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3,101 results for “tables”
Supplementary tables from: Long-term outcomes of patients diagnosed with differentiated thyroid cancer in childhood and young adulthood
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Supplementary Table of Petrocodon mirus (Gesneriaceae), a new species from southwest Guangxi, China
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Marcell Experimental Forest site, station Watershed S2, peatland water table bogwell site, study of water table elevation above mean sea level in units of meter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Marcell Experimental Forest (MAR) contains water table elevation above mean sea level measurements in meter units and were aggregated to a monthly timescale.
Marcell Experimental Forest site, station Watershed S2, peatland water table bogwell site, study of water table elevation above mean sea level in units of meter on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Marcell Experimental Forest (MAR) contains water table elevation above mean sea level measurements in meter units and were aggregated to a yearly timescale.
Marcell Experimental Forest site, station Watershed S2, groundwater deepwell #202, study of water table elevation above mean sea level in units of meter on a monthly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Marcell Experimental Forest (MAR) contains water table elevation above mean sea level measurements in meter units and were aggregated to a monthly timescale.
Marcell Experimental Forest site, station Watershed S2, groundwater deepwell #202, study of water table elevation above mean sea level in units of meter on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Marcell Experimental Forest (MAR) contains water table elevation above mean sea level measurements in meter units and were aggregated to a yearly timescale.
Biodiversity - Fauna - Bird Survey - Table 2 of 4 - Taxalist
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The database consists of four tables. Sites, Surveys, Taxalist, and Birds. Sites records thje sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: The tables form a set. Here are the fields and relationship information: Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class
Biodiversity - Fauna - Bird Survey - Table 3 of 4 - Sites
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The database consists of four tables. Sites, Surveys, Taxalist, and Birds. Sites records thje sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: The tables form a set. Here are the fields and relationship information: Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class
Biodiversity - Fauna - Bird Survey - Table 4 of 4 - Surveys
This dataset is associated with BES Bird Monitoring Bird Monitoring Project: ================= The BES Bird Monitoring Project is a breeding bird survey designed to find out what birds are found in the breeding season in Baltimore and where. Our monitoring efforts will show associations among block group socioeconomic variables, land cover, land use, and habitat features with breeding bird abundance, to provide information for land managers on possible consequences of land use changes on bird communities. A distinguishing feature of the bird monitoring at BES LTER, relative to other urban bird work, is the capacity for long-term monitoring of features at multiple scales through links to other parts of the project. Different processes influence habitat for birds at different scales, e.g. ongoing household level human decision-making at lot scale vs. block or neighborhood scale abandonment/re-development. Our project seeks to understand how these processes impact bird occurrence, abundance, and composition differ at the lot, block and neighborhood scale. The database consists of four tables. Sites, Surveys, Taxalist, and Birds. Sites records thje sites and their characteristics. Surveys describe the actual outings or sampling sessions. They describe the weather, the temperature, the sites visited. Taxalist provides the integration of speciaies abbreviations and common names, and Birds describes the actual sightings, linking to the other three tables. Attribute information: The tables form a set. Here are the fields and relationship information: Surveys: site_id FK->Sites[site_id] survey_id survey_date time_start time_end observer wind_speed wind_dir air_temp temp_units cloud_cover notes Sites: site_id park_code park_district park_name point_code point_location park_acreage Taxalist: species_id common_name Birds: survey_id FK->surveys[survey_id] site_id FK->surveys[site_id] species_id FK->taxalist[species_id] distance bird_count notes seen heard direction time_class
Plant species percent cover data: Distribution of Wetland Plant Species in Relation to the Level of the Water Table
This study established permanent plots along transects in fifteen wetlands covering a range of wetland types. The plot are used to: 1) characterize the non-wooded wetlands at CCESR; 2) determine correlations of plant community type with environmental factors; 3) examine changes over a five year period.
Depth to water table
Eighty-seven piezometers (cased bore holes) were installed along topographic transects within the Cedar Creek Natural History Area. Depth to water table is measured at each well at a monthly to quarterly interval. Water samples are collected periodically and analyzed for pH and major cations and anions.
