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12,393 results for “materiality”
Research Data - Microstructural and material property changes in severely deformed Eurofer-97
<p>Research data and associated processing and plotting scripts for the article:</p> <p>Song <em>et al</em>., 'Microstructural and material property changes in severely deformed Eurofer-97', <em>Materials Characterization</em>, 114144, 2024</p> <p><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.matchar.2024.114144" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.matchar.2024.114144</span></span></a></p>
Supplemental Material for "Slow-to-fast Transition and Shear Localization in Accelerating Creep of Clayey Soil"
<div> <p>Dataset and plotter for "Slow-to-fast Transition and Shear Localization in Accelerating Creep of Clayey Soil" by Chengrui Chang.</p> <p>This dataset contains all 40 fluid-injection shear experiments on clayey soil. Each .mat file includes raw data and constrained parameters for the accelerating creep. A spreadsheet summarizes the experimental protocols and constrained parameters.</p> </div> <div>Article information:</div> <div>Chang, C., Noda, H., Xu, Q., Huang, D., & Yamaguchi, T. (2024). Slow‐to‐fast transition and shear localization in accelerating creep of clayey soil.<br>Geophysical Research Letters, 51, e2024GL111839. <a href="https://doi.org/10.1029/2024GL111839">https://doi.org/10.1029/2024GL111839</a></div>
Supplementary Material - Active Learning in Software Engineering A Rapid Review
<p>Supplementary Material for paper Active Learning in Software Engineering: A Rapid Review presented in CLEI 2024. The spreadsheet contains the studies considered for the Rapid Review.<br><br></p>
Statistical Analysis of Selected Mixtures of Alkali-activated Materials Exposed to Thermal
<p>Alkaline-activated materials have come to the forefront of the interest of construction experts in recent decades.<br>It is a composite material, an alternative to concrete, where the binder component can be a by-product (with pozzolanic or<br>latent hydraulic properties) of some industrial processes instead of ecologically disadvantageous cement. The work is<br>focused on the statistical analysis of the compressive strength of alkali-activated materials exposed to temperature stress,<br>where the first part contains three mixtures of alkali-activated composites that were subjected to the frost resistance test,<br>and the second part follows the functional dependence of the compressive strength of the selected mixture of the alkaliactivated system on exposure to high temperatures with the selection of the optimal statistical model.</p>
Inductively heatable catalytic materials for the dehydrogenation of the liquid organic hydrogen carrier (LOHC) perhydro dibenzyltoluene
<p>This data publication is based on the metadata and datasets underlying the manuscript: "Inductively heatable catalytic materials for the dehydrogenation of the liquid organic hydrogen carrier (LOHC) perhydro dibenzyltoluene "</p>
Supplementary Materials for Respiratory Syncytial Virus Genetic Diversity and Lineage Changes in Ireland pre- and post-COVID-19 pandemic
<p><span>The datasets presented here are the list of publicly available reference sequences used in NextClade (</span><a href="https://github.com/rsv-lineages"><span>https://github.com/rsv-lineages</span></a><span>) to provide the lineage classification of samples and used as reference for analysis of Irish RSV sequences (Supplementary Table 1), the list of sequenced Human respiratory syncytial viruses (RSV) in the Republic of Ireland during the period 2015-2024 (Supplementary Table 2) and the details of sequences downloaded from GISAID corresponding to European RSV sequences for the same period of time.</span></p> <p><span> </span></p> <p><span>Description of the data and file structure</span></p> <p><span>The files in this dataset were formatted in Microsoft Excel 2019 to allow easy access and manipulation of the data. The data corresponds to details on the sequences used in the analysis of RSV in Europe during the 2015-2024 period. The contents of the files are described below: -<strong>Supplementary Table 1</strong>: NextClade Reference Sequences publicly available at </span><a href="https://github.com/rsv-lineages"><span>https://github.com/rsv-lineages</span></a><span>. -<strong>Supplementary Table 2</strong>: Irish RSV Sequence Details contains details on the sequences generated in our study with the GenBank accession number, the GISAID accession number, reported collection RSV season, Nextclade assigned taxonomical clade. -<strong><span>Supplementary Table 3</span></strong>: European RSV Sequence Details contains a list of European RSV sequences downloaded from GISAID (</span><a href="https://gisaid.org/"><span>https://gisaid.org/</span></a><span>) with details on the sampling RSV season, the accession number, country of collection, and lineage assigned by NextClade.