVjAx2qtQEgJOEuNngK1/+MttsMx0HPP300/zlLzcRFjsg0L07qb7qt14AEmsqftKKacW6ty+/R0pQJiVJiySuk9jpvLEdXGmcAdJzmxKPBaZkaZdxq4kT9BiPZpO9Prw3n/rkJ3DOMdg/xDW/voZGvU4s3vtgSp0Hu9NMQXwGWaJrGRVK/OKX1/Dqq8uoVeu2ncHvZzPccjYW0HixC2nrGEUzFn70o8vp6+0H4LOf/yzbz9xBN9D6PiUBAtatXUciMGPrGUycNNFiIWbhpa7HgCTRig0NO2W40dCTzuNWtuE7SWKk1aDR8KdQ12g2qnqKsHlPwGWWgXMICZO6upg6dQqtVov3338fUj7ghZ7RkfWDJcgkCbhQa6YWopDvfe/77LarusDtsVxyh8LIWTV5DOeUpgMLZaD4msu+DAK13pyDarXMSSctYt99NOt35arVXHvNbyi0dZjA9Qub6MepIhDHDRqtKs1G2U4srwJCYLStIYOYuOW3jzRpNup64GQAgW1aDgJV8NU6SbXQdKxhFGZhkyCi1NZJVOzk2WefTZNNdt11F4KgaHxF3ej+8jzLexEScYRhG/fd/wBi8V0RzVbfd9+PAFCv1nnk0UcJonbEuVSJb+8YxWuvLaO3bxDnHB/a/UO6tzW14HJJPijNe/wIgpAwLFAqdbDm/bVce911LH/jTYZHKhrPxnDHhaxdt55WHBMEju23317bCgLCoJDmJWCxUcUZxW/dbWt9+0E4VRZTpBNj3l5z1ttZ3MzlY1I5g94LkJSp2cmh2XS95qPv+L9RPE0BpAuebcKOoixA6Bmnn1TahiUeOBM6zgu41FzdcnzOiAkvpOx30GMiUmGdi23538kxbn8vXVynRONdWomoVWvTpFgsss+++wCwauVq+vr7rS3d9gCkm49vuulmnn7qCUodEyh1jqOtcyKvv/4SN998CyLwod12Zp999tbinKbZJ60mE8eP47DDDkvHusPM7fjQ7rvZlgmFW0d7W7rfDNs4euCBs2nFLcQ5QqvwEeA0lbtQIGnp+Mrlsu7Ut3JZukcnUnecJTkMDAxCGOnJws0aW209nQu+dD4AjWbCFVdczSsvv0SpbQwuzDwCqpEG2rMpNZogZAPNPMqqOad7+AzmPhnAYKj4ohVMJPG4UGBwaJBaTZMrhkZUKw0CB3GMxE3O/vTZzLSU8f/cv4Tb77iDtvYxRGGBMPR7/bQ1F4S0tXdQKLYTFtooltpp7xjDC0tf4b77HsA5GDNmjDHUgEKhmAkloFBqo2P0ONo7RiPiePrZ5zn77M/w5z/dBMCJixdw4YUX0mzWDM8glgRxWr7rjTdWALDPPvswZtRoU3I1TZ0cjgah4r3Sr7qOvZsudXsmMeD06DFEd1c5Zbie5tXlr25XEFrNBl0TJ7KTKWlvvrlCq7uktGWqShAyYq71keEyYbHD4jABgYtoNOrssOOOfOtbX9ex6KtKpxazDcKIIIxoNDSpqFyv0Wg2cWG7eQtCoECt7ktE6f6nKCrinCNuNRk9qoMvX6ilwgB+97sbeeKxJ+kYM8ZOrFae55wqAHie6GeSJuxkvE6zIT1sVOlXfIwUr02gqnWvMU1cBKEdwWJXvdaAoIOOUWNp7xhDpVbn+t9dx1VX/ZIkEaZPm8L8+fMVJkEAhNRzuKQCskh7xyhK7Z20tXey4s03ufmvtwDoWW+iSs3JJ57E+HHjSJKE3/zmeh599L90jh7PqDET6BwzkTffeptLLv0hlUqFWTvtyKGHHqylswyfnAtSngVobDnqpFjsoFBoJ4pKEBb49513s25dN52jOlMlRBdWx//WWytoNmO2224G226zLSSJ8hTjpR5nvUGUh6/XkzJuLeo6ICdgtmDOmAtSdA9Z+htZcA5j8IEJEG9pOYxJeTemPesH5ZyWi3EYBuk0U4GUjsWG6i0rZ/04E1C+nJAkSUpIgXK4FBCiHF/HZxqeszn7DEjfnw7H5mkH8GkKtb7vRKtjpzBK4xNZO1pKBtA8vVQ4z549m/a2EuvWdfPasmUUikXtX2IgTpWId1a/y4knf4yPf/wUvvrV/+Gssz7JcfOP59VXljFhwji++73vsPW0abSaTUjXRGgrFThwtu6qB9hjzz3omjiJuNVK051brZgDZs9On9lppx3YddfdaDZbWi3cuz9CR8+mTfzg+5fw/PMvAlCp1Pn617/B0heXEpWKVCoVfv/73/HMM1qloFZr8OX/+Qr/uf9eisUCDiFu1jjllFPYe2+NV6x+511OO+10/n7rLTRbMYEFl/MBajG4qjWkjFMSX9FBYzJOdO+Mc1qFRBFfXdzKkMz9bAcaAtxzz7+57NIf0jDhe//99/OP225VjdRpjbkdd5rF2WefDUArTjj//C/xne98i82bN7N+wwau+sUvWL36HQDeX7OWk0/6GPOPW8DxJyzm2PkLOeLIozj99DNYv2ED4GjvaAMXMDw8wlVXX82qt98Fi2t++jOfYfGJJ7HoxJM4Yu5RLFywgL//4zbaO9v4+te/yg2/v57O9rb0hACV6AGFYpHu7m7efPNNAA4+8EAKxSIgGmMwAMRJYtqtCqXUxamSgkCJGMCsb3VR+Th5kM8OjDUzTUMJSlfNVpPxE8axr+1fXLb8DTZu3qzljxKx04YDHv7vo/z5pr+Cwfzyn/yQcrlspaCUFhu1Mqec+jFOXHwCAI16Q8MdTgVBqxXzxz/+gccffwyA/v4hLr3sMh5+eAmFYokgCHnwwfu53TboiwjX33ADSx58EOciwiCkXq0x/5hjOfKIwwHo6+/n1NM+wa9/9Wv1J/mKIiqBDY80IYJElfQkaalLznAqjlsq5Mxq0WoYtndWdG9kol7LlMOFQcR/H36Y31x3Hf666aabmH/sPE7+2CmcsHAxhx8+l3PP/SLd3T1Mnz6NX/3qF+y5xx40azUQ4c5/384f/nBj+v7f/vY35h87j/nHHc/xCxZy1FHHcMwxx7FylXpoVBxr5vO+H/kwl1zyfUZ1dvDOO+9y4uJT+NhHT+OrX/0mZ37qLOYdNZ/HHnuSadOm8rOfXc6MGVvTajVxgfLExx9/nOuu+13a9y03/4Pj5h9lNLCAeUcfzUEHHsTFF19KYolxURiaK1Tjvs1GjZdfehmA/fffnymTu9KM39jOdQNzU5tM8MLUG0sA6REwrWY1J2FV4oEeaY4JHkWmzN8rXrAYwmAanmfoSAIuRHxJJ2dtmyDyQk9ygisIbEdfOhIbvL+8sEs1PpMV1qYXKtj48GZ3DgD+HbEMGt9v2p4HlB+Tfy8/LmO03kpMgSsC/sTfQJUAHIjFBH3bkyZ18eSTT7PirZVM7uriyDlH0Go2dL5W4mVoeJi29naajQbLli/nxaUvsnLlSkaPGsNhhx3M1VdfxQnHzader2qAPbTtBUlCEIQUiiVeeuklOjo6WLTgeA45+ECSxAqSOgiCkPb2dh757yOMHjOGM8/4OIccejDNZpMQFQoJUGor8cyzz/PLX/6GMWPG0DV5EhMnTqBn0yYqtSrHHnsM77z7Dhf/4GLCsMD06ZOZ3NVFrd6gVi0z98i5RFGBOG4xYdJkJk6cwIoVbzJ+/HgajSbvvfcOhxx8CF1TJiNW282pty1dw+xSi+uuu+/l+edfZPfdd2HxohP0BGe1e5AgVM1ORDeVO8t+RfG1UW9y2WU/YWPPZrbeahpTp06ho72D1159lQMOOIBp06anaeN77LE7r7/+KqX2EqNHj2HZsuWMnzCOvv4Bfv2ra5nUNYkpU6cyYeIEBvoH6O8fYGBwiIGBIYYGhwmDgMlTJrP19GksXryQHXbcmeeef5bf/vZ6xo0bz+TJXUzumsjw0DA9GzcyODBIWAjZeZedOfXUj3HVVVdyxic/QXuxSKNVx/kYkdFksdTJnXffxZ//dBM77rg93/3ed5kwdoziklNhJYK5I02yCyl1ZF6KkFtu+Tsr3lrFAbM/wlHzjtRivmbZSZptq948nCqxiRXTTiQhCguM6uzkttv/yfr16znkkIOZtfNOtJoNCoUS67q7ueyynzAyUmbK1Cl0dHTw+mvL2HPP3dl551lI0jLFBUpt7eyx++688MLzjB07muOOm8+228wgjEJefuVVfvbTn9Pe1sa0qVPpmjSRvv4B1q1dw8knnczQ0BBf/epXGRopM3my4mIYBLy/9n3mHH4oo0eNJk5adHS0M3Pm9rz22ut0juokSYQ3lr/BvHlHalHoOCFCo65eucUOrHXmMYiKRR595DH++8hj7Ljj9nz0oyfRqGtBbvNppHxF76C1UF1AGAXEAr+97re88uoyZkyfztQpU+hsb6e/v5/e/j4GhwYJo4g99/gQZ3zy4/z6l1dz0AH702ro3rWBwSEu+vZF9A8MMn36dCZP7qIQRfT1bqZ/YIDe3j4GBgYIopBpU6YydepUTjhhPrvtuou51oWDDjiAA2bvz8jIMNVqjeXLlrN06Uu8/fZqJkyYyPHHHcM1v/4FBx84m2ajqvFS54gT+M21v+OVV15j+vRpTJs2lVKxSH9/P+VyhaHhESrVKvVanfHjxzFlyhT22P1DLDzhBDra2hASomKJ115/nauu+iX1Wo0vf/kC9v3IbFqtuqKrYWpqVOT4MyhPDpwjKnaQnjRdr/SqYEnETo6GRFSYibnJnDNGaQJOjKBUIKB+YHSxVZUxpo9qNC7QxcwLniTxz+oAA3MtegGUxrqMGemGbot2eetMaSsTqOZ6yRi7avYY8XrhRd7y9O6THKB8e74//44fn7fUnHOWdahjDUPtN7FxqTsmF6x00N7RyR/+cBOfO/d8ttpqOkv+cw8zt9uGRqOKQ4iKbYRhkb6BQTb39tLf30etVqMQRkydNpXttt2OQqFArVa2Ncmtha0dBGzY0EOz2WRy10Q6OttU28bDzeFcyMaeXsqVCjO2nk7JguIpCzO4tVoxmzb3aTq6ZZ4GgWP0qFGMGzeWVhzTu7mPOPGlvXT27e0lxo0ZrRYs6i