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1,670 results for “FORCE”
Experimental Study of the Drag Force Applied by Supercritical Flows on Emerging Obstacles
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Input files for T4 lysozyme free energy calculations with DMBIS non-bonded force field parameters
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Supplementary materials for the article entitled 'Metaphor Forces Argument Overtness', published in Linguistics
<p>see the publication for details</p>
Atomic Force Microscopy data of Poly-3-hydroxybutarate and Poly-3-hydroxyvalerate films
<p>This dataset consists of atomic force microscopy (AFM) scans of <em><strong>Polyhydroxyalkanoate</strong></em> films in text (.txt) format as well as their corresponding previews in (.png) format. </p> <p>The surfaces of <strong><em>Poly-3-hydroxybutarate (P3HB [100%])</em></strong> and <em><strong>Poly-3-hydroxyvalerate (P3HB-co-P3HV) [90% :10%]) </strong></em>of six film thicknesses, three scan sizes (5µm, 10µm and 30µm) and three unique scan areas have been scanned with AFM equipment from NT-MDT spectrum instruments.</p> <p>This dataset has been used in the work <a href="../doi/10.5281/zenodo.10621269" target="_blank" rel="noopener">10.5281/zenodo.10621269</a> within which the scan data has been divided into multiple sub-pools for experimentation. Details on the structure of the dataset are as follows: </p> <ul> <li>The (.txt) format of the scanned images can be opened using Gwyddion (<a href="http://gwyddion.net/">gwyddion.net</a>)</li> </ul> <pre><code>FOLDER INDEX ITMO_PHA-AFM-SCAN-Data/ ├── Set.1_P3HB.(Homopolymer) │ ├── Size_5um │ │ ├── TXT │ │ │ └── 17(.txt)s │ │ └── IMG │ │ │ └── 17(.png)s │ ├── Size_10um │ │ ├── TXT │ │ │ └── 17(.txt)s │ │ └── IMG │ │ │ └── 17(.png)s │ └── Size_30um │ ├── TXT │ │ └── 18(.txt)s │ └── IMG │ └── 18(.png)s ├── Set.2_P3HB-co-P3HV.(Heteropolymer) │ ├── Size_5um │ │ ├── TXT │ │ │ └── 18(.txt)s │ │ └── IMG │ │ │ └── 18(.png)s │ ├── Size_10um │ │ ├── TXT │ │ │ └── 18(.txt)s │ │ └── IMG │ │ │ └── 18(.png)s │ └── Size_30um │ ├── TXT │ │ └── 17(.txt)s │ └── IMG │ └── 17(.png)s │ └── Read_me.txt</code></pre> <p><br>For convenience, we show an example of referencing data pools using the <em><strong>Folder Index</strong></em></p> <p>E.g. </p> <ul> <li>With reference to the article(<a href="https://doi.org/10.1021/acsomega.4c02502">https://doi.org/10.1021/acsomega.4c02502</a>), Case 1(a) is a data pool consisting only of scan data from P3HB polymer with all three sizes of data, in this case the reference is written as: <strong><em>(P1,L2) </em></strong></li> <li>Similarly, in case of Case 2(b), which is a data pool consisting of scan data from P3HB and P3HB-co-P3HV polymers with exclusively 30µm scan sizes, the reference is written as: <strong><em>(P1, L2[30]) + (P2, L2[30])</em></strong></li> </ul> <p>The .txt and .png files have been named using the following nomenculatrue: </p> <h3><strong> P_Thickness.N_Area.A_Size.S.txt</strong></h3> <p> <strong>P </strong>– Polymer (P3HB or P3HBV)<br><strong>Thickness.N</strong> – Film thickness of the scanned sample (1-6)<br><strong> Area.A</strong> – Scanned area within the film (1-3)<br><strong> Size.S</strong> – Size of the scanned area (5µm,10µm,30µm)</p> <p>e.g. (P3HB_Thickness.1_Area.1_Size.5.txt)</p> <p><strong>Please cite this dataset when used in applications as:</strong><br><em>Ireddy, A. T. S., & Ghorabe, F. D. E. (2024). Atomic Force Microscopy data of Poly-3-hydroxybutarate and Poly-3-hydroxyvalerate films [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10649355</em></p> <p><br>For additonal details, please contact: <a href="mailto:ireddy@itmo.ru">ireddy@itmo.ru</a></p>
Experimental Estimation of Gap Thickness and Electrostatic Forces Between Contacting Surfaces Under Electroadhesion
<p>Electroadhesion (EA) is a promising technology with potential applications in robotics, automation, space missions, textiles, tactile displays, and some other fields where efficient and versatile adhesion is required. However, a comprehensive understanding of the physics behind it is lacking due to the limited development of theoretical models and insufficient experimental data to validate them. This article proposes a new and systematic approach based on electrical impedance measurements to infer the electrostatic forces between two dielectric materials under EA. The proposed approach is applied to tactile displays, where skin and voltage-induced touchscreen impedances are measured and subtracted from the total impedance to obtain the remaining impedance to estimate the electrostatic forces between the finger and the touchscreen. This approach also marks the first instance of experimental estimation of the average air gap thickness between a human finger and a voltage-induced capacitive touchscreen. Moreover, the effect of electrode polarization impedance on EA is investigated. Precise measurements of electrical impedances confirm that electrode polarization impedance exists in parallel with the impedance of the air gap, particularly at low frequencies, giving rise to the commonly observed charge leakage phenomenon in EA.</p>
MD simulation of POPC bilayer with OPLS4 force field. 12 w/l.
