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3,684 results for “extract”
Data for Water deficit and potassium affect carbon isotope composition in cassava bulk leaf material and extracted carbohydrates
<p>This repository contains data and scripts to reproduce results that are presented in the manuscript: Van Laere, J., Merckx, R., Hood-Nowotny, R., Dercon, G. (2023) Water deficit and potassium affect carbon isotope composition in cassava bulk leaf material and extracted carbohydrates. <em>Front. Plant Sci</em>. 14:1222558 doi: 10.3389/fpls.2023.1222558</p>
Metabolic profiling and antibacterial activity of tree wood extracts obtained under variable extraction conditions
<p>Scripts and dataset for Vinchira-Villarraga et al., 2024 "Metabolic profiling and antibacterial activity of tree wood extracts obtained under variable extraction conditions". The files label as A1, C6, H2/HCN2 and O1 correspond to the dataset obtained for Ash, Cherry, Horse-chestnut and Oak respectively. </p> <p>_batch.xml files contains the script for the pre-processing of .mzML mass spectrometry data created on MzMine 3.2.8. The file can be uploaded to newer versions of MzMine, but due to the addition of new modules, some parameters name have changed.</p> <p>_SIRIUS.mfg files contains the mass spectrometry data of each dataset for analysis in SIRIUS. The files were used for chemical formula prediction, classification and compound annotation using SIRIUS 5.0</p> <p>_quant.csv correspond to the output matrix as it was obtained from MzMine without noise, adducts and highly variable features filtering.</p> <p>_abundance.csv correspond to the output matrix after noise, adducts and highly variable features filtering.</p>
Model America - Arizona extract from ORNL's AutoBEM
<p>Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (<a href="https://bit.ly/AutoBEM">bit.ly/AutoBEM</a>).</p> <p>Two sets of sample data are provided for 2,555,152 buildings located within the boundary of Arizona in the United States:</p> <ol> <li><strong>Data (884.3MB *.csv) - minimalist list of each building (rows) for the following fields (columns)</strong> <ol> <li>ID - unique building ID</li> <li>Centroid - building center location in latitude/longitude (from Footprint2D)</li> <li>Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...)</li> <li>State_abbr - state name</li> <li>Area - estimate of total conditioned floor area (ft<sup>2</sup>)</li> <li>Area2D - footprint area (ft<sup>2</sup>)</li> <li>Height - building height (ft)</li> <li>NumFloors - number of floors (above-grade)</li> <li>WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings)</li> <li>CZ - ASHRAE Climate Zone designation</li> <li>BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards</li> <li>Standard - building vintage</li> </ol> </li> <li><strong>Sample Models (21.74GB*.zip by county) – OpenStudio and EnergyPlus building energy models named according to ID</strong></li> </ol> <p><span><span>ESS-Dive Revised dataset: New </span><span>J ;</span><span> Stubbings </span><span>A ;</span><span> Li </span><span>F ;</span><span> Bass </span><span>B ;</span><span> Adams </span><span>M ;</span><span> Berres A (2023): Model America - Arizona extract from ORNL's </span><span>AutoBEM</span><span> v1.1. Southwest Urban Corridor Integrated Field Laboratory (SW-IFL), ESS-DIVE repository. Dataset. </span></span><a href="https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2212792" target="_blank" rel="noreferrer noopener"><span><span>doi:10.15485/2212792</span></span></a><span><span> accessed via </span></span><a href="https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2212792" target="_blank" rel="noreferrer noopener"><span><span>https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2212792</span></span></a><span><span> </span></span></p> <p>This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).</p>
TrainTicket microservice testbench extracted information for our work: Evaluating ChatGPT's Proficiency in Understanding and Answering Microservice Architecture Queries Using Source Code Insights
<p>It contains the CSV file output of our tool implemented in the paper: "Evaluating ChatGPT’s Proficiency in Understanding and Answering Microservice Architecture Queries Using Source Code Insights." applied to the TrainTicket microservice testbench. The information in this CSV was used for In-Context-Learning for ChatGPT.</p>
Gold standard annotation of epilepsy clinic letters for the development of information extraction tools