</span></p> <p><span> </span></p> <p><span>Sharing/Access information</span></p> <p><span>The databases used to extract and deposit the data were:</span></p> <p><span>-GenBank: the North American repository of sequences and publicly available at: </span><a href="https://www.ncbi.nlm.nih.gov/genbank/"><strong><span>https://www.ncbi.nlm.nih.gov/genbank/</span></strong></a><span> </span></p> <p><span>-GISAID:International consortium of sequences with some metadata and clinical data. It is a semi-public repository with easy access requiring only to create an account. Available at: </span><a href="https://gisaid.org/"><strong><span>https://gisaid.org/</span></strong></a></p> <p><span>-Github: reference sequences of RSV are available at the repository </span><a href="https://github.com/"><strong><span>https://github.com/</span></strong></a></p>
Experimental volumetric hydrogen uptake determination at 77 K of commercially available metal-organic framework materials
<p>File: carbon-08-00005-with-cover.pdf</p> <p>This file contains the published paper (PDF) with a cover page.</p> <p> </p> <p>File: carbon-1535765-supplementary.pdf</p> <p>This file (PDF) contains supporting data on the characterization of MOFs and hydrogen adsorption measurements.</p>
Supporting materials for "Suppressing torsional buckling in auxetic meta-shells"
<p>The repository of the supporting materials for the manuscript entitled "Suppressing torsional buckling in auxetic meta-shells"<br>Supporting materials include:</p> <ol> <li>Experimental and finite element data sets</li> <li>Python codes for (i) analyzing the data and visualizing the figures in the manuscript and (ii) performing image analysis to obtain the radial strain of the meta-shells</li> <li>CAD files used for 3D printing the models and simulating them via finite element simulation</li> <li>The input files for the finite element analysis.</li> </ol>
Dataset for Modelling of infiltration rates in soils derived from contrasting parent materials using Horton's model
<p>This dataset was initially generated as part of a broader project investigating infiltration and various soil properties in soils derived from three parent materials in Akwa Ibom State, Nigeria: Alluvial Clay, Coastal Plain Sands, and Sandstone. Utin and Oguike (2018) initially utilized this data to evaluate Philip's and Kostiakov's models in these soils. Subsequently, the infiltration data were employed as secondary data to assess the performance of Horton's model in predicting infiltration rates for the three soil types.</p>
Material stock map of the United Kingdom and the Republic of Ireland
<p>Understanding the size and spatial distribution of material stocks is crucial for sustainable resource management and climate change mitigation. This study presents high-resolution maps of buildings and mobility infrastructure stocks for the United Kingdom (UK) and the Republic of Ireland (IRL) at 10 m, combining satellite-based Earth observations, OpenStreetMaps, and material intensities research. Stocks in the UK and IRL amount to 19.8 Gigatons or 279 tons/cap, predominantly aggregate, concrete and bricks, as well as various metals and timber. Building stocks per capita are surprisingly similar across medium to high population density, with only the lowest population densities having substantially larger per capita stocks. Infrastructure stocks per capita decrease with higher population density. Interestingly, for a given building stock within an area, infrastructure stocks are substantially larger in IRL than in the UK. These maps can provide useful insights for sustainable urban planning and advancing a circular economy.</p> <p>This dataset features a detailed map of material stocks in the United Kingdom and the Republic of Ireland on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors.</p> <p><strong>Spatial extent</strong><br>This dataset covers the whole British Isles. Due to processing reasons, the dataset is internally structured into the Island of Ireland, and the Island of Great Britain.