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1,670 results for “FORCE”
Pure POPC membrane simulations with 790 mM CaCl2 with the CHARMM-Drude2023 force field (OpenMM)
<p>214.85 ns MD simulation of pure POPC membrane using Charmm-Drude2023 polarizable force field (</p> <p><strong>Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion:<br> Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids</strong></p> <p><strong>)</strong></p> <p>.The system contains 128 POPC lipids, 91 CaCl2, and 6400 SWM4 water molecules.</p> <p>Before running the Drude simulation, the system has been equilibriated using Charmm36 force field for 200 ns. The last frame of that simulation was used to generate Drude polarizable model. Frame saving frequency is 10ps. There are 21485 frames in this trajectory.</p>
Pure POPC membrane simulations with 350 mM NaCl with the CHARMM-Drude2023 force field (OpenMM)
<p>223.97 ns MD simulation of pure POPC membrane using Charmm-Drude2023 polarizable force field (</p> <p><strong>Drude Polarizable Lipid Force Field with Explicit Treatment of LongRange Dispersion:<br> Parametrization and Validation for Saturated and Monounsaturated Zwitterionic Lipids</strong></p> <p><strong>)</strong></p> <p>.The system contains 128 POPC lipids, 41 NaCl, and 6400 SWM4 water molecules.</p> <p>Before running the Drude simulation, the system has been equilibriated using Charmm36 force field for 200 ns. The last frame of that simulation was used to generate Drude polarizable model. Frame saving frequency is 10ps. There are 22397 frames in this trajectory.</p>
data collection for machine learning using eddy force function data
<p>Data for "On the choice of training data for machine learning of geostrophic mesoscale turbulence". Contains</p> <ul> <li>qgm2 code (from James Maddison, University of Edinburgh) for generating the data</li> <li>codes to process data from qgm2 for machine learning, and train convolutional neural networks to use the data</li> <li>sample data</li> <li>processed data to reproduce plots in the paper</li> </ul> <p>Files collected in different zip files to avoid the need to download the whole pack in one go. See readme for data/folder structure.</p>
Table 5 for the Study: "Correlation Study: Triggering and Magnitude of Earthquakes in Italy (≥M4.3) in Relation to the Positions and Gravitational Forces of the Sun, Moon, and Planets Relative to Earth."
<p><strong>Random sample extraction of 145 earthquakes.</strong></p><p>In this short video we illustrate an example of the method used for the random sample extraction of 145 earthquakes for the Study: <i>"Correlation Study: Triggering and Magnitude of Earthquakes in Italy (≥M4.3) in Relation to the Positions and Gravitational Forces of the Sun, Moon, and Planets Relative to Earth" </i>for Section 2.10.1.</p><p> </p>
Biogeochemical dataset for ''Persistent Equatorial Pacific iron limitation under ENSO forcing" by Browning et al.
<p>Biogeochemical dataset for ''Persistent Equatorial Pacific iron limitation under ENSO forcing" by Browning et al.</p>
CICE gx1 JRA55do Forcing Data by year - 2023.07.03
<p>These files contain the gx1 JRA55do forcing data by year for CICE. </p> <p>The latest information about CICE forcing data and files can be found at the GitHub Resource Index: <a href="https://github.com/CICE-Consortium/About-Us/wiki/Resource-Index">https://github.com/CICE-Consortium/About-Us/wiki/Resource-Index</a> under the "Input Data" link. This is a dataset remapped from the original JRA55do dataset (Tsujino et al. 2018; https://doi.org/10.1016/j.ocemod.2018.07.002; version 1.5.0.1).</p> <p>These data are provided by the CICE Consortium (<a href="https://github.com/CICE-Consortium">https://github.com/CICE-Consortium</a>).</p>
CICE tx1 JRA55do Forcing Data by year - 2023.07.03
<p>These files contain the tx1 JRA55do forcing data by year for CICE. </p> <p>The latest information about CICE forcing data and files can be found at the GitHub Resource Index: <a href="https://github.com/CICE-Consortium/About-Us/wiki/Resource-Index">https://github.com/CICE-Consortium/About-Us/wiki/Resource-Index</a> under the "Input Data" link. This is a dataset remapped from the original JRA55do dataset (Tsujino et al. 2018; https://doi.org/10.1016/j.ocemod.2018.07.002; version 1.5.0.1).</p> <p>These data are provided by the CICE Consortium (<a href="https://github.com/CICE-Consortium">https://github.com/CICE-Consortium</a>).</p>
CICE JRA55 gx1 forcing by year. 2020.03.20
<p>Breaking the JRA55 forcing into individual years. Note that this version just changes the names of the files to include the string "gx1".</p>
Table 10 for the Study: "Correlation Study: Triggering and Magnitude of Earthquakes in Italy (≥M4.3) in Relation to the Positions and Gravitational Forces of the Sun, Moon, and Planets Relative to Earth."
