The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set contains vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were converted to ARC/INFO EXPORT files. These data cover 1-kilometer diameters around each of the NSA tower sites, and another layer covers the NSA-MSA.

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set and documentation were compiled from field notes and other information provided by Hugo Veldhuis, who did the original soils mapping in the field during 1994. The information here describes the soils and landscape characteristics of the NSA-MSA and tower sites.

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set and documentation were compiled from field notes and other information provided by Hugo Veldhuis, who did the original soils mapping in the field during 1994. The information here describes the soils and landscape characteristics of the NSA-MSA and tower sites.

This data set was gridded from vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were gridded into raster files that cover the NSA-MSA and tower sites.

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set contains vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were converted to ARC/INFO EXPORT files. These data cover 1-kilometer diameters around each of the NSA tower sites, and another layer covers the NSA-MSA.

In November 2024, Google.com was the most popular website worldwide with 136 billion average monthly visits. The online platform has held the top spot as the most popular website since June 2010, when it pulled ahead of Yahoo into first place. Second-ranked YouTube generated more than 72.8 billion monthly visits in the measured period. The internet leaders: search, social, and e-commerce Social networks, search engines, and e-commerce websites shape the online experience as we know it. While Google leads the global online search market by far, YouTube and Facebook have become the world’s most popular websites for user generated content, solidifying Alphabet’s and Meta’s leadership over the online landscape. Meanwhile, websites such as Amazon and eBay generate millions in profits from the sale and distribution of goods, making the e-market sector an integral part of the global retail scene. What is next for online content? Powering social media and websites like Reddit and Wikipedia, user-generated content keeps moving the internet’s engines. However, the rise of generative artificial intelligence will bring significant changes to how online content is produced and handled. ChatGPT is already transforming how online search is performed, and news of Google's 2024 deal for licensing Reddit content to train large language models (LLMs) signal that the internet is likely to go through a new revolution. While AI's impact on the online market might bring both opportunities and challenges, effective content management will remain crucial for profitability on the web.

Beneficiaries of the Patrimony of Regional Interest Label, appointed at permanent committees, the first having taken place on 4 July 2018. This label makes it possible to develop the tourist attractiveness of the region and to reveal an unknown heritage, by setting up paths focused on themes that are fundamental to regional history.

Total numbers of each 3′ splice sites were calculated as described in Methods. The proportions of the top 20 sites were presented as a percentage of all identified 3′ splice sites in the groups of genes specified. Pairwise Z-test was performed for each 3′ splice site to test the signficance of difference between proportions of operonic and non-operonic genes. p≤0.01 is the confidence level.

This dataset contains properties eligible for inspection as part of the Parks Inspection Program, and contains internal directives and comments related to the inspection process. Each row represents a property or sub-property. All of these properties have associated geometry. For Parks Inspection Program - All Sites (UNMAPPED), go here: https://data.cityofnewyork.us/City-Government/Parks-Inspection-Program-All-Sites-UNMAPPED-/xs5m-jrpm Data Dictionary and User Guide can be found here: https://docs.google.com/spreadsheets/d/17LSfFUkhHPHJS4hszOYMVmVyU3xVF7J_dILhtIwWKKA/edit?usp=sharing A complete list of all datasets in the series can be found here: https://data.cityofnewyork.us/browse?Data-Collection_Data-Collection=Parks%20Inspection%20Program%20(PIP)&sortBy=alpha

A complete list of live websites using the Twenty20 technology, compiled through global website indexing conducted by WebTechSurvey.

This dataset contains model-based county estimates. PLACES covers the entire United States—50 states and the District of Columbia—at county, place, census tract, and ZIP Code Tabulation Area levels. It provides information uniformly on this large scale for local areas at four geographic levels. Estimates were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. PLACES was funded by the Robert Wood Johnson Foundation in conjunction with the CDC Foundation. This dataset includes estimates for 40 measures: 12 for health outcomes, 7 for preventive services use, 4 for chronic disease-related health risk behaviors, 7 for disabilities, 3 for health status, and 7 for health-related social needs. These estimates can be used to identify emerging health problems and to help develop and carry out effective, targeted public health prevention activities. Because the small area model cannot detect effects due to local interventions, users are cautioned against using these estimates for program or policy evaluations. Data sources used to generate these model-based estimates are Behavioral Risk Factor Surveillance System (BRFSS) 2022 or 2021 data, Census Bureau 2022 county population estimate data, and American Community Survey 2018–2022 estimates. The 2024 release uses 2022 BRFSS data for 36 measures and 2021 BRFSS data for 4 measures (high blood pressure, high cholesterol, cholesterol screening, and taking medicine for high blood pressure control among those with high blood pressure) that the survey collects data on every other year. More information about the methodology can be found at www.cdc.gov/places.