The Effects of Climate Downscaling Technique and Observational Dataset on Modeled Ecological Responses: Supporting Data Tables
These data have been prepared as a supplement to Pourmokhtarian et al. (2016; full citation below), where complete details on methods can be found. We evaluated three downscaling methods: the delta method (or the change factor method); monthly quantile mapping (Bias Correction-Spatial Disaggregation, or BCSD); and daily quantile regression (Asynchronous Regional Regression Model, or ARRM). Additionally, we trained outputs from four atmosphere-ocean general circulation models (AOGCMs) (CCSM3, HadCM3, PCM, and GFDL-CM2.1) driven by higher (A1fi) and lower (B1) future emissions scenarios on two sets of observations (1/8th degree resolution grid vs. individual weather station) to generate the high-resolution climate input for the forest biogeochemical model PnET-BGC (8 ensembles of 6 runs). This dataset consists of three files - 1) a zip archive file of all raw daily downscaled AOGCMs (csv format; years 1960-2099; delta method 2012-2099 only) which were used as input for PnET-BGC model, 2) a zip archive file of all PnET-BGC output files for each model run (csv format; years 1000-2100), and 3) a pdf document file that describes the content of the input and output files. Data were also used from the following Hubbard Brook longterm datasests: Daily Streamflow Watershed 6: http://dx.doi.org/10.6073/pasta/727ee240e0b1e10c92fa28641bedb0a3 Chemistry of Streamwater at the Hubbard Brook Experimental Forest, Watershed 6: http://dx.doi.org/10.6073/pasta/2ec152b0ab1d4e64aa40f4aa9bc492ac Daily Precipitation Watershed 6: http://dx.doi.org/10.6073/pasta/17c8ff8b160bf7893ef39f75a02652e5 Daily Maximum/Minimum Temperature Data: http://dx.doi.org/10.6073/pasta/2a4ab5522ce15f28196a6035802b09e8 Daily Solar Radiation Data: http://dx.doi.org/10.6073/pasta/2fa098a5aa191c64e622b253c0fee5af These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest
Extended Data Table 2 in Isolation of an archaeon at the prokaryote eukaryote interface
Extended Data Table 2 | Carbon isotope fractionation values in MK-D1 cultures after 120 days incubation with and without stable isotope labelled amino acids
Extended Data Table 1 in Isolation of an archaeon at the prokaryote eukaryote interface
Extended Data Table 1 | SSU rRNA gene clones obtained from the primary and six successive transferred enrichment cultures
Tables of the paper"A Conceptual Model of Chinese Oral Memory Based on Digital Humanities"
<p>Those are the tables used for the paper "A Conceptual Model of Chinese Oral Memory Based on Digital Humanities".</p>
Table of Contents for Meeting Artifacts from Chapman Conference on Scientific Challenges Pertaining to Space Weather Forecasting Including Extremes
<p>Table of Contents of Meeting Artifacts and Output from the Chapman Conference on Scientific Challenges Pertaining to Space Weather Forecasting Including Extremes, 11-15 February 2019, Pasadena, CA, USA</p> <p>Each entry in the table of contents provides a short description and/or artifact title, along with the number of associated files and a weblink showing the associated DOI or permanent URL.</p> <p>The Chapman Conference was supported by NSF Award AGS 1848885 and NASA grants 936723.02.01.09.14 and 936723.02.01.11.21</p>
Tables S2-S3. SMR-HEIDI results for 8q24.21 locus between back pain and other phenotypes.
<p><strong>Supplementary Table S2. SMR-HEIDI results for 8q24.21 locus between back pain and other complex traits. </strong></p> <p><strong>Column headers of Tables S2:</strong></p> <p>Secondary Trait Name: Name of complex trait<br> Dataset: Name of dataset (UKB Neale's lab or UKB Gene Atlas)<br> Index_SNP: RsID of SNP used as target in SMR-HEID analysis<br> Proxy_SNP: RsID of top SNP in the selected locus - SNP presented in both GWAS data with minimum P-values in back pain GWAS<br> r(proxy_SNP,index_SNP): linkage disequilibrium coefficient between index and proxy SNP<br> beta_SMR: Beta SMR for proxy SNP<br> p_SMR: P-value of beta SMR<br> qFDR-BH SMR: P-value of beta SMR after Bonferroni correction<br> p_HEIDI: P-value of HEIDI test<br> n_HEIDI: Number of SNPs used in HEIDI test<br> SNPs_HEIDI: List of rsID of SNPs used in HEIDI test</p> <p> </p> <p><strong>Supplementary Table S3.</strong> <strong>SMR-HEIDI results for 8q24.21 locus between back pain and expression of genes.</strong></p> <p><strong>Column headers of Tables S3:</strong></p> <p>Secondary Trait Name: Name of complex trait<br> Tissue: Name of the tissue from which the samples were taken to study gene expression<br> Gene_name: Gene name corresponding to the transcript name<br> Transcript Name: Transcript name (ID)<br> Dataset: Name of dataset (CEDAR, GTEx_v6)<br> beta_SMR: Beta SMR for proxy SNP<br> p_SMR: P-value of beta SMR<br> qFDR-BH SMR: P-value of beta SMR after Bonferroni correction<br> p_HEIDI: P-value of HEIDI test<br> n_HEIDI: Number of SNPs used in HEIDI test<br> SNPs_HEIDI: List of rsID of SNPs used in HEIDI test</p> <p> </p> <p>Part of the article: Williams FMK et al. "Sequence variation at 8q24.21 and risk of back pain"</p>
Table S1. List of relevant studies of gene expression with available eQTL data.
<p><strong>Supplementary Table S1. List of relevant studies of gene expression with available eQTL data.</strong> The table contains information of gene expression eQTL data used in the current study: source name (CEDAR, GTEx, blood eQTL by Westra et al.), tissue name and corresponding article DOI.</p> <p>Part of the article: Williams FMK et al. "Sequence variation at 8q24.21 and risk of back pain"</p>
IO Islamic 089. The Revenues of the Muḥammadâbâd Bîdar, Full Statistical Tables of the Assessment of All the Various Provinces
<p>IO Islamic 089. The Revenues of the Muḥammadâbâd Bîdar, Full Statistical Tables of the Assessment of All the Various Provinces</p>
IO Islamic 1632. The Revenues of the Khândîsh, Full Statistical Tables of the Assessment of All the Various Provinces
<p>IO Islamic 1632. The Revenues of the Khândîsh, Full Statistical Tables of the Assessment of All the Various Provinces</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.