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7,195 results for “SET”
SPICE Test Set 1
<p>This is a test set for use with the SPICE quantum chemistry dataset (https://zenodo.org/doi/10.5281/zenodo.7258939). It contains 10 conformations each for 600 molecules not found in the SPICE dataset. They range in size from 40 to 110 atoms. Properties were calculated with identical settings to the ones in the SPICE dataset.</p>
Vamos motif set v2.0
<p>This is an updated motif set on 953,875 loci including both VNTR and STR loci. This uses an updated clustering algorithm to ensure that redundant, repetitive motifs are not included.</p>
The metabolomics raw data and a supporting statistical analyses data set for publication: Metabolomic analysis revealed the absence of the principal antimicrobial compound of Pseudomonas donghuensis P482, 7-hydroxytropolone, under restricted nutrient conditions.
<p><a href="../api/records/11220997/draft/files/Metabolomic%20analyses%20raw%20files.zip/content" target="_blank" rel="noopener noreferrer">Metabolomic analyses raw files</a>, Compounds analyses, Hierarchical Condition tress and PCA Scores are uploaded.</p>
Chemical Measurement Data Set
<p><span>The original data from:</span></p> <p><span>NAnderson2020MendeleyMangoNIRData.csv: <a href="https://data.mendeley.com/datasets/46htwnp833/2">https://data.mendeley.com/datasets/46htwnp833/2</a></span></p> <p><span>wheat kernels of 30 varieties.csv:</span> <span><a href="https://github.com/L-Zhou17/Wheat-kernels/tree/master">https://github.com/L-Zhou17/Wheat-kernels/tree/master</a></span></p> <p><span>SMRT_dataset.csv: <a href="https://doi.org/10.6084/m9.figshare.8038913">https://doi.org/10.6084/m9.figshare.8038913</a></span></p> <p><span>CCSbase_data.csv:</span> <span><a href="https://ccsbase.net/about">https://ccsbase.net/about</a></span></p> <p><span>Pubchem_semistdnp_RI.csv: <a href="https://pubchem.ncbi.nlm.nih.gov/">https://pubchem.ncbi.nlm.nih.gov/</a></span></p>
African wood density database with matches to the taxonomic backbone data sets of World Flora Online (version 2023.12) and the World Checklist of Vascular Plants (version 11)
<p>The <strong><span>African Wood Density Database </span></strong><span>provides air-dry wood density data for over 750 tree species grown in Africa.</span></p> <p>This archive provides taxonomic matches with recent versions of <strong>World Flora Online</strong> (WFO; <a href="../records/10425161">version 2023.12 downloaded from Zenodo</a>; Borch et al. <a href="https://onlinelibrary.wiley.com/doi/10.1002/tax.12373">2020</a>) and the <strong>World Checklist of Vascular Plants</strong> (WCVP; <a href="https://sftp.kew.org/pub/data-repositories/WCVP/Archive/">version 11 downloaded from the Kew data depository</a>; Govaerts et al. <a href="https://doi.org/10.1038/s41597-021-00997-6">2021</a>). Matching was done via the <strong>WorldFlora</strong> package (<a href="https://cran.r-project.org/package=WorldFlora">version 1.14-3</a>; Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">2020</a>), using similar scripts as documented in this Rpub: <a href="https://rpubs.com/Roeland-KINDT/1134151">https://rpubs.com/Roeland-KINDT/1134151</a>.</p> <p> </p> <ul> <li><span>Carsan, S. Orwa, C. Harwood, C. Kindt, R. Stroebel, A. Neufeldt, H. and Jamnadass, R. 2012. African Wood Density Database. World Agroforestry Centre, Nairobi. <a href="https://apps.worldagroforestry.org/treesnmarkets/wood/">https://apps.worldagroforestry.org/treesnmarkets/wood/#</a> </span></li> <li><span>Borsch, T., Berendsohn, W., Dalcin, E., Delmas, M., Demissew, S., Elliott, A., Fritsch, P., Fuchs, A., Geltman, D., Güner, A., Haevermans, T., Knapp, S., le Roux, M.M., Loizeau, P.-A., Miller, C., Miller, J., Miller, J.T., Palese, R., Paton, A., Parnell, J., Pendry, C., Qin, H.-N., Sosa, V., Sosef, M., von Raab-Straube, E., Ranwashe, F., Raz, L., Salimov, R., Smets, E., Thiers, B., Thomas, W., Tulig, M., Ulate, W., Ung, V., Watson, M., Jackson, P.W. and Zamora, N. (2020), World Flora Online: Placing taxonomists at the heart of a definitive and comprehensive global resource on the world's plants. TAXON, 69: 1311-1341. <a href="https://doi.org/10.1002/tax.12373">https://doi.org/10.1002/tax.12373</a></span></li> <li><span>Govaerts, R., Nic Lughadha, E., Black, N. <em>et al.