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1,393
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1,393 results for “traces”
Effect of Parenteral Trace Element Supplementation on RNA-sequencing Profile of Peripheral Blood in Peripartum Dairy Cows
GEO Series GSE231491. Bos taurus. 12 samples. Type: Expression profiling by high throughput sequencing.
Tracing immunological interaction in trimethylamine N-oxide hydrogel-derived zwitterionic microenvironment during promoted diabetic wound regeneration
GEO Series GSE267890. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Olfactory expression of trace amine-associated receptors requires cooperative cis-acting enhancers
GEO Series GSE171241. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing.
Traces of scientific workflows
<p>This is an anonymized dataset containing the traces we obtained when we executed our scientific workflows.</p>
Tracing Data for Unveiling the Energy Vampires: A Methodology for Debugging Software Energy Consumption
Open the record for dataset details and reuse information.
Data Traces
<p>System call traces obtained by the execution of faulty Puppet modules along with the faults reported by our approach.</p>
Tracing the cellular origin of in-stent restenosis
<p>The goal of this study is to elucidate the cellular origin and underlying mechanisms of cells contributing to neointima formation following stent placement.</p>
Arctic campaign 2020 - YAK-AEROSIB - trace gas measurements
<p>Trace gas measurements during the 2020 YAK-AEROSIB follow-up campaign </p>
Data and code archive for project "Tracing caffeine and its metabolite in wastewater to understand the spread of SARS-CoV-2"
<p>This dataset/code archive included all the data and R codes that were used to explore the universal and robust wastewater biomarkers for population normalization in the SARS-CoV-2 wastewater-based epidemiology. There are nine R code files to produce figures and tables. The data included:</p> <ol> <li>Raw data of weekly biomarkers (caffeine, paraxanthine, and PMMoV) wastewater concentrations, weekly new COVID-19 case numbers, SARS-CoV-2 N1/N2 copies in wastewater, wastewater flow rate <ul> <li>A total of 2,624 wastewater samples (41 weeks) were collected weekly from May 2021- April 2022 from 64 wastewater treatment plants across Missouri, US;</li> <li>pMMoV data was only available from Sep 13 2021-April 2022 for Missouri data;</li> <li>Validation dataset from 10 wastewater treatment plants across Wisconsin, US, to test the relationship between wastewater biomarkers and population. </li> </ul> </li> <li>Downloaded Apple mobility data during the pandemic </li> <li>Validation dataset for wastewater flowrate estimation using paraxanthine concentrations.</li> </ol>
Activity modeling under uncertainty by trace of objects in smart homes
A typical resident of a smart home can be an Alzheimer patient that forgets sometimes to complete the activities that he begins. The key point to assist the smart home resident is to model the activities and discover correct realization patterns of activities. To accomplish this task, we apply sensors to provide primary data about realization patterns of actions, operations, plans, goals and generally any objective that the smart home resident may desire to do. In the consequence, by applying fuzzy clustering techniques, we are able to mine sensor data to retrieve the realization patterns of activities, and so the prediction patterns of intentions are recognizable. Comparing the realization patterns with prediction patterns of activities, we would be able to predict the intention of the resident about the activity that the resident considers to realize. In this way, we would be able to provide hypotheses about the resident goals and his possible goal achievement’s defects. Spatiotemporal aspects of daily activities such as movement of objects are surveyed to discover the patterns of activities realized by the smart homes residents. In this research, uncertainty is considered as a property of activity recognition.
Chemical ionization quadrupole mass spectrometer with an electrical discharge ion source for atmospheric trace gas measurement (dataset)
<p>Data from field studies provided in Fig. 6 (CYPHEX), 7 (NOTOMO) and 8 (IBAIRN) of</p> <p>Eger, P. G., Helleis, F., Schuster, G., Phillips, G. J., Lelieveld, J., and Crowley, J. N.: Chemical ionization quadrupole mass spectrometer with an electrical discharge ion source for atmospheric trace gas measurement, Atmos. Meas. Tech., 12, 1935–1954, https://doi.org/10.5194/amt-12-1935-2019, 2019.</p>
Workflow memoization traces for a walk in the graph
<p>This is a collection of anonymized traces describing the execution of workflows on a POWER8 and a x86-64 cluster. These traces are the results of the experimental evaluation of the workflow memoization method that the paper "A walk in the graph: Fast, flexible, and high-fidelity cache keys for workflow memoization" introduces.</p>
NAAMES C-130 Trace Gas In Situ Data, Version 1
NAAMES_TraceGas_AircraftInSitu_Data are in situ trace gas measurements collected onboard the C-130 aircraft during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). These measurements were collected from November 4, 2015 – November 29, 2015, May 11, 2016 – June 5, 2016 and August 30, 2017-September 22, 2017 over the North Atlantic Ocean. The primary objective of NAAMES was to resolve key processes controlling ocean system function, their influences on atmospheric aerosols and clouds and their implications for climate. The airborne products link local-scale processes and properties to the larger scale continuous satellite record. Data collection for this product is complete. The NASA North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) project was the first NASA Earth Venture – Suborbital mission focused on studying the coupled ocean ecosystem and atmosphere. NAAMES utilizes a combination of ship-based, airborne, autonomous sensor, and remote sensing measurements that directly link ocean ecosystem processes, emissions of ocean-generated aerosols and precursor gases, and subsequent atmospheric evolution and processing. Four deployments coincide with the seasonal cycle of phytoplankton in the North Atlantic Ocean: the Winter Transition (November 5 – December 2, 2015), the Bloom Climax (May 11 – June 5, 2016), the Deceleration Phase (August 30 – September 24, 2017), and the Acceleration Phase (March 20 – April 13, 2018). Ship-based measurements were conducted from the Woods Hole Oceanographic Institution Research Vessel Atlantis in the middle of the North Atlantic Ocean, while airborne measurements were conducted on a NASA Wallops Flight Facility C-130 Hercules that was based at St. John's International Airport, Newfoundland, Canada. Data products in the ASDC archive focus on the NAAMES atmospheric aerosol, cloud, and trace gas data from the ship and aircraft, as well as related satellite and model data subsets. While a few ocean-remote sensing data products (e.g., from the high-spectral resolution lidar) are also included in the ASDC archive, most ocean data products reside in a companion archive at SeaBass.
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.