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150 results for “Use of Force”
Individual molecular motors use low forces to bypass roadblocks during collective cargo transport
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A monthly shortwave radiative forcing kernel for surface albedo change using CERES satellite data
We present a radiative kernel for surface albedo change founded on a novel, simplified parameterization of shortwave radiative transfer driven with inputs from the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balance and Filled (EBAF) Edition 4.0 products based on a 16-year climatology (2001-2016). Both monthly temporally-explicit and monthly climatological mean CERES albedo change kernels (CACK) are provided with their respective uncertainty layers. Octave script files for generating monthly CACK from CERES EBAF data and demonstrating the application of CACK with user-specified temporal and spatial extents are also included.
Data-driven subgrid-scale modeling of forced Burgers turbulence using deep learning with generalization to higher Reynolds numbers via transfer learning
<p>These are the data files for use with the codes in https://github.com/envfluids/Burgers_DDP_and_TL.</p>
Simulations of large POPC bilayers using the Charmm36 force field.
<p>An earlier simulation (DOI:10.5281/zenodo.159759) of a POPC bilayer consisting of 200 lipids (100 per leaflet) is extended to 4 and 9 times larger (800 and 1800 lipids) and simulated for 100 ns using Gromacs v5.1.x [1]. The Charmm36 model [2] is employed for lipids and the Charmm-compatible variant of the tip3p model for water.</p> <p>The Charmm36 force field parameters were obtained from CHARMM-GUI [3] at http://www.charmm-gui.org</p> <p>––––––––––––––––––––––––––––––––––––––––––––––––––––––</p> <p>The files are in GROMACS format. The number in the file name corresponds to how many times larger the system is compared to that in (DOI:10.5281/zenodo.159759), either 4 (2x2) or 9 (3x3). Trajectories (.xtc) is 100 ns long with data saved every 100 ps. Additionally, the topology (.top), binary run input file for GROMACS v. 5.0–> (.tpr), the continue point file (.cpt), and the energy output file (.edr) are provided. The provided simulation paremeter file (.mdp) is common for both simulations. </p> <p>––––––––––––––––––––––––––––––––––––––––––––––––––––––</p> <p>[1] GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. Mark J. Abraham, Teemu Murtola, Roland Schulz, Szilárd Páll, Jeremy C. Smith, Berk Hess, and Erik Lindahl. SoftwareX 2015 1–2, 19–25, DOI: 10.1016/j.softx.2015.06.001</p> <p>[2] Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types. Jeffery B. Klauda, Richard M. Venable, J. Alfredo Freites, Joseph W. O’Connor, Douglas J. Tobias, Carlos Mondragon-Ramirez, Igor Vorobyov, Alexander D. MacKerell, Jr., and Richard W. Pastor. The Journal of Physical Chemistry B 2010 114 (23), 7830-7843, DOI: 10.1021/jp101759q</p> <p>[3] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field. Jumin Lee, Xi Cheng, Jason M. Swails, Min Sun Yeom, Peter K. Eastman, Justin A. Lemkul, Shuai Wei, Joshua Buckner, Jong Cheol Jeong, Yifei Qi, Sunhwan Jo, Vijay S. Pande, David A. Case, Charles L. Brooks, III, Alexander D. MacKerell, Jr., Jeffery B. Klauda, and Wonpil Im. Journal of Chemical Theory and Computation 2016 12 (1), 405-413, DOI: 10.1021/acs.jctc.5b00935</p>
Data and code for the manuscript "Internal vs Forced Variability Metrics for General Circulation Models Using Information Theory"
<p>Data and code for the manuscript "Internal vs Forced Variability Metrics for General Circulation Models Using Information Theory" published in the Journal of Geophysical Research Oceans. <br>URL of the manuscript: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023JC020101<br>DOI of the manuscript: https://doi.org/10.1029/2023JC020101</p>
Data and scripts used to produce the figures for state-dependent CO2 forcing paper
<p>Data and scripts used to produce the figures for state-dependent CO2 forcing paper (He et al., 2023)</p>
Energy and forces annotated atomic structures of platinum using first-principles calculations
<p>Dataset for training machine learning potential of platinum.</p> <p>Detailed explanation of data generation is described in the preprint. below</p> <p>Chun, H., Kang, J., Kang, D., Heo, J., Cho, H., Heo, J., … & Han, B. (2022). Tracking the 3d atomic structures during thermal treatment and catalytic activity of individual pt nanoparticles.. https://doi.org/10.21203/rs.3.rs-1441062/v1</p>