<p>This folder contains 200 synthetic letters, based on hospital outpatient epilepsy clinic consultations, written by neurology consultants, specialist trainees, and epilepsy specialist nurses. The letters were double annotated by trained researchers, according to annotation guidelines, uploaded separately (What and How of annotating with Markup). The 200 .ann annotation files are also included.</p> <p>We used Markup (https://getmarkup.com) for annotation (the configuration file is within the uploaded set of annotations) with an epilepsy concept list based on the Unified Medical Language System (UMLS) ontology. All annotations were compared, reviewed, and corrected to form a gold standard annotation set.</p> <p> </p>
Evaluation dataset for Relation Extraction of relationships between Organisms and Natural-Products
<p>A curated evaluation dataset for end-to-end Relation Extraction of relationships between organisms and natural-products.</p> <p>Details about the manual annotation:</p> <ul> <li>For Chemicals: <ul> <li>The chemical labels are annotated as they appear in the abstract.</li> <li>In abstracts, singular chemicals and classes of chemicals produced by a specific organism were distinguished.</li> <li>The "type" attribute {“chemical”, “class”} is used to indicate the nature of the mentioned name.</li> <li>A "class" attribute for chemical entities has also been included if class information is present in the abstract.</li> <li>A Wikidata and PubChem identifiers were assigned to chemicals and classes when available.</li> </ul> </li> <li>For Organisms: <ul> <li>The organism labels are annotated as they appear in the abstract.</li> <li>If in an abstract, the genus name was mention first, e.g. "Plakinastrella sp." and then the specie name e.g "Plakinastrella clathrata" is precise, then only the specie name is used.</li> <li>A Wikidata identifier was assigned to all organisms.</li> <li>In some abstracts, only the genus name is mentioned.</li> </ul> </li> <li>For Relations: <ul> <li>Only the relations explicitly mentioned in the abstract are reported in the output labels.</li> <li>Relations are reported in their order of appearance in the abstract.</li> </ul> </li> </ul>
NEON Biorepository Soil Microbe Collection (DNA Extracts ) (repackaging of occurrences published by the NEON Biorepository Data Portal)
This collection contains genetic extracts from soil microbes collected during periodic soil sampling at NEON terrestrial sites (NEON sample class: mic_dnaExtraction_in.soilDnaSampleID). Three unique locations are sampled per plot with ten soil plots per site. Bouts occur three times per year in order to capture the prevailing conditions at the site during different seasons, except in Alaska where there only 1 bout is possible. However, the frequency of genetic analysis and thus DNA archiving varies by site type. Soil sampling is conducted to a maximum depth of 30 ± 1 cm, and when organic (O) and mineral (M) horizons are present within a single profile, they are separated prior to analysis and archiving. However, other sub-horizons are not separated. During the majority of bouts, only the top horizon (O if present, else M) is analyzed for genetic content. Soils are homogenized and non-soil material is removed by hand in the field, then subsamples are immediately frozen on dry ice. They are maintained in ultra-low temperature freezers until they are shipped to an analytical facility for DNA extraction, sample preparation and sequencing. During peak greenness bouts, subsamples from each of the 3 sampling locations per plot are combined to form a plot-level composite that is used for metagenomics analysis. Laboratory metadata are delivered to NEON for QC testing and acceptance, and then formatted for upload to public sequence repositories. Genetic extracts are shipped from the analytical facility in 96-well plates to the NEON Biorepository to be archived at -80 degrees Celsius. See links below for NEON data products that provide physical, chemical, and biological measurements for these same soils (soil pH, moisture, and microbial properties are always measured; chemical properties are determined only for a subset of collection bouts). The metabarcoding protocol used by Battelle Applied Genomics is available in the NEON document library (https://data.neonscience.org/docu
Effects of drying temperature on potential carbon mineralization and water-extractable organic carbon in Iowa cropland and riparian buffer soils
Measuring carbon dioxide (CO2) produced after re-wetting a previously dried soil is an increasingly popular soil health assay, but there is disagreement on the optimal soil drying temperature. We tested whether soil drying temperature impacts water-extractable organic carbon (WEOC) and soil CO2 emissions (potential carbon mineralization) following rewetting of dried soil. Samples were collected at four sites in north-central Iowa, US, and each site had soils planted to corn/soybean or perennial vegetation. The dataset includes measurements of WEOC prior to the incubation experiment, and measurements of CO2 flux and its stable carbon isotope ratio over the course of a 28-day incubation. The manuscript describing these data is under review in Geoderma.
