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610 results for “Static”
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 3, part 2.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 3, part 1.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 2, part 2.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 1, part 2.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 5, part 2.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 6, part 1.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 7, part 2.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 7, part 3.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 6, part 2.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Data for high-clay content submarine slope failure flume experiments. Experiment 100% clay, static 7, part 1.
<p>These video and photographic data support the following manuscripts:</p><p>Silver, M.M.W., Dugan, B., 2020, The influence of clay content on submarine slope failure: insights from laboratory experiments and numerical models, Geological Society of London, Special Publications, 500, 301-309, <a href="https://doi.org/10.1144/SP500-2019-186">https://doi.org/10.1144/SP500-2019-186</a>. </p><p>Silver, M.M.W., Dugan, B., 2023, Cohesion, permeability, and slope failure dynamics: implications for failure morphology and tsunamigenesis from benchtop flume experiments, Marine Geology, 462, <a href="https://doi.org/10.1016/j.margeo.2023.107079">https://doi.org/10.1016/j.margeo.2023.107079</a>.</p><p>Log sheets are included for each experiment file.</p>
Static and Dynamic Model Calibration for Upper Thermosphere Determination (2023SW003810)
<p>The dataset contains the background and static calibration models, associated with the figure data and routines. </p>
Test results from quasi-static impact tests over SMC materials reinforced with glass fibre (ramdom and textile)
<p>Test results from quasi-static impact tests over SMC materials with structural properties conceived for automotive applications, reinforced with glass fibre (samples with ramdom distribution of fibres and samples reinforced with GF textile)</p>
Water weakening and the compressive brittle strength of carbonates: influence of fracture toughness and static friction
<p>This is the ReadMe file corresponding to the study entitled:<br>"Water weakening and the compressive brittle strength of carbonates: influence of fracture toughness and static friction"<br>By Noël C., Fryer B., Baud P. and Violay M.</p> <p>This Read-Me file has been last edited in January 2024</p> <p>This readme file describes the data repository files accompanying the above publication published in IJRMMS. <br>For any further queries please contact corentin.noel@geoazur.unice.fr</p> <p>For each type of experiments (uniaxial compression, fracture toughness and friction), a zip file contains the the file of the experiments. Each file name contain the information of the sample tested and the experimental condition (dry or saturated):<br>- The first leter(s) stands for the limestone tested: In=Indiana, L=Leitha, S=Solnhofen, St=Saint Maximin, T=Tavel.<br>- The number following is for sample referencing.<br>- The next letter is for the experiment performed: U=Uniaxial compression, K=Fracture toughness, F=Friction<br>- After a "_", the experimental conditions are described: dry=dray experiments, sat=water saturated experiments</p> <p><br>*** Uniaxial compression ***<br>Each .txt file contains:<br>- Column 1: Axial stress (MPa)<br>- Column 2: Axial strain (-)<br>- Column 3: Radial strain (-)<br>- Column 4: Volumetric strain (-)</p> <p>Additionally, each experiments also have an accoustic file (.txt ending with _AE) containing:<br>- Column 1: Axial strain (-)<br>- Column 2: Cumulative AE number</p> <p>*** Fracture toughness ***<br>Each .txt file contains:<br>- Column 1: Axial displacement (mm)<br>- Column 2: Mode I stress intensity factor KI (MPa.m(1/2))<br>- Column 3: Crack mouth openning (mm)</p> <p>*** Friction ***<br>Each .txt file contains:<br>- Column 1: Time (s)<br>- Column 2: Shear stress (MPa)<br>- Column 3: Normal stress (MPa)<br>- Column 4: Shear displacement (mm)</p> <p>Additionally, for each experiment and both under dry and water saturated conditions a .xlsx file contains the picked static shear stress at the onset of sliding for each tested normal stress as follow:<br>- Column A: Normal stress (MPa)<br>- Column B: Shear stress at onset of sliding (MPa)<br>- Column C: Shear stress at onset of sliding lower boundary (MPa)<br>- Column D: Shear stress at onset of sliding higher boundary (MPa)<br>- Column E: Uncertainty on the shear stress at onset of sliding (MPa)</p>
Evaluation Artifacts of RESTRuler, a Static Analysis Tool to Detect Design Rule Violations in OpenAPI Definitions
<p>All artifacts related to the empirical evaluation of the RESTRuler CLI, a Java-based tool to identify design rule violations in OpenAPI descriptions</p> <p>You can find the latest version here: <a href="https://github.com/restful-ma/rest-ruler-evaluation">https://github.com/restful-ma/rest-ruler-evaluation</a></p>
Foot kinematics and kinetics data for different static foot posture collected using a multi-segment foot model
<p>Dataset presented in the paper <em>"Foot kinematics and kinetics data for different static foot posture collected using a multi-segment foot model".</em></p> <p>This dataset contains human foot joints kinematics and kinetics data collected during walking, classified depending on their static foot posture. The kinematics data were recorded using a three-dimensional motion analysis system, and kinetics data were recorded through a pressure platform. The data was collected considering a multi-segment foot model that considers the ankle, midtarsal and first metatarsophalangeal joint. A total of 70 healthy subjects with different static posture (highly pronated, highly supinated and normal, as classified by the foot posture index) participated in the experiments. This dataset contains a total of 350 continuous recordings of anatomical angles and joint moments of the ankle, midtarsal, and first metatarsophalangeal joints of the right foot during walking, as well as the right foot contact pressures recorded. The recordings were collected at 100 Hz, and the resulting data are provided filtered and resampled to 100 frames evenly distributed along the stance phase. Participants’ descriptive data are also provided: age, weight, height, and foot anthropometric data and foot posture index for both feet. The data are presented as a spreadsheet file (.xlsx) and a Matlab structure file (.mat), with contact pressures provided only in the .mat file. Further details and data validation are provided in the main paper.</p>
