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1,670 results for “FORCE”
Allometric tissue-scale forces activate mechanoresponsive immune cells to determine pathological foreign body response to biomedical implants
GEO Series GSE227908. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Gene expression profile upon IL-22 stimulation, forced expression of Hes1, or IL-22 stimulation under forced expression of Hes1, in human colon carcinoma-derived LS174T cells
GEO Series GSE43012. Homo sapiens. 3 samples. Type: Expression profiling by array.
Selective retrieval of individual cells from microfluidic arrays combining dielectrophoretic force and directed hydrodynamic flow
GEO Series GSE143190. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Targeting DNA topoisomerases or checkpoint kinases forces a shift in global protein homeostasis, triggering widespread protein aggregation
GEO Series GSE173940. Homo sapiens. 32 samples. Type: Expression profiling by high throughput sequencing.
Atmospheric forcing dataset for Numerical study of the seasonal thermal and gas regimes of the large artificial lake in Western Europe using LAKE2.0
<p>Input dataset for the LAKE2.0 model (http://tesla.parallel.ru/Viktor/LAKE/wikis/LAKE-model) that was used for the experiments in the "Numerical study of the seasonal thermal and gas regimes of the large artificial lake in Western Europe using LAKE2.0" article. Archive contains the atmospheric forcing file itself, file with the header description, and the setup and driver files for the LAKE2.0 model.</p> <p>Source code of the current version of the LAKE2.0 model used in the work mentioned above, pre-compiled exec of the FLake model as well as its source code (freely available under the terms of the MIT license) are also provided as separate archive files.</p> <p> </p>
Simulations of POPC:POPG 1:1 membranes with varying levels of CaCl_2 using the Slipids force field
<p>Simulations of POPC/POPG lipid bilayers consisting of a total of 256 lipids (128 POPC + 128 POPG) spread equally between the two leaflets. The initial CaCl_2 concentration in the water phase was either 0, 100, 200, 500, or 1000 mM. Na+ was used as the counterion for the POPG charges. The simuatlions were performed using the Slipids model, available at http://www.fos.su.se/~sasha/SLipids/ . The Dang ion parameters were used, and they were obtained from https://bitbucket.org/hseara/ions/ . The common simulation parameters are given in the md.mdp file. The simulations are 1500 ns long (except CA0, which is 500 ns long), and the "extend" files contain the last 1000 ns of the outputs. The "extend" continue points should also be used to extend the simulations beyond 1500 ns. All relevant input and output files are provided to repeat or extend the simulations.</p>
Initial condition and forcing files for the circulation and sea ice MITgcm model for the West Antarctic Peninsula
<p>This dataset contains the initial condition, grid and forcing files used to run a circulation and sea ice model for the West Antarctic Peninsula (WAP), in hindcast experiments that simulated the period between 1980-2014. The files include glacial runoff, atmospheric forcings, boundary conditions, shelf ice files and grid. </p>
MD simulation of HpTonB(30-285) in 150mM NaCl with Amber ff03ws force field
<p>MD simulation of periplasmic part of TonB protein from <em>Helicobacter Pylori</em> HpTonB(30-285) with Amber ff03ws force field with 150 mM NaCl. Trajectory contains the last 1000ns of the simulation.</p> <p>micro_nojump_nowater.xtc (10 ps saving frequency), nowater.tpr, and confENDprot.gro contain only protein.</p> <p>1microsecondSKIP.xtc (100 ps saving frequency), md.tpr and confEND.gro contain also solvent.</p> <p>Force field parameters for proteins and counterions are dowloaded from https://github.com/bestlab/force_fields, for NaCl from https://bitbucket.org/hseara/ions</p>
MD simulation of HpTonB(30-285) in 40mM NaCl with Amber ff03ws force field
<p>MD simulation of periplasmic part of TonB protein from <em>Helicobacter Pylori</em> HpTonB(30-285) with Amber ff03ws force field with 40 mM NaCl. Trajectory contains the last 1000ns of the simulation.</p> <p>nojump_nowater.xtc (10 ps saving frequency), md_noSOL.tpr, and confENDprot.gro contain only protein.</p> <p>micro_40mMNaClskip.xtc (100 ps saving frequency), md.tpr and confEND.gro contain also solvent.</p> <p>Force field parameters for proteins and counterions are dowloaded from https://github.com/bestlab/force_fields, for NaCl from https://bitbucket.org/hseara/ions</p>
Primary data for "Identification of molecular quantum states using phase-sensitive forces"