Hydroxycinnamic acid extraction from prairie biomass for enhancing performance in anaerobic digestion, Iowa, 2021-2022.
This dataset contains a series of batch and continuous anaerobic digestion (AD) experiments that document the effects of hydroxycinnamic acid (HCA) extraction as a pretreatment strategy for prairie biomass to enhance methane production and digestion performance. It includes data on chemical composition of raw inputs (prairie biomass, manure, inoculum), including elemental and solids content; methane and biogas yields under various conditions: untreated vs. HCA-treated biomass, co-digestion with manure at different ratios, and operational enhancements such as biochar supplementation and liquid digestate recirculation; digestate characteristics, including pH, ammonia concentration, and total phenolic content, under different treatment and operational scenarios; optimization data for HCA extraction, detailing the influence of temperature and time on HCA yield and lignin removal; and HCA composition data, including cumulative and species-specific yields (ferulic and p-coumaric acids), and acetyl bromide soluble lignin content.
Seasonal relationships between soil respiration and water-extractable carbon as influenced by soil temperature and moisture in forest soils of the Andrews Experimental Forest, 1992-1993
The overall objective of this study is to model trace gas emissions from forest soils of the H. J. Andrews Experimental Forest. This is to be accomplished by studying trace gas emissions and related variable at a set of 20 permanent plots at the HJA.
Tanana River Floodplain Dissolved Organic Nitrogen (DON) Budget, extracted soil protein content
Ammonium, Nitrate, and Amino Acid concentrations in .5M K2SO4 extracted T0 Tanana Floodplain soils Ammonium, Nitrate, and Amino Acid concentrations in .5M K2SO4 extracted T30 Tanana Floodplain soils Sodium Bicarbonate Extracted Tanana River Floodplain Soil Protein Concentrations, 2001 Plot locations for the Tanana River Floodplain DON buget study. GPS coordinates for the Tanana River Floodplain Dissolved Organic Nitrogen (DON) Budget Study plots All values given are in micrograms of bovine serum albumin equivalents per gram dry weight. Site designations in parenthesis are specific to the study and represent individual transects,each within a unique stand of the following standtypes: W=willow,A=alder,BP=balsam poplar,4=white spruce,5=black spruce. Months: 6=June,7=July,etc.
Burial mounds dataset associated with the paper Geomorphometric methods for tumuli recognition and extraction from high resolution LiDAR DEMs
<p>This dataset consist of the burial (tumuli) mounds delineation and the associated data produced for the article Geomorphometric methods for tumuli recognition and extraction from high resolution LiDAR DEMs, submitted to Sensors. The dataset work in conjunction with the script (http://doi.org/10.5281/zenodo.3628805) to make the work reproductible. The DEM is available only by request to mihai.niculita@uaic.ro.</p>
VAMDC extraction with identifier = 7974a04d-3adc-4d26-a1df-10c0e3be44ba
<div>This is a dataset extracted from http://vald.astro.uu.se/atoms-12.07/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( atomsymbol in ['h'] and radtranswavelength <= 11634.49275862069 and radtranswavelength >= 8827.596206896555 ); </div><div> Data source version: 2020-01-24</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 7974a04d-3adc-4d26-a1df-10c0e3be44ba</div>
VAMDC extraction with identifier = 9202de74-a9b0-4e4d-9c1c-15a9673360bb
<div>This is a dataset extracted from http://topbase.obspm.fr/12.07/vamdc/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( atomsymbol in ['h'] and radtranswavelength <= 12450.010000000002 and radtranswavelength >= 2550.0100000000007 ); </div><div> Data source version: 2017-01-30</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 9202de74-a9b0-4e4d-9c1c-15a9673360bb</div>
