Angola AO: Net Official Flows from UN Agencies: UNFPA data was reported at 3.413 USD mn in 2022. This records an increase from the previous number of 3.158 USD mn for 2021. Angola AO: Net Official Flows from UN Agencies: UNFPA data is updated yearly, averaging 1.760 USD mn from Dec 1980 (Median) to 2022, with 43 observations. The data reached an all-time high of 3.572 USD mn in 2013 and a record low of 0.050 USD mn in 1980. Angola AO: Net Official Flows from UN Agencies: UNFPA data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Angola – Table AO.World Bank.WDI: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO), United Nations Institute for Disarmament Research (UNIDIR), United Nations Capital Development Fund (UNCDF), WHO-Strategic Preparedness and Response Plan (SPRP), United Nations Women (UNWOMEN), Covid-19 Response and Recovery Multi-Partner Trust Fund (UNCOVID), Joint Sustainable Development Goals Fund (SDGFUND), Central Emergency Response Fund (CERF), WTO-International Trade Centre (WTO-ITC), United National Conference on Trade and Development (UNCTAD), and United Nations Industrial Development Organization (UNIDO). Data are in current U.S. dollars.;Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: https://data-explorer.oecd.org/.;Sum;

Database Security Solution Market Outlook

The global database security solution market was valued at USD 4.5 billion in 2023 and is projected to reach USD 11.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.5% from 2024 to 2032. This remarkable growth can be attributed to the increasing volume of data generated and stored by organizations, rising cyber threats, regulatory compliance requirements, and the growing adoption of cloud-based services across various industries.

One of the primary growth factors for the database security solution market is the exponential increase in data generation and storage. With the advent of big data, IoT, and advanced analytics, organizations are producing vast amounts of data that need to be securely stored and managed to prevent unauthorized access and data breaches. As a result, there is a growing demand for robust database security solutions that can protect sensitive information across diverse databases and platforms, ensuring data privacy and integrity.

Another significant growth driver is the rising number of cyber threats and data breaches. Organizations face sophisticated cyber-attacks that target confidential and high-value data, leading to financial losses, reputational damage, and regulatory penalties. This has necessitated the implementation of advanced database security solutions that offer real-time threat detection, encryption, access control, and audit capabilities to safeguard critical data and maintain business continuity.

Compliance with stringent regulatory frameworks is also propelling the growth of the database security solution market. Regulations such as GDPR, HIPAA, and CCPA mandate the protection of personal and sensitive information, compelling organizations to adopt comprehensive database security measures. Businesses are investing heavily in database security solutions to meet these regulatory requirements, avoid hefty fines, and build customer trust by ensuring data confidentiality and compliance.

The advent of Big Data Security has become a pivotal aspect in the realm of database security solutions. As organizations increasingly rely on big data analytics to drive business insights, the security of this data becomes paramount. Big Data Security involves implementing comprehensive measures to protect large volumes of data from unauthorized access and breaches. It encompasses various strategies, including encryption, access controls, and real-time monitoring, to ensure that sensitive data remains protected throughout its lifecycle. As the volume and complexity of data continue to grow, the demand for advanced Big Data Security solutions is expected to rise, driving further innovation and investment in this area.

Regionally, the database security solution market is witnessing significant growth, with North America leading the charge due to its advanced technological infrastructure, early adoption of innovative security solutions, and stringent data protection laws. Europe is also experiencing substantial growth driven by the enforcement of GDPR and increasing awareness of data privacy issues. The Asia Pacific region is projected to witness the highest CAGR during the forecast period, fueled by the rapid digital transformation, rising cyber threats, and growing government initiatives to enhance cybersecurity.

Component Analysis

The database security solution market can be segmented by component into software, hardware, and services. The software segment holds the largest market share, driven by the extensive use of database security software to protect data against unauthorized access, malware, and other cyber threats. These software solutions offer various functionalities such as encryption, access control, auditing, and monitoring, making them indispensable for organizations looking to secure their databases effectively.