</em> The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. <em>Sci Data</em> <strong>8</strong>, 215 (2021). <a href="https://doi.org/10.1038/s41597-021-00997-6">https://doi.org/10.1038/s41597-021-00997-6</a></span></li> <li><span>Kindt, R. 2020. WorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online taxonomic backbone data. <em>Applications in Plant Sciences</em> 8(9): e11388. <a href="https://doi.org/10.1002/aps3.11388">https://doi.org/10.1002/aps3.11388</a></span></li> </ul> <p> </p> <p>Original funding for the database was provided <span>by the Carbon Benefits Project (CBP) supported by The Global Environment Facility (GEF). Development of the 2024 version </span>was supported by the <strong>Darwin Initiative</strong> to project DAREX001 of <em>Developing a Global Biodiversity Standard certification for tree-planting and restoration</em>, by <strong>Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia</strong> to the <em>Provision of Adequate Tree Seed Portfolio</em> project in Ethiopia, by the <strong>Green Climate Fund</strong> through the IUCN-led <em>Transforming the Eastern Province of Rwanda through Adaptation</em> project and through the <em>Readiness proposal on Climate Appropriate Portfolios of Tree Diversity for Burkina Faso</em>, by the <strong>Bezos Earth Fund</strong> to the <em>Bezos Quality Tree Seed for Africa in Kenya and Rwanda</em> project and by the <strong>German International Climate Initiative (IKI)</strong> to the regional tree seed programme on <em>The Right Tree for the Right Place for the Right Purpose in Africa</em>. When using <strong>African Wood Density database</strong> in your work, cite the 2012 version (Carsan et al. <a href="https://apps.worldagroforestry.org/treesnmarkets/wood/">2012</a>) as well as this repository using the DOI.</p>
Data sets used in Lee et al. (2024)
<p>Data sets used in the following article (submitted):</p> <p> </p> <p>Hoontaek Lee, Martin Jung, Nuno Carvalhais, et al. Spatial attribution of temporal variability in global land-atmosphere CO2 exchange using a model-data integration framework. <em> ESS Open Archive .</em></p>
Cleaned libraries and settings matchms library cleaning pipeline
<p>Contains the results of library cleaning by matchms library cleaning pipelines. </p><p>ALL_GNPS_NO_PROPOGATED_21_08_2023.mgf library downloaded on 21-08-2023 from https://gnps-external.ucsd.edu/gnpslibrary/ALL_GNPS_NO_PROPOGATED.mgf</p><p>The 2 folders contain 2 different cleaning pipelines on the GNPS library.</p><p>Each folder contains:</p><p>A yaml file: This contains the settings used for this run. Should be used to rerun the pipeline with the same settings.</p><p>A .py file: This was the script used to run the pipeline. Not recommended to reuse, instead use the yaml file. </p><p>A .log file: Containing the log of the run. At the end the processing report is given.</p><p>A .mgf file: The cleaned library spectra.</p>
Vamos set v2.1
<p>This is a reference TR motif set for HG38 and CHM13 genomes.</p> <p>The following files are the efficient motif sets. Most analyses should use these because the unflitered motif sets are likely dominated by sequencing error rather than rare variation.</p> <p>vamos.motif.hg38.v2.1.e0.1.tsv.gz</p> <p>vamos.motif.CHM13.v2.1.e0.1.tsv.gz</p> <p>The following are the original unfiltered motif sets:</p> <p>vamos.motif.hg38.v2.1.orig.tsv.gz</p> <p>vamos.motif.CHM13.v2.1.orig.tsv.gz</p> <p> </p>
Complete Data Set, Raman spectra for strains A/Nebraska/14/2019 and A/Hawaii/47/2014 collected at 785 nm and 532 nm
<p>This data contains Raman spectra for two different strains of Influenza A; A/Nebraska/14/2019 which is an H1N1 subtype and A/Hawaii/47/2014 which is an H3N2 subtype. There contains data for 10 separate growth cultures (i.e. 10 files) for each subtype, collected at two different wavelengths; 785 nm and 532 nm. This makes a total of 40 files. Each file has 400 spectra collected. All spectra were collected at 100x with a 5 second accumulation time. </p>
Supplementary File 10; The full data set used for the analysis presented herein:
Open the record for dataset details and reuse information.