</p> <p><strong>Temporal extent</strong><br>The map is representative for ca. 2018.</p> <p><strong>Data format</strong><br>The data are organized by nations. Within each nation, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided.</p> <p>Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types).</p> <p>Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e.</p> <ul> <li>t at 10m x 10m</li> <li>kt at 100m x 100m</li> <li>Mt at 1km x 1km</li> <li>Gt at 10km x 10km</li> </ul> <p>For each nation, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming. </p> <p>Additionally, the grand total mass per nation is tabulated for each island in <em>mass_grand_total_t_10m2.tif.csv</em>. County code and the ID in this table can be related via zones_name_pop<em>.csv</em>.</p> <p><strong>Material layers</strong><br>Note that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). </p> <p><strong>Further information</strong><br>For further information, please see the publication.<br>Visit our <a href="https://boku.ac.at/understanding-the-role-of-material-stock-patterns-for-the-transformation-to-a-sustainable-society-mat-stocks">website</a> to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.</p> <p><strong>Publication</strong></p> <p>D. Wiedenhofer, F. Schug, H. Gauch, M. Lanau, M. Drewniok, A. Baumgart, D. Virág, H. Watt, A. Cabrera Serrenho, D. Densley Tingley, H. Haberl, D. Frantz (2024): Mapping material stocks of buildings and mobility infrastructure in the United Kingdom and the Republic of Ireland. <em>Resources, Conservation and Recycling</em> 206, 107630. <a href="https://doi.org/10.1016/j.resconrec.2024.107630">https://doi.org/10.1016/j.resconrec.2024.107630</a></p> <p><strong>Funding</strong><br>This research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). </p> <p><strong>Acknowledgments</strong><br>We thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on <a href="https://eodc.eu/">EODC</a> - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC, and Wolfgang Wagner for granting access to preprocessed Sentinel-1 data.</p>
Supporting material for the paper " Test Smells Learning by a Gamification Approach"
<p>Table reporting the frequencies of answers to the 31 questions (1 = Strongly Disagree, 5 = Strongly Agree) to the survey about the use of the TSGame tool.</p> <p>Figures reporting:</p> <ul> <li>the architecture of the TSGame tool</li> <li>Detection Game Web page</li> <li>Refactoring Game Web page</li> <li>Solution Sharing Web page</li> </ul>
Supporting material for the paper "Testing Robot Challenge: a Serious Game for Testing Learning"
<p><strong>Experimental data</strong></p> <p>Table reporting the frequencies of student answers to the 29 questions (1 = Strongly Disagree, 5 = Strongly Agree) to the survey about the use of the Testing Robot Challenge Web application.</p> <p> </p> <p><strong>Figures</strong></p> <ul> <li>Game Main Page</li> <li>End Game Page</li> <li>Game mechanics of the Testing Robot Challenge</li> <li>Game Selection Page</li> <li>Home Page</li> <li>Software Architecture</li> </ul>
Supplementary Material for "Investigating Software Development Teams Members' Perceptions of Data Privacy in the Use of Large Language Models (LLMs)"
<h3>ABSTRACT<strong>: </strong></h3> <p><strong>Context</strong>: Large Language Models (LLMs) have revolutionized natural language generation and understanding. However, they raise significant data privacy concerns, especially when sensitive data is processed and stored by third parties. <br><strong>Goal</strong>: This paper investigates the perception of software development teams members regarding data privacy when using LLMs in their professional activities. Additionally, we examine the challenges faced and the practices adopted by these practitioners. <br><strong>Method</strong>: We conducted a survey with 78 ICT practitioners from five regions of the country. <br><strong>Results</strong>: Software development teams members have basic knowledge about data privacy and LGPD, but most have never received formal training on LLMs and possess only basic knowledge about them. Their main concerns include the leakage of sensitive data and the misuse of personal data. To mitigate risks, they avoid using sensitive data and implement anonymization techniques. The primary challenges practitioners face are ensuring transparency in the use of LLMs and minimizing data collection. Software development teams members consider current legislation inadequate for protecting data privacy in the context of LLM use. <br><strong>Conclusions</strong>: The results reveal a need to improve knowledge and practices related to data privacy in the context of LLM use. According to software development teams members, organizations need to invest in training, develop new tools, and adopt more robust policies to protect user data privacy. They advocate for a multifaceted approach that combines education, technology, and regulation to ensure the safe and responsible use of LLMs.</p>