The hardware segment, although smaller compared to software, plays a crucial role in enhancing database security. Hardware-based security solutions, such as hardware security modules (HSMs), are used for cryptographic key management and secure storage of sensitive data. These solutions provide an additional layer of security by ensuring that cryptographic operations are performed in a tamper-resistant environment, thus preventing unauthorized access and key compromise.

The services segment is also witnessing significant growth, driven by the increasing demand for m

The Database Security market is experiencing robust growth, projected to reach $2556.1 million in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 11.4% from 2025 to 2033. This expansion is fueled by the increasing frequency and sophistication of cyberattacks targeting sensitive data stored in databases, coupled with stringent data privacy regulations like GDPR and CCPA. The rising adoption of cloud computing and the proliferation of big data also contribute significantly to market growth, as organizations require robust security solutions to protect their valuable data assets across diverse environments. The market is segmented by application (SMEs, Large Enterprises) and type (Marketing, Sales, Operations, Finance, HR & Legal), with large enterprises and applications involving sensitive financial data demonstrating particularly high demand for advanced database security solutions. North America currently holds a dominant market share due to early adoption of advanced technologies and a strong regulatory landscape, but the Asia-Pacific region is poised for significant growth, driven by increasing digitalization and a rapidly expanding economy. The competitive landscape is characterized by a mix of established players like Oracle and IBM, alongside specialized security vendors such as Trustwave and McAfee. These companies offer a wide range of solutions, including database activity monitoring, encryption, access control, and vulnerability management. The market is witnessing innovation in areas like AI-powered threat detection and automated security response, which are enhancing the effectiveness and efficiency of database security solutions. However, challenges remain, including the rising complexity of cyber threats, the skills gap in cybersecurity professionals, and the high cost of implementing and maintaining comprehensive database security systems. The continued evolution of cyberattacks and data privacy regulations will be key drivers shaping the future of this dynamic market.

This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera (2020), with the processed data through September 30, 2020. The primary data for water year 2020 (a water year is the 12-month period, October 1 through September 30, in which it ends) is downloaded from the Argonne National Laboratory (ANL) (Argonne National Laboratory, 2020) and is processed following the guidelines documented in Over and others (2010). Daily potential evapotranspiration (PET) in thousandths of an inch is computed from average daily air temperature in degrees Fahrenheit (°F), average daily dewpoint temperature in degrees Fahrenheit (°F), daily total wind movement in miles (mi), and daily total solar radiation in Langleys per day (Lg/d) and disaggregated to hourly PET in thousandths of an inch using the Fortran program LXPET (Murphy, 2005). Missing and apparently erroneous data values were replaced with adjusted values from nearby stations used as "backup". Temporal variations in the statistical properties of the data resulting from changes in measurement and data storage methodologies were adjusted to match the statistical properties resulting from the data collection procedures that have been in place since January 1, 1989 (Over and others, 2010). The adjustments were computed based on the regressions between the primary data series from ANL and the backup series using data obtained during common periods; the statistical properties of the regressions were used to assign estimated standard errors to values that were adjusted or filled from other series. The Illinois Climate Network (Water and Atmospheric Resources Monitoring Program, 2020) station at St. Charles, Illinois is used as "backup" for the air temperature, solar radiation and wind speed data. The Midwestern Regional Climate Center (Midwestern Regional Climate Center, 2020) provided the hourly dewpoint temperature and wind speed data collected by the National Weather Service from the station at O'Hare International Airport and used as "backup". Each data source flag is of the form "xyz" that allows the user to determine its source and the methods used to process the data (Over and others, 2010). References Cited: Argonne National Laboratory, 2020, Meteorological data, accessed on November 17, 2020, at http://gonzalo.er.anl.gov/ANLMET/. Bera, M., 2020, Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2019: U.S. Geological Survey data release, https://doi.org/10.5066/P9X0P4HZ. Midwestern Regional Climate Center, 2020, Meteorological data, accessed on November 3, 2020, at https://mrcc.illinois.edu/CLIMATE/. Murphy, E.A., 2005, Comparison of potential evapotranspiration calculated by the LXPET (Lamoreux Potential Evapotranspiration) Program and by the WDMUtil (Watershed Data Management Utility) Program: U.S. Geological Survey Open-File Report 2005-1020, 20 p., https://pubs.er.usgs.gov/publication/ofr20051020. Over, T.M., Price, T.H., and Ishii, A.L., 2010, Development and analysis of a meteorological database, Argonne National Laboratory, Illinois: U.S. Geological Survey Open-File Report 2010-1220, 67 p., http://pubs.usgs.gov/of/2010/1220/. Water and Atmospheric Resources Monitoring Program. Illinois Climate Network, 2020. Illinois State Water Survey, 2204 Griffith Drive, Champaign, IL 61820-7495. Data accessed on November 9, 2020, at http://dx.doi.org/10.13012/J8MW2F2Q.