<p><strong>Details of the 200 analyzed earthquakes encompassing values and indices for σFR Parameters A, B, and the percentile of Alert Time across the three Analysis Lines, for Section 3.2.6.</strong></p><p>It contains the 6 Excel calculation files: 2 excel sheets for each of the 3 lines of analysis.</p><p>In case of display problems or missing data: </p><p>the file <a href="https://zenodo.org/api/files/0b63ead2-6802-4089-849b-949758da13fd/Eqs%201-112%20-%20All%20Planets%20FR%20Graphs.xlsx">Eqs 1-112 - All Planets FR Graphs.xlsx</a> is available also on the Drive: <a href="https://docs.google.com/spreadsheets/d/1hxAsh6BZZH70z7C2iBVI4LqNsbl7gCcGmRJIX9CVLUA/edit?usp=sharing">https://docs.google.com/spreadsheets/d/1hxAsh6BZZH70z7C2iBVI4LqNsbl7gCcGmRJIX9CVLUA/edit?usp=sharing</a></p><p>the file <a href="https://zenodo.org/api/files/0b63ead2-6802-4089-849b-949758da13fd/Eqs%20113-200%20-%20All%20Planets%20FR%20Graphs.xlsx">Eqs 113-200 - All Planets FR Graphs.xlsx</a> is available also on the Drive: <a href="https://docs.google.com/spreadsheets/d/1bGcgwL5R_GPO3aQO3tdscGFjPrFdIJ-s16yQE9_eMXY/edit?usp=sharing">https://docs.google.com/spreadsheets/d/1bGcgwL5R_GPO3aQO3tdscGFjPrFdIJ-s16yQE9_eMXY/edit?usp=sharing</a> </p><p>the file <a href="https://zenodo.org/api/files/0b63ead2-6802-4089-849b-949758da13fd/Eqs%201-112%20-%20Moon%20and%20Sun%20FR%20Graphs.xlsx">Eqs 1-112 - Moon and Sun FR Graphs.xlsx</a> is available also on the Drive: <a href="https://docs.google.com/spreadsheets/d/1CLGRDgp-eyGMUZjvNjIfuxI-7fzUsY0NYs0qyAs1XRE/edit?usp=sharing">https://docs.google.com/spreadsheets/d/1CLGRDgp-eyGMUZjvNjIfuxI-7fzUsY0NYs0qyAs1XRE/edit?usp=sharing</a></p><p>the file <a href="https://zenodo.org/api/files/0b63ead2-6802-4089-849b-949758da13fd/Eqs%20113-200%20-%20Moon%20and%20Sun%20FR%20Graphs.xlsx">Eqs 113-200 - Moon and Sun FR Graphs.xlsx</a> is available also on the Drive: <a href="https://docs.google.com/spreadsheets/d/15CYvjS-4-FxKFLcYy4jIKKiFuiWYxSM89zzOliodyFg/edit?usp=sharing">https://docs.google.com/spreadsheets/d/15CYvjS-4-FxKFLcYy4jIKKiFuiWYxSM89zzOliodyFg/edit?usp=sharing</a></p><p>the file <a href="https://zenodo.org/api/files/0b63ead2-6802-4089-849b-949758da13fd/Eqs%201-112%20-%20without%20Moon%20and%20Sun%20FR%20Graphs.xlsx">Eqs 1-112 - without Moon and Sun FR Graphs.xlsx</a> is available also on the Drive: <a href="https://docs.google.com/spreadsheets/d/1zzwugZ4ZZzy6vnQP_SBrjjYaL5fjul29CBZS2Qheq_E/edit?usp=sharing">https://docs.google.com/spreadsheets/d/1zzwugZ4ZZzy6vnQP_SBrjjYaL5fjul29CBZS2Qheq_E/edit?usp=sharing</a> </p><p>the file <a href="https://zenodo.org/api/files/0b63ead2-6802-4089-849b-949758da13fd/Eqs%20113-200%20-%20without%20Moon%20and%20Sun%20FR%20Graphs.xlsx">Eqs 113-200 - without Moon and Sun FR Graphs.xlsx</a> is available also on the Drive: <a href="https://docs.google.com/spreadsheets/d/12phjR1r1pQXqzdclBCbV76nXpne4B9VqksDj4RqgEKw/edit?usp=sharing">https://docs.google.com/spreadsheets/d/12phjR1r1pQXqzdclBCbV76nXpne4B9VqksDj4RqgEKw/edit?usp=sharing</a></p>
Table 4 for the Study: "Correlation Study: Triggering and Magnitude of Earthquakes in Italy (≥M4.3) in Relation to the Positions and Gravitational Forces of the Sun, Moon, and Planets Relative to Earth."
