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461,131 results for “FIGURES”
3D Archaeological Greek Pottery: MDDS-2017-0299, Attic red-figure trefoil oinochoe, Class N, The Cook Class
<p><strong>This 3D dataset is related to the publication</strong>:</p> <ul> <li>Moitinho de Almeida, V. (2023). "<a href="https://www.researchgate.net/publication/353038967_Contributions_of_3D_digital_methods_and_techniques_to_the_study_of_ancient_pottery">Contributions of 3D digital methods and techniques to the study of ancient pottery</a>". In <em>Myths, Gods, and Heroes. Greek vase collections in Portugal / Mitos, Deuses e Heróis. As coleções de vasos gregos em Portugal</em>. R. Morais, R. Centeno, D. Ferreira (eds.). Câmara Municipal de Santa Maria da Feira - Museu Convento dos Lóios; Reitoria da Universidade do Porto; Faculdade de Letras da Universidade do Porto; Imprensa da Universidade de Coimbra. Pp.269-291. (ISBN: 978-989-8183-25-5)</li> </ul> <p>3D processed dataset for object 2017-0299, from the Museu de Arqueologia D. Diogo de Sousa (MDDS) in Braga, Portugal. <strong>CC BY-NC-SA 4.0 license</strong>.</p> <p>2017-0299 is an Attic red-figure trefoil <em>oinochoe</em>, Class N, The Cook Class, dating from c. 500-475 BCE and unknown provenance (Fundação Buehler Brockhaus / Museu D. Diogo de Sousa, 2020; Morais et al., 2021).</p> <p><strong>Aims</strong>: 3D digital documentation; morphological characterization; technological and functional analysis of archaeological Greek pottery.</p> <p><strong>Data acquisition</strong>: at the Museu de História Natural e da Ciência da Universidade do Porto (MHNC-UP), with a portable non-contact structured white light scanner, Breukmann smartSCAN3D-HE, equipped with stereo colour cameras at 250 mm FOV. Additional metadata included in associated spreadsheet.<br><strong>Data processing</strong>: 29 scans aligned and merged. MDDS-2017-0299_3D01.ply: non-manifold edges, self-intersections, small components, and small tunnels in the mesh automatically fixed, noise data removed; orientation and position normalised. MDDS-2017-0299_3D01-holesFilled.ply: holes filled for calculation of material density, filling volume, and centre of mass. Mesh is not watertight (inner surface not digitised due to occlusion). Additional metadata included in associated spreadsheet.</p> <p>Access to the 2017-0299 was granted by the MDDS.</p> <p>When citing this material: please include the original inventory ID (2017-0299) reference to the physical object.</p>
3D Archaeological Greek Pottery: MHNC-UP-020053, Attic black-figure shoulder lekythos, Group of Vatican G 52
<p><strong>This 3D dataset is related to the publication</strong>:</p> <ul> <li>Moitinho de Almeida, V. (2023). "<a href="https://www.researchgate.net/publication/353038967_Contributions_of_3D_digital_methods_and_techniques_to_the_study_of_ancient_pottery">Contributions of 3D digital methods and techniques to the study of ancient pottery</a>". In <em>Myths, Gods, and Heroes. Greek vase collections in Portugal / Mitos, Deuses e Heróis. As coleções de vasos gregos em Portugal</em>. R. Morais, R. Centeno, D. Ferreira (eds.). Câmara Municipal de Santa Maria da Feira - Museu Convento dos Lóios; Reitoria da Universidade do Porto; Faculdade de Letras da Universidade do Porto; Imprensa da Universidade de Coimbra. Pp.269-291. (ISBN: 978-989-8183-25-5)</li> </ul> <p>3D processed dataset for object MHNC-UP-020053 in the Museu de História Natural e da Ciência da Universidade do Porto (MHNC-UP), Portugal. <strong>CC BY-NC-SA 4.0 license</strong>.</p> <p>MHNC-UP-020053 is an Attic black-figure shoulder <em>lekythos</em>, Group of Vatican G 52, dating from c. 550-500 BCE and unknown provenance (Rocha Pereira & Morais, 2007; Morais, 2019; Morais et al., 2021).</p> <p><strong>Aims</strong>: 3D digital documentation; morphological characterization; technological and functional analysis of archaeological Greek pottery.</p> <p><strong>Data acquisition</strong>: at the MHNC-UP, with a portable non-contact structured white light scanner, Breukmann smartSCAN3D-HE, equipped with stereo colour cameras at 250 mm FOV. Additional metadata is included in the associated spreadsheet.<br><strong>Data processing</strong>: 35 scans aligned and merged. MHNC-UP-020053_3D01.ply: non-manifold edges, self-intersections, small components, and small tunnels in the mesh automatically fixed, noise data removed; orientation and position normalised. MHNC-UP-020053_3D01-holesFilled.ply: holes filled for calculation of material density, filling volume, and centre of mass. Mesh is not watertight (inner surface not digitised due to occlusion). Additional metadata is included in the associated spreadsheet.</p> <p>Access to the MHNC-UP-020053 was granted by the MHNC-UP.</p> <p>When citing this material: please include the original inventory ID (MHNC-UP-020053) reference to the physical object.</p>