4IoiJr167XvVtAR2cHkydOIHQ+vduhsQpb90RT1r1FHoYRDyx5iP/850EOO+xAFi9aQNxUC8u5gAQf57PL70+xMTkXUq7UtJizC4DA8FOYMG4cxUKURnvDMGKoXGZgQGMGksDoUR0UiwVL/1cLKY61BBeoBqlrYd2TEIUR48ePp1gs0Gy1GKlUaTRb5i3ILPkwihg1ahTjxo2hUGgjliateh3dk6dKiv4NYaFArd7ilFNP5f77lvDd73yLy374Q1q1EVqthtICGkRPxFL/DbqYZwFngiqIuPmW23jppVc4at4RHH/8cTQa1cytGJgEQ2PAzvDfwzQRzXwtFts448zP8I9b7+CE44/ltttuplmvmUIBw0MjxHrkMc1GkzAK6Zo4nlKpYGxAY19xIhSigJ6ezQwODzN1chedHSUAGq2Yzb0DunfJudRiH9XRQdekCcQi9PUPUq/b6dVG16WCnsEYBH7LDARRid7+foaGR2g1GkQBbDV9K4pFpecATXZSCxZip7FkZ7QRldp47NEneOCB/2W//fbhpBMX0mw2lEd6GgPjS0HmxTI+E0YhA4NDVKt1tQAtBKDxXt0gXioVGTd2LMVSG626xi7BDAkJ6Ont+7/FefH4Z/kCovRTKEaMGzeaQlSwqiMOxFFqbyeOE95/fx2bejZSqzcoFQtM22o606ZNw4lmwqYZ7ZIQuAJDw2Uq1RpRsaC46byBYnIjB39xQiGMmDB+HE600EbU1skPvv8DLr3sx8zefx/uv+8+xo4dS6tVS2P1iu1mHOW8WwoErZpf6pyUCbNmtQ+xisme2SfGSJxzJC4mdFlasRceCYrY3npRa0f7CYLA0pdVXmHV7nND0Su3uPnLmfXlgeK8i9IDx54RI0zP7DwDDALdt+YBrMSdSXo/5owwtZJz+t3P3WJzYS7NOW0zN1Z/ZbBIyd/2fKhJrHNx4CJO/uhp3Hf/Ej75idP4/fXXEbfsIFJj2mFUJAwLqmA4ZSRJrEFm7/ZJEcjPUSCmpQkIkQZa41aTOIkRh24gThKC0EESUCy14cKQVq1OK2mmx5/j1zjRzCotE6UuAkMbkiSh2VTBViwUjWjNPekckrSIm3FOmOka6lHtZv3FMa24oaV+zGkTBlrLT0SL5KoFEaq7KoFCQTdEJ3FMs6mxEe8/V3yxyigeRjob+79L5wJmlYtmZbZaTSUe0wqt4S2rhbd0E6m66hyJOHPTJbjAFC07ZkPhqMpes9VEYu0vKhQUFuoh1XGJFhvQ6iBNdecFykR9uaMMz0JKHWO57jfXcN75F7DXnrvx0EMPMmH8eJJmXYVXoHsBrXGwPZSeNpxVuohF47neRadbGlooGCy+HWT7usiVZlOF1+glTiiV2nhr5WoOn3MMm3v7+PWvruALn/8s1eoIzkGhUCRwmpnoBWTcaiCSpMfO+DkmkhBFRXCYG92SVFxIVCiaIpLxgCRpkTSbJAFEUdEKgOu6JA6k1TJBkFeQhbBQsIQEFQTNuh3No5RrPMj4hNMq8qrkK9yiKCII9YSEZr2hbm7b0G4dIZgwQ5Wd9DeHutdzirn2nOCcloASiTW0Y8UnnNGWNU1UKGplGs+WnCp/GX/SJBYSELRIusQZ3Dwt+4o2YRjq/NAsTt224vmBtqeoHWhJNOOZ4tCzM5xmIAImwJ3KTEyhb7VIJKbYMZrnn3uOY46ZT7VW49Z/3MKChSfSqo0Yr1SYxJJYFf+E0FyU3ijRuULH6Mk5y6y6CZIAcTGSONtwmSVneKpQpqzOxBSJddj+P71ENHVcNB6WiAqDbJNwBkx7O9UCxVx+njmLCRIMpH4igMZUcoJJEVT7dybwxAPBv2cW4RZWoL3rXaixF5AeydJ5Kik4E4zYeNJU0Q/0jc0Nb8XadyGmrdTByrffZeHCk1nx1kq+951v861vfY0APdrBucBgYXviAmMiXjDkkN+RWNxRiczDNvsXc/1abE9AgoSQwLLDNMakpbm8ZWbwFK+B64wS1N/t0I2gWrMvW1dFBJfWAA2SQM8vMiJUFPAMUYnGJypo2SNl4Jp/kG2Ox+acWOYozqUFg/1vfs74jeupHmMZrJYAA6LZoYHiaLowNsY0+UTE5ua3WljmpSkl+odlRTpJNVffmL7vcUx/E0tP91D2bemaBqaF+rXTtiQLKuOCiEKhjfvuu59PnfNpSoUSt/z9r8yZcxj1StmYh2riiWiGcUov0rL1tLRniyfqOH3Ks1mYoiXAkiSjC40fZVp/EGQJNqo3BnR0jOZvf7+Nz597PsVCkRtuuJbFC4+n0agoUydTlpxP2HKquCTeA5Jo4WldR8ULRDfUB4GOVSEq5vlQnJAExOI5JKL5BYkXSKZMi61TIiTOIl5iSrL3WjhVXhwxoc05QQtCIHoEUWDxQL9Wfr2cy2/oTrRSvSlbuASX6PjFmXJmVkqS6NwyZcpwSKWQrlGgRRUU39T4yBBX+3POx5cymkySVorvhqr6ry+5ZvFPTwhqtWc8z