A novel subject classification scheme should often be applied to a preclassified bibliographic database for the research evaluation task. Generally, adopting a new subject classification scheme is labor intensive and time consuming, and an effective and efficient approach is necessary. Hence, we propose an approach to apply a new subject classification scheme for a subject-classified database using a data-driven correspondence between the new and present ones. In this paper, we define a subject classification model of the bibliographic database comprising a topological space. Then, we show our approach based on this model, wherein forming a compact topological space is required for a novel subject classification scheme. To form the space, a correspondence between two subject classification schemes using a research project database is utilized as data. As a case study, we applied our approach to a practical example. It is a tool used as world proprietary benchmarking for research evaluation based on a citation database. We tried to add a novel subject classification of a research project database.

The French database is implemented as a relational database that integrates multiple interconnected data frames. It is organized around four main components:

• Thesis Metadata: This table contains the core information for each dissertation. Each entry corresponds to a single thesis and includes details such as the title, defense date, abstract, and other relevant metadata.
• Edges Data: This table captures the connections between the other three tables, linking individuals, institutions, and theses. It associates each thesis with the individuals and institutions involved in its production, thereby enabling a synthetized view of these relationships. The edges data are provided in two formats: (1) a ready-to-use format with cleaned and standardized information; and (2) a more extensive format that allows for comparison between the original collected data and the results of the cleaning process.
• Institutions Data: This table includes information on universities, laboratories, doctoral schools, and other institutions associated with the dissertations. Each entry corresponds to a single institution.
• Individual Data: This table contains information on the individuals involved in the dissertations, including authors, supervisors, and jury members. Each entry corresponds to a single individual.

The data used in this project comes from three mains sources:

• Theses.fr: https://theses.fr/
• Sudoc: https://www.sudoc.fr/
• IdRef: https://www.idref.fr/

If you use our data or scripts, please cite the following reference: “Delcey Thomas, and Aurélien Goutsmedt. (2024). Becoming an Economist: A Database of French Economics PhDs. Zenodo. https://doi.org/10.5281/zenodo.14541427”

Nepal Net Official Flows from UN Agencies: UNWOMEN data was reported at 0.802 USD mn in 2022. This records an increase from the previous number of 0.769 USD mn for 2021. Nepal Net Official Flows from UN Agencies: UNWOMEN data is updated yearly, averaging 0.785 USD mn from Dec 2021 (Median) to 2022, with 2 observations. The data reached an all-time high of 0.802 USD mn in 2022 and a record low of 0.769 USD mn in 2021. Nepal Net Official Flows from UN Agencies: UNWOMEN data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nepal – Table NP.World Bank.WDI: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO), United Nations Institute for Disarmament Research (UNIDIR), United Nations Capital Development Fund (UNCDF), WHO-Strategic Preparedness and Response Plan (SPRP), United Nations Women (UNWOMEN), Covid-19 Response and Recovery Multi-Partner Trust Fund (UNCOVID), Joint Sustainable Development Goals Fund (SDGFUND), Central Emergency Response Fund (CERF), WTO-International Trade Centre (WTO-ITC), United National Conference on Trade and Development (UNCTAD), and United Nations Industrial Development Organization (UNIDO). Data are in current U.S. dollars.;Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: https://data-explorer.oecd.org/.;Sum;

