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Dataset results
20 results for “Source term”
Genome-Wide DNA Methylation in Peripheral Blood and Long-Term Exposure to Source-Specific Transportation Noise and Air Pollution: The SAPALDIA Study (Supplementary Data)
<p>The zip file contains supplementary data for the publication - Genome-Wide DNA Methylation in Peripheral Blood and Long-Term Exposure to Source-Specific Transportation Noise and Air Pollution: The SAPALDIA Study, accepted for publication in Environmental Health Perspectives (DOI: 10.1289/EHP6174).</p> <p>The description of the files are noted below:</p> <p><strong>1. Readme File for SAPALDIA Noise and Air Pollution EWAS Single Exposure.zip </strong></p> <p>This zip file contains all the results of the association between source-specific transportation noise (aircraft, railway and road traffic), air pollution (NO<sub>2</sub> and PM<sub>2.5</sub>), and genome-wide DNA methylation, derived from multi-exposure models.</p> <p><strong>SAPALDIA_EWAS_SingleExposure_AircraftLden.txt</strong> contains the results for aircraft noise</p> <p><strong>SAPALDIA_EWAS_SingleExposure_RailwayLden.txt</strong> contains the results for railway noise</p> <p><strong>SAPALDIA_EWAS_SingleExposure_RoadtrafficLden.txt</strong> contains the results for road traffic noise</p> <p><strong>SAPALDIA_EWAS_SingleExposure_NO2.txt</strong> contains the results for nitrogen dioxide</p> <p><strong>SAPALDIA_EWAS_SingleExposure_PM25.txt</strong> contains the results for fine particulate matter</p> <p> </p> <p><strong>General footnote for all files:</strong>SAPALDIA: Swiss cohort study on air pollution and lung and heart diseases in adults. CpG: Cytosine-phosphate-Guanine. CHR: chromosome. SE: standard error. Lden: day-evening-night noise level. NO<sub>2</sub>: nitrogen dioxide. PM<sub>2.5</sub>: particulate matter with aerodynamic diameter <2.5 µm. Beta coefficients represent increase or decrease in DNA methylation per 10 dB increase in aircraft, railway or road traffic Lden or 10 µg/m<sup>3</sup> increase in NO<sub>2</sub> or PM<sub>2.5</sub>. All estimates were from single exposure epigenome-wide linear mixed models, with random intercept at the level of participant. Each model was adjusted for age, sex, educational level, area, and neighborhood socio-economic status, greenness index, smoking status and pack years, exposure to passive smoke, consumption of fruits, vegetables and alcohol, nested study, asthma status, survey, source-specific noise truncation indicator (for Lden models) and leukocyte composition. In a preliminary step, DNA methylation β-values were regressed on the Illumina control probe-derived first 30 principal components to correct for correlation structures and technical bias, and residuals of these regressions covering 430,477 CpGs were used as the technical bias-corrected methylation level at the CpG sites.</p> <p>Extreme values of the residuals (lying beyond three times the interquartile range below the first quartile and above the third quartile at each CpG site) were replaced with their corresponding detection threshold value (“modified winsorization”). The “winsorized” data were then used as the dependent variables in the epigenome-wide association study.</p> <p> </p> <p><strong>2. Readme File for SAPALDIA Noise and Air Pollution EWAS Multi Exposure.zip </strong></p> <p>This zip file contains all the results of the association between source-specific transportation noise (aircraft, railway and road traffic), air pollution (NO<sub>2</sub> and PM<sub>2.5</sub>), and genome-wide DNA methylation, derived from multi-exposure models.</p> <p><strong>SAPALDIA_EWAS_MultiExposure_AircraftLden.txt</strong> contains the results for aircraft noise</p> <p><strong>SAPALDIA_EWAS_MultiExposure_RailwayLden.txt</strong> contains the results for railway noise</p> <p><strong>SAPALDIA_EWAS_MultiExposure_RoadtrafficLden.txt</strong> contains the results for road traffic noise</p> <p><strong>SAPALDIA_EWAS_MultiExposure_NO2.txt</strong> contains the results for nitrogen dioxide</p> <p><strong>SAPALDIA_EWAS_MultiExposure_PM25.txt</strong> contains the results for fine particulate matter</p> <p><strong>General table footnotes: </strong>SAPALDIA: Swiss cohort study on air pollution and lung and heart diseases in adults. CpG: Cytosine-phosphate-Guanine. CHR: chromosome. SE: standard error. Lden: day-evening-night noise level. NO<sub>2</sub>: nitrogen dioxide. PM<sub>2.5</sub>: particulate matter with aerodynamic diameter <2.5 µm. Beta coefficients represent increase or decrease in DNA methylation per 10 dB increase in aircraft, railway or road traffic Lden or 10 µg/m<sup>3</sup> increase in NO<sub>2</sub> or PM<sub>2.5</sub>. All estimates were from multi-exposure epigenome-wide linear mixed models, with random intercept at the level of participant, and were adjusted for age, sex, educational level, area, and neighborhood socio-economic status, greenness index, smoking status and pack years, exposure to passive smoke, consumption of fruits, vegetables and alcohol, nested study, asthma status, survey, source-specific noise truncation indicator and leukocyte composition. Multi-exposure models included all five exposures (Aircraft, railway, road traffic Lden and respective truncation indicators, NO<sub>2</sub> and PM<sub>2.5</sub>) at the same time. In a preliminary step, DNA methylation β-values were regressed on the Illumina control probe-derived first 30 principal components to correct for correlation structures and technical bias, and residuals of these regressions covering 430,477 CpGs were used as the technical bias-corrected methylation level at the CpG sites. Extreme values of the residuals (lying beyond three times the interquartile range below the first quartile and above the third quartile at each CpG site) were replaced with their corresponding detection threshold value (“modified winsorization”). The “winsorized” data were then used as the dependent variables in the epigenome-wide association study.</p>
