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1,670 results for “FORCE”
Hercules Fights the Forces of Evil
This ensemble is set halfway up the slope of the Schönbrunn Palace Park. Originally, water should have sprung up here as a representation of the overwhelming strength of the victorious positive (Hercules), which then flows down the slope via cascades and washes away the negative, namely Carthage, the ruins of which are set up at the foot of the slope. However, there was a lack of water and money to complete this installation. The group of statues shows Hercules fighting the three-headed Cerberus as well as the embodiment of envy and other vices (an old woman, a dog and a snake with a dog's head). It was purchased by Johann Ferdinand Hetzendorf von Hohenberg and erected in 1771. Source: Objaverse 1.0 / Sketchfab
MD simulation trajectory of a POPC/POPS (4:1) bilayer with 715mM CaCl2, Berger force field for lipids, scaled charges for Ca2+ and Cl-
<p>MD simulation trajectory of a POPC/POPS (4:1) bilayer with 715 mM CaCl2 (104 POPC, 24 POPS, 26 POPS, 4306 WAT, 72 Ca2+, 112 Cl-). Additional Ca2+ cations added to neutralize the negative charge of POPS (leading to total Ca2+ concentration of 919 mM). Berger force field for lipids, scaled charges employed for calcium and chloride ions. Gromacs 4.5.5, T=310K, 300 ns trajectories were calculated with the last 100 ns stored here.</p> <p>Used in (see therein also a detailed description of ion scaling):</p> <p>A. Melcrova, S. Pokorna, S. Pullanchery, M. Kohagen, P. Jurkiewicz, M. Hof, P. Jungwirth, P. S. Cremer, L. Cwiklik, The complex nature of calcium cation interactions with phospholipid bilayers<br> Scientific Reports 2016, 6, 38035.<br> DOI: 10.1038/srep38035</p>
MD simulation trajectory of a POPC bilayer with 716mM CaCl2, Berger force field for lipids, scaled charges for Ca2+ and Cl-
<p>MD simulation trajectory of a POPC bilayer with 716 mM CaCl2 (128 POPC, 26 POPS, 4308 WAT, 56 Ca2+, 112 Cl-). Berger force field for lipids, scaled charges employed for calcium and chloride ions. Gromacs 4.5.5, T=310K, 200 ns trajectories were calculated with the last 100 ns stored here.</p> <p>Used in (see therein also a detailed description of ion scaling):</p> <p>A. Melcrova, S. Pokorna, S. Pullanchery, M. Kohagen, P. Jurkiewicz, M. Hof, P. Jungwirth, P. S. Cremer, L. Cwiklik, The complex nature of calcium cation interactions with phospholipid bilayers<br> Scientific Reports 2016, 6, 38035.<br> DOI: 10.1038/srep38035</p>
MD simulation trajectory of a POPC/POPS (4:1) bilayer with 102mM CaCl2, Berger force field for lipids, scaled charges for Ca2+ and Cl-
<p>MD simulation trajectory of a POPC/POPS (4:1) bilayer with 102 mM CaCl2 (104 POPC, 24 POPS, 26 POPS, 4306 WAT, 24 Ca2+, 16 Cl-). Additional Ca2+ cations added to neutralize the negative charge of POPS (leading to total Ca2+ concentration of 306 mM). Berger force field for lipids, scaled charges employed for calcium and chloride ions. Gromacs 4.5.5, T=310K, 300 ns trajectories were calculated with the last 100 ns stored here.</p> <p>Used in (see therein also a detailed description of ion scaling):</p> <p>A. Melcrova, S. Pokorna, S. Pullanchery, M. Kohagen, P. Jurkiewicz, M. Hof, P. Jungwirth, P. S. Cremer, L. Cwiklik, The complex nature of calcium cation interactions with phospholipid bilayers<br> Scientific Reports 2016, 6, 38035.<br> DOI: 10.1038/srep38035</p>
MD simulation trajectory of a POPC bilayer with 100mM CaCl2, Berger force field for lipids, scaled charges for Ca2+ and Cl-
<p>MD simulation trajectory of a POPC bilayer with 100 mM CaCl2 (128 POPC, 26 POPS, 4452 WAT, 8 Ca2+, 16 Cl-). Berger force field for lipids, scaled charges employed for calcium and chloride ions. Gromacs 4.5.5, T=310K, 200 ns trajectories were calculated with the last 100 ns stored here).</p> <p>Used in (see therein also a detailed description of ion scaling):</p> <p>A. Melcrova, S. Pokorna, S. Pullanchery, M. Kohagen, P. Jurkiewicz, M. Hof, P. Jungwirth, P. S. Cremer, L. Cwiklik, The complex nature of calcium cation interactions with phospholipid bilayers<br> Scientific Reports 2016, 6, 38035.<br> DOI: 10.1038/srep38035</p>