Net official flows from UN agencies, IFAD (current US$) in Dominican Republic was reported at 51000 USD in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Dominican Republic - Net official flows from UN agencies, IFAD - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Public DNA databases are composed of data from many different taxa, although the taxonomic annotation on sequences is not always complete, which impedes the utilization of mined data for species-level applications. There is much ongoing work on species identification and delineation based on the molecular data itself, although applying species clustering to whole databases requires consolidation of results from numerous undefined gene regions, and introduces significant obstacles in data organization and computational load. In the current paper, we demonstrate an approach for species delineation of a sequence database. All DNA sequences for the insects were obtained and processed. After filtration of duplicated data, delineation of the database into species or molecular operational taxonomic units (MOTUs) followed a three-step process in which i) the genetic loci L are partitioned, ii) the species S are delineated within each locus, then iii) species units are matched across loci to form the matrix LxS, a set of global (multi-locus) species units. Partitioning the database into a set of homologous gene fragments was achieved by Markov clustering using edge weights calculated from the amount of overlap between pairs of sequences, then delineation of species units and assignment of species names was performed for the set of genes necessary to capture most of the species diversity. The complexity of computing pairwise similarities for species clustering was substantial at the COI locus in particular, but made feasible through the development of software that performs pairwise alignments within the taxonomic framework, while accounting for the different ranks at which sequences are labeled with taxonomic information. Over 24 different homologs, the unidentified sequences numbered ~194,000, containing 41,525 species ID's (98.7 percent of all found in the insect database), and were grouped into 59,173 single-locus MOTUs by hierarchical clustering under parameters optimized independently for each locus. Species units from different loci were matched using a multi-partite matching algorithm to form multi-locus species units with minimal incongruence between loci. After matching, the insect database as represented by these 24 loci was found to be composed of 78,091 species units in total. 38,574 of these units contained only species labeled data, 34,891 contained only unlabeled data, leaving 4,626 units composed both of labeled and unlabeled sequences. In addition to giving estimates of species diversity of sequence repositories, the protocol developed here will facilitate species level applications of modern day sequence datasets. In particular, the LxS matrix represents a post-taxonomic framework that can be used for species level organization of meta-genomic data, and incorporation of these methods into phylogenetic pipelines will yield matrices more representative of species diversity.

The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Water quality data can be downloaded in Excel, CSV, TSV, and KML formats. Fourteen site types are found in the WQP: aggregate groundwater use, aggregate surface water use, atmosphere, estuary, facility, glacier, lake, land, ocean, spring, stream, subsurface, well, and wetland. Water quality characteristic groups include physical conditions, chemical and bacteriological water analyses, chemical analyses of fish tissue, taxon abundance data, toxicity data, habitat assessment scores, and biological index scores, among others. Within these groups, thousands of water quality variables registered in the EPA Substance Registry Service (https://iaspub.epa.gov/sor_internet/registry/substreg/home/overview/home.do) and the Integrated Taxonomic Information System (https://www.itis.gov/) are represented. Across all site types, physical characteristics (e.g., temperature and water level) are the most common water quality result type in the system. The Water Quality Exchange data model (WQX; http://www.exchangenetwork.net/data-exchange/wqx/), initially developed by the Environmental Information Exchange Network, was adapted by EPA to support submission of water quality records to the EPA STORET Data Warehouse [USEPA, 2016], and has subsequently become the standard data model for the WQP. Contributing organizations: ACWI The Advisory Committee on Water Information (ACWI) represents the interests of water information users and professionals in advising the federal government on federal water information programs and their effectiveness in meeting the nation's water information needs. ARS The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief in-house scientific research agency, whose job is finding solutions to agricultural problems that affect Americans every day, from field to table. ARS conducts research to develop and transfer solutions to agricultural problems of high national priority and provide information access and dissemination to, among other topics, enhance the natural resource base and the environment. Water quality data from STEWARDS, the primary database for the USDA/ARS Conservation Effects Assessment Project (CEAP) are ingested into WQP via a web service. EPA The Environmental Protection Agency (EPA) gathers and distributes water quality monitoring data collected by states, tribes, watershed groups, other federal agencies, volunteer groups, and universities through the Water Quality Exchange framework in the STORET Warehouse. NWQMC The National Water Quality Monitoring Council (NWQMC) provides a national forum for coordination of comparable and scientifically defensible methods and strategies to improve water quality monitoring, assessment, and reporting. It also promotes partnerships to foster collaboration, advance the science, and improve management within all elements of the water quality monitoring community. USGS The United States Geological Survey (USGS) investigates the occurrence, quantity, quality, distribution, and movement of surface waters and ground waters and disseminates the data to the public, state, and local governments, public and private utilities, and other federal agencies involved with managing the United States' water resources. Resources in this dataset:Resource Title: Website Pointer for Water Quality Portal. File Name: Web Page, url: https://www.waterqualitydata.us/ The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Links to Download Data, User Guide, Contributing Organizations, National coverage by state.