Source parameters of short-term slow slip events in southcentral Alaska
<p>Source parameters of short-term slow slip events (SSEs) in southcentral Alaska from April 1, 2007, to March 31, 2021. This data set is a CSV format version of Table S5 in our manuscript recently accepted in Geophysical Research Letters (GRL). Please read the GRL paper for the details of the detection method and data we used. The format of this data set is as follows:</p> <p> </p> <p><strong>Okada-Nishimura2023_short-term_SSE_southcentral-Alaska.csv</strong></p> <p>Col 1: event date (yyyymmdd: middle date of duration)</p> <p>Col 2: longitude of the fault center (degree)</p> <p>Col 3: latitude of the fault center (degree)</p> <p>Col 4: depth of the fault center (km)</p> <p>Col 5: length of the fault (km)</p> <p>Col 6: width of the fault (km)</p> <p>Col 7: strike angle of the fault (degree)</p> <p>Col 8: dip angle of the fault (degree)</p> <p>Col 9: rake angle of the slip (degree)</p> <p>Col 10: slip amount (m)</p> <p>Col 11: seismic moment (Nm)</p> <p>Col 12: moment magnitude</p> <p>Col 13: duration (day)</p> <p>Col 14: event category (1: SSEs, 2: potential transient events)</p> <p> </p> <p># Version Info</p> <p>Version 1: Initial submission</p>
The first 500-meter, long-term winter wheat grain protein content dataset for China from multi-source data
<p>In China, the demand for precise perception of wheat Grain Protein Content (GPC) has gained increased urgency, driven by the rising demands in the food consumption market and intensifying international market competition. However, due to the lack of extensive, prolonged high-resolution benchmark data, previous GPC studies have primarily focused on experimental fields, small geographic units, and limited temporal scopes. Additionally, the diversified geographical landscape in China introduces spatiotemporal heterogeneity and intricacy to the influence of wheat GPC, further amplifying the challenges of large-scale GPC estimation. To address this challenge and the data gap, the first 500-meter spatial resolution, long-term winter wheat dataset covering major planting regions in China (CNWheatGPC-500) was created by integrating multi-source data from ERA5 and MODIS.</p>
Experimental sloshing pressure data from "Improving stability of moving particle semi-implicit method by source terms based on time-scale correction of particle-level impulses"
<p>3D sloshing in a prismatic tank under translational coupled surge-sway (X and Y axis) motions. The main dimensions are height H<sub>T</sub> = 0.54m, width W<sub>T</sub> = 0.84m and length L<sub>T</sub> = 0.72m. The filling ratio of 50% (H<sub>F</sub> = 0.27m). The periods of surge and sway excitations are T<sub>s</sub> = 1.25s with amplitude motions of A<sub>x</sub> = 0.0144m (0.02 x length) and A<sub>y</sub> = 0.0168m (0.02 x width).</p> <p>Files:</p> <p><strong>experimental_slosh_h50_20cycles_p1_dt0p000100.txt</strong>: Experimental pressure data at sensor P1</p> <p><strong>slosh_3d_exp_timer</strong>: Experimental movie</p> <p><strong>sloshing_tank_dimensions.pdf</strong>: Tank main dimensions</p> <p> </p> <p>The experimental data was used in:</p> <p>Cheng, L.Y., Amaro Junior, R.A., Favero, E.H. (2021). Improving stability of moving particle semi-implicit method by source terms based on time-scale correction of particle-level impulses. Engineering Analysis with Boundary Elements, 131, 118-145. Available at. doi: <a href="https://doi.org/10.1016/j.enganabound.2021.06.018">https://doi.org/10.1016/j.enganabound.2021.06.018</a></p>
Data for "Symbiotic nutrient cycling enables the long-term survival of Aiptasia in the absence of heterotrophic food sources"
<p>Supplementary figures and raw data associated with the publication "Symbiotic nutrient cycling enables the long-term survival of Aiptasia in the absence of heterotrophic food sources". Data for physiological and NanoSIMS measurements are uploaded as individual sheets/tabs in the .xslx file. </p> <p>"Fig. 1" contains data for physiological measurements (biomass, protein content, and symbiont density) of fed and starved Aiptasia. </p> <p>"Fig. 2" contains data for NanoSIMS measurements for regions of interest from the tissue of fed and starved Aiptasia as well as unlabelled control Aiptasia. </p> <p>The R script contains all code required to repeat the data analysis and plotting.</p> <p> </p>
Data and software associated with PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources
<p>Data and software associated with the paper:</p> <p>PHENOstruct: Prediction of human phenotype ontology terms using heterogeneous data sources</p>
Data from: Long-term trends in the occupancy of ants revealed through use of multi-sourced datasets
