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6,452 results for “Application”
Epigenetic application of ATAC-seq based on Tn5 transposase purification technology
GEO Series GSE199016. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
The 14 pairs of FF and FFPE data for the application of 95GC to FFPE in 2019
GEO Series GSE236723. Homo sapiens. 28 samples. Type: Expression profiling by array.
Pilot application of hepatic cDNA microarray of the sentinel fish striped sea bream as environmental biomarker
GEO Series GSE14673. Lithognathus mormyrus. 3 samples. Type: Expression profiling by array.
Application of Functional Genomics to the Study of Solanacea's Defense Mechanisms against Xanthomonas sp. Pathogenicity
GEO Series GSE8276. Nicotiana benthamiana; Solanum tuberosum. 11 samples. Type: Expression profiling by array.
SNIAPE: Sensor Network and IoT Application Performance Evaluation Benchmark
<p>This repository is currently anonymised for submission. It contains the code, data, questionnaire and the full report version of SNIAPE, which is a sensor network and IoT application performance evaluation benchmark</p>
Landmark Data of Objects as Basis for Navigation and Wayfinding Applications
<p>This dataset is the result of a data collection project and includes objects of the inner city of Augsburg and their so-called landmark dimensions consisting of visual, semantic, and structural dimensions. All the attributes of these dimensions are available for 47 objects - mainly buildings but also fountains and monuments - located at street intersections. For 302 further objects the attributes color and surface area of the visual dimension are available. The dataset for the landmark dimensions is based on OpenStreetMap data and additional data which was collected during a field study. The dataset might be used as a basis for landmark identification, validation of landmark models, as well as for landmark integration as a basis for navigation and wayfinding applications.</p>
Decomposing the complexity of heart-rate variability by the multifractal–multiscale approach to detrended fluctuation analysis: an application to low-level spinal cord injury
<p>Raw data for reproducing (figure 2) and the main results of the paper: doi: 10.1088/1361-6579/ab2b4a</p>
Sub-5 min RP-UHPLC-TIMS for high-throughput untargeted lipidomics and its application to multiple matrices
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A Digital Fragmentation Method More Applicable to Artificial Intelligence Drug Design
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Implementation of Battery Thermal Management System for High-Performance Electromobility Application: A Hybrid Cold Plate and Phase Change Material Approach
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Optimal sizing and lifetime investigation of second life lithium-ion battery for grid-scale stationary application
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Metaverse Gaming Application Addiction
<p>Data set for an empirical study on Metaverse Gaming Application Addiction</p>
A flexible framework for N-mixture occupancy models: applications to breeding bird surveys
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A Flexible Framework for N-mixture Occupancy Models of Count Data Applications to Breeding Bird Surveys
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Data associated with "RxTrends: An R Shiny Application for Visualising Open Data on Prescribed Medications in Ireland"
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Material characterization for circular automotive applications
<p>Characterization of materials employed in ECOBULK circular solutions for the automotive sector.</p>
Taxonomic and functional diversity of the microbiome in a jet fuel contaminated site as revealed by combined application of in situ microcosms with metagenomic analysis
<p>Natural attenuation represents all processes that govern contaminant mass removal, which mainly occurs via microbial degradation in the environment. Although this process is intrinsic its rate and efficiency depend on multiple factors. This study aimed to characterize the microbial taxonomic and functional diversity in different aquifer sediments collected in the saturated zone and <em>in situ</em> microcosms (BACTRAP®s) amended with hydrocarbons (<sup>13</sup>C-labeled and non-labeled benzene, toluene and naphthalene) using 16S rRNA gene and “<em>shotgun</em>” Illumina high throughput sequencing at a jet-fuel contaminated site. The BACTRAP®s were installed to assess hydrocarbon metabolism by native bacteria. Results indicated that Proteobacteria, Actinobacteria and Firmicutes were the most dominant phyla (~98%) in the aquifer sediment samples. Meanwhile, in the benzene- and toluene-amended BACTRAP®s the phyla Firmicutes and Proteobacteria accounted for about 