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10,119 results for “IT Support”
Raw data supporting Identifying invertebrates from pitfall, flight interception traps and hand collecting
<p>Raw data supporting identifying invertebrates from pitfall, flight interception traps and hand collecting: comparing metabarcoding with traditional methods.</p> <p>Two step PCRs were performed on each sample replicate using modified primers mICOIintF and jgHCO2198 followed by the Nextera XT index kit v2 Set A (Illumina).</p> <p>The pool was loaded onto an illumina MiSeq using a MiSeq Reagent Kit v2 500 cycle kit (Illumina), with 10% Phi-X to generate 250-bp paired-end reads.</p>
Combining statistical and mechanistic models to unravel the drivers of mortality within a rear-edge beech population - Supporting Material
<p>Supporting material for the study:</p> <p><strong>"Combining statistical and mechanistic models to unravel the drivers of mortality within a rear-edge beech population."</strong></p> <p><strong>Authors:</strong></p> <p>Cathleen Petit-Cailleux1, Hendrik Davi1, François Lefèvre1, Joseph Garrigue<strong>2</strong>, Jean-André Magdalou<strong>2</strong>, Christophe Hurson<strong>2,3</strong><strong>, </strong>Elodie Magnanou<strong>2,4</strong>, and Sylvie Oddou-Muratorio1.</p> <p> </p> <p>Adresses</p> <p>1INRA, UR 629 Ecologie des Forêts Méditerranéennes, URFM, Avignon, France</p> <p><strong>2</strong>Réserve Naturelle Nationale de la Forêt de la Massane, France</p> <p><strong>3</strong>Fédération des Réserves Naturelles Catalanes, Prades, France</p> <p><strong>4</strong>Sorbonne Université, CNRS, Biologie Intégrative des Organismes Marins, BIOM, F-66650 Banyuls-sur-Mer, France</p> <p><strong>ORCID:</strong></p> <p>Cathleen Petit-Cailleux: <a href="https://orcid.org/0000-0001-7714-6583">https://orcid.org/0000-0001-7714-6583</a></p> <p>François Lefèvre : <a href="https://orcid.org/0000-0003-2242-7251">https://orcid.org/0000-0003-2242-7251</a></p> <p>Sylvie Oddou-Muratorio <a href="https://orcid.org/0000-0003-2374-8313">https://orcid.org/0000-0003-2374-8313</a></p> <p> </p> <p>-------------</p> <p>Raw data of the Table_Massane_moratlity_trees.csv and climate can be obtained from Joseph Garrigue, Jean-André Magdalou and Christophe Hurson.</p> <p>The inventories files and daily climate are the input dataset to run CASTANEA models.</p> <p>All details are provided in the article.</p>
CLDF dataset derived from Lee and Hasegawa's "Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages" from 2011
<p>Cite the source of the dataset as:</p> <blockquote> <p>Lee, Sean and Hasegawa, Toshikazu (2011). Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages. Proceedings of the Royal Society B: Biological Sciences, 278(1725), 3662–3669. doi:10.1098/rspb.2011.0518.</p> </blockquote>
Data supporting publication: Revealing Mode Formation in Quasi-Bound States in the Continuum Metasurfaces via Near-Field Optical Microscopy
<p>This repository includes the data corresponding to the figures shown in the journal article entitledRevealing Mode Formation in Quasi-Bound States in the Continuum Metasurfaces via Near-Field Optical Microscopy, published in Advanced Materials on 02.08.2024</p>
Supporting Data for "Identifying the Origins of Nanoplastics in the Abyssal South Atlantic Using Backtracking Lagrangian Simulations with Fragmentation"
<p>Supporting Data for "Identifying the Origins of Nanoplastics in the Abyssal South Atlantic Using Backtracking Lagrangian Simulations with Fragmentation", published in the Ocean and Coastal Research Journal. The repository consists of the code used for the simulations and analysis, and the supplementary information document associated with the main manuscript, the Lagrangian simulation outputs and aditional data used for the analysis.</p>
Data supporting publication: Nanoscale Mechanical Manipulation of Ultrathin SiN Membranes Enabling Infrared Near-Field Microscopy of Liquid-Immersed samples
<p>This repository includes the data corresponding to the figures shown in the journal article entitled Nanoscale Mechanical Manipulation of Ultrathin SiN Membranes Enabling Infrared Near-Field Microscopy of Liquid-Immersed samples, published in small. </p>
Application of optical tweezer technology reveals that PfEBA and PfRH ligands, not PfMSP1, play a central role in Plasmodium-falciparum merozoite-erythrocyte attachment, Supporting Information