<p><span>We combined participatory science data and museum records to understand long-term changes in occupancy for 29 ant species in Denmark over 119 years. Bayesian occupancy modelling indicated change in occupancy for 15 species: five increased, four declined and six showed fluctuating trends. We consider how trends may have been influenced by life-history and habitat changes. Our results build on an emerging picture that biodiversity change in insects is more complex than implied by the simple insect decline narrative.</span></p>
Porting the WAVEWATCH III Wave Action Source Terms to GPU - WaveWatchIII configuration files
<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a global ustructured grid.</p> <ul> <li>global_refined_59K.msh <ul> <li>Unstructured mesh file in gmsh format. An unstructured mesh of 1 degree global resolution and 0.25 degree in regions with depth less than 4km e.g. 1 degree at the equator and 0.25 degree at the coastal regions </li> </ul> </li> <li>global_refined_228K.msh <ul> <li>Unstructured mesh file in gmsh format. An unstructured mesh of 0.5 degree global resolution and 0.125 degree in regions with depth less than 4km.</li> </ul> </li> <li>ww3_grid.inp <ul> <li>The input file for the ww3_grid pre-processing program. This file contains many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>
Data from: Long-term trends in the occupancy of ants revealed through use of multi-sourced datasets
Open the record for dataset details and reuse information.
Supplementary information: Integrative taxonomy unravels the true identity of Linnaeus’ <em>Termes fatalis</em> (Isoptera: Termitidae), the source of termites’ name
Open the record for dataset details and reuse information.
Data Source file for manuscript: Within-host genetic diversity of extended-spectrum beta-lactamase-producing Enterobacterales in long-term colonized patients
<p>ABSTRACT</p><p>Infections caused by extended-spectrum beta-lactamase (ESBL)-producing Enterobacterales (ESBL-PE) are associated with excess morbidity and mortality. Despite recognition of this immediate impact on human health, essential aspects of their molecular epidemiology remain under-investigated. This includes knowledge on the potential of a particular strain to persist in a host, mutational events during colonization, and the genetic diversity in individual patients over time. To investigate long-term genetic diversity of colonizing and infecting ESBL-producing <i>Klebsiella pneumoniae </i>species complex and ESBL-<i>Escherichia coli</i> in individual patients over time, we conducted performed a ten-year longitudinal retrospective study and extracted clinical and microbiological data from electronic health records. In this investigation, 76 ESBL-<i>K. pneumoniae</i> species complex and 284 ESBL-<i>E. coli</i> isolates were recovered from 19 and 61 patients. Strain persistence was detected in all patients colonized with ESBL-<i>K. pneumoniae </i>species complex, and 83.6% of patients colonized with ES BL-<i>E. coli</i>. Antimicrobial resistance genes, plasmid replicons, and whole ESBL-plasmids were shared between isolates regardless of chromosomal relatedness. Our study suggests that patients colonized with ESBL-producers may act as durable reservoirs for ongoing transmission of ESBLs, and that they are at a prolonged risk of recurrent infection with colonizing strains.</p><p>DATA SOURCE FILE</p><p>In this Data Source file, you will find access to the raw data, metadata and results obtained during the study: "Within-host genetic diversity of extended-spectrum beta-lactamase-producing Enterobacterales in long-term colonized patients". Data is organized following the structure of Figures/Tables of the manuscript and Supplementary Material. Additional figures not included in the main manuscript nor in the Supplementary Material are also available.</p><p>All sequencing and sample data from this study can be accessed at the NCBI database under the BioProject number PRJNA910977: <a href="http://dataview.ncbi.nlm.nih.gov/object/PRJNA910977">http://dataview.ncbi.nlm.nih.gov/object/PRJNA910977. </a>No new software was developed during this study. Standard bioinformatics software was used and the commands used can be accessed at the Supplementary Information file.</p>
Dataset for testing the Adaptive Source Term Estimation algorithm
<p>The objective of this work is to study the Adaptive Source Term Estimation algorithm developed by the authors and that will be presented in a future article. Briefly, source term estimation (STE) is a mathematical tool aimed to characterize the source parameters of some gas hazard based on its measurements at given positions. The adaptive STE (ASTE) is aimed to perform this procedure iteratively, i.e. based on the received measurements at a given set of deployed detectors, the algorithm proposes the location for the next detector in order to optimally solve the STE problem.</p>
idealized spectral source terms
<p>A simple representation of the major source terms in spectral wave model.</p>
Pre-operative Short-term Administration of a Formula Diet Containing a Non-milk-derived Protein Source for Prevention of Acute Kidney Injury After Cardiac Surgery
ClinicalTrials.gov study NCT03715868. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Dataset for testing the Adaptive Source Term Estimation algorithm
Open the record for dataset details and reuse information.