VAMDC extraction with identifier = 47ac70f9-ac49-410f-a8bd-801cf43cdf18
<div>This is a dataset extracted from https://cdms.astro.uni-koeln.de/cdms/tap/ VAMDC node.</div><div>Query originating this dataset: query=select * where ( inchikey in ['ugfairiumavxcw-uhfffaoysa-n'] and radtranswavelength <= 2.6075892488699395E7 and radtranswavelength >= 2.594919405550487E7 ); </div><div> Data source version: 2019-11-27</div><div>Data format: XSAMS 12.07</div><div>Query uuid in VAMDC query store: 47ac70f9-ac49-410f-a8bd-801cf43cdf18</div>
SSH data set used for Rossby Wave Analysis, extraction from ORCA12.L46-MJM189 DRAKKAR simulation
<p>This data set corresponds to the Sea Surface Heigh (SSH) silmulated by the NEMO ocean circulation model, under the ORCA12.L46-MJM189 configuration, developped in the frame of the DRAKKAR project. This particular data set is an extraction from the native numerical grid, covering the area between 38N and 40N in the North Altantic ocean, for the period 1970 to 2015. The data are concatenated in a single file with 5-days average of SSH. The corresponding metrics for this sub domain are also present in this netcdf file. This subset was used in Watelet et al. (2020) submitted paper, dealing with Rossby waves analysis.</p>
Āryatathāgatoṣṇīṣasītātapatre aparajītamahāpratyaṃgīraparamasiddhanāma dhāraṇī (extract)
<p><em>Āryatathāgatoṣṇīṣasītātapatre aparajītamahāpratyaṃgīraparamasiddhanāma dhāraṇī</em>, extract from the <em>gzungs ‘dus</em> titled <em>The garland of wish-fulfilling gems wrapped around the precious essence of the ocean of sacred writing in the Sūtras and Tantras</em>. Collection of the Royal Asiatic Society of Great Britain and Ireland.</p>
silverCID — a silver standard corpus for Chemical-induced Diseases relation extraction — Edit
<p>silverCID — a silver standard corpus for Chemical-induced Diseases relation extraction — Edit</p>
Extract Article Numbers by Publisher from ZORA
<p>Pentaho Transformation to Extract Metadata from EPrints XML-Export:</p> <ol> <li>Download/Install Pentaho Data Integration (Free community Edition) from: http://sourceforge.net/projects/pentaho/files/Data%20Integration/</li> <li>Download EP3-XML-Export from: http://www.zora.uzh.ch/cgi/search/archive/advanced?screen=Search&dataset=archive&type=article&date%2Fevent_end=2008-2015&_action_search=Search</li> <li>Move ZORA Export XML in the same directory as the Pentaho Script "Extract Article Number by Publisher ZORA.ktr"</li> <li>Rename Export File like "export_zora_XML_articles_01.01.2016.xml" or change the source name in the XML importstep "Get data from ZORA Export XML"</li> <li>Run Script which creates csv files with the results in the directory</li> </ol>
Medical Relation Extraction Gold Standard with CrowdTruth
<p>The lack of annotated datasets for training and benchmarking is one of the main challenges of Clinical Natural Language Processing. In addition, current methods for collecting annotations attempt to minimize disagreement between annotators, and therefore fail to model the ambiguity inherent in language. We propose the <strong>CrowdTruth</strong> method for collecting medical ground truth through crowdsourcing, based on the observation that disagreement between annotators can signal ambiguity in the text, target semantics, or the worker's interpretation.</p> <p>This repository contains a dataset of 3,984 English sentences for medical relation extraction, centering on the cause and treat medical relations, that have been processed with CrowdTruth disagreement analytics to capture ambiguity. In addition, we provide the raw crowdsourcing data used to compile this ground truth, as well as the task templates used to collect the data on CrowdFlower.</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.