<p>Figure4_v3.m is a Matlab file that creates Figure4 of the manuscript. It uses auxiliary functions to calculate the polarizability of N2+.</p> <p>Table_I_v3.m is a Matlab file that crates Table I of the manuscript. It uses same auxiliary functions as the last script.</p> <p>RawData.pdf gives the Rabi signals from which the data points in Figure 4 are calculated.</p> <p>CalibrationProcedure.pdf gives additional information on the calibration made using Ca+.</p>
Input forcing data for CLM4.5 or CLM5 at Soltis Center in Costa Rica
<p>Input forcing data for CLM4.5 or CLM5 at Soltis Center in Costa Rica</p>
CORE inter-annual forced ocean ice simulation using E3SMv0-HiLAT-tx0.3v2 (HiLAT03)
<p>This data set supports the analysis presented in the manuscript: “Labrador Sea freshening linked to Beaufort Gyre freshwater release” (LA-UR-20-20936), which is under review for publication by Nature Communications. The model output is from a 186-year long simulation with the E3SMv0-HiLAT code that was described in the technical report: “An eddy-permitting ocean-sea ice general circulation model (E3SMv0-HiLAT03): Description and evaluation” (LA-UR-19-25177; doi: 10.2172/1542803), by Zhang et al.. The ocean and sea ice components are active, and their grid is configured with a nominal 0.3 degree horizontal resolution. The model is forced by an atmospheric data set that represents the atmospheric state from 1948 through 2009, and is repeated for 3 cycles.</p> <p>#----------------------------------------------------------------------------------------------------------<br> # Data description<br> # Fri Jul 24 16:55:12 MDT 2020<br> # Contacts: Jiaxu Zhang (jiaxuzh@uw.edu) and Wilbert Weijer (wilbert@lanl.gov)<br> #----------------------------------------------------------------------------------------------------------<br> Simulation length: 186 years<br> Simulation machine: LANL HPC facility, on Grizzly<br> Case name: t32_GIAF_woa13rest_deepenNares_Griz<br> Time range: 012101-018612 (corresponding to Jan 1948 to Dec 2009)<br> Grid file: gridFile/tx0.3v2_grid.nc<br> In the post-processed files:<br> pop = ocean output from POP2<br> mon = monthly<br> ann = annual mean<br> clim = monthly climatology<br> ltm = long-term annual mean<br> dec = decadal mean<br> YYYYMM-YYYYMM = time range<br> FastRel = Fast release case, corresponding to the 016001-017212 period<br> FastAcc = Fast accumulation case, corresponding to the 017301-018512 period<br> NH = data only contain the Northern Hemisphere</p> <p>Similarly, there are files for "BG" (Beaufort Gyre), "Davis_Strait", "Fram_Strait", "Labrador_Sea", "Labrador_Sea_Outflow", "Lancaster_Sound", and "Nares_Strait". These regions are illustrated in Figure 1 of the manuscript.</p> <p>Variable names:<br> SALT = salinity<br> UES = East flux of SALT<br> UVEL = Zonal Velocity<br> VNS = North flux of SALT<br> VVEL = Meridional velocity<br> DYE01 = dye tracer that tags the Beaufort Gyre freshwater (from surface to the reference salinity of 34.6)<br> DSALT01 = salt tracer that tags the Beaufort Gyre salinity (from surface to the reference salinity of 34.6)<br> UE_DSALT01 = East flux of DSALT01<br> VN_DSALT01 = North flux of DSALT01</p> <p>In the transport folder:<br> File names: transport.[StraitName].012101-018612.txt<br> Content: Diagnosed transport at a specific strait.<br> Structure: 4 columns are<br> 1. Model time (days since 0001-01)<br> 2. Volume transport (Sv)<br> 3. Heat transport (PW)<br> 4. Liquid freshwater transport (mSv)<br> For all the transports, positive is poleward, negative is equatorward.</p> <p><br> File names: [CaseName].transport.BG_portion.[StraitName].txt<br> Content: Diagnosed BG-sourced transport at a specific strait for either FastRel or FastAcc case.<br> Structure: 8 columes are<br> 1. Model time (days since 0001-01)<br> 2. Volume transport (Sv)<br> 3. Liquid freshwater transport (mSv)<br> 4. Validation data, please ignore<br> 5. Validation data, please ignore<br> 6. Volume transport sourced from BG alone (Sv)<br> 7. Liquid freshwater transport sourced from BG alone (mSv)<br> 8. Validation data, please ignore</p> <p> </p> <p> </p> <p> </p> <p> </p>
Data from: Deformability assessment of waterborne protozoa using a microfluidic-enabled force microscopy probe
Many modern filtration technologies are incapable of the complete removal of Cryptosporidium oocysts from drinking-water. Consequently, Cryptosporidium-contaminated drinking-water supplies can severely implicate both water utilities and consumers. Existing methods for the detection of Cryptosporidium in drinking-water do not discern between non-pathogenic and pathogenic species, nor between viable and non-viable oocysts. Using FluidFM, a novel force spectroscopy method employing microchannelled cantilevers for single-cell level manipulation, we assessed the size and deformability properties of two species of Cryptosporidium that pose varying levels of risk to human health. A comparison of such characteristics demonstrated the ability of FluidFM to discern between Cryptosporidium muris and Cryptosporidium parvum with 86% efficiency, whilst using a measurement throughput which exceeded 50 discrete oocysts per hour. In addition, we measured the deformability properties for untreated and temperature-inactivated oocysts of the highly infective, human pathogenic C. parvum to assess whether deformability may be a marker of viability. Our results indicate that untreated and temperature-inactivated C. parvum oocysts had overlapping but significantly different deformability distributions.