Model Output and Figure Scripts for: "Uncertainty in reconstructing paleo-elevation of the Antarctic Ice Sheet from temperature-sensitive ice core records"
<p>New climate model output and figure scripts for the paper "Uncertainty in reconstructing paleo-elevation of the Antarctic Ice Sheet from temperature-sensitive ice core records".</p>
Data and figures for "A half-century of global collaboration in science and the 'Shrinking World'"
<p>This package supplements the paper entitled <i>"A half-century of global collaboration in science and the 'Shrinking World'"</i> published in <i>Quantitative Science Studies</i> (doi: <a href="https://doi.org/10.1162/qss_a_00268">10.1162/qss_a_00268</a>).</p><p>It contains the datasets and figures used in the original paper based on bibliometric data from a broad set of scientific publications (works), including journal articles, preprints and datasets; see the subfolder named "all_works".</p><p>In addition, for reference, it also contains datasets and figures based on bibliometric data from journal articles only; see the subfolder named "journal_only". The bottom-level files in this subfolder are suffixed with '_j' for identification.</p><p> </p><p><strong>Contents and Instructions</strong></p><p>The datasets and figures in this package are based on the data obtained via <a href="https://docs.openalex.org/api/">OpenAlex API</a>. See the original paper for details. The following file and folders are found at the next level of the subfolders named "all_works" or "journal_only".</p><p> </p><p><strong>- nworks_intlrate_master</strong> (.csv file)</p><ul><li>This file contains information on the number of works ('nworks_all') produced in each of the 15 research disciplines ('discipline' and 'disc_ID'; see below) by 18 countries (Australia, Canada, China, France, Germany, India, Indonesia, Iran, Italy, Japan, Netherlands, Poland, Russia, South Korea, Spain, Switzerland, UK and US) ('country' and 'country_code') from 1970 to 2021 ('year'), the number of international collaborative works among them ('nworks_intl'), and the international collaboration rate ('intlrate') calculated from the ratio of the two.</li><li>The 15 disciplines are Artificial Intelligence ('disc_ID' = 1; 'ai'), Quantum Science (2; 'quantum'), Biotechnology (3; 'bio'), Nanotechnology (4; 'nano'), Agricultural Engineering (5; 'agri'), Particle Physics (6; 'particle'), Aerospace Engineering (7; 'aerospace'), Nuclear Engineering (8; 'nuclear'), Marine Engineering (9; 'marine'), Neuroscience (10; 'neuro'), Condensed Matter Physics (11; 'condensed'), Environmental Engineering (12; 'envi'), Earth Science (13; 'earth'), Astronomy (14; 'astro') and Pure Mathematics (15; 'math'). See the original paper for the definitions of these disciplines.</li><li>The figures contained in the folders '[line]_nworks' and '[line]_intlrate' are based on this dataset.</li></ul><p> </p><p><strong> - [line]_nworks</strong> (Folder)</p><ul><li>This folder contains line plots (.pdf/.png) representing the trends in the number of works by discipline and country, corresponding to the left-hand side diagrams of Fig. 1 and Suppl. Fig. S2 in the v1 preprint.</li></ul><p> </p><p><strong>- [line]_intlrate</strong> (Folder)</p><ul><li>This folder contains line plots (.pdf/.png) representing the trends in the international collaboration rate by discipline and country, corresponding to the right-hand side diagrams of Fig. 1 and Suppl. Fig. S2 in the v1 preprint.</li></ul><p> </p><p><strong>- [chord]_bilateral</strong> (Folder)</p><ul><li>This folder contains chord diagrams (.pdf/.png) representing the bilateral collaborative relationships by discipline and period, corresponding to Fig. 2 and Suppl. Fig. S4 in the v1 preprint. The number at the end of the file name indicates the period represented by the diagram; specifically, '1' = 1971–1990, '2' = 1991–2000, '3' = 2001–2010 and '4' = 2011–2020.