<p>This repository contains the dataset and analysis scripts associated with the upcoming publication titled <em>Application of optical tweezer technology reveals that PfEBA and PfRH ligands, not PfMSP1, play a central role in Plasmodium-falciparum merozoite-erythrocyte attachment</em>. The repository includes a comprehensive collection of data and scripts related to optical tweezer experiments, growth assays, qPCR data, and supplementary information. It is organized into several sections, each detailing different aspects of the study:</p> <ul> <li><strong>Growth Assays:</strong> Includes raw and processed data on parasitemia levels, invasion rates, and growth rate assays, along with corresponding Jupyter notebooks and Python scripts for data visualization (e.g., <code>GrowthAssayPlotlib.py</code>, <code>Plot GA1.ipynb</code>, and <code>GA2_df_melted.json</code>).</li> <li><strong>qPCR Data:</strong> Contains results from multiple qPCR runs, including quantification data for various samples, as well as analysis scripts and plotted results (<code>qpcr_plotbench.ipynb</code>, <code>qPCR_plotting.py</code>, etc.). Data files such as <code>.xlsx</code> and <code>.json</code> contain gene expression data and fold changes to NF54.</li> <li><strong>Optical Tweezer Experiments:</strong> Includes detailed results and plots from optical tweezer measurements of attachment forces, time dependence, and multiple merozoite attachments. Notebooks (<code>tweezer_plots.ipynb</code>, <code>Antibody_binding_assay_plots.ipynb</code>) and data files support these analyses.</li> <li><strong>Optical Tweezer Images</strong>: Includes images that were used to measure RBC diameters for deformation and force measurements in <code>.tiff</code> format.</li> <li><strong>Supplementary Information (SI):</strong> Provides additional data and visualizations, such as scatter plots of two stretched RBCs, time post-egress vs. detachment force, and antibody GIA flow data. The accompanying figures (e.g., <code>SupFig1d_egress time vs force_3D7.svg</code>, <code>SupFig5a_GIA.svg</code>) are provided as <code>.svg</code> files.</li> </ul> <p>This repository offers all necessary resources to replicate the findings, including the complete codebase, raw data, and graphical representations of results. Researchers are encouraged to explore the included notebooks and datasets for detailed insights.</p>
Supporting information of a study for the definition and evaluation of a graphical user interface for housing co-design
<p>This dataset is from a study that intends to define, prototype and test a graphical user interface for a housing co-design system. To define the requirements of the interface, we conducted interviews with professionals of architecture, urbanism and social sciences areas, as well as with housing cooperatives and inhabitants of these institutions. An interface solution was prototyped, tested and refined. Then we conducted a heuristic evaluation and a summative evaluation. Such evaluations involved the testing of a high-fidelity prototype, to receive feedback from UX/UI experts, potential users (inhabitants) and architects.</p> <p>S1_File refers to the interview protocol used with the three groups of interviewees. We share the English and Portuguese versions of the interviews with professionals and the original (Portuguese) and translated versions of the remaining ones since these were conducted in Portuguese.</p> <p>S2_File is a dataset reporting the results of the interviews. Each question includes the answers given and the identification (anonymized) of the interviewees who responded to that question.</p> <p>S3_File describes the usability issues identified by the experts during the heuristic evaluation of the high-fidelity prototype. The first page organizes the issues by severity (left) and priority (right). The remaining pages have a table for each issue, including rows for problem designation, heuristic violated, problem description, solution proposal, severity degree, and an image of the interface pointing to the referred issue.</p> <p>S4_File refers to the results of the heuristic evaluation. It includes the identification of each issue, which expert (anonymized) identified such issue, and the heuristic it violates, with the sum of the times each heuristic was violated at the end of each column. At the right, a table presents the consolidation of issues, organized by priority, with columns identifying the issue, severity level, frequency, and priority.</p> <p>S5_File is the script given to potential users to experiment with the interface during the summative evaluation. This script guides the user through the tasks to perform since the prototype does not have all the features functioning.</p> <p>S6_File refers to the questionnaires applied during the summative evaluation with inhabitants. It includes a preliminary questionnaire, a Single Ease Question (SEQ) questionnaire, a System Usability Scale (SUS) questionnaire, and a Graphical User Interface (GUI) questionnaire.