Data from: Priority effects are interactively regulated by top-down and bottom-up forces: evidence from wood decomposer communities
Both top-down (grazing) and bottom-up (resource availability) forces can determine the strength of priority effects, or the effects of species arrival history on the structure and function of ecological communities, but their combined influences remain unresolved. To test for such influences, we assembled experimental communities of wood-decomposing fungi using a factorial manipulation of fungivore (Folsomia candida) presence, nitrogen availability, and fungal assembly history. We found interactive effects of all three factors on fungal species composition and wood decomposition 1 year after the fungi were introduced. The strength of priority effects on community structure was affected primarily by nitrogen availability, whereas the strength of priority effects on decomposition rate was interactively regulated by nitrogen and fungivores. These results demonstrate that top-down and bottom-up forces jointly determine how strongly assembly history affects community structure and function.
Thoracic gas compression during forced expiration is greater in men than women
<p>Intrapleural pressure during a forced vital capacity (VC) manoeuvre is often in excess of that required to generate maximal expiratory airflow. This excess pressure compresses alveolar gas (i.e., thoracic gas compression; TGC), resulting in underestimated forced expiratory flows (FEFs) at a given lung volume. It is unknown if TGC is influenced by sex; however, because men have larger lungs and stronger respiratory muscles, we hypothesized that men would have greater TGC. We examined TGC across the "effort-dependent" region of VC in healthy young men (n=11) and women (n=12). Subjects performed VC manoeuvres at varying efforts while airflow, volume, and oesophageal pressure (P<sub>OES</sub>) were measured. Quasi-static expiratory deflation curves were used to obtain lung recoil (P<sub>LUNG</sub>) and alveolar pressures (i.e., P<sub>ALV</sub>=P<sub>OES</sub>–P<sub>LUNG</sub>). The raw maximal expiratory flow-volume (MEFV<sub>raw</sub>) curve was obtained from the "maximum effort" VC manoeuvre. The TGC-corrected curve was obtained by constructing a "maximal perimeter" curve from all VC efforts (MEFV<sub>corr</sub>). TGC was examined via differences between curves in FEFs (∆FEF), area under the expiratory curves (∆A<sub>EX</sub>), and estimated compressed gas volume (∆VGC) across the VC range. Men displayed greater total ∆A<sub>EX</sub> (5.4±2.0 vs. 2.0±1.5 L<sup>2</sup>∙s<sup>-1</sup>; <i>p</i><0.001). ∆FEF was greater in men at 25% of exhaled volume only (<i>p</i><0.05), whereas ∆VGC was systematically greater in men across the entire VC (main effect; <i>p</i><0.05). P<sub>ALV</sub> was also greater in men throughout forced expiration (<i>p</i><0.01). Taken together, these findings demonstrate that men display more TGC, occurring early in forced expiration, likely due to greater expiratory pressures throughout the forced VC manoeuvre. </p>
An Investigation into the Mechanisms of Media Use Influencing Pro-environmental Contextual Forces and Sustainable Behaviors in Rural Tourism
<p><strong>An Investigation into the Mechanisms of Media Use Influencing Pro-environmental Contextual Forces and Sustainable Behaviors in Rural Tourism</strong></p>
Arctic Climate Response to European Radiative Forcing: A Deep Learning Study on Circulation Pattern Changes (control run daily dataset)
<p>30-year Control run with MPI-ESM1.2 coupled atmosphere-ocean–land surface model with preindustrial boundary and initial condition (for more information see the paper)<br> </p>
Arctic Climate Response to European Radiative Forcing: A Deep Learning Study on Circulation Pattern Changes (Experiment run daily dataset)
<p>0-year Experiment run with excerted negative radiative forcing over Europe with MPI-ESM1.2 coupled atmosphere-ocean–land surface model with preindustrial boundary and initial condition (for more information see the paper) </p>
Data from: The ozone radiative forcing of nitrogen oxide emissions from aviation can be estimated using a probabilistic approach.
