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6,498 results for “Physicality”
Dataset for the intervention effects and long-term changes in physical activity and cardiometabolic outcomes among children at risk of noncommunicable diseases in South Africa
<p>Dataset used to evaluate the short-term effects of the physical and health <em>KaziKidz</em> intervention on cardiometabolic risk factors and the long-term changes thereof among school-aged children at risk of NCDs from disadvantaged communities in South Africa.</p> <p>It encompasses anonymized, unique, identification numbers, anthropometric and clinical measures, such as blood pressure, blood sugar and blood lipids, and Actigraphy-measured physical activity levels. Assigned categories to each cardiovascular risk factor and the overall classification as at risk or not is available too.</p>
Predicting International and Internal Migration in Guatemala with Social, Physical and Climatic Variables (Data)
<p>Accompanying data for the Depsky and Pons (2023) PLoS ONE publication - Predicting International and Internal Migration in Guatemala with Social, Physical and Climatic Variables.</p> <p>This repository contains tables of the raw 2018 Guatemalan national census values at the individual, household, and residence levels, as well as its migration-specific data table. Municipality-average climate values from ERA5-Land are provided as well, in addition to a shapefile of the municipal boundaries. All standardized outcome and predictor variables used for each of the five models are provided as separate tables as well.</p>
The influence of twin tunnel excavation on single and group pile loading by physical modeling
<p>This study uses small-scale physical models to assess the interaction between piles and twin tunnels, considering varying tunnel distances and surface loads. The excavation process of the tunnels is simulated by gradually releasing air pressure from rubber tubes while hydraulic jacks apply loads to aluminum piles. Surface linear variable differential transformers (LVDTs) and strain gauges are utilized for measuring pile responses. Data related to bending moment and axial forces extracted from tests are also provided.</p>
Comparison of children's physical activity profiles before and after COVID-19 lockdowns - dataset
<p>This dataset represents a subset of the Active-6 data used to produce the children's activity profiles reported in the manuscript 'Comparison of children's physical activity profiles before and after COVID-19 lockdowns: a latent profile analysis'. Included in this repository is the dataset and a data dictionary.</p> <p>This dataset has been made available so that future researchers can replicate the study findings using the data. If you wish to use the data for any purpose other than replicating the study findings, please contact the Principal Investigator Professor Russ Jago (russ.jago@bristol.ac.uk) to discuss this.</p>
Delving into the relationship between regular physical exercise and cardiac interoception in two cross-sectional studies.
<p>This repository contains raw data from two studies corresponding to the article "No evidence of a relationship between regular physical exercise and cardiac interoception" by Yoris et al. In Study I, 45 resting EEG files are included for the Active (N = 24) and Inactive (N = 21) groups, both for the eyes closed and eyes open conditions. For Study II, there are 60 resting EEG files (30 Active/30 Inactive). Data are in EEGLAB format .set/fdt. The project is publicly available for free use and can be accessed at <a href="https://osf.io/xrsgn/">https://osf.io/xrsgn/</a>.</p>
Selected BMRB 1D 1H NMR data and physical chemistry values compiled from literature
