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ShareScore release 0.9.0
Dataset results
8 results for “elasticity analysis”
dataset for "basic setting", "+ binary semantic loss", "+ class weights", "+ height weights", "+ region weights", "+ elastic distortion and subsampling", "+ TreeMix" in paper Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning
<p>dataset for "basic setting", "+ binary semantic loss", "+ class weights", "+ height weights", "+ region weights", "+ elastic distortion and subsampling", "+ TreeMix" in paper Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning</p>
Surrogate-modelling & machine learning dataset : finite element stress analysis of biaxial specimen with random elastic properties - 1000 samples
<p>Dataset finite element stress analysis of biaxial specimen with random elastic properties</p> <p>Unzip and execute dataset.py to visualise data samples. PyVista is needed.</p>
Surrogate-modelling & machine learning dataset : finite element stress analysis of biaxial specimen with random elastic properties - 100 samples
<p>Dataset finite element stress analysis of biaxial specimen with random elastic properties</p> <p>Unzip and execute dataset.py to visualise data samples. PyVista is needed</p>
Supplemental material to 'A variational rigid-block modelling approach to nonlinear elastic and kinematic analysis of failure mechanisms in historic masonry structures subjected to lateral actions'
<p>This repository contains the data necessary to reproduce the content of the article:</p> <blockquote> <p>A variational rigid-block modelling approach to nonlinear elastic and kinematic analysis of failure mechanisms in historic masonry structures subjected to lateral actions (2021). Earthquake Engineering & Structural Dynamics, 1–23. <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/eqe.3512">https://doi.org/10.1002/eqe.3512</a></p> </blockquote> <p>The file <strong>01_Dataset.zip</strong> contains the dataset. The companion document <strong>00_Dataset_description.pdf </strong>describes the content of the dataset, guiding the analyst to its use in order to (i) reproduce the article's results and (ii) compare the article's results to new results brought by the analyst, e.g. by comparison with other numerical models.</p> <p>Version history</p> <p>v2: updated references in 00_dataset description.pdf </p>
Data from: Use of elastic stability analysis to explain the stress-dependent nature of soil strength
The peak and critical state strengths of sands are linearly related to the stress level, just as the frictional resistance to sliding along an interface is related to the normal force. The analogy with frictional sliding has led to the use of a 'friction angle' to describe the relationship between strength and stress for soils. The term 'friction angle' implies that the underlying mechanism is frictional resistance at the particle contacts. However, experiments and discrete element simulations indicate that the material friction angle is not simply related to the friction angle at the particle contacts. Experiments and particle-scale simulations of model sands have also revealed the presence of strong force chains, aligned with the major principal stress. Buckling of these strong force chains has been proposed as an alternative to the frictional-sliding failure mechanism. Here, using an idealized abstraction of a strong force chain, the resistance is shown to be linearly proportional to the magnitude of the lateral forces supporting the force chain. Considering a triaxial stress state, and drawing an analogy between the lateral forces and the confining pressure in a triaxial test, a linear relationship between stress level and strength is seen to emerge from the failure-by-buckling hypothesis.
Data from: Use of elastic stability analysis to explain the stress-dependent nature of soil strength
Open the record for dataset details and reuse information.
RNA-seq analysis of Jak2-V617F monocytes in elastic versus viscous fibrotic matrix
GEO Series GSE206771. Mus. 8 samples. Type: Expression profiling by high throughput sequencing.
Dynamic Arterial Elastance Measured by Uncalibrated Pulse Contour Analysis Predicts Arterial Pressure Response to a Decrease in Norepinephrine
ClinicalTrials.gov study NCT03455738. IPD Sharing: Not stated. Countries: 0. Publications: 0.
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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.