Forcing data, evaluation data, model output and analysis scripts used in LPJ-GUESS/LSM description paper
<p>This archive contains:</p> <p>- model_output.tar.gz: Model output<br> - extracted_fluxes.tar.gz: Sensible heat, latent heat and CO2 fluxes extracted from the FLUXNET2015 dataset, used to evaluate the model output<br> - extracted_climate.tar.gz: Climate data extracted from the FLUXNET2015 dataset, used to force the simulations<br> - scripts.tar.gz: Python scripts used to analyze the data and produce the results reported in the model description paper</p> <p>The climate forcing data has been extracted from the FLUXNET2015 dataset [1]. Input and output data is stored in netCDF files. Evaluation data is stored in python serialized files (pickle).</p> <p>[1] Pastorello, G., Trotta, C., Canfora, E. <em>et al.</em> The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. <em>Sci Data</em> <strong>7, </strong>225 (2020). https://doi.org/10.1038/s41597-020-0534-3</p>
Data for "Estimation of microtubule-generated forces using a DNA origami nanospring"
<p>Data in support of the publication "Estimation of microtubule-generated forces using a DNA origami nanospring"</p>
Data from: A brief history and popularity of methods and tools used to estimate micro-evolutionary forces
<p class="western">Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome-wide estimates of the four major micro-evolutionary forces – mutation, gene flow, genetic drift and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and High Throughput Sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro-evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.</p>
Model simulation data used in "An inconsistency in aviation emissions between CMIP5 and CMIP6 and the implications for short-lived species and their radiative forcing" (Thor et al., GMD, 2022)
<p>This archive contains files that were used to produce the results published in the article "An inconsistency in aviation emissions between CMIP5 and CMIP6 and the implications for short-lived species and their radiative forcing" by Thor et al.</p> <p>The directory nml contains namelist setups (configuration files) used for each of the simulations that were performed for this study.<br> The used MESSy version is d2.54.0.3-pre2.55-02-2077-g6eca90858-dirty_6eca90858ecb4ee8fb8900681a94a79ac3d612af_2021-01-26T11:10:08+01:00_2021-02-18T09:14:01+0100 for the QCTM simulations and d2.54.0.3-pre2.55-02-1466-g1fb086944_1fb0869442bf4f1bb10a7dd5f36e4bde5c0cf6d7_2020-10-27T18:17:50+01:00_2020-10-27T18:24:16+0100 for the aerosol simulations (http://www.messy-interface.org).</p> <p>The directory figures contains ipython scripts that were used to produce the figures in the paper.</p>
Simulations of POPC lipid bilayer in water solution with various molar fractions of cationic surfactant dihexadecylammonium using ECC-POPC force field
<p>Classical molecular dynamics simulations of a POPC lipid bilayer in water solution with various molar fractions of cationic surfactant dihexadecylammonium using ECC-POPC force field parameters, SPC/E water model and ECC-ions.</p> <p>Simulation at pure water is in a separate Zenodo deposit<br> https://doi.org/10.5281/zenodo.1118266</p> <p>file names report molar fraction of cations (i.e. not bulk concentrations)</p> <p>simulations performed with Gromacs 5.1.4 (*.xtc files) and openMM 7 (*.dcd files)</p> <p>simulation length 200 ns</p> <p>temperature 313 K (otherwise noted)</p>
Simulations of POPC lipid bilayer in water solution at various NaCl and CaCl2 concentrations using ECC-POPC force field and various water models
<p>Classical molecular dynamics simulations of a POPC lipid bilayer in water solution at various NaCl and CaCl2 concentrations using ECC-POPC force field parameters, various water models and ECC-ions.</p> <p>Simulations with SPC/E water model are in a separate Zenodo deposit<br> https://doi.org/10.5281/zenodo.1118266</p> <p>file names report molar fraction of cations (i.e. not bulk concentrations)</p> <p>simulations performed with Gromacs 5.1.4 (*.xtc files) and openMM 7 (*.dcd files)</p> <p>simulation length 300 ns</p> <p>temperature 313 K (otherwise noted)</p>
Changes Monitoring in Hongjiannao Lake from 1987-2023 using Google Earth Engine and Analysis of Climatic and Anthropogenic Forces
Open the record for dataset details and reuse information.