</li><li>The raw data (.xlsx) to reproduce the contained diagrams are also provided by discipline in the accompanied 'Data' folder. The file named '[list]_nworks_(discipline name).xlsx' shows, for the top 30 countries ('country' and 'country_code') in work production during the period indicated by the sheet name, their work production ('nworks_all'), the number of international collaborative works among them ('nworks_intl'), and the international collaboration rate ('intlrate') calculated from the ratio of the two. The file named '[mat]_bilat_nworks_(discipline name)' shows the number of works produced by each country pair during the period indicated by the sheet name. Country names are abbreviated by two-letter country codes (ISO 3166-1 alpha-2).</li></ul><p> </p><p><strong>- [dend]_hcluster</strong> (Folder)</p><ul><li>This folder contains circularised dendrograms (.pdf/.png) representing the international research collaboration clusters by discipline and period, corresponding to Fig. 3 and Suppl. Fig. S5 in the v1 preprint.</li><li>The raw data (.xlsx) to reproduce the contained diagrams are also provided by discipline in the accompanied 'Data' folder. The file named '[mat]_bilat_dist_(discipline name)' shows the distance between each country pair for the period indicated by the sheet name, calculated based on the formula presented in the original paper. Country names are abbreviated by two-letter country codes (ISO 3166-1 alpha-2).</li></ul>
Section 5.1 "Task Area 1: Image (meta)data formats and standardization)" Figure 8
<p>Figure 8. A FAIR-IO bundle combines the necessary acquisition and provenance metadata together with multi-resolution, chunked binary data in a single cloud-compatible format for simplified sharing and re-use.</p> <p>from NFDI Grant Application, "<strong>National Research Data Infrastructure for Microscopy and Bioimage Analysis</strong>" (NFDI4BIOIMAGE)</p>
Supplementary Figure 1 Gating strategy for Treg phenotype analysis.
<p><strong>Supplementary Figure 1. Gating strategy for Treg phenotype analysis. |</strong> Isolated and purified cells (see Methods) were analysed by flow cytometry with <strong>(A)</strong> gating performed as indicated including the exclusion of dead cells (by Live/Dead staining kit) and analysing only CD4+CD25+ double-positive cells. <strong>(B)</strong> These cells were then stained with indicated marker antibodies. The histogram quantification areas indicated by the black bars were set against control staining performed with non-specific isotype antibodies corresponding to each marker antibody.</p>
Data for figures in the global streamflow change paper
<p>This is the dataset used for generating figures 1-4 in the manuscript of "<strong>Future global streamflow declines likely more severe than previously estimated</strong>"</p>
Datasets for figures in Implementation and evaluation of Wet Bulb Globe Temperature within non-urban environments in the Community Land Model version 5
<p>The files contain 4 scripts and 6 netcdf files. </p> <p>"laborCap_200400.ncl" uses "Lancet_LRF.nc" to create Figure 1.</p> <p>Script "world_plot_ensemble_Avg.I2000.csh", drives a NCL script, "plot_modern.I2000.WBGT.ncl" to make figures 3 and 4, using the netcdf files, "I2000_PR_22_x1_60_5.exceed.WBGT.20yrs.75_99.nc," "I2000_PR_22_x1_60_5.exceed.WBGT_BG_R.20yrs.75_99.nc," "I2000_PR_22_x1_60_5.exceed.WBGT_BC_R.20yrs.75_99.nc," and "I2000_PR_22_x1_60_5.exceed.WBGT_AC_R.20yrs.75_99.nc."</p> <p>"heatmap.wbgt.v4.org.ncl" uses netcdf "I2000_PR_23_Chicago_x1_60_1.11-17.Chicago.allvars.nc" to create figures 5-7. </p>
COALMOD-World 2.0 data, results, figures for: Stranded Assets in the Coal Export Industry? The Case of the Australian Galilee Basin
<p>This dataset contains all COALMOD-World 2.0 data for Hauenstein et al. (2023): New coal mines in the Australian Galilee Basin are not economically viable and are prone to become stranded assets (doi.org/10.1016/j.oneear.2023.07.005).</p> <p>With the input data files and the GAMS scenario file the model (https://github.com/chauenstein/COALMOD-World_v2.0) can be run to reproduce the model results.</p> <p>Furthermore, the output.zip folder contains the results file, the R code to compile the figures, and PDFs of the figures.</p>
Data for Figures in "Unexpected Long-Term Variability in Jupiter's Tropospheric Temperatures
<p>This repository provides the data submitted by the primary author that were used to create Figures 1, 2, 3, 4 and 5 in the text for the article: <strong>"Unexpected Long-Term Variability in Jupiter's Tropospheric Temperatures", by </strong> Glenn S. Orton, Arrate Antuñano, Leigh N. Fletcher, James Sinclair, Thomas Momary, Takuya Fujoyoshi, Padma Yanamandra-Fisher, Padraig T. Donnelly, Jennifer Greco, Anna Payne, Kimberly Boydstun, Laura Wakefield.</p> <p>The repository consists of five files in text (ASCII) format: (1) User Guide to Data (16 kb), (2) figure1_data.txt (1.5 MB), (3) figure2_data.txt (142 kb), figure4_data.txt (61 kb), and figure5_data.txt (59 kb). Data for Figure 3 are provided in the User Guide.</p>