<p>This dataset accompanies the journal article entitled "The ozone radiative forcing of nitrogen oxide emissions from aviation can be estimated using a probabilistic approach.", currently under review, and contains:</p> <p>1) The post-processed version of the original dataset that is available here [1]: https://data.4tu.nl/private_datasets/cLnjZscxOJDZnBSajrE0XxooMxJspT40byq4FVnq26A. </p> <p>The original dataset has been generated from several simulations performed with the ECHAM/MESSy Atmospheric Chemistry model (EMAC). The short-term impact on atmospheric ozone (O<sub>3</sub>) from aircraft nitrogen oxide (NO<sub>x</sub>) emissions is estimated for five regions (North America, Eurasia, South America, Africa and Australasia), three pressure altitudes (200, 250 and 300 hPa) and two seasons (July 1, 2014 representing the Northern summer and January 1, 2014 representing Northern winter) using three calculation methods: Eulerian tagging, Lagrangian tagging and perturbation. Each region has 28 points at which 0.5 Gg of NO are introduced in the form of a 15-min pulse emission. </p> <p>In our manuscript, we use the Lagrangian tagging dataset. We compute the global annual mean radiative forcing of O<sub>3 </sub>from NO<sub>x </sub>for each and every emission point, and plot them in Figure 1 (b). The mass curves of NO<sub>x </sub>and O<sub>3</sub> for two emission points are also plotted using the original data in Figure 1 (c). </p> <p>2) Meteorological data, fllight path data from EUROCONTROL, great circle data which are plotted in Figure 5 (b) of the manuscript. </p> <p>Please consult the README file for specific details regarding the data.</p>
The impact of planting density on the morphological traits and peak pullout force of vegetation and slope stability
<p><a href="../api/records/10937858/draft/files/NC_morphological.xls/content" target="_blank" rel="noopener noreferrer">NC_morphological.xl</a>s and <a href="../api/records/10937858/draft/files/NC_morphological.xls/content" target="_blank" rel="noopener noreferrer">MS_morphological.xls files include all morphological traits of two species, </a><a href="../api/records/10937858/draft/files/ms_force_space.RData/content" target="_blank" rel="noopener noreferrer">ms_force_space.RData</a><a href="../api/records/10937858/draft/files/NC_morphological.xls/content" target="_blank" rel="noopener noreferrer"> and nc</a><a href="../api/records/10937858/draft/files/ms_force_space.RData/content" target="_blank" rel="noopener noreferrer">_force_space.RData files include the uprooting force - time data.</a></p> <p><a href="../api/records/10937858/draft/files/ms_force_space.RData/content" target="_blank" rel="noopener noreferrer">In ms_force_space.RData</a><a href="../api/records/10937858/draft/files/NC_morphological.xls/content" target="_blank" rel="noopener noreferrer"> and nc</a><a href="../api/records/10937858/draft/files/ms_force_space.RData/content" target="_blank" rel="noopener noreferrer">_force_space.RData, Time means sampling time, AI1.01 means uprooting force, sample means the sampling ID, test means different planting densities. </a></p> <p><span>This study examines the influence of planting density on the morphological traits and peak pullout force of two herbaceous plant species, <em>Medicago sativa</em> (MS) and <em>Nepeta cataria</em> (NC), and their collective impact on slope stability. Through field experiments across six planting densities (8, 11, 16, 25, 44, and 100 plants/m²), we evaluated changes in plant morphology, root and shoot biomass, and root anchorage strength. The peak pullout force was analyzed using the infinite slope stability model to assess its correlation with slope stability coefficients.</span></p>
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.