</p> <p>S7_File refers to the results of the summative evaluation with inhabitants (potential users).</p> <ul> <li>Page A refers to the preliminary questionnaire with demographic information such as age, gender, education, relationship with digital technologies, etc. Each field corresponds with each inhabitant (anonymised) and the sum and percentage. In the middle, a table presents a summary of the consolidation. In the right possible relations are presented. </li> <li>Page B presents the results of the SEQ questionnaire, identifying the ratings each inhabitant (anonymized) gave each task. A summary of such values is at the right. </li> <li>On page C, the result of each rating for the SUS questionnaire given by each inhabitant (anonymized) is shown. At the bottom is the calculation of the SUS score.</li> <li>Page D presents the GUI questionnaire results for each inhabitant (anonymized), with the average and SD identified for each question. A summary of such results is on the right.</li> <li>Page E holds the notes taken by the researchers based on their observations regarding task performance. The information is organized in tables for each step of each task and includes the completeness, attempts, and time taken for each inhabitant (anonymized) to complete such task. Also, the sum, percentage, average, and SD are registered. Next to each task is a table identifying how many participants accomplished the task at the first attempt.</li> <li>Page F refers to the strong and weak aspects identified by the inhabitants. Strong and weak aspects are identified, as well as which inhabitant (anonymized) has identified them. The sum and percentage are also given. At the right, there is a table with the consolidation of results by combining similar answers. </li> </ul> <p>S8_File refers to the results of the discussion with architects after experiencing the interface. Such results relate to the positive and negative aspects that the architects identified in the interface and its usefulness for architecture. The left table identifies the strong and weak aspects that architects (anonymized) identified and the sum and percentage associated with them. The table on the right consolidates such results, with similar responses combined.</p>
Data supporting 'Ice loss in the European Alps until 2050 using a fully assimilated, deep-learning-aided 3D ice-flow model'
<p>The dataset supporting our publication '<strong>Ice loss in the European Alps until 2050 using a fully assimilated, deep-learning-aided 3D ice-flow model</strong>' in <em>Geophysical Research Letters.</em></p> <p>The main .zip archive contains a set of NetCDF files detailing:</p> <ul> <li>Initial optimised glacier states (geology-optimized...)</li> <li>Simulation results (Prog20...)</li> </ul> <p>Initial states and results are given by cluster (see Figure 1 in the paper), as shown in all filenames (C1 through to C12). Prognostic simulation filenames additionally distinguish between runs between 1999 and 2019 (Prog2020) and between 2020 and 2050 (Prog2050). 'NV'/'NoVel' and 'NT'/'NoThk' refer to simulations using the partial optimisation (optimisation without including velocity/thickness observations) as detailed in the paper. 'AV' at the end of the filename denotes the integrated area/volume results file, as opposed to the 2D raster results file. A 'V' before the cluster designation shows that the simulation used the variable SMB as opposed to the fixed SMB (see the paper for details). 'ID' before the cluster designation shows that the simulation was using extrapolated SMB based on the trend in SMB since 2000, instead of assuming the continuation of the current SMB. 'ID' on its own denotes linear extrapolation and 'IDQ' denotes quadratic extrapolation (not used in the published paper). 'SMBF' in the filename shows that the simulation used the SMB-elevation feedback.</p> <p>The additional .zip archive contains the code of IGM v1.0 used to produce the model results. For details on installing and using IGM, please see the Github page at <a href="https://github.com/jouvetg/igm.The">https://github.com/jouvetg/igm</a>.</p> <p>A further .zip archive (in version 3 - Sims2010-2022.zip) contains the simulations based on linear extrapolation of the observed trend in SMB between 2010 and 2022, following the same nomenclature as in the principal archive (see above).</p> <p>Version 4 contains an additional mosaicked DEM of the results for the whole Alps with the ice removed to give the complete basal topography (kindly processed by T. Léger at UNIL) using the Japan Aerospace Exploration Agency (2021) ALOS World 3D 30 meter DEM. V3.2, Jan 2021. Distributed by OpenTopography. <a title="https://doi.org/10.5069/G94M92HB" href="https://doi.org/10.5069/G94M92HB" target="_blank" rel="noreferrer noopener">https://doi.org/10.5069/G94M92HB</a>. Accessed: 2024-09-09.</p>