Application Of Substantial And Sustained Force To Vertical Surfaces Using A Quadrotor
<p><strong>One of the challenges in the interaction between aerial manipulators (drones with manipulator arms) and the environment is to maintain stability under high interaction forces. The dynamics of the system change, and due to limitations to the drone-platform-- the drone not being to apply sideways forces and having limited yaw-torque-- stability is not naturally guaranteed. </strong></p> <p> </p> <p><strong>In this video we demonstrate a new control approach to overcome these limitations. The video shows a quadrotor drone with manipulator pushing on the environment. More precisely, the stability is achieved using a state-feedback approach to compensate for the roll and yaw errors. This approach uses the linearized contact dynamics under pseudo-static conditions. The key element is that non-zero roll-states are used to compensate for errors in the yaw-state. At a certain point the drone reaches pitch angles of over 45º. Given that the drone has a mass of 1.5 kg, this means that the drone is pushing with 15N(!) of force on the environment. The video demonstrates that the drone is easily able to maintain stability over a longer time period.</strong></p> <p> </p> <p><strong>These high interaction forces can be extremely useful when operating tools on the environment, as tasks such as grinding and brushing require sufficient contact pressure to function.</strong></p>
Changes Monitoring in Hongjiannao Lake from 1987-2023 using Google Earth Engine and Analysis of Climatic and Anthropogenic Forces (Climatic Data)
<p>This dataset presents temporal (1987 to 2023) climatic data for the weather station near Hongjiannao Lake.</p>
Zyxin, VASP, and profilin-G-actin force reconstitution assay dataset
<p>This dataset contains the raw TIRF microscopy data from single motor assays with zyxin, VASP, and profilin-G-actin, as well as the script used to analyze the data.</p>
A Stochastically Generated meteorological forcings for the Laurentian Great Lakes to support the Great Lakes Restoration Initiative
<p>The dataset consists of three folders, each with time series for the Laurentian Great Lakes and their contributing watersheds: </p> <ol> <li>"observed_historical.zip" : containing daily forcings for Large Lake Thermodynamics Model and Large Basin Runoff Model and Overlake Precipitation time series from GLERL Hydrometeorological Database and consistent with the inputs of GLSGyFS software.</li> <li>"baseline.zip" : 1000-yr long simulated daily meteorological time series using the Stochastic Weather Generator, without any thermodynamic climate perturbations. </li> <li>"scenarios.zip" : 30 scenarios of each 1000-yr long simulated daily meteorological time series using the Stochastic Weather Generator with different thermodynamic perturbations, consistent with Coupled Model Intercomparison Project 6 (CMIP6) projections for the Great Lakes region. </li> </ol> <p> </p> <p><strong>Acknowledgements: </strong></p> <p>This work was funded by the Great Lakes Restoration Initiative (GLRI) Action Plan 3, Focus Area 5.2 Conduct Comprehensive Science Programs and Projects. Funding for this work was also provided through the National Science Foundation Grant No. CBET-2144332, and the U.S. Geological Survey Northeast Climate Adaptation Science Center, which is managed by the USGS National Climate Adaptation Science Center, under Grant/Cooperative Agreement No. G21AC10601-00. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the Northeast Climate Adaptation Science Center or the U.S. Geological Survey.</p>
DFT torsiondrive data for: MACE-OFF23: Transferable Machine Learning Force Fields for Organic Molecules