<p>This dataset contains a collection of a few 1D 1H nuclear magnetic resonance (NMR) spectroscopy experiment data from the Biological Magnetic Resonance Data Bank (BMRB). I collected them for reference on Zenodo because the BMRB in recent years have switched servers and adopted new web APIs, and I want to have this data in a data archive for ease of reproducing the results in my work. Please cite (doi: 10.1093/nar/gkac1050) if you use the BMRB data from this dataset, or consider downloading from their website.</p> <p>This dataset also contains my compiled lists of physical chemistry NMR parameters (chemical shift, J-coupling) from literature and public domain sources for select compounds. One source is the Guided Ideographic Spin System Model Optimization (GISSMO) website, which is based on (DOI: 10.1021/acs.analchem.7b02884) and (DOI: 10.1021/acs.analchem.8b02660). Another source I used is (DOI: 10.1002/nbm.3336). Please cite these sources in addition to this dataset if you use any of the physical chemistry information in this dataset. See the read me file for the format details.</p> <p>I do not guarantee the accuracy of any of the data in this dataset.</p>
Soil physical quality of a tropical sandy Ferralsol
<p>Dados de pesquisa da dissertação de mestrado do primeiro autor, vinculado à Universidade Estadual de Maringá, Maringá, BR.</p>
Reanalysis and future climate projections of the physical state of the Gulf of Riga 1993-2100
<p><strong>Data sets</strong></p> <p>There are two data sets: (1) reanalysis (1993-2021) and (2) future projection (2015-2100). Future projection data set is split into 10 files.<br> The dataset provides gridded monthly mean values of physical parameters in the Gulf of Riga, Baltic Sea. The variables of the dataset of the physical state of the Gulf of Riga are as follows (Long name: <em>acronym</em>, <em>units</em>)</p> <ul> <li>Potential temperature: <em>thetao, </em>°<em>C</em></li> <li>Sea water salinity: <em>s, g/kg</em></li> <li>Eastward sea water velocity: <em>ocu, m/s</em></li> <li>Northward sea water velocity: <em>ocv, m/s</em></li> <li>Deviation of sea-level from the mean sea level: <em>zos, m</em></li> <li>Sea ice area fraction <em>siconc</em>, m<sup>2</sup>/ m<sup>2</sup></li> <li>Sea ice thickness: <em>sithick, m</em></li> <li>Bathymetry: <em>bathymetry, m </em>(included only in reanalysis data set)</li> </ul> <p>The grid size of the dataset is 15 (depth) x 203 (latitude) x 187 (longitude). The horizontal grid spacing is 0.5 nm; the vertical grid has 15 depth layers – 2 m deep surface layer and 4 m step for deeper layers. The time resolution of the dataset is monthly – the monthly mean value is provided in the 1st day of the month in time dimension.<br> The original climatic calculations are based on the University of Latvia (UL) set-up of the Hiromb-BOOS model routinely implemented for the operational oceanography in the Baltic Sea and the Gulf of Riga in Latvia. Its parametrization is empirically suited for climatical reanalysis in the Gulf of Riga domain. The original output of the model run is hourly data series.</p> <p><strong>Reanalysis</strong></p> <p>Time period: 1993-2021 (29 years).<br> The main characteristics of the input data and approach for the reanalysis run are as follows:</p> <ul> <li>EMODNET2020 bathymetry.</li> <li>Initial conditions – bias corrected Copernicus Marine Service (CMS).</li> <li>Atmospheric forcing – ERA5 meteorology with improved cloudiness.</li> <li>Boundary conditions from CMS 1993-2018 reanalysis and CMS operational archive (2019-2021) with bias correction for waterlevel in CMS forecast.</li> <li>River inflow – 15 main rivers taken into consideration according to E-HYPE hydrological model data. E-HYPE discharge multiplied by 0.75.</li> <li>Tides: astronomic calculations.</li> </ul> <p><strong>Future climate projection</strong></p> <p>Time period: 2015-2100 (86 yrs).<br> The main characteristics of the input data and approach for the future climate projections run are as follows:</p> <ul> <li>Emodnet2020 bathymetry.</li> <li>Initial conditions – bias corrected Copernicus Marine Service (CMS).</li> <li>Boundary conditions from downscaled CMIP6 climate projection model NorESM2-MM_ssp585_r1i1p1f1 (search string – project:'CMIP6', source_id:'NorESM2-MM', experiment_id:'ssp585', variant_label:'r1i1p1f1').</li> <li>River inflow – 15 main rivers taken into consideration according to E-HYPE climatological model (SMHI_RCA4_HadGEM2-ES_rcp45). E-HYPE discharge multiplied by 1.093.</li> <li>The past period data was used for the downscaling: <ul> <li>ERA5 reanalysis data was used for the downscaling of the atmospheric forcing time series of CMIP6 climate projection model,</li> <li>CMS reanalysis model data was used for the downscaling of the sea state time series.</li> </ul> </li> <li>Downscaled variables: eastward and northward components of the near surface wind, air temperature, air pressure, water temperature, water salinity, sea level.</li> </ul>