90% of total community. In the naphthalene-amended BACTRAP®, members of the SR-FBR-L83 family (Order Ignavibacteriales) accounted for almost 80% of bacterial community. Functional annotation of metagenomes showed that only the sediment sample located at the source zone border and with the lowest BTEX concentration, has metabolic potential to degrade hydrocarbons aerobically. On the other hand, <em>in situ</em> BACTRAP®s allowed enrichment of hydrocarbon-degrading bacteria. Metagenomic data suggest that fumarate addition is the main mechanism for hydrocarbon activation of toluene. Also, indications for methylation, hydroxylation and carboxylation as activation mechanisms for benzene anaerobic conversion were found. After 120 days of exposure in the contaminated groundwater, the isotopic analysis of fatty acids extracted from BACTRAP®s demonstrated the assimilation of isotopic labeled compounds in the cells of microbes expressed by strong isotopic enrichment. We propose that the microbiota in this jet-fuel contaminated site has metabolic potential to degrade benzene and toluene by a syntrophic process, between members of the families Geobacteraceae and Peptococcaceae (genus <em>Pelotomaculum</em>), coupled to nitrate, iron and/or sulfate reduction.</p>
Factors associated with emotional exhaustion in healthcare professionals involved in the COVID-19 pandemic: an application of the job demands-resources model
<p>Dataset from Barello S, Caruso R, Palamenghi L, Nania T, Dellafiore F, Bonetti L, Silenzi A, Marotta C, Graffigna G. Factors associated with emotional exhaustion in healthcare professionals involved in the COVID-19 pandemic: an application of the job demands-resources model. Int Arch Occup Environ Health. 2021 Nov;94(8):1751-1761. doi: 10.1007/s00420-021-01669-z. Epub 2021 Mar 3. PMID: 33660030; PMCID: PMC7928172.</p> <p>Abstract</p> <p><strong>Purpose: </strong>The purpose of the present cross-sectional study is to investigate the role of perceived COVID-19-related organizational demands and threats in predicting emotional exhaustion, and the role of organizational support in reducing the negative influence of perceived COVID-19 work-related stressors on burnout. Moreover, the present study aims to add to the understanding of the role of personal resources in the Job Demands-Resources model (JD-R) by examining whether personal resources-such as the professionals' orientation towards patient engagement-may also strengthen the impact of job resources and mitigate the impact of job demands.</p> <p><strong>Methods: </strong>This cross-sectional study involved 532 healthcare professionals working during the COVID-19 pandemic in Italy. It adopted the Job-Demands-Resource Model to study the determinants of professional's burnout. An integrative model describing how increasing job demands experienced by this specific population are related to burnout and in particular to emotional exhaustion symptoms was developed.</p> <p><strong>Results: </strong>The results of the logistic regression models provided strong support for the proposed model, as both Job Demands and Resources are significant predictors (OR = 2.359 and 0.563 respectively, with p < 0.001). Moreover, healthcare professionals' orientation towards patient engagement appears as a significant moderator of this relationship, as it reduces Demands' effect (OR = 1.188) and increases Resources' effect (OR = 0.501).</p> <p><strong>Conclusions: </strong>These findings integrate previous findings on the JD-R Model and suggest the relevance of personal resources and of relational factors in affecting professionals' experience of burnout.</p>
Dataset for McClelland et al. 2022. Infrequent compost applications increased plant productivity and soil organic carbon in irrigated pasture but not degraded rangeland. Agriculture, Ecosystems, and Environment.
<p>Raw data files accompanying the published article "Infrequent compost applications increased plant productivity and soil organic carbon in irrigated pasture but not degraded rangeland" in <em>Agriculture, Ecosystems, and Environment</em>. <a href="https://authors.elsevier.com/a/1etJPcA-Ik6yb">https://authors.elsevier.com/a/1etJPcA-Ik6yb</a></p> <p>Units for response variables in .csv files are as follows. Please reach out to scm229@cornell.edu with any questions about using the files or the data within.</p> <p>--</p> <p>Aboveground biomass: total (Mg ha-1), carbon (Mg C ha-1), nitrogen (kg N ha-1)</p> <p>Bulk density: g cm-3</p> <p>Respiration (Rs): micro mol m-2 s-1</p> <p>Roots: Mg C ha-1</p> <p>Soil C and N: organic and inorganic carbon (Mg C ha-1), nitrogen (Mg N ha-1)</p> <p> </p>
Data Deposit for "Ligation-based Assay for Variant-Typing without Sequencing: Application to SARS-CoV-2 Variants of Concern"
<p>No description provided.</p>
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.