<p>MACE-OFF23: Transferable Machine Learning Force Fields for Organic Molecules</p> <div><a href="https://arxiv.org/search/physics?searchtype=author&query=Kov%C3%A1cs,+D+P">Dávid Péter Kovács</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Moore,+J+H">J. Harry Moore</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Browning,+N+J">Nicholas J. Browning</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Batatia,+I">Ilyes Batatia</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Horton,+J+T">Joshua T. Horton</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Kapil,+V">Venkat Kapil</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Witt,+W+C">William C. Witt</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Magd%C4%83u,+I">Ioan-Bogdan Magdău</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Cole,+D+J">Daniel J. Cole</a>, <a href="https://arxiv.org/search/physics?searchtype=author&query=Cs%C3%A1nyi,+G">Gábor Csányi </a><a href="https://doi.org/10.48550/arXiv.2312.15211">https://doi.org/10.48550/arXiv.2312.15211</a></div> <p> </p> <p>Supporting data including raw outputs from SPICE consistent torsion drives on the TorsionNet500 and OpenFF Biaryl datasets and HDF5 versions formated to be consistent with the rest of the SPICE dataset. See the <a href="../records/10975225">SPICE release</a> for more details. </p>
Other Supplementary Material for 'Myosin-I Synergizes with Arp2/3 Complex to Enhance Pushing Forces of Branched Actin Networks' by Xu et al.
<div> <p>Other Supplementary Material for "Myosin-I Synergizes with Arp2/3 Complex to Enhance Pushing Forces of Branched Actin Networks" by Xu, Rutkowski, Rebowski, Boczkowska, Pollard, Dominguez, Vavylonis, and Ostap, bioRxiv, <a href="https://doi.org/10.1101/2024.02.09.579714" rel="nofollow">https://doi.org/10.1101/2024.02.09.579714</a> </p> <p> </p> </div>
Data from: Linking in vivo muscle dynamics to in situ force-length and force-velocity reveals that guinea fowl lateral gastrocnemius operates at shorter than optimal lengths
<p>Force-length (F-L) and force-velocity (F-V) properties characterize skeletal muscle's intrinsic properties under controlled conditions, and it is thought that these properties can inform and predict <em>in vivo</em> muscle function. Here, we map dynamic <em>in vivo</em> operating range and mechanical function during walking and running, to the measured <em>in situ</em> F-L and F-V characteristics of guinea fowl (<em>Numida meleagris</em>) lateral gastrocnemius (LG), a primary ankle extensor. We use <em>in vivo</em> patterns of muscle (tendon) force, fascicle length, and activation to test the hypothesis that muscle fascicles operate at optimal lengths and velocities to maximize force or power production during walking and running. Our findings only partly support our hypothesis: <em>in vivo</em> LG velocities are consistent with optimizing power during work production, and economy of force at higher loads. However, LG does not operate at lengths on the force plateau (±5% Fmax) during force production. LG length was near L<sub>0</sub> at the time of EMG onset but shortened rapidly such that force development during stance occurred almost entirely on the ascending limb of the F-L curve, at shorter than optimal lengths. These data suggest that muscle fascicles shorten across optimal lengths in late swing, to optimize the potential for rapid force development near the swing-stance transition. This may provide resistance against unexpected perturbations that require rapid force development at foot contact. We also found evidence of passive force rise (in absence of EMG activity) in late swing, at lengths where passive force is zero <em>in situ</em>, suggesting that history dependent and viscoelastic effects may contribute to <em>in vivo</em> force development. Direct comparison of<em> in vivo </em>work loops and physiological operating ranges to traditional measures of F-L and F-V properties suggests the need for new approaches to characterize dynamic muscle properties in controlled conditions that more closely resemble <em>in vivo </em>dynamics.</p>
Force extension curves with hairpin
Open the record for dataset details and reuse information.