<p><strong>Table 5, APPENDIX </strong>for the Study: "<i>Correlation Study: Triggering and Magnitude of Earthquakes in Italy (≥M4.3) in Relation to the Positions and Gravitational Forces of the Sun, Moon, and Planets Relative to Earth</i>," for Section 2.10.</p><p>Contains the list of M>4.3 earthquakes that occurred in Italy from 1600 to 2022 AD and the list of earthquakes analyzed.</p>
Active Brownian particles in external force fields: field-theoretical models, generalized barometric law, and programmable density patterns
<p>Supplementary data for the following manuscript: Jens Bickmann, Stephan Bröker, Michael te Vrugt, Raphael Wittkowski, "Active Brownian particles in external force fields: field-theoretical models, generalized barometric law, and programmable density patterns".</p>
Model output for the effects of topography and orbital forcing
<p>modeling data for the Asia</p>
Microstructure-based prediction of hydrodynamic forces in stationary particle assemblies
<p>#Data linked to the manuscript: <br> Microstructure-based prediction of hydrodynamic forces in stationary particle assemblies</p> <p>#Corresponding author:<br> Berend.van.Wachem@gmail.com</p> <p>#Acknowleddgements</p> <p>This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 422037413 - TRR 287. This funding is gratefully acknowledged.</p> <p>#Files<br> - Minkowski tensors and Lagrangian forces computed for all simulations stored in the .csv files<br> - Python script to read Minkowski tensors and Lagrangian forces stored in the .csv files<br> - One flow configuration results with hdf fields files at mean flow Reynolds number 100 and solid volume fraction 0.5.</p> <p>#SimulationResult</p> <p>Note to open the simulation results:</p> <p>The Eulerian fields and Lagrangian particles information are stored in HDF5 files.<br> The relevant fileds are:<br> #Eulerian:<br> - Velocity vector<br> - Pressure<br> - AMR Level<br> - Other information relevant for the coupling between the IBM particles and<br> the fluid<br> <br> #Lagrangian:<br> - Particles coordinates<br> - Particles diameter<br> - Particles hydrodynamic force components<br> - Particles torque components<br> - Particles velocity components<br> - Particles rotational velocity components<br> <br> A .xmf file is provided to read the simulation results in paraview.<br> Only the initial state and the converged state of the simulation are provided due to storage limits.</p>
A platform for dissecting force sensitivity and multivalency in actin networks (supplemental)
<p>These data support the supplemental figures in our publication "<strong>A platform for dissecting force sensitivity and multivalency in actin networks</strong>". Unzip for a README file explaining data. See DOI 8239706 for main figure data. BioRxiv: https://www.biorxiv.org/content/10.1101/2023.08.15.553463v1</p>
Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations (Data)
<p>README file for LBL-ERA5, LBL-GCM, and band datasets used in:<br> Raghuraman et al., 2023, Geophysical Research Letters,<br> "Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations "</p> <p>Point of Contact: Shiv Priyam Raghuraman, shivr@alumni.princeton.edu</p> <p> </p> <p>LBL-ERA5</p> <p>6 files (3 experiments with olr and olr_clr output separately):</p> <p>2003-2021.GFDL.all-2010-o3_*.nc - varying WMGHG,Ts,T,q,clouds, fixed o3</p> <p>2003-2021.GFDL.fo3_*.nc - varying WMGHG and fixed Ts,T,q,clouds,surface albedo,o3</p> <p>2003-2021.GFDL.ff_*.nc - fixed Ts,T,q,clouds,surface albedo, varying o3</p> <p> </p> <p>LBL-GCM (clear-sky only)</p> <p>4 AM4 files:</p> <p>AM4piclim-control.nc (for ERF)</p> <p>AM4piclim-4xCO2_1xCO2IRF.nc (for ERF)</p> <p>AM4piclim-control_STRAT.nc (for SARF)</p> <p>AM4piclim-4xCO2_1xCO2IRF_STRAT.nc (for SARF)</p> <p>4 CM3/AM3 files:</p> <p>CTLAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>EXPAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>CTLAM3CM3_P1_2003C.nc (for IRF)</p> <p>CTLAM3CM3_P1_2021C.nc (for IRF)</p> <p> </p> <p>Band-AM4/MERRA-Total: GFDL AM4 with prescribed SSTs and sea-ice (AMIP) and nudged with MERRA winds</p> <p>2 files:</p> <p>atmos.200001-202112.olr.nc - all-sky OLR</p> <p>atmos.200001-202112.olr_clr.nc - clear-sky OLR</p> <p> </p> <p>Observational and reanalysis files used in paper (AIRS, CERES EBAF and SSF, GISTEMP, ERA5 input data) can be downloaded from their respective websites (see paper's "Open Research" section).</p> <p> </p>
Use of Hand-held Dynamometry to Obtain Objective Measures of Lower Extremity Force Production With Chronic Stroke
ClinicalTrials.gov study NCT05941962. IPD Sharing: NO. Countries: 1. Publications: 7.
The Canadian Armed Forces PEER Study
ClinicalTrials.gov study NCT03625271. IPD Sharing: NO. Countries: 1. Publications: 5.
Influence of Electrode Positioning and Current Type on Fatigue, Force and Discomfort
ClinicalTrials.gov study NCT04200677. IPD Sharing: UNDECIDED. Countries: 1. Publications: 20.
Combination of Force Control Training and Mirror Visual Feedback Device on Stroke Patients on Brain Activation and Hand Function
ClinicalTrials.gov study NCT07150325. IPD Sharing: Not stated. Countries: 1. Publications: 89.
Digital Occlusal Analysis and Bite Force Evaluation of Primary Molars Restored With Zirconia Crowns Using T-Scan
ClinicalTrials.gov study NCT07276841. IPD Sharing: NO. Countries: 1. Publications: 7.
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.