Data of industrial heat source between 2012 and 2021 using long-term Active Fire/Hotspot data in China
<p>Industrial heat sources serve as crucial indicators of energy consumption levels and air pollution. Energy-intensive industries are facing substantial challenges in transforming and upgrading in China. Therefore, accurately identifying industrial heat source locations and monitoring their temporal patterns are becoming utmost importance. In this study, a long-term industrial heat source datasets between 2012 and 2021 in China using long-term Active Fire/Hotspots (ACF) data has been constructed to monitor and analyze large-scale industrial heat sources. Firstly, density segmentation method based on an improved k-means algorithm using long-term ACF data and spatial topological correlation analysis was conducted to build industrial heat sources. Then, 4410 industrial heat sources were obtained between 2012 and 2021 in China, with an identification accuracy of 95.08% by manual verification using high-resolution remote sensing images and point of interest (POI) data. Finally, the trend in the spatio-temporal variation of industrial heat sources was analyzed using long-term series. The results from 2012 to 2021 showed that the spatial distribution of industrial heat sources in China exhibits local aggregation and a gradual shift from east to west.And,the number of industrial heat sources in China has followed a trend of an initial increase from 2012 to 2014, followed by a decrease since 2014, consistent with national energy reform-related policies.The result of this study indicated the temporal variation of industrial heat sources, enhanced the accuracy of fire points category identification, and demonstrated potential for advancing energy efficiency, emission reduction, and sustainable development in China.</p>
Umbilical cord as a long-term source of activatable MSC for immunomodulation
GEO Series GSE117901. Homo sapiens. 21 samples. Type: Expression profiling by array.
Input data for manuscript "An open-source low-cost sensor for SNR-based GNSS reflectometry: Design and long-term validation towards sea level altimetry"
<p>Input data for Fagundes et al. (2021), "An open-source low-cost sensor for SNR-based GNSS reflectometry: Design and long-term validation towards sea level altimetry", GPS Solutions (in press). <a href="https://www.researchgate.net/publication/341946011">preprint</a></p>
Fermi LAT Long-Term Transient Source Catalog
The First Catalog of Long-Term Transient Sources detected by Fermi Large Area Telescope (LAT) comprises of 142 unique, transient sources that were detected on monthly time intervals during Fermi-LAT operations. The monthly time scale allows to identify transient and variable sources that were not yet reported in other Fermi-LAT catalogs. The monthly datasets were analyzed using a wavelet-based source detection algorithm that provided the candidate new transient sources. The search was limited to the extragalactic regions of the sky to avoid the dominance of the Galactic diffuse emission at low Galactic latitudes. The transient candidates were then analyzed using the standard Fermi-LAT maximum likelihood analysis method. All sources detected with a statistical significance above 4 sigma in at least one monthly bin were listed in the final catalog. This database table was ingested by the HEASARC in September 2021 and is based upon file downloaded from the Space Science Data Center (SSDC) Fermi-1FLT <a href="https://www.ssdc.asi.it/fermi1flt/">website</a>. This is a service provided by NASA HEASARC .
XTE All-Sky Monitor Long-Term Observed Sources
The XTEASMLONG table was created for the purpose of providing a complete listing of RXTE's All-Sky Monitor (ASM) observations of sources. It is based on information culled from the definitive 1-dwell long-term ASM light curve data products. These data products are available for downloading at <a href="https://heasarc.gsfc.nasa.gov/FTP/xte/data/archive/ASMProducts/definitive_1dwell/lightcurves/">https://heasarc.gsfc.nasa.gov/FTP/xte/data/archive/ASMProducts/definitive_1dwell/lightcurves/</a> The XTEASMLONG table is updated usually every week or two whenever new definitive ASM data products are delivered to the RXTE GOF from MIT where the definitive ASM processing is done. This is a service provided by NASA HEASARC .
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.