HOTSSea v1 Forcings - RDRS v2.1
<p> RDRS v2.1 atmospheric forcings provided here to support publication of HOTSSea v1.0 NEMO oceanographic model of the Salish Sea in compliance with the data policy (GMD-2024-58; https://doi.org/10.5194/gmd-2024-58) with code and data found here (<a href="../doi/10.5281/zenodo.12520930">10.5281/zenodo.12520930</a>)</p> <p>All forcings provided here have been pre-processed for use in NEMO v3.6 HOTSSea v1 model. Original repositories are referenced below.</p> <p>See </p> <div> <div>Gasset, N., Fortin, V., Dimitrijevic, M., Carrera, M., Bilodeau, B., Muncaster, R., Gaborit, É., Roy, G., Pentcheva, N., Bulat, M., Wang, X., Pavlovic, R., Lespinas, F., & Khedhaouiria, D. (2021). <em>A 10 km North American Precipitation and Land SurfaceReanalysis Based on the GEM Atmospheric Model</em> [Preprint]. Hydrometeorology/Modelling approaches. <a href="https://doi.org/10.5194/hess-2021-41">https://doi.org/10.5194/hess-2021-41</a></div> </div> <p>10.5194/hess-2021-41</p> <p> </p>
Quantifying mechanical forces during vertebrate morphogenesis
<p>Morphogenesis requires embryonic cells to generate forces and perform mechanical work to shape their tissues. Incorrect functioning of these force fields can lead to congenital malformations. Understanding these dynamic processes requires the quantification and profiling of three-dimensional mechanics during evolving vertebrate morphogenesis. Here we describe elastic spring-like force sensors with micrometre-level resolution, fabricated by intravital three-dimensional bioprinting directly in the closing neural tubes of growing chicken embryos. Integration of calibrated sensor read-outs with computational mechanical modelling allows direct quantification of the forces and work performed by the embryonic tissues. As they displace towards the embryonic midline, the two halves of the closing neural tube reach a compression of over a hundred nano-newtons during neural fold apposition. Pharmacological inhibition of Rho-associated kinase to decrease the pro-closure force shows the existence of active anti-closure forces, which progressively widen the neural tube and must be overcome to achieve neural tube closure. Overall, our approach and findings highlight the intricate interplay between mechanical forces and tissue morphogenesis.</p>
Addressing Observational Gaps in Aerosol Parameters using Machine Learning: Implications to Aerosol Radiative Forcing
<p>This dataset represents Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA), and Absorption Parameter (AP) data over Kanpur, India, sourced from AERONET with initial data gaps of approximately 37%, 62%, and 58% respectively. To reduce these gaps, XGBoost, a machine learning model trained with reanalysis and satellite datasets, was employed with optimized hyperparameter tuning. Using AERONET data for training, XGBoost effectively addressed gaps, improving AOD by 10%, SSA by 23%, and AP by 21%.</p>
Relationship between Channel Island Melospiza melodia (Song Sparrow) bill size and vegetation, seed extraction time, bite force, and climate (2014-2016)
<p>Inferring the environmental selection pressures responsible for phenotypic variation is a challenge in adaptation studies as traits often have multiple functions and are shaped by complex selection regimes. We provide indirect evidence that morphology of the multifunctional avian bill is primarily shaped by climate and thermoregulatory ability in <em>Melospiza melodia</em> (Song Sparrows) on the California Channel Islands. Our research builds on a study in Song Sparrow museum specimens that demonstrated a positive correlation between bill surface area and maximum temperature, suggesting a greater demand for dry heat dissipation in hotter, xeric environments. We sampled contemporary sparrow populations across three climatically distinct islands to test the hypotheses that bill morphology is influenced by habitat differences with functional consequences for foraging efficiency and is related to maximum temperature and, consequently, important for thermoregulation. Measurements of >500 live individuals indicated a significant, positive relationship between maximum temperature and bill surface area when correcting for body size. In contrast, maximum bite force, seed extraction time, and vegetation on breeding territories (a proxy for food resources) were not significantly associated with bill dimensions. While we cannot exclude the influence of foraging ability and diet on bill morphology, our results are consistent with the hypothesis that variation in Song Sparrows' need for thermoregulatory capacity across the northern Channel Islands selects for divergence in bill surface area.</p>