MD simulation of POPC bilayer using a force field calibrated to NMR order parameters
<p>Force field parameters and simulation trajectory for 34-lipid bilayer simulation where the force field has been calibrated to reproduce the NMR C-H 13C order parameters. Temperature is 300K, and simulation was conducted in NPT ensemble with asymmetric pressure coupling. The trajectory is 1 microsecond long. The simulation was started from an equilibrated conformation and few tens of nanoseconds of pre-equilibration was run before obtaining the 1 microsecond production run. The trajectory has been centered to the simulation box. The simulations where conducted on GROMACS 2020 (GPU). </p>
Disentangling forced trends in the North Atlantic jet from natural variability using deep learning
<p>Code used to train the LLAE to obtain forced trends in the North Atlantic jet stream and to produce plots.</p>
Simulations of POPC lipid bilayer in water solution at various NaCl, KCl and CaCl2 concentrations using ECC-POPC force field
<p>Classical molecular dynamics simulations of a POPC lipid bilayer in water solution at various NaCl, KCl and CaCl2 concentrations using ECC-POPC force field parameters, SPC/E water model and ECC-ions.</p> <p>file names report molar fraction of cations (i.e. not bulk concentrations)</p> <p>simulations performed with Gromacs 5.1.4 (*.xtc files) and openMM 7 (*.dcd files)</p> <p>simulation length 300 ns</p> <p>temperature 313 K (otherwise noted)</p> <p>Gromacs simulation setting is in the file npt_lipid_bilayer.mdp</p>
Data from: Assessing bite force estimates in extinct mammals and archosaurs using phylogenetic predictions
Bite force is an ecologically important biomechanical performance measure is informative in inferring the ecology of extinct taxa. However, biomechanical modelling to estimate bite force is associated with some level of uncertainty. Here, I assess the accuracy of bite force estimates in extinct taxa using a Bayesian phylogenetic prediction model. I first fitted a phylogenetic regression model on a training set comprising extant data. The model predicts bite force from body mass and skull width while accounting for differences owning to biting position. The posterior predictive model has a 93% prediction accuracy as evaluated through leave-one-out cross-validation. I then predicted bite force in 37 species of extinct mammals and archosaurs from the posterior distribution of predictive models. Biomechanically estimated bite forces fall within the posterior predictive distributions for all except four species of extinct taxa and are thus as accurate as that predicted from body size and skull width, given the variation inherent in extant taxa and the amount of time available for variance to accrue. Biomechanical modelling remains a valuable means to estimate bite force in extinct taxa and should be reliably informative of functional performances and serve to provide insights into past ecologies.
Inputs (forcing and observations) ready for use by 'MuSA: The Multiscale Snow Data Assimilation System (v1.0)'
<p>MuSA is a snow data assimilation system that can fuse observations with snowpack simulations generated by the Flexible Snow Model (FSM2). This repository contains meteorological forcing developed with the Micromet model and 5 m resolution snow depth observations in the Izas basin (central Spanish Pyrenees) generated with drones, ready to be used in MuSA.</p>
Last glacial cycle simulations forced by PMIP3 climate with a matrix and index method using a 3D thermodynamical ice-sheet model IMAU-ICE
<p>IMAU-ICE 2.0 model output of the ice evolution during the last glacial cycle at a 10 ka temporal resolution, as described in Scherrenberg at al., 2023.</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.