9lWnMC8HmL0q7RruOGFmRk72o4jcJEVzxD1LkhAWCzx7nvvceqpp/Hi0lf5zne+xWWXXUarXlVFKu3XQSwql4w/e2+YMx6bxDHtoydnMbO4WbWBaz0yUCYWOCV0pUmdsPIKm4R1oHRmjCRlphrfUGTMGI3/2Pz1+oAAyD/rv+eREY/0hoT5K//MB99P7/tl+0Af/nKA8xqU/9hleJRentCzPknjhfm2FZam5aJ1JKdMnsL+s2fz9NNPccc//029XuOwQw9J03h9CndgwsgjuDNh6uekIFatyI9OBYUOKPBWq6WyBikT9+ugEEnMRWYGgVUQ0CaV0SpMgsDShwNRiDhNPU7n7/QATyVUXSNDK2NoWIq9tqfu4+ygPW+JZA0qjqS3RMfrmY9XE5xV8vexnsDKfGHz8fgc6ITS9fEL6vBw8cJbmY3C2CZm99Okk/xmbMnjgzLYvKWexpGtnRRXRdJj4ZVBoEkIgloMCjBcEFAsFnn44Yc57fRP0lZq4/rrf8MxR8+jXh3JTrcwqwUTkh5y2lVglkUG0iDUbEb/rCbRYIxJ4SsO21yoSxJ6ga53bN6OuBWz5157MnHSJO65+x7uvvc+Dj3oQGZuP9PmYww1UB7hYeyxUHmBh5/ioi6g9uXJ0bNahbEKXn8puPT3IM9vbLtIqvBZg7aJRAWRC5SH2Xl8zuBGoDDyPMMZDumaK6ww60tlpfXp8SgPLx+qSQ//RCFvP2dro2eipX2htOHnHhheeFhpPMvcmemqey+Z9pnyvDzv8ziWwzXFNwz2pHF0sbmLKYFhaHsARelS4a3GgnjFUzEIEggLEWvXruOMM87g2eeW8qULv8All1yMk1iTS5wJTKNB58MEGPxsTZwiCaFzhMWOXDajIVKqIPtJG2EGFg/D7qdM1ASKB4pqaToQyWX/WbMpIP2iBrmajH7AeOZsH+y+78OnzauWbXvKcu37dnWRNbXY95kuZA7J03dtM16qhTqnDMV+9+/nLbk8LPSVDNCCxkJ8VlOKqaZNOueo1yvs95F9+M999/Dpcz5FrVrVvTx+DNpR2nbKO3KErVdGdMow9PKwVZLyrgB9N10DL6S2WB+DpbO2PR4EWqHeMyWvhaYZhDm/Ofh0b20zsbpsvh9186nlnMS+Skw2DhGxb5aNmOiBgfkx6mVzS8/Xy+arGVQRmTNP193jnQ7ToOXUg+BIdMtSSkzZhnFNB1bGoP1bynWKMnrfOUcQqhvRfrB5ZeNQhpCtLTliFYw5eIZrbxhYcU449tgjuf/+u1m0aAGNahmM8WtTFofLeUKUNlVQJymSaH+6l8cfbhnqkS1OvQIp7Rk9bMFMbE6eZpTuhLjV4Avnfo577v4Xcw49SCvdmMKi7xi+aEM2u2ycnmeIZRgnFqvwS6VxIGXy3npMaw3aOoqQKmviCSNnAevy+ZM4NLNQC0nraPwYE6MbrJan/uaFnilMhs+BD0VgVgzqdfAWkL6u7llvRXm+kAqfdMHN+vG0aJePGena2n2Xfbzi4Yti6zz8GHXMpgamdOz5hOebGS2bcHbZXjZHNqYteAGKF4gVDzCFFvQcylRBFKjXK3R1dfGrX1/J1VdeSSHQKjB4b6D4+dtu5ZyM8YMQkz8pDWUJIJtwoj5hHZQPYNpLWTPZGVImWPxvsU9HNwHnr/wgnBdkOYGWv5xJc/uyZZwqJzw++I6/xJ7xC549k0OSnGDzV2ICx1tPifUX5GIF/h3xBOGRysbgUvclyggDR2wHWyqcDPnMF67jUESIChHOQdyKEYu/6CPZfFUjUtCqwqT3E3Nb+THiGbC/nE/IsHEDTnWxnAspc4c4p4xUi3tmzWCCQNdCCTuw8+wSyc4GU6blmaj2RLoGCd5V5XKMOl0Lie0gQY3rxAmqmYm6GhxhGkvz7/h2UjxN4WSM2ooBiOE2qECUlDmZ2yXQMTudntX4DCyYrcToQh/Ly2ApVndRac4UANsWpXP2f+hPiYhmtImAHZOi8PD37cHcpb+HgJC4hMiKBidJQqupBXnF8FWrN2CCVWONSWJu6MBiKRLouFFBBqbI2oGUQajKGM6RtFSIBJFuQXNOGanGaUypdbKFwuCnUCq1ITharQaxbZfxv2NvJDht09Ou1+YNLdUEzuLicWIxSsBJoPEws3BA3YyIt95Dhav1mLadG4fL4Uu6puma2dhyPMmvZKZq6eXnpL8aXtpeQKcImj7j14r0OYFQNJZlo03bVuCk7xHY4VzGpwS1ctU9rb17Yb0lj1L813maAZFIOvIt1iYHE4env4DAEgG919vDyb/pnMaQ0zb9M3b5NXaBniIehkUa9bolrGnx4sCZTHGiRU9NBqaWFqReD8XghFJnVybMauXNaafOGLNOxK4ckuWtBsll+mXv60yz73qkjOTiU3rfmaZtbQlGsLYwTn23Hrj6jAmhVMPK4l8eZL6H/O8Y4QqZZZWIAsuhFRtwhqLGKFW+2T6nRKzoKBZTVI3FF4iNCrpHys9ZF