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3,481 results for “data set”
Data from: Drivers of coastal benthic communities in a complex environmental setting
<p>Analyzing the environmental factors affecting benthic communities in coastal areas is crucial for uncovering key factors that require conservation action. Here, we collected benthic and environmental (physical-chemical-historical and land-based) data for 433 transects in Taiwan. Using a k-means approach, five communities dominated by crustose coralline algae, turfs, stony corals, digitate, or bushy octocorals were first delineated. Conditional random forest models then identified physical, chemical, and land-based factors (e.g., light intensity, nitrite, and population density) relevant to community delineation and occurrence. Historical factors, including typhoons and temperature anomalies, had only little effect. The prevalent turf community correlated positively with chemical and land-based drivers, which suggests that anthropogenic impacts are causing a benthic homogenization. This mechanism may mask the effects of climate disturbances and regional differentiation of benthic assemblages. Consequently, management of nutrient enrichment and terrestrial runoff is urgently needed to improve community resilience in Taiwan amidst increasing challenges of climate change.</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>
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>
Data from a drought experiment on saplings of Crataegus monogyna in a common garden setting with three provenances (Belgian, Swedish and Spanish)
<p><span>Data are from the common shrub <em>Crataegus monogyna</em> that experienced two summer droughts, each followed by rewatering. The experimental design consisted of a common garden with potted saplings from a local Belgian, a Swedish and a Spanish-Pyrenean provenance. We quantified the effects on growth and leaf phenology, focusing on the legacies in the year following the droughts. Responses were influenced by the severity of the drought and by its timing. </span></p>
Morphological and molecular data sets from a taxonomic revision of the gecko Lygodactylus tolampyae
<p>Original data sets (raw morphological data, metadata of specimens, and alignments / treefiles of DNA data) for the paper:</p> <p><strong>Taxonomizing a truely morphologically cryptic complex of dwarf geckos from Madagascar: molecular evidence for new species-level lineages within <em>Lygodactylus tolampyae</em></strong></p> <p>Authors of original paper: Miguel Vences, Malte Multzsch, Milena V. Zerbe, Sven Gippner, Franco Andreone, Angelica Crottini, Frank Glaw, Jörn Köhler, Sandratra Rakotomanga, Solohery Rasamison, Achille P. Raselimanana</p>
MARSIS Electron Cyclotron Echo Data Set
<p>This data set contains the electron cyclotron period, T_ce, manually extracted from electron cyclotron echoes recorded in MARSIS ionograms. The local magnetic field magnitude can be derived as B = 2 pi m_e / (e * T_ce).</p>
RNA flow additional data sets
<p>Additional raw data files and mathematical derivations to accompany the publication in Mol. Cell. (2024) by Ietswaart, Smalec, Xu, et al: Genome-wide quantification of RNA flow across subcellular compartments reveals determinants of the mammalian transcript life cycle.</p>
Walker et al - Prolactin and the shared regulation of parental care and cooperative helping behaviour in white-browed sparrow weaver societies - Data Set
<p>This file provides the data set supporting the analyses presented in a Walker et al manuscript titled "Prolactin and the shared regulation of parental care and cooperative helping behaviour in white-browed sparrow weaver societies" at first submission for review.</p>
Data Set for Self-adapting short-range correlation functional for complete active space-based approximations
<p>Data Set to accompany:</p> <p> Self-adapting short-range correlation functional for complete active space-based approximations</p>
Fiber-optic seismic sensing of vadose zone soil moisture dynamics data sets
<p>CC_daily.h5: Daily cross-correlation functions for common-offset DAS channels.</p> <p>RCC_dv_v_full.csv: Summary of all the measured dv/v from the ballistic surface waves in daily cross-correlation functions.</p>
Data from: Primer sets evaluation and sampling method assessment for the monitoring of fish communities in the North-western part of the Mediterranean Sea through eDNA metabarcoding
<p>Environmental DNA (eDNA) metabarcoding appears to be a promising tool for surveying fish communities. However, the effectiveness of this method relies on primer set performance and on a robust sampling strategy. While some studies have evaluated the efficiency of several primers for fish detection, it has not yet been assessed <em>in situ </em>for the Mediterranean Sea. In addition, mainly surface waters were sampled and no filter porosity testing was performed. In this pilot study, our aim was to evaluate the ability of six primer sets, targeting 12S rRNA (AcMDB07; MiFish; Tele04) or 16S rRNA (Fish16S; Fish16SFD; Vert16S) loci, to detect fish species in the Mediterranean Sea using a metabarcoding approach. We also assessed the influence of sampling depth and filter pore size (0.45 µm <em>versus</em> 5 µm filters). To achieve this, we developed a novel sampling strategy allowing simultaneous surface and bottom filtration of large water volumes along on-site the same transect. We found that 16S rRNA primer sets enabled more fish taxa to be detected across each taxonomic level. The best combination was Fish16S/Vert16S/AcMDB07, which recovered 95% of the 97 fish species detected in our study. There were highly significant differences in species composition between surface and bottom samples. Filters of 0.45 µm led to the detection of significantly more fish species. Therefore, to maximize fish detection in the studied area, we recommend to filter both surface and bottom waters through 0.45 µm filters and to use a combination of these three primer sets.</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.