A large body of research has demonstrated that land use and urban form can have a significant effect on transportation outcomes. People who live and/or work in compact neighborhoods with a walkable street grid and easy access to public transit, jobs, stores, and services are more likely to have several transportation options to meet their everyday needs. As a result, they can choose to drive less, which reduces their emissions of greenhouse gases and other pollutants compared to people who live and work in places that are not location efficient. Walking, biking, and taking public transit can also save people money and improve their health by encouraging physical activity. The Smart Location Database summarizes several demographic, employment, and built environment variables for every census block group (CBG) in the United States. The database includes indicators of the commonly cited “D” variables shown in the transportation research literature to be related to travel behavior. The Ds include residential and employment density, land use diversity, design of the built environment, access to destinations, and distance to transit. SLD variables can be used as inputs to travel demand models, baseline data for scenario planning studies, and combined into composite indicators characterizing the relative location efficiency of CBG within U.S. metropolitan regions. This update features the most recent geographic boundaries (2019 Census Block Groups) and new and expanded sources of data used to calculate variables. Entirely new variables have been added and the methods used to calculate some of the SLD variables have changed. More information on the National Walkability index: https://www.epa.gov/smartgrowth/smart-location-mapping More information on the Smart Location Calculator: https://www.slc.gsa.gov/slc/

The King County Groundwater Protection Program maintains a database of groundwater wells, water quality and water level sampling data. Users may search the database using Quick or Advanced Search OR use King County Groundwater iMap map set. The viewer provides a searchable map interface for locating groundwater well data.

The U.S. Geological Survey (USGS), in association with the Multi-Resolution Land Characteristics (MRLC) Consortium, produces the National Land Cover Database (NLCD) for the United States. The MRLC, a consortium of federal agencies who coordinate and generate consistent and relevant land cover information at the national scale for a wide variety of environmental, land management, and modeling applications, have been providing the scientific community with detailed land cover products for more than 30 years. Over that time, NLCD has been one of the most widely used geospatial datasets in the U.S., serving as a basis for understanding the Nation’s landscapes in thousands of studies and applications, trusted by scientists, land managers, students, city planners, and many more as a definitive source of U.S. land cover. NLCD land cover suite is created through the classification of Landsat imagery and uses partner data from the MRLC Consortium to help refine many of the land cover classes. The classification system used by NLCD is modified from the Anderson Land Cover Classification System. The NLCD Class Legend and Description is maintained at https://www.mrlc.gov/data/legends/national-land-cover-database-class-legend-and-description. The land cover theme includes two separate products. The first is a standard land cover product suite that provides 16 land cover classes for the conterminous United States and Alaska only land cover types and is available at https://www.mrlc.gov/data. The second product suite, NLCD Land Cover Science Products, provides additional discrimination and land cover classes differentiating grass and shrub and regenerating forest regime from grass and shrub and rangeland setting and is available at https://www.mrlc.gov/nlcd-2021-science-research-products. The latest release of NLCD land cover spans the timeframe from 2001 to 2021 in 2 to 3-year intervals. These new products use a streamlined compositing process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a theme-based post-classification protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and a scripted operational system.