9lw0C+goajeysUhRGGmTFsFnH83vxaYMEk3cOvbmXZixO5Rya+f6IDs4RywbTwZbAHbBKrxIe3fv+/Hol+1PWXMfqJJqsn7dxI7hRh8Zqm+H5sLN51Dfk1yfaXzsGw4TPh7YvF4J36sfp6esUNGsHncM4VNExyU0eNiPaNODGd8+4nTmI1TAe8SjfOpL8lW1Wmb1rtfPB2TpxE/RyBf99Ovn6ePFLYoM0rpLfFlj5QOA4+XIhDqjDz8fNukkNI+k3ROOp/AeesxSffleZxIFYZEGXcQKiwzXAwgFBJT2ATM3erMPYnCyZTbdG38cPz8/Lr4eGk6dtGx5PDN/+bXWv9VvHUOPWk8cbrCuWe0tUTFjylwImbB2Dpqyr0KSB25neNoSk4KV7/vzIy4DKsyq0mVSZ9JaBv+nSoDWoDdLFz/shistsDubA3BFAhnDzvMelfFU0NVApbYofPPxmzszd5VZQZEnzG82oJ+7HnndO0xtNJhZ4q7n6/nv7np5GZhPMmSOLwl7/mM8ilVArPyiZlXyfMYbSPDI0EII+XdxY5JeWXajmtx6grwL/kF9h34f33j//fyVlEmCOOWLyicR3htSAlLzWkFnLkUUg0CYlH3Euji5F0nKUKbS2WLCRtD9oLH/88DUD+6QGQeFPxIg0AXUvuWVCj7MQgqSIIgUOYkupzefeDMgvJIYh6WdB6Jd6cYg9cmvJltrrAcMvu5bWmFZTDwgszfS49u+QCSkjIQRUjxbhzTrFKY+nesbd+u+LHb3NJmMYsmNz4xhFck9kJC+0rH/YH54GGWflPQBkYEYlZt9qxXCnLvo7BMDIf9mJ1Ox3Ahl3iiak4aM8Tp+3p6gq6rc8o8PAycjxOJnvDg4aHrlxFdtgaeKWZjds4LW39lzN2l4/O/S/a7xa2tMQ/4tA/fhsf1AHXHe9xxLif8EsUp7w4XyyBNx+F0u4nWtdT3dDQaY8XWHVuCdD1tjSVR+heyv7X/7EpENxs7Y7AKL/0tMBrW9g2maYxO10n/VVj6Nc7gntGavpwpK4on2q7inK124AWad3FmSrzniSJ2OoAufNqedpHNTix5yPcv+gAYzasXTKWd2DgTS2zyY/dbVjIUz9YRP1cvwBOF4xb0BCTGZ/18sx8VxzyPdc6lypbyVYWNeS3B8Cpdw5wnK4Wr2zJpyROdp18/r7Q/ix+nFZzStbPfTRZkz5silihfxvBEH8g16lwWV9B2tiQQJWRbTHs/sImZAqIIb4F2Pa5B4wrpRMw3GqvvI4OSJOayMGHoVPB5jd5rVH48/uNrMdoPKXKSthyY1adXupQpbxWtAejrJOZggSUpBE4D50GQuWBdzs9MKqhNkuVg5Z9TvM/KhNlD6aI55/3rdoSGCQTfhnWqhxH679aPx3TxmpIhrXh3qR+rH1dOkATmughCS+ywfrbQ9H38zQSNbzudn20fEJu7pvlG5poy4WSFhD1M/Xi1u2w8+axXRLXHFPm3cM+oOy8dI6aUpIxUrXZyDNF5nPDuy/RexhAUJfWu5rup9WE7JUHUY+ph6/FS+zfFwgs2p8TodGApvvj9eE5vG44bA3Ca9BMYn1PlyWjDZSPWtdA5iAhhpHjl+/AwFYN/Hod8K4EplJoUYowJj5fanyRa9T6dj9G7T8HW7rIYCqYUajveCnTpc+RghS8yLs48FMp4A3tOK3Fk+KpzyPAyn+nsvDKZw890GJbMYl9MydKtHtouKWNMzNJ0vtamcxaTNfq0jF9PY3nlLjCPk78CY2+e1fg1ENGEJ9UH9J4LAsMRr5zY+M3Sc+YxSmJSXNSf1LL2l3/PwyAxr0gQaBxUfwN14WIu5ZxA8mO0fxPR6kTiFSSy/AjPWzy+iedZzpFlBWt2rXO6QT81KDyPs/Y83fh2dKmz0FXwgbwGtZJ1rv9n07QilqZre3RMG85J5DC3EdlbSn4QeWA4/UGB6RlaymztfXsuSV1DZgkR6DlhSUwU6qbKhEyz88iT9uMRxAM0j1wafEnn5JmP+toDy8zJbY5OL0Ek0Tpqdm6bpmJnzBg/Do94gfdFa9qoh4t/LnHmPrW4EDZ3XSw0Vd7DyBZZ4ZLBLT9HbP6SxkyyufvLuSwWKR94Nn3GE4FH4FxKtxKBXj5mqi8pfH2fYW5vX2BbHOI4VoUmxI6ZAOf0ANgUJ2w8ieFZOkf8gJ25+rSeoCQxcS5lPF1/IJFWSkTO+9x9ExKomuR0vXUKxjQNF9BNKSpX7DcPBw9XERUukDF09TuZMpRoxRtBeYTTjtJ1S9sT8b2RumOsD4duIvfWY94Fp20oc/Cp9Pk2/Xf/rN7HYpLal1hffi290Pc0no4zUZ6nCgh2ORXmxOputALMfj38u0mSqHtfefEWc/dwSq/cfcwqQmwdbA9a9miO0X9gzrpelujg7G9Ik4f8846ci34LuGbjyNOAGI06p/iTtyw0LpcpNILCC2fF4FPABXiEzLfv9IbO1xlGOD3YWB82L45TN6kq55lS