DS4. Experimental evaluation of the TERAWAY physical layer system, implementing optical injection locking and optical beamforming, using bulk components
<p>This set comprises experimental results from the performance evaluation of the TERAWAY system in the physical layer, implementing bulk components. This performance evaluation focused on the optical generation of millimeter-wave signals implementing injection locking technique by means of inserting an optical frequency comb into the reference optical laser source, the fiber transmission of the optical signals, as well as the processing of this signal via an optical beamforming network.</p> <p>The data set consists of multiple waveforms that correspond to 16-QAM electrical signals of 500 MBaud symbol rate, at a central frequency of 60 GHz. These waveforms were obtained directly after the photodetection stage that consists of two high-speed photodetectors in order to emulate an optical beamforming scenario. The set is separated into different folders that correspond to the injection-locked and unlocked scenarios, both in back-to-back configuration and after a 25 km transmission of the signal through an optical fiber. Each folder contains the waveforms of the electrical signals, as they were generated at the photodetection stage, under various optical power values.</p>
Physical link between effective viscosity and electrical resistivity for dislocation creep in upper mantle and its application in Northwest Xinjiang, China
<p>Cross-section of electrical resistivity extracted from the preferred 3-D resistivity model from Liu (2022)</p> <p>Format: X (Km), Z (Km), rho (ohm-m), T (K)</p> <p>Notes: Temperature(T) extracted from Sun et al., 2022, available at https://doi.org/10.5281/zenodo.6459746</p> <p> (lat, lon) of the ends of the profile: (,40.71,79.8300), -->, (,46.84,86.0700)</p>
philip928lin/Flood-Risks-of-Cyber-physical-Attacks-in-a-Smart-Storm-Water-System: Flood Risks of Cyber-physical Attacks in a Smart Storm Water System
<p>This is the code archive for the publication "Flood Risks of Cyber-physical Attacks in a Smart Storm Water System" in Water Resources Research.</p>
Physical Therapy and Occupational Therapy After Transcatheter Aortic Valve Replacement
ClinicalTrials.gov study NCT03117296. IPD Sharing: NO. Countries: 1. Publications: 3.
Reducing Hopelessness Through Improved Physical Activity in Adults With Heart Disease: With COVID-19 Considerations
ClinicalTrials.gov study NCT03907891. IPD Sharing: YES. Countries: 1. Publications: 5.
Molecular Transducers of Physical Activity Consortium (MoTrPAC) - Pediatric Protocol
ClinicalTrials.gov study NCT04151199. IPD Sharing: YES. Countries: 1. Publications: 1.
Comparative Effectiveness of Early Physical Therapy Versus Usual Care for Low Back Pain
ClinicalTrials.gov study NCT01556581. IPD Sharing: YES. Countries: 1. Publications: 5.
Implementing Group Physical Therapy (PT) for Veterans With Knee Osteoarthritis (Group PT): Function QUERI 2.0
ClinicalTrials.gov study NCT05282927. IPD Sharing: YES. Countries: 1. Publications: 3.
Preventing Posttraumatic Osteoarthritis With Physical Activity Promotion
ClinicalTrials.gov study NCT04906499. IPD Sharing: YES. Countries: 1. Publications: 26.
Targeting Physical Health in Schizophrenia: Physical Activity Can Enhance Life Randomized Control Trial
ClinicalTrials.gov study NCT04173572. IPD Sharing: YES. Countries: 1. Publications: 0.
Molecular Transducers of Physical Activity Consortium
ClinicalTrials.gov study NCT03960827. IPD Sharing: YES. Countries: 1. Publications: 1.
Effect of Exercise Training on Physical, Cognitive, and Behavioral Function in People With TBI
ClinicalTrials.gov study NCT02504866. IPD Sharing: YES. Countries: 1. Publications: 3.
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.