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AFM measured and simulated adhesion force
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Moral dilemmas: Insights about morality from forced choice and budget allocation methods
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River plume modulation by infragravity wave forcing
<p>Data sets corresponding to "River plume modulation by infragravity wave forcing". This includes:</p> <ul> <li>Salinity, pressure and temperatura data at locations specified in the article (matlab file)</li> <li>ADCP channel velocity (raw, matlab file)</li> <li>16 Hz pressure data from RBR pressure sensor (raw, needs to be imported into matlab/excel, see RBR's website)</li> </ul>
Climbing parrots achieve pitch stability using axial-appendicular force couples
<p class="Default">During vertical climbing, the gravitational moment tends to pitch the animal's head away from the climbing surface and this may be countered by 1) applying a correcting torque at a discrete contact point, or 2) applying opposing horizontal forces at separate contact points to produce a free moment. We tested these potential strategies in small parrots with an experimental climbing apparatus imitating the fine branches and vines of their natural habitat. The birds climbed on a vertical ladder with four instrumented rungs that measured three-dimensional force and torque, representing the first measurements of multiple contacts from a climbing bird. The parrots ascend primarily by pulling upward from the upper rung using the beak and feet. They resist the gravitational pitching moment with a free moment produced by horizontal force couples between the beak and feet during the first third of the stride and the tail and feet during the last third of the stride. The reaction torque from individual rungs did not counter, but exacerbated the gravitational pitching moment. Possible climbing limitations were explored using two different rung radii, each with low and high friction surfaces. Rung torque was limited in the large-radius, low-friction condition, however, rung condition did not significantly influence free moments produced. These findings have implications for our understanding of avian locomotor modules (i.e., coordinated actions of the head-neck, hindlimbs, and tail), the use of force couples in vertical locomotion, and the evolution of associated structures.</p>
Generalized Rayleigh-Taylor Instability: Ion Inertia, Acceleration Forces, and E Region Drivers
<p>electron density and growth rate data files</p>
pyqg Subgrid Forcing Datasets
<p><strong><a href="https://pyqg.readthedocs.io/en/latest">pyqg</a> Subgrid Forcing Datasets</strong></p> <p>This repository contains a set of <a href="https://zarr.readthedocs.io/en/stable/">zarr</a> datasets which (when uncompressed) contain snapshots from different series of <code>pyqg.QGModel</code> simulations run with different sets of parameters (one which produces isotropic eddies, stored in <code>eddy/</code>, and one which produces strong jets, stored in <code>jet/</code>. These parameters are stored as JSON in each dataset's metadata as the <code>pyqg_params</code> attribute.</p> <p>Descriptions of each dataset:</p> <ul> <li><code>low_res.zarr</code> contains snapshots saved every 1000 hours from 5 simulations run for 10 years at <code>nx=64</code> (which is eddy-permitting but not resolving)</li> <li><code>high_res.zarr</code> contains similar snapshots but for simulations at <code>nx=256</code> (which is fully eddy-resolving)</li> <li><code>forcing{1,2,3}.zarr</code> contain subgrid forcing variables (described below) and coarsened state variables which can be used to predict them for 275 simulations. Each <code>forcing</code> dataset is computed using a different filtering and coarse-graining operator: <ul> <li><code>forcing1</code> is computed by truncating high-frequency potential vorticity (PV) modes in spectral space, then applying the sharp, scale-selective spectral filter described <a href="https://pyqg.readthedocs.io/en/latest/equations/notation_twolayer_model.html#marching-forward">here</a></li> <li><code>forcing2</code> is computed by truncating high-frequency PV modes in spectral space, then applying a Gaussian spectral filter used <a href="https://arxiv.org/abs/2102.11400">here</a></li> <li><code>forcing3</code> is computed by applying a diffusive filter from <a href="https://gcm-filters.readthedocs.io/en/latest/">GCM-Filters</a> to the PV in real space, then averaging in real space</li> </ul> </li> </ul> <p>Descriptions and units for the variables in each dataset are stored in metadata which can be viewed when the files are loaded. More details (and links to datasets in different configurations) can be found at <a href="https://github.com/m2lines/pyqg_parameterization_benchmarks">https://github.com/m2lines/pyqg_parameterization_benchmarks</a>.</p>
Source Data for "Forced and spontaneous symmetry breaking in cell polarization."