A complete list of live websites using the Gravity Forms Wcag 20 Form Fields technology, compiled through global website indexing conducted by WebTechSurvey.

Latitude Longitude, and basic metadata for sites in Water Data Exchange WaDE2.0 API https://app.swaggerhub.com/apis/WesternStatesWater/WaDE2.0/1.0.0

WaDE will update sites. This data is intended only for experimental use in association with the geoconnex.us project (https://github.com/internetofwater/geoconnex.us) w wade.geojson was created with code here: https://github.com/dblodgett-usgs/geoconnex_prep wade_[state].geojson and wade_sites.gpkg are hosted at https://wade-test.geoconnex.us

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Plant Macrofossil. The data include parameters of plant macrofossil (population abundance) with a geographic location of Mississippi, United States Of America. The time period coverage is from 22313 to 22287 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Cancer genomics unveils many cancer-related mutations, including some chromosome 20 (Chr.20) genes. The mutated messages have been found in the corresponding mRNAs; however, whether they could be translated to proteins still requires more evidence. Herein, we proposed a transomics strategy to profile the expression status of human Chr.20 genes (555 in Ensembl v72). The data of transcriptome and translatome (the mRNAs bound with ribosome, translating mRNAs) revealed that ∼80% of the coding genes on Chr.20 were detected with mRNA signals in three liver cancer cell lines, whereas of the proteome identified, only ∼45% of the Chr.20 coding genes were detected. The high amount of overlapping of identified genes in mRNA and RNC-mRNA (ribosome nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent distribution of the abundance averages of mRNA and RNC-mRNA along the Chr.20 subregions in three liver cancer cell lines indicate that the mRNA information is efficiently transmitted from transcriptional to translational stage, qualitatively and quantitatively. Of the 457 genes identified in mRNAs and RNC-mRNA, 136 were found to contain SNVs with 213 sites, and >40% of these SNVs existed only in metastatic cell lines, suggesting them as the metastasis-related SNVs. Proteomics analysis showed that 16 genes with 20 SNV sites were detected with reliable MS/MS signals, and some SNVs were further validated by the MRM approach. With the integration of the omics data at the three expression phases, therefore, we are able to achieve the overall view of the gene expression of Chr.20, which is constructive in understanding the potential trend of encoding genes in a cell line and exploration of a new type of markers related to cancers.

n = number of pairs.

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set contains measurements of site characteristics conducted in the SSA from 18-Jul-1994 to 30-Jul-1994.

This dataset is comprised of penetrometer (soil resistance) data for 20 sites in South-West England. The sites are physically close but are on four different soil types. At each site a dipwell was sunk to ~85 cm and water levels measured. Penetrometer measurements (10 replicates) were made with a cone and with a bespoke metal plate designed to replicate cattle grazing the land. Sites were visited through Autumn, Winter and Spring at approximately 10-day intervals, or more closely when significant weather events occurred. Measurements were taken between 15/9/1983 and 24/12/1985, with a one-off additional measurement of penetrometer data on 24/1/1989. Sites 17 to 20 were only sampled from 2/10/1985 onwards.
Grazing of improved pastures is an important land-use in South-West England and more widely. Poaching is the compaction, marking and smearing of the topsoil by the hooves of grazing animals. Agronomically it is recognised as a form of soil degradation, which inhibits subsequent grass growth, as well as providing sites for weed species to enter the sward. There can also be hydrological consequences through enhanced runoff and sediment transfer. Different soils vary in their vulnerability to poaching, particularly due to their texture (particle-size and organic matter content) and hydrological properties. Wet soils have a lower soil strength and are more at risk of poaching, and therefore poorly draining soil types pose a higher risk of soil damage. Ill-timed traffic by farm machinery has similar effects to poaching by livestock.
The soils in this study include both freely draining soils and those more prone to waterlogging. The measurement of soil strength over two annual cycles on similarly managed grass fields demonstrates the varying risk of poaching on different soil types and their speed of recovery after being wet.

Filtered view for the purpose of creating Approved CEs measure for TDA F&N Program Dashboard.