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2,214
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ShareScore release 0.9.0
Dataset results
2,214 results for “Strength”
Activity-Induced Regulation of Synaptic Strength through the Chromatin Reader L3mbtl1
GEO Series GSE104802. Mus musculus. 14 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Variability in intrinsic promoter strength underlies the temporal hierarchy of the Caulobacter SOS response induction
GEO Series GSE311073. Caulobacter vibrioides. 8 samples. Type: Expression profiling by high throughput sequencing.
Strength and spatial structure of the perturbation induced by a tropical cyclone to the underlying eddies
<p>The model data for the geostrophic response to a tropic cyclone.</p> <p>dd------model time (day)<br> depth---model depth (m)<br> y-------cross-track distance (km)<br> U-------along-track currents (m/s)<br> V-------cross-track currents (m/s)<br> TEM-----temperature (C)<br> SALN----salnity (psu)<br> SSH-----sea surface height (cm);</p> <p>The subscript "tot" denote the total response while the subscript "geo" the geostrophic response.</p>
Intraspecific difference among herbivore lineages and their host-plant specialization drive the strength of trophic cascades
<p>Dataset from the publication Intraspecific difference among herbivore lineages and their host-plant specialization drive the strength of trophic cascades</p>
FIGURE 3 in Body Mass, Bone "Strength Indicator," and Cursorial Potential of Tyrannosaurus rex
FIGURE 3. How to kill a Tyrannosaurus rex.
Data for "Shear zone development in serpentinised mantle: Implications for the strength of oceanic transform faults"
<p>Data (structural data used in serpentinite shear zone maps, Raman point analysis data, and EDS point analysis for oxide weight percents) used in the paper "Shear zone development in serpentinised mantle: Implications for the strength of oceanic transform faults"</p>
Geometries for "Equation-of-motion MLCCSD and CCSD-in-HF oscillator strengths and their application to core excitations"
<p>Geometries used in "Equation-of-motion MLCCSD and CCSD-in-HF oscillator strengths and their application to core excitations"</p>
Figures and graphics used in "Optimizing Strength of Shared Anchors in an Array of Floating Offshore Wind Turbines"
<p>All figures and graphics used in tables are included in PDF format here. Instructions on how to reproduce the MATLAB-generated plots (or similar plots) are included in the README of the software package, also cited in the paper.</p>
Data from: Non-consumptive effects of a top-predator decrease the strength of the trophic cascade in a four-level terrestrial food web
The fear of predators can strongly impact food web dynamics and ecosystem functioning through effects on herbivores morphology, physiology or behaviour. While non-consumptive predator effects have been mostly studied in three-level food chains, we lack evidence for the propagation of non-consumptive indirect effects of apex predators in four level food-webs, notably in terrestrial ecosystems. In experimental mesocosms, we manipulated a four-level food chain including top-predator cues (snakes), mesopredators (lizards), herbivores (crickets), and primary producers (plants). The strength of the trophic cascade induced by mesopredators through the consumption of herbivores decreased in the presence of top-predator cues. Specifically, primary production was higher in mesocosms where mesopredators were present relative to mesocosms with herbivores only, and this difference was reduced in presence of top-predator cues, probably through a trait-mediated effect on lizard foraging. Our study demonstrates that non-consumptive effects of predation risk can cascade down to affect both herbivores and plants in a four-level terrestrial food chain and emphasises the need to quantify the importance of such indirect effects in natural communities.