Data for impacts of topography-based subgrid scheme and downscaling of atmospheric forcing on modeling land surface processes in the conterminous US
<p>The effects of small-scale topography-induced land surface heterogeneity are not well represented in current Earth System Models (ESMs). A topography-based subgrid structure and methods of downscaling of atmospheric forcing from the atmospheric grid to the subgrids of the land model grid (TGUs) have been implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) to improve representation of the effects of small-scale topography-induced land surface heterogeneity on land surface processes. This study evaluates the impacts of the topography-based subgrid structure and downscaling of atmospheric forcing on modeling land surface processes in E3SM over the conterminous United States (CONUS). For this purpose, ELM simulations are performed using two configurations without (NoD ELM) and with (D ELM) downscaling, both using TGUs derived for the 0.5-degree grids and the same land surface parameters. Simulations using the two ELM configurations are compared over the CONUS domain, regional levels, and at observational sites (e.g., SNOTEL). The CONUS-level results suggest that D ELM simulates more snowfall and snow water equivalent (SWE), higher runoff, and less ET during spring and summer. Regional-level results suggest more pronounced impacts of downscaling over regions dominated by higher elevation TGUs and regions with maximum precipitation occurring during cool seasons. Results at the SNOTEL sites suggest that D ELM has superior capability of reproducing the observed SWE at 83% of the sites, with more pronounced performance over topographically heterogeneous TGUs with their maximum precipitation occurring during cool seasons. The results highlight the importance of improving representation of small-scale surface heterogeneity in ESMs and motivate future research to understand their effects on land-atmosphere interactions, streamflow, and water resources management over mountainous regions.</p> <p>The data utilized to evaluate effects of the topography-based subgrid structure and downscaling of atmospheric forcing in land surface modeling include a TGU level land surface data file, atmospheric forcing to drive the land model, ELM user name list configuration parameters, regionalization variables (topographic regions, snow fraction regions, water versus energy limited regions, and regions of season of maximum precipitation), model restart files for both ELM configurations, and model outputs (grid and subgrid levels), model outputs aggregated to TGUs and grid levels.</p> <p>The data files include:</p> <ol> <li><a href="../api/files/12bc9f1c-be98-4721-8c92-6e23845be441/daily_prism_precip.zip?versionId=be97ca8d-182a-4f1e-9ae3-9da3f2b87e24">DELM.zip</a>: Directory containing the following files relevant to the D ELM configuration and model output files.</li> <ol> <li>Restart file: 202201289.tgu_all_disag_yr1850surfdata.ielm.r05_r05.compy.elm.r.2005-01-01-00000.nc</li> <li>Configuration file: user_nl_elm</li> <li>Aggregated grid-level monthly output file: grd_level_output_disag_mnly_run_11_new_20221109.nc</li> <li>Aggregated grid-level daily output file: grd_level_output_disag_daily_20220512.nc</li> <li>TGU-level monthly output file: tgu_level_output_all_disag_20221109.nc</li> </ol> <li> <a href="../api/files/12bc9f1c-be98-4721-8c92-6e23845be441/dem_4km4.nc">NoDELM.zip</a>: Directory containing the following files relevant to the NoD ELM configuration and model output files.