6fdM6hadHJxAcdUMBJ9JG2SPGO5pna3AjllJ10A70LZysPL8nBy/9Ovv4ZKHJTYWfz+/1in8bSwpPKxr5+nI7vnLTyFwjkL7hEyUpwLIme/YtAC/IW6LTnPMOb3nNVG7lyELKVKqlmPCxQusDzB6ZxaQ90urxqBuiFSbz/VDumDZ6qREZWNIcq4u64gk1Qi8K1V9+x+cV7pQSaJ7KLy7SR9KAezItJjQeZet0wMo88+bIPNzTdLVMk3FkjlcoNlDHpbav7aRiRXfbKaBfnDRRZQA80zDa02Ssyr8s3m4eWHnn/UwS+ecR1Q/n1wMFOd0vS1lX8fo9GCgnGvQ2bMekSXVQLU/1VIznPIMIMghfSIWL3SeQBSHfVaechV9Wu9nuONhj18zp7ESr8dnmJU9n7o2MbYrar04pwzF0FT7sXV1fp2dWnralJhqrTju56ZwN2+CBCC5AI1ZvorPZrXbuLYYj2TB8xQPHFqeCYV5ipM5urLVsjXQv9PL2nQ2H0+nue7B44ZXmGzDrr/v8jRmf7ucMBWDF/40a+zQXv1xi7btBcNXSwzRBzNhYvwnDW/8f8bhyOgiW7MtadNeTP/2Cp41qW2ZqPLYpa4235fDpds8/g/A9H1nqe8CeIXIodmIqNKQCjIbZ34ear27FKc8Hul7BrfMPrXvyrO2xGk04cOsUt9WYGMLMD7h1MumCpDigrO1VFiaBW8wF3wlqBwftXF4uDjrS/HbYJ2Du87Jy4os2S8dfb6j/CXGCJOcCSiie6TSK8MQnXDOheZtB88YddBecpvJmltUyRMh6GbbgNQEFk8guX+1ny3f97GOTIDZWtpz/pJ0+IZ+OQBrW1hFeP2OJQf4dsUTgn5BLCnE95MKNecTSXxcIrOqErO8dMEymPs5eqJ16GC9Hq9fjamnyKMFTvMwxc/Fz9fShIUtreog5y7I38u3JYZI6ZiMAYq5bJReFG7q5/dMRD9RFGrFhLxrIqdEQBZDciZYPVIr7pmbOs4Q2r+ZJBrbCJyzlGDDsUTMaZ3NDXNFkXtf52JzzWWIBvm0antHGV+gCppTsRcETq17kfT4mXRagQ5G10jb97GIJLFxpIJY+xLRKuyeTBVG5pJLx5UpKfqOCUc/zUxuW/t4TAJj8OrRyvpVuHoaU3zRAWcE5PFUZ+7xJXM9+RvqXnKZgEl/0rXzeOiTRPBzAIOpZhMHOU+QEmVmGfnLpTEls+idU6U8xXxj/ul4tf907kY/Hi/Bu3ez8SqO6BhEsuScvLvLt405gEVyCrM17Z/MwyHxioa5nvXEeX02STL4ewGTH5deqvh7Rc45dYlqP145M+GS4pu+KRaTTi/Dm1S50kbSOadt59rw8VPPjwJPE3gcMoiIwcUrx/75nHxJh2Fw9s9hY0+SXKzfnv9/bt98TuuG1MkAAAAASUVORK5CYII=\" style=\"width: 304px; height: 59.4023px;\" width=\"304\" height=\"59.4023\"\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Desertification Susceptibility Index (DSI)\u003c/h2\u003e \u003cp\u003eA composite index was developed to integrate vegetation condition and bare soil exposure:\u003c/p\u003e \u003cp\u003eWeight Justification:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e\u0026bull; BSI was assigned a higher weight (1.5) because bare soil exposure represents a direct and advanced stage of land degradation. It responds more rapidly to environmental stress in dryland ecosystems.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e\u0026bull; NDVI was assigned a negative weight (-1.2) because vegetation cover acts as a protective factor that reduces desertification risk. Its influence is therefore inversely proportional to degradation intensity.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe asymmetric weighting reflects the non-linear and unbalanced nature of degradation processes in semi-arid environments.