Data used for Investigating the role of Amazonian mesoscale wind patterns and strength on the spatial distribution of Martian bedrock exposures
<p>This upload contains four distinct zipped files with several different datasets contained within used for the analysis in publication "Investigating the role of Amazonian mesoscale wind patterns and strength on the spatial distribution of Martian bedrock exposures" by Gary-Bicas et al., 2022 Description for each dataset is below.</p> <p>- External data (Contains data used for thermophysical and morphological analysis).</p> <ul> <li>binary files NBmap2007.bin (Putzig and Mellon, 2007) and nmap2003.bin( Putzig et al., 2005) . These contain global Mars thermal inertia maps using the Thermal Emission Spectrometer (TES) onboard Mars Global Surveyor (MGS) </li> <li>Comma separated files with terminations "...USGS.csv" these are files extracting data for the studies' regions from the Mars global USGS geologic map #3292 (Tanaka et al., 2014) </li> <li>Shape file for bedrock designations (bedrock.[shp,shx,prj,dbf]) created by Cowart et al., 2019 where they mapped locations with bedrock exposures on Mars. We also include comma separated value files of the same maps for locations studied in this analysis (files with termination "...bedrock.csv")</li> <li>Shape file included has the locations of craters identified in all study regions for analysis (craters.point.[shp,shx,prj,dbf] and craters.polygon.[shp,shx,prj,dbf]) paired with the comma separated value intracrat.csv</li> <li>Shape file with study locations for analysis (windo_modeling_locations_revised3.[shp,shx,prj,dbf])</li> </ul> <p>- MRAMS data files.zip</p> <ul> <li>Contains 11 simulated climate states for each of the ten study location in analysis as well as Jezero crater using the Mars Regional Atmospheric Modeling System (MRAMS, Rafkin and Michaels, 2019). For each simulated case there are 4 seasonal time steps equating to 44 simulated cases for each study region in total (484 files) see associated python software publication indicating ingestion and processing of MRAMS datasets</li> </ul> <p>- MRAMS output files.zip</p> <ul> <li>After ingesting the datasets in MARS data files.zip into a python algorithm (see associated software publication) values for Wind Erosion Potential were extracted from the datasets and weighted sums were conducted to get annual values (see manuscript publication and associated python software publication,"MRAMS Data Output.ipynb") data was output into comma separated values for ease of use</li> </ul> <p>-MRAMS elevation and slope files.zip</p> <ul> <li>MRAMS data from output files.zip was further ingested into other algorithms to extract elevation and terrain slope values (see associated python software publication, "MRAMS Data Output.ipynb") that were output into comma separated values for ease of use</li> </ul> <p> </p> <p> </p>
DATASET FOR STUDY: Test-retest reliability of belt-fixated dynamometer for assessing maximal knee strength, inter-limb asymmetries and hamstring-quadriceps ratios
<p>Evaluating maximal strength, inter-limb asymmetries, and the hamstring-to-quadriceps (HQ) ratio is essential for identifying strength deficits in athletes. This cross-sectional study assessed the test–retest (inter-visit) reliability of the EasyForce dynamometer for knee extension and flexion strength in 21 young healthy participants (11 women and 10 men; age = 19.4 ± 0.7 years). The dynamometer demonstrated excellent relative reliability, with ICC values of 0.99 for knee extension and 0.95–0.98 for knee flexion. Absolute reliability was also acceptable (typical error = 5.63–16.44 N; coefficient of variation = 3.94–6.80%). Reliability for inter-limb asymmetries (ICC = 0.90) and HQ ratios (ICC = 0.91–0.92) was good to excellent. Agreement for inter-limb asymmetry direction between visits was excellent for knee extension (κ = 0.90) and substantial for knee flexion (κ = 0.71). These findings suggest that EasyForce is reliable for assessing muscle strength, inter-limb asymmetries, and HQ ratios in physically active adults. Future research should explore the broader applicability of EasyForce in muscle strength assessment, particularly for professional athletes and during rehabilitation.</p>
Dataset for machine learning guided prediction of the yield strength and hardness of multi-principal element alloys
<p>These data sets were used to develop machine-learning models to predict yield strength and hardness of multi-principal element alloys. We mainly collected the alloys and their mechanical properties from different published works. A list of references is provided at the end of each data set.</p>
The Relationship Between Hand Grip Strength, Trunk Control and Functional Performance in Individuals With Mild Mental Retardation
ClinicalTrials.gov study NCT06934850. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Reliability and Validity of the Evaluation of Hip Abductors Strength (RAVEHABDS)
ClinicalTrials.gov study NCT05140577. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Study of Intensive Care Unit (ICU)-Acquired Weakness (Handgrip Strength Study)
ClinicalTrials.gov study NCT00702000. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effects of Kinesiotape on Quadriceps and Hamstring Muscle Strength
ClinicalTrials.gov study NCT01994421. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Prospective Assessment of Loss of Grip Strength by Baseline BMI in Breast Cancer Patients Receiving Adjuvant Aromatase Inhibitors and Tamoxifen
ClinicalTrials.gov study NCT01223833. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Strength and Function Following Total Hip Arthroplasty
ClinicalTrials.gov study NCT01817010. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Effects of a 16-Week Individualized, Intensive Strength Training Program in Patients With Rheumatoid Arthritis
ClinicalTrials.gov study NCT00327275. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Investigation of Impacts of Vibration on Muscular Strength and Functional Performance of Upper Limbs of Older Adults
ClinicalTrials.gov study NCT04767932. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.