Dataset supporting the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)"
<p>Dataset corresponding to theoretical calculations in the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)" DOI: https://doi.org/10.1103/PhysRevResearch.5.033027</p> <p>Please cite as:</p> <p>Tzu-Chao Hung, Roberto Robles, Brian Kiraly, Julian H. Strik, Bram A. Rutten, Alexander A. Khajetoorians, Nicolas Lorente and Daniel Wegner. Dataset supporting the paper "Bipolar single-molecule electroluminescence and electrofluorochromism. Physical Review Research 5, 033027 (2023)" DOI:10.5281/zenodo.13768737</p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <p>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (https://jp-minerals.org/vesta/en/).</p> <p>.agr: grace files (https://plasma-gate.weizmann.ac.il/Grace/).</p> <p>Image files in png format.</p>
Dataset supporting the paper "Single-Spin Sensing: A Molecule-on-Tip Approach. ACS Nano 18, 13829 (2024)"
<p>Dataset corresponding to theoretical calculations in the paper "Single-Spin Sensing: A Molecule-on-Tip Approach" ACS Nano 18, 13829 (2024) DOI: https://doi.org/10.1021/acsnano.4c02470</p> <p>Please cite as:</p> <p>Alex Fétida, Olivier Bengone, Michelangelo Romeo, Fabrice Scheurer, Roberto Robles, Nicolás Lorente, and Laurent Limot. Dataset supporting the paper "Single-Spin Sensing: A Molecule-on-Tip Approach. ACS Nano 18, 13829 (2024)" DOI: 10.5281/zenodo.13774118</p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <p>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (https://jp-minerals.org/vesta/en/).</p> <p>.agr: grace files (https://plasma-gate.weizmann.ac.il/Grace/).</p> <p>Image files in png format.</p>
Powering the Circular Future: Climate Change and Economic Perspectives on Second-Life Batteries in the Belgian Context - Supporting Information S2 and S3
<p>The data contains the databases used to calculate the climate change impacts of second-life batteries including full Life Cycle Inventory data published in the article entitled "Powering the Circular Future: Climate Change and Economic Perspectives on Second-Life Batteries in the Belgian Context".</p> <p>The second file S3 contains the economic data and the climate change impacts of the same article.</p> <p>In version 2.0 of S2, a sensitivity analysis and more detail is added in the results.</p> <p> </p>
Data supporting "Burn Period: A use-inspired metric to track wildfire risk across the southwest U.S."
<p>Comma delimited data file of derived daily meteorological metrics from hourly, gap filled and quality controlled Remote Automated Weather Station (RAWS) data for Arizona and New Mexico (southwest U.S.) provided by the Climate, Ecosystems, and Fire Applications (CEFA) program at the Desert Research Institute (Brown, 2022, unpublished data). Data file contains daily average dewpoint temperature, air temperature, maximum Hot-Dry-Windy Index, maximum Fosberg Fire Weather Index, maximum vapor pressure deficit, and total number of hours/day with relative humidity below 20% for 124 RAWS from 2000-2022.</p>
The Brief Symptom Inventory in the Swiss general population: Presentation of norm scores and predictors of psychological distress: Data supporting the publication
This is the dataset on which the following publication is based: • Michel G, Baenziger J, Brodbeck J, Mader L, Kuehni CE, Roser K (2024). The Brief Symptom Inventory in the Swiss general population: Presentation of norm scores and predictors of psychological distress. PLOS One. 19(7), e0305192. Doi: 10.1371/journal.pone.0305192, https://doi.org/10.1371/journal.pone.0305192 A description of the sample and the data collection procedure is available in the publication. The dataset contains the following variables: • Socio-demographic characteristics of the sample - Weights according to representative general population sample - Sex from Swiss Federal Statistical Office (SFSO) - Age at study (rounded to integer) - Age categories (10-year age groups) - Language questionnaire (German/Rumantsch, French, Italian) - Nationality from SFSO - Migration background - Education - Employment status • Original and prepared data on the Brief Symptom Inventory A detailed data dictionary is available in a separate excel file. Version • 1.0 (15 August 2024)
Supporting Data: Phylogeny of Arbacia Gray, 1835 (Echinoidea) reveals diversification patterns in the Atlantic and Pacific Oceans.