\u003c/p\u003e \u003cp\u003e\u003cimg 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\" style=\"width: 316px; height: 63.344px;\" width=\"316\" height=\"63.344\"\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cp\u003eThe results show a clear spatial gradient of land degradation across the study area. Stable vegetation zones are mainly located in northern regions, while transitional zones dominate the central steppe.\u003c/p\u003e \u003cp\u003eIn contrast, critical desertification hotspots are concentrated in southern and peripheral areas, indicating strong environmental stress. The spatial pattern is highly heterogeneous and follows a hotspot distribution rather than a uniform trend.\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe observed desertification dynamics are driven by multiple interacting factors, including overgrazing pressure, climate variability, and soil degradation processes.\u003c/p\u003e \u003cp\u003eThe results demonstrate that combining NDVI and BSI improves classification accuracy compared to single-index approaches. This confirms the importance of integrating vegetation and soil indicators for reliable desertification monitoring in semi-arid ecosystems.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study demonstrates the effectiveness of remote sensing techniques combined with Google Earth Engine for detecting desertification hotspots. The proposed framework is scalable, reproducible, and applicable to other dryland regions worldwide. Future improvements may include the integration of additional environmental variables to enhance model robustness.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBorrelli P et al (2017) An assessment of global soil erosion trends. Nature Communications, 8, 2013\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFakroun MF, Belaid L (2020) Wind erosion hazard assessment using GIS techniques: El-Mesran Area, Djelfa Wilaya, Algeria. Eco. Env. Cons 26(4):1555\u0026ndash;1562\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGorelick N et al (2017) Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sens Environ 202:18\u0026ndash;27\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHugueney P et al (2021) Topographic controls on aeolian processes in the Maghreb: A remote sensing approach. Geomorphology 375:107542\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSahane VV et al (2022) Assessment of soil erosion and land degradation using Bare Soil Index and NDVI. J Arid Environ 