Urbanus and Cosgrove et al. Nature Communications (2023) - CellRanger outputs for scRNAseq experiments in Figures 2,5, and 6
<p>Attached are the outputs of the cell ranger pipeline for 10x 3' scRNAseq of HSPCs. For any questions regarding this dataset please contact Leila Perie (leila.perie@curie.fr)</p>
Urbanus and Cosgrove et al. Nature Communications (2023) - 12 months scRNAseq fastq files (mouse 1) for Figures 5 and 6
<p>This dataset contains .fastq files for the 12 month timepoint (mouse 1) scRNAseq dataset used in Figures 5 and 6. For any questions about this dataset please contact Leila Perie (leile.perie@curie.fr)</p>
Urbanus and Cosgrove et al. Nature Communications (2023) - 12 months scRNAseq fastq files (mouse 2) for Figures 5 and 6
<p>This dataset contains .fastq files for the 12 month timepoint (mouse 2) scRNAseq dataset used in Figures 5 and 6. For any questions about this dataset please contact Leila Perie (leile.perie@curie.fr)</p>
Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces (Figures)
<p>High resolution figures related to the below manuscript:</p> <p>Atul Deshpande, Melanie Loth, et al., <a href="https://doi.org/10.1101/2022.06.02.490672">Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces</a>. <em>bioRxiv</em> 2022. doi:10.1101/2022.06.02.490672</p>
raw data of figures 3, 4 and 5
<p>Raw data plotted in figures 3, 4 and 5 of the article with DOI: https://doi.org/10.1103/PhysRevApplied.18.064048</p>
CYJAX: A package for Calabi-Yau metrics with JAX [data & figures]
<p>Data of achieved accuracies of numerically approximated Calabi-Yau metrics as presented in the associated paper "CYJAX: A package for Calabi-Yau metrics with JAX" [<a href="https://arxiv.org/abs/2211.12520">2211.12520</a>].</p>
Processed data to regenerate figures in Noecker et al, "Systems biology elucidates the distinctive metabolic niche filled by the human gut microbe Eggerthella lenta"
<p>This archive contains the processed source data for the publication by Noecker et al, "Systems biology elucidates the distinctive metabolic niche filled by the human gut microbe <em>Eggerthella lenta</em>" (2023, in review). Data tables underlying each figure panel are included, except for the following panels:</p> <ul> <li>Figure S1A: Source data is in Table S1 of the publication</li> <li>Figure 6D: Source data can be found at NCBI GEO accession GSE212420 (supplementary counts data matrix)</li> </ul> <p>Raw metabolomics data can also be found at Metabolomics Workbench accession PR001620.</p> <p>Methods used to summarize these data and generate the figures are described in the manuscript Materials and Methods and figure captions. Code to generate all figures is also available at www.github.com/turnbaughlab/2022_Noecker_ElentaMetabolism and 10.5281/zenodo.7779454.</p>
Data, scripts, and figures of the article: The effect of oregano essential oils on Feed Passage Syndrome in broilers: 2. Assessment under a challenge model
<p>This data set contains the data, JMP scripts, and figures of the article titled "The effect of oregano essential oil on Feed Passage Syndrome in broilers: 2. Assessment under a challenge model" to be published in the journal Animal - Open Space.</p>
Data, scripts, and figures of the article: The effect of oregano essential oils on Feed Passage Syndrome in broilers: 1. Assessment under field conditions
<p>This data set contains the data, JMP scripts, and figures of the article titled "The effect of oregano essential oils on Feed Passage Syndrome in broilers: 1. Assessment under field conditions" to be published in the journal Animal - Open Space.</p>
Psychophysical thresholds for figure-ground discrimination driven by binary textures
<p>Documentation and matlab data files containing psychophysical data for figure-ground segregation driven by binary textures. Methodological details of measurements and analyses (along with interpretation) are provided in Victor, J.D., and Conte. M.M. (2022) Functional recursion of orientation cues in figure-ground separation. Vision Research 197, 108047, doi.org/10.1016/j.visres.2022.108047.</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.