Supplementary Material for the Paper "Characterizing Software Developers by Perceptions of Productivity"
<p>Contains the survey questions and preprint for the paper "Characterizing Software Developers by Perceptions of Productivity" submitted to ESEM'17. </p> <p>Please contact Thomas Zimmermann (tzimmer@microsoft.com) in case you have any questions.</p> <p> </p> <p><strong>Paper Abstract:</strong></p> <p>Understanding developer productivity is important to deliver software on time and at reasonable cost. Yet, there are numerous definitions of productivity and, as previous research found, productivity means different things to different developers. In this paper, we analyze the variation in productivity perceptions based on an online survey with 413 professional software developers at Microsoft. Through a cluster analysis, we identify and describe six groups of developers with similar perceptions of productivity: social, lone, focused, balanced, leading, and goal-oriented developers. We discuss design implications of these clusters for tools to support developers’ productivity.</p>
Supporting material for "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test"
<p>The data were uploaded to support the manuscript "Pharmacological validation of individual animal locomotion, temperature and behavioural analysis in group-housed rats using a novel automated home cage analysis system: a comparison with the modified Irwin test" for the submission to Journal of Pharmacological and Toxicological Methods.</p>
Supplementary Material v1: Multivariate entropy characterizes the gene expression and protein -protein networks in four types of cancer
<p>Supplementary Material PDF</p> <p>Multivariate entropy characterizes the gene expression and protein -protein networks in four types of cancer</p>
Galaxy Hi-C Training material dm3
<p>Hi-C data for Galaxy training, dm3 cells.</p>
Workshop Material - 3D-e-Chem Structural Cheminformatics Workflows for Computer-Aided Drug Discovery
<p>The workshop at the KNIME user meeting (Berlin 9th of March 2018) is set up to stimulate participants with varying degrees of experience in cheminformatics to learn and apply the different structural cheminformatics tools and workflows developed within the context of the 3D-e-Chem project. You will learn how to construct and apply integrated cheminformatics workflows using the 3D-e-Chem KNIME nodes for the exploitation of G protein-coupled receptor and kinase data (two important pharmaceutical target classes) to obtain useful information for drug discovery.</p> <p>Information on the 3D-e-Chem KNIME nodes and workflows can be found online:</p> <p>3D-e-Chem GitHub website: <a href="http://3d-e-chem.github.io/">http://3d-e-chem.github.io/</a></p>
Supplementary material - Comparative genitalic morphology in ten genera of thread-legged bugs of the tribe Metapterini, and its phylogenetic importance (Hemiptera: Heteroptera: Reduviidae)
<p><strong>Supplementary information of the paper entitled: Comparative genitalic morphology in ten genera of thread-legged bugs of the tribe Metapterini, and its phylogenetic importance (Hemiptera: Heteroptera: Reduviidae), original images and data matrix in nexus format.</strong></p>
Data set for: Proposal for a micromagnetic standard problem for materials with Dzyaloshinskii-Moriya interaction
<p>Scripts and Jupyter notebooks for the data reproduction of the paper: "Proposal for a micromagnetic standard problem for materials with Dzyaloshinskii-Moriya interaction"</p> <p>Files include notebooks and scripts with simulations using the OOMMF, MuMax3 and Fidimag codes. Data analysis is performed using Python tools such as Numpy and Scipy.</p> <p>The latest version of this data set can be found in the Github repository:</p> <p><a href="https://github.com/fangohr/paper-supplement-standard-problem-dmi">https://github.com/fangohr/paper-supplement-standard-problem-dmi</a></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.