The influence of permafrost and other environmental controls on stream thermal sensitivity across Yukon, Canada -- data set
<p>Data set used to conduct the research presented in the manuscript entitled "<span>The influence of permafrost and other environmental controls on stream thermal sensitivity across Yukon, Canada</span>", submitted to the journal Hydrology and Earth System Science.</p>
Data set for manuscript titled "Morphological, physiological and metabolic responses of diverse barley inbreds to dry down and moderate drought stress"
<p>The primary aim of the study was to understand the genotypic diversity on plant morphology, photosynthetic responses, metabolite shift and their relationship in diverse barley inbreds under dry down (DD) and moderate drought (MD) stress using 23 genetically diverse parental inbreds. The data were collected from over a period of 28 days after the start of stress treatment. The publised data set indcludes the emmeans of all the evaluated characters. Metabolite profiling was done in samples collected from 7 d and 12 d after the start of DD and MD stress.</p>
Calculating Supraglacial Debris Properties at Pirámide Glacier, Chile (Data Sets and Codes)
<p>This repository contains the inputs and codes for calculating thermal conductivity and aerodynamic surface roughness length presented in the research paper.</p> <div>Codes:</div> <div> <ol> <li>Functions for thermal conductivity estimations: <ol> <li>RunThermalConductivity_allSites (to calculate CRh or CRi) -> in here choose the parameters to consider (sensor uncertainty, soil moisture, lithological properties) and the method to use (CRh or CRi)</li> <li>ThermalConductivity_CRh</li> <li>ThermalConductivity_CRi</li> <li>Conductivity_Brock (to calculate NYB)</li> <li>Calibrate_deb_par_PIR_k_z0 (calculates optimised value of k (and z0))</li> </ol> </li> <li>Functions for aerodynamic surface roughness lenght: <ol> <li>Runz0 (main) -> in here choose the parameters (d or no d, surface temperature, sensor uncertainty, period of measurements)</li> <li>z0Calc</li> <li>Calibrate_deb_par_PIR_k_z0 -> it calibrates z0 if chosen</li> </ol> </li> </ol> </div> <div> </div> <div>Data:</div> <div> <ol> <li>Ablation_Tower1.mat, Ablation_Tower2.mat and Ablation_Tower3.mat: Timetables containing the automatic distances measured from the ablation stake pictures in m and the calculated ablation in mm w.e.</li> <li>DATA_Piramide.mat: <ol> <li>debtemp: structure containing timetables of thermistor data (°C) for the three sites, where DT1 is the closest to the surface and DT5 the closest to the ice.</li> <li>sm: structure containing timetables of moisture content (m3/m3) data for the three sites, where SM1 is the closest to the surface and SM3 the closest to the ice.</li> <li>trh: structure containing timetables of temperature (°C) and relative humidity (%) data for the three sites, where XX_1, XX_2, XX_3 and XX_4 correspond to the variables at 0.5, 1, 2 and 2.7 m above the surface. TA is the air temperature, RH is the relative humidity and DTA is the dew temperature.</li> <li>wind: structure containing timetables of wind speed (m/s) and direction (°) data for the three sites, where L1, L2, L3 and L4 correspond to 0.5, 1, 2 and 2.7 m above the surface and FF is the wind speed, FFmx is the maximum wind speed, FFstd is the standard deviation, and DIR is the direction.</li> </ol> </li> <li>LithologyData: structure containing the density (kg/m3) and specific heat capacity (J/kg/K) for each site.</li> <li>SM_data: structure containing the moisture content (m3/m3) for the selected period, as well as the mean value for each site</li> <li>Calibration: data required to run the k and z0 calibrations with T&C</li> </ol> </div> <div> </div> <div> </div>
Data set for ODI cricket matches from 1987 to 2023 (extracted from ESPN Cricinfo) and code (R) used for a statistical study
<p>Here I present the data and code that has been used to study the statistical evolution of ODI cricket. The preprint for this research is available at: </p> <div> <div> <div> <table> <tbody> <tr> <td><a href="https://doi.org/10.48550/arXiv.2406.11652">https://doi.org/10.48550/arXiv.2406.11652</a> <div><span>Focus to learn more</span></div> </td> </tr> </tbody> </table> </div> </div> </div> <div> </div>
Data set: A solid-state high harmonic generation spectrometer with cryogenic cooling
<p>Solid-state high harmonic generation (sHHG) spectroscopy is a promising technique for studying electronic structure, symmetry, and dynamics in condensed matter systems. Here, we report on the implementation of an advanced sHHG spectrometer based on a vacuum chamber and closed-cycle helium cryostat. Using an in situ temperature probe, it is demonstrated that the sample interaction region retains cryogenic temperature during the application of high-intensity femtosecond laser pulses that generate high harmonics. The presented implementation opens the door for temperature-dependent sHHG measurements down to a few Kelvin, which makes sHHG spectroscopy a new tool for studying phases of matter that emerge at low temperatures, which is particularly interesting for highly correlated materials.</p>
Figure 23 in A revised faunal list and geological setting for Bullock Creek, a Camfieldian site from the Northern Territory of Australia
Figure 23. Occlusal stereopair of NTMAG P9464-218, bulungamayine Rp2. Scale bar = 3 mm.
Figure 11 in A revised faunal list and geological setting for Bullock Creek, a Camfieldian site from the Northern Territory of Australia
Figure 11. Profiles of a, Horseshoe Centre; b, Camp Quarry; and c, Microsite.
Figure 8 in A revised faunal list and geological setting for Bullock Creek, a Camfieldian site from the Northern Territory of Australia
Figure 8. Slabbed surface of location A6 showing pink and yellow banding. Scale bar = 1 cm.
Figure 22 in A revised faunal list and geological setting for Bullock Creek, a Camfieldian site from the Northern Territory of Australia
Figure 22. Occlusal stereopair of NTMAG P9464-243, RM2 of cf. Palepotorous. Scale bar = 3 mm.
Figure 19 in A revised faunal list and geological setting for Bullock Creek, a Camfieldian site from the Northern Territory of Australia
Figure 19. Occlusal steropair of NTMAG P9464-245, pseudocheirid Lm2/3. Scale bar = 3 mm.
ScienceDex guides
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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.