Food and Agriculture Organization of the United Nations (2017). Food and Agriculture Organization Statistics: Food Security - Indicators from Household Surveys | Survey: Sudan (former) - 2009 | Breakdown: Income terciles: Highest income tercile | Gender: Female-headed household | Indicator: Share of Dietary Energy Consumption from total car | Measure: Number Observations, 2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. [Data-file]. Dataset-ID: 067-001-070. Dataset: Presents statistics for food security indicators by sociodemographic and socioeconomic characteristics of households. For definitions of each indicator, see the technical documentation. The time-series and cross-sectional data provided here are from the FAOSTAT database of the Food and Agriculture Organization of the United Nations. Statistics include measures related to the food supply; forestry; agricultural production, prices, and investment; and trade and use of resources, such as fertilizers, land, and pesticides. As available, data are provided for approximately 245 countries and 35 regional areas from 1961 through the present. The data are typically supplied by governments to FAO Statistics through national publications and FAO questionnaires. Official data have sometimes been supplemented with data from unofficial sources and from other national or international agencies or organizations. In particular, for the European Union member countries, with the exception of Spain, data obtained from EUROSTAT have been used. Category: Agriculture and Food, International Relations and Trade Source: Food and Agriculture Organization of the United Nations Established in 1945 as a specialized agency of the United Nations, the Food and Agricultural Organization’s mandate is to raise levels of nutrition, improve agricultural productivity, better the lives of rural populations, and contribute to the growth of the world economy. Staff experts in seven FAO departments serve as a knowledge network to collect, analyze, and disseminate data, sharing policy expertise with member countries and implementing projects and programs throughout the world aimed at achieving rural development and hunger alleviation goals. The Statistics Division of the Food and Agricultural Organization collates and disseminates food and agricultural statistics globally. http://www.fao.org/ Subject: Food Supply, Sociodemographic Characteristics, Social Development, Food Security

The Database Automation Systems market is experiencing robust growth, driven by the increasing complexity of databases, the rising demand for improved operational efficiency, and the need for enhanced data security. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated $45 billion by 2033. This expansion is fueled by several key trends, including the widespread adoption of cloud-based database solutions, the growing popularity of DevOps methodologies, and the increasing focus on automation across various industries. The on-premise segment currently holds a significant market share, but cloud-based solutions are rapidly gaining traction due to their scalability, cost-effectiveness, and accessibility. The IT & Telecom sector is a major driver of market growth, followed by the Government and Transportation sectors. However, challenges such as the high initial investment costs associated with implementing database automation systems and the need for skilled professionals to manage these systems act as restraints. The geographical distribution of the market reflects a strong presence in North America, followed by Europe and Asia Pacific. North America’s dominance is attributed to early adoption of advanced technologies and a robust IT infrastructure. However, emerging economies in Asia Pacific, particularly India and China, are showing significant growth potential due to increasing digitalization and investments in IT infrastructure. The competitive landscape is characterized by a mix of established players like Oracle, IBM, and Microsoft, alongside specialized database automation vendors like Datavail and Quest Software. These companies are continuously innovating to enhance their offerings, focusing on AI-powered automation, improved integration with other IT tools, and enhanced security features to maintain their competitive edge.

Net official flows from UN agencies, ILO (current US$) in Senegal was reported at 1240066 USD in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Senegal - Net official flows from UN agencies, ILO - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Net official flows from UN agencies, UNHCR (current US$) in Mexico was reported at 1837100 USD in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Mexico - Net official flows from UN agencies, UNHCR - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Net official flows from UN agencies, UNAIDS (current US$) in Uganda was reported at 276598 USD in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Uganda - Net official flows from UN agencies, UNAIDS - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

BPS is a database of RNA base pairs with quantitative information on the spatial arrangements of interacting bases, including higher-order base associations, and the context of these interactions in high-resolution crystal structures. The structures are taken from the Nucleic Acid Database (NDB), and the base pairs are identified and characterized with the 3DNA software package. The interactions are classified in terms of residue identities, base-pair positioning, and hydrogen-bonding patterns and related to the structural context in which they occur. A user can browse the atlas of base-pair patterns and carry out searches for patterns of specific types or from specific structures.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information