</li> <ol> <li>Restart file: 202201289.tgu_no_disag_yr1850surfdata.ielm.r05_r05.compy.elm.r.2005-01-01-00000.nc</li> <li>Configuration file: user_nl_elm</li> <li>Aggregated grid-level monthly output file: grd_level_output_nodisag_mnly_run_11_new_20221109.nc</li> <li>Aggregated grid-level daily output file: grd_level_output_nodisag_daily_20220512.nc </li> <li>TGU-level monthly output file: tgu_level_output_no_disag_20221109.nc</li> </ol> <li><a href="../api/files/12bc9f1c-be98-4721-8c92-6e23845be441/fr_number.zip?versionId=eacb5b60-9561-47f9-97c6-cd91e96afa1f">shared.zip</a>: Directory containing the following files relevant to both the D ELM and NoD ELM configurations.</li> <ol> <li>Subgrid-based surface data file: MASKED.half_degree_merge.surfdata_0.5x0.5_simyr1850_c200924.pft17.10262022v2.nc</li> <li>Regionalization file used to generate regions based on snow fraction, water versus energy limited state, and seasons of maximum precipitation: half_deg_budyko_curve_analysis_20230104_disag.nc</li> <li>Topographic ratio file used to generate topography-based regions: grd_level_output_nodisag_run_11_new_20221109.nc</li> <li>TGU-level surface elevation data file where surface elevation data are derived from high resolution surface elevation data (90 m) obtained from HydroSHEDS [Lehner et al. 2008, Lehner and Grill 2013]: half_deg_subgrids_with_PFTs_and_stat_20210403.nc</li> </ol> <li><a href="../api/files/12bc9f1c-be98-4721-8c92-6e23845be441/fr_number.zip?versionId=eacb5b60-9561-47f9-97c6-cd91e96afa1f">SNOTEL_files.zip</a>: Directory containing the following SNOTEL data related files used to evaluate model performance.</li> <ol> <li> SNOTEL list of stations file: SNOTEL_halfdegree_intersect4.csv</li> <li>SNOTEL data files/folders: csv</li> </ol> </ol> <p> </p> <p><strong>References</strong></p> <p>Lehner, B., et al. (2008). "New Global Hydrography Derived From Spaceborne Elevation Data." Eos, Transactions American Geophysical Union <strong>89</strong>(10): 93-94.</p> <p>Lehner, B. and G. Grill (2013). "Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems." Hydrological Processes <strong>27</strong>(15): 2171-2186.</p> <p> </p>
Electrically -Modulated Photothermal Force Microscopy for Revealing the Chemical Origins of Polarization Switching at the Nanoscale
<p>The data include all display items that are presented in the main manuscrit and supplementray information files.</p>
Data from: Connections between the Southern Ocean and the Eastern tropical Pacific in unforced and forced climate model simulations
<p>The sea surface temperature (SST) over the eastern tropical Pacific significantly influences global-mean climate feedback and may be driven in part by the SST over the Southern Ocean. Previous studies demonstrated a teleconnection from the Southern Ocean to the eastern tropical Pacific by perturbing the Southern Ocean climate. We investigate if this teleconnection holds in a fully coupled, freely running climate system using CMIP6 models. We assess the relationship between the Southern Ocean (SO) and the eastern tropical Pacific (SEP) by calculating correlations between SO and SEP SST timeseries within each model and regressions between mean SO and SEP SSTs across models. We show robust, positive SO-SEP relationships in an unforced climate using pre-industrial SSTs, in a forced climate using SST anomalies between pre-industrial and quadrupled CO<sub>2</sub> simulations, and in the SST pattern of the forced response relative to the global-mean SST anomaly. The strength of SO-SEP correlations is positively related to the stratocumulus cloud feedback off the west coast of South America, and negatively related to ocean heat uptake in the same region. As both shortwave cloud feedback and ocean heat uptake are underestimated in climate models, understanding their effects on SO-SEP teleconnections and their interactions is crucial for determining the strength of SO-SEP teleconnection in the real world and its trustworthiness in climate model projection.</p>
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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.