Dataset for On the Relevance of Static Cells for Fast Scale-Up of New Redox Flow Battery Chemistries
<p>Dataset for the results shown in the publications "On the Relevance of Static Cells for Fast Scale-Up of New Redox Flow Battery Chemistries"</p>
Replication package for "An Empirical Evaluation of Static, Dynamic, and Hybrid Slicing of WebAssembly Binaries"
<p>This is the replication package that accompanies the paper "An Empirical Evaluation of Static, Dynamic, and Hybrid Slicing of WebAssembly Binaries".</p> <p>It is structured as follows.</p> <p> - RQs.py is the script that generates the data that is included in the paper. For each research question, it generates statistics and plots.<br> - The .csv files and nok.txt are used by RQs.py. They contain the raw size and timing data for each slice. The headers of the .csv files indicate what each column represents.<br> - `sqlite-slices.csv` contains the raw data for RQ8, which is contained in the paper<br> - The .tar.gz files contain the source and the slices generated by each slicer, namely:<br> - `static_slices.tar.gz` contains the slices generated by CsE, the static slicer. For example, the file `static_slices/adpcm/adpcm_ah1_254_expr/static_adpcm.wat.slice` is the slice of the adpcm program taken with respect to the variable `ah1` at line `254` of the original `.c` program.<br> - `slice.tar.gz` contains slices from the dynamic slicers:<br> - slice-sce - the SCE slices<br> - slice-ces - the CES slices<br> - slice-cse - the CSE slices<br> - slice-sces - the SCES slices<br> - slice-cses - the CsES slices<br> - `src.tar.gz` includes the unsliced `C` and `wasm` source<br> - `bc.support.tar.gz` includes the complete `bc` source code <br> - `sqlite.tar.gz` contains the slices of RQ8, each in a directory named after the slicer used. For example, the file `sqlite/CES/avg.wat` contains the CES slice for the `avg` slicing criterion.<br> <br>In order to regenerate the data and plots that are in the paper, you should simply run:</p> <p>```<br>python RQs.py<br>```</p>
Research Data Supporting "Electrostatic co-assembly of nanoparticles with oppositely charged small molecules into static and dynamic superstructures"
<p>This repository contains the set of data shown in the paper "<strong>Electrostatic co-assembly of nanoparticles with oppositely charged small molecules into static and dynamic superstructures</strong>", published on <strong>Nature Chemistry </strong>(DOI: 10.1038/s41557-021-00752-9).</p> <p>The files in the folders are organized as follow:</p> <p><strong>AA_models/ : </strong>contains all the files needed to run the Atomistic simulations discussed in the paper (including the topologies and starting configurations).</p> <p><strong>CG_models/ : </strong>contains all the files needed to run the Coarse Grained simulations discussed in the paper (including the topologies and starting configurations).</p> <p><strong>citrate_analysis/ : </strong>contains all the files needed to reproduce the analysis of the CV and SOAP+PCA+PAMM (including input files and python scripts).</p> <p>Additional details are available in the methods section and in the Supporting Information of the main paper.</p>
Modelling of static liquefaction of partially saturated non-cohesive soils - Supplementary Materials
<p><strong>Supplementary Material - Repository S1: Experimental data</strong></p> <p>Article title: Modelling of static liquefaction of partially saturated non-cohesive soils<br> Journal name: Applied Sciences</p> <p>Detailed data of undrained triaxial laboratory tests conducted on partially saturated samples of non-cohesive soils. <br> This spreadsheet contains values of initial parameter of each sample (saturation level, density and porosity, stress state and back pressure) and values of stresses, strains and pore pressure measured during the experiments. File includes also information about physical properties of tested soils: medium Skarpa sand and copper mining post-floating tailings OZM50.</p>
What really changes when developers intend to improve their source code: A commit-level study of static metric value and static analysis warning changes
<p>This is the dataset for the publication "What really changes when developers intend to improve their source code: A commit-level study of static metric value and static analysis warning changes".</p> <p>It contains a random sample of 2533 commits from 54 Java Apache open source projects classified by two researchers into perfective, corrective and other changes (manual_labels.csv). Moreover, we include static source code metrics and static analysis warnings for the 2533 changes in al_changes_gt.csv.gz.</p> <p>In addition, we include the full dataset of 125482 commits in all_changes_sebert.csv.gz with all metrics and automatic labels for every commit that was not manually labeled. The automatic labels were provided by a fine-tuned transformer model (BERT) pre-trained exclusively on software engineering data.</p> <p>We also provide the fine tuned version of the pre-trained model in seBERT_fine_tuned_commit_intent.tar.gz as well as a Snapshot of the SmartSHARK MongoDB database used in gathering the raw data in smartshark_emse.agz.</p> <p>The model can be tested live on the <a href="https://user.informatik.uni-goettingen.de/~trautsch2/emse_2021/commit_intent.html">website</a> accompanying the publication.</p>
ScienceDex guides
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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.