198:104685\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSidiropoulou A et al (2023) Monitoring desertification risk in semi-arid Mediterranean ecosystems using Sentinel-2. Environ Monit Assess 195:412\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Cities, Regions and Territorial Governance Laboratory, Faculty of Earth Sciences and Country Planning, University of Sciences and Technology Houari Boumediene (USTHB), Algiers, Algeria","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Desertification, Algerian steppe, Remote Sensing, Google Earth Engine, NDVI, BSI, land degradation","lastPublishedDoi":"10.21203/rs.3.rs-9680091/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9680091/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Algerian steppe represents one of the most fragile ecosystems in North Africa due to the combined influence of climatic variability and human pressures. This study aims to detect desertification hotspots using remote sensing data processed within the Google Earth Engine environment. The methodology is based on integrating the Normalized Difference Vegetation Index (NDVI) and the Bare Soil Index (BSI) to develop a composite Desertification Susceptibility Index (DSI), enabling the spatial identification of degradation gradients. The study covers ten provinces within the Algerian steppe between 2020 and 2025. The results reveal significant spatial variability in land degradation intensity, with critical hotspots concentrated in southern and peripheral areas, while transitional zones dominate the central steppe. The findings confirm the effectiveness of spectral-based modelling for early detection of environmental degradation.\u003c/p\u003e","manuscriptTitle":"Detection of Desertification Hotspots in the Algerian Steppe Using Remote Sensing Techniques and Google Earth Engine","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 14:30:59","doi":"10.21203/rs.3.rs-9680091/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5cae2961-1e59-4e8e-884b-ef6e4fe2b653","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67936452,"name":"Geographic Information Systems"}],"tags":[],"updatedAt":"2026-05-14T14:30:59+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 14:30:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9680091","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9680091","identity":"rs-9680091","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

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