<p>This dataset contains:</p> <ol> <li>Appendix S1, metadata asociated with the specimens (collection localities, specimen numbers)</li> <li>The aligned sequence files for each marker: COI_fasta, 16S_fasta, CR_fasta</li> <li>The concatenated sequence file COI + 16S + CRA + 28S Arbacia_supermatrix_fasta and the partition file partitions_concat</li> <li>The Bayesian trees for COI, 16S, CRA, and the supermatrix: BI_tree_16S, BI_tree_COI, BI_tree_CR, BI_tree_Arbacia_supermatrix</li> <li>The ML tree of the supermatrix: ML_tree_Arbacia_supermatrix</li> <li>Appendix S2, which includes various information on the primers used, PCR cycles, etc.</li> <li>Appendix S3, which includes the index calculations for each marker.</li> </ol>
The Application of a Snowpack Runoff Decision Support System for Rain-on-Snow Events Dataset
<p>This work was funded by the State of Nevada - Department of Transportation award No. P296-22-803 and UCAR COMET Outreach Program SUBAWD004566. </p>
Miocene construction of the High Andes recorded by exhumation of the Frontal Cordillera, La Ramada Massif of western Argentina (32°S) (Supporting Information)
<p>Supporting datasets for Howlett et al., "Miocene construction of the High Andes recorded by exhumation of the Frontal Cordillera, La Ramada Massif of western Argentina (32°S)" in <em>TECTONICS.</em></p>
Supporting data for "Raising awareness of potential biases in medical machine learning: Experience from a Datathon"
<p>This archive contains files from a Datathon held virtually in February<br>2024 to introduce clinicians and data scientists to the challenge of<br>reviewing a clinical dataset for potential biases.</p>
Stacks of microCT Scans, Cell size, weight, volume and thallus size data supporting the paper 'Mechanical regulation of tissue flatness in Marchantia'
<div> <div> <div> <p>These data are the supporting elements to the following paper: 'Mechanical regulation of tissue flatness in Marchantia'</p> </div> </div> </div> <p> .tif files contain MicroCT (MCT) scans of 16-day-old <em>Marchantia polymorpha</em> thalli. Three genotypes were analysed here: <strong><em>fer-2</em></strong> mutant (from Mecchia et al., 2022), <strong>FER-OE #9</strong> (proMpEF1::MpFERONIA-mCitrine trangenic line 9)<strong> </strong>from Mecchia et al., 2022), and Tak-1 (WT line). These plants were grown in 3 different media: Gamborgh B5 + vitamins and 0.6, 1.2 and 2.5% agar, and one stress condition consisting of the adjunction of a thin PDMS film at 4, to mimich external mechanical stimulus (only performed on thalli grown on 1.2% agar).</p> <p>MicroCT scans were performed at the faculity of odontology of Université Paris-Cité (Plateform imagerie du vivant) with the technical support of Lotfi Slimani and Baptiste Casel. https://piv.u-paris.fr/micro-ct-haute-resolution/ </p> <p>All files already have embeded scales.</p> <p>Each file name consists of a unique ID number in the following form:</p> <p>P+<LETTER>+<NUMBER>-<CONDITION></p> <p>-LETTER: One letter = one imaging session</p> <p>-NUMBER: Individual and Genotype: 33-40 -> Tak1; 200-207-><em>fer-2</em>; 41-49 -> FER-OE</p> <p>-CONDITION : AGAR0.6/AGAR2.5/PDMS. Absence of condition indicates growth on standard medium (1.2% agar). PDMS indicated growth on standard medium and supplementation of a topping PDMS film at day 4)</p> <p> </p> <p>-Volume data were calculated from MicroCT scans</p> <p>-thallus projected surfaces were calculated from MicroCT scans</p> <p><a href="https://zenodo.org/api/records/13981438/draft/files/Lambda%20curvature%20calculation.ipynb/content" target="_blank" rel="noopener noreferrer">-Lambda curvature calculation.ipynb</a> is suited for MorphographX mesh exported .txt files.</p> <p> </p> <p> </p> <p> </p>
Overview: Simulation Module + Optimisation Algorithm + LCA Support Tool
<p>Overview of the Model2Bio elements: Simulation Module + Optimisation Algorithm + LCA Support Tool</p> <p>Platforms showing all the processes of the Model2Bio project. From the beginning of the Simulation Module, the variables for the production line models (agriculture and food production industries) to bio-products created from the residues.</p>
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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.