<p>Source Data for Figures 2-4</p>
Supplementary Data for Forced Cenozoic continental subduction of Tarim craton-like lithosphere below the Tianshan revealed by ambient noise tomography
<p>Please read the README.txt file for more information.</p>
A Geometric Pulling Force Controller for Aerial Robotic Workers
<p> This video presents a geometric, pulling force control scheme in order to enable the concept of Aerial Robotic Workers (ARWs), where the capabilities of the Unmanned Aerial Vehicles (UAVs) are enhanced by aerial manipulators in order to exert known pulling forces on the environment, with characteristic applications such as levers actuation, debris removal and safety assessments. The proposed novel approach consists of interfacing a cascaded position control scheme with a manipulation framework in such a way that the UAV, together with the manipulator are being controlled in a complete system.</p>
"Methodological and force field effects in the molecular dynamics-based prediction of binding free energies of host-guest systems"
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CESM ISMIP6 Forcing Data
<div> <p>The Community Earth System Model (CESM) version 2.1 is a world-class coupled climate system model that includes components for the atmosphere, ocean, terrestrial system, river run-off, and fully active glaciers (Danabasoglu et al. 2020). This version of CESM was used in many experiments as part of the Coupled Model Intercomparison Project 6 (CMIP6, Eyring et al. (2016)) including the Ice Sheet Model Inter-comparison Project 6 (ISMIP6).</p> <p>These data come from historical simulations (1950–2014) and future projections (2015–2100) using the fully-coupled earth system model, including an active ice sheet model (the Community Ice Sheet Model, or CISM, Lipscomb et al. (2019)) with feedbacks to the atmosphere, land, and oceans. We have provided data from these two transient experiments to the community through Ghub for analysis and to force uncoupled ice sheet models.</p> <p><u><strong>Downloading the Data</strong></u></p> <p><strong><a href="https://theghub.org/resources?id=4761">The data can be downloaded from the GHub.</a> Please log in and click on the Download tab to receive the Download instructions.</strong>For more information on how to obtain data from GHub visit <a href="https://theghub.org/accessing-data-with-globus" target="_blank" rel="noopener">Accessing Data</a> web page. There is also a tool available to <a href="https://theghub.org/resources?alias=ncarismipplots" target="_blank" rel="noopener">visualize these data here on Ghub</a>.</p> </div> <h4>Sponsoredby</h4> <div>The CESM project is supported primarily by the National Science Foundation (NSF). This material is based upon study supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement no. 1852977.</div> <h4>References</h4> <div> <p>Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., et al. (2020). The Community Earth System Model Version 2 (CESM2). Journal of Advances in Modeling Earth Systems, 12, e2019MS001916. https://doi.org/10.1029/2019MS001916</p> <p>Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, doi:10.5194/gmd-9-1937-2016.</p> <p>Lipscomb, W. H., Price, S. F., Hoffman, M. J., Leguy, G. R., Bennett, A. R., Bradley, S. L., Evans, K. J., Fyke, J. G., Kennedy, J. H., Perego, M., Ranken, D. M., Sacks, W. J., Salinger, A. G., Vargo, L. J., and Worley, P. H. (2019). Description and evaluation of the Community Ice Sheet Model (CISM) v2.1, Geosci. Model Dev., 12, 387–424, https://doi.org/10.5194/gmd-12-387-2019.</p> </div> <h4>Publications</h4> <div>Muntjewerf, L., Sacks, W. J., Lofverstrom, M., Fyke, J., Lipscomb, W. H., Ernani da Silva, C., etal. (2021). Description and demonstration of the coupled Community Earth System Model v2 – Community Ice Sheet Model v2 (CESM2-CISM2). Journal of Advances in Modeling Earth Systems, 13, e2020MS002356. https://doi.org/10.1029/2020MS002356</div> <h4> </h4>
Machine Learning for Analyzing Atomic Force Microscopy (AFM) Images Generated from Polymer Blends
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MD simulation of DMPC bilayer with OPLS4 force field. 5 w/l.
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MD simulation of DMPC bilayer with OPLS4 force field. 10 w/l.
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ScienceDex guides
Understand access before you commit
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.