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1,773 results for “Supplementary data,”
Supplementary data for "Revised and extended analysis of Ar VI"
<p>Supplementary data for "Revised and extended analysis of Ar VI," Table 4. The table contains the four least-squares adjustment calculations mentioned in the article. The input and output files of these calculations are available here.<br> The file names contain the set to which it belongs, the program to which it refers, whether it is an input or output file, and the name of the file as generally used in Cowan's package of programs.</p>
Supplementary Data S1-2
<p>Supplementary Data S1: Observed and predicted PSSMs for 711 proteins with their features. This set of proteins was treated as the test data set. </p> <p>Supplementary Data S2: Observed and predicted DMS scores for 59 DMS targets for EvoRator2 ("evorator_pred" column) and all baselines given in <a href="https://github.com/OATML-Markslab/ProteinGym">ProteinGym</a> substitution benchmark.</p> <p> </p> <p> </p>
Supplementary data to the article "The first larva of the cucujiform superfamily Cleroidea from the Mesozoic and its ecological implications (Coleoptera)"
<p>The supplementery data to the article "The first larva of the cucujiform superfamily Cleroidea from the Mesozoic and its ecological implications (Coleoptera)" contain the 8 bit TIFF image stack obtained at the Imaging Beamline P05 (IBL) operated by the Helmholtz-Zentrum Hereon at the storage ring PETRA III (Deutsches Elektronen Synchrotron-DESY, Hamburg, Germany) using synchrotron radiation based micro-computed tomography (SRμCT). The scan of the holotype specimen of <em>Cretorhadalus constantini</em> Kolibáč & Prokop, 2023 was used for the segmentation and volume renders. </p>
Supplementary data to: Grassland greening and water resource availability may coexist in a warming climate
<p>This data archive includes the boundary of the North China and Tibetan Plateau (NCTP), three sub-regions, and respective province, the CLCD landcover in 2020, annual PM ET in 1982, and trends in projected water yield and leaf area index by the end of the 21<sup>st</sup> century (up to 2100). The boundary of the NCTP, three sub-regions, and respective province is in the shapefile (.shp) format, and other processed data are in the geotiff (.tif) or in the mat format. For calculation details please see the publication.</p>
The underlying radial acceleration relation -- supplementary data
<p>Supplementary data and plots associated with "The underlying radial acceleration relation", Desmond (2023). See the README for further information.</p>
Supplementary code and data for the paper `From stage to page: language independent bootstrap measures of distinctiveness in fictional speech`
<p>The repository provides full data and processing / analysis pipeline for the paper <strong>'From stage to page: language independent bootstrap measures of distinctiveness in fictional speech</strong>'<br> <br> Rendered notebooks are also available through Github:</p> <p>1) <a href="https://github.com/perechen/difs-character-voices/blob/master/data/all_stars_clean.ipynb">Preparation, energy distance and exploration</a> (main)</p> <p>2) <a href="https://github.com/perechen/difs-character-voices/blob/master/03_analysis.md">Keyword curves & formal modeling</a></p> <p> </p> <p>- `00_dracor_get_data.R`. Script uses <a href="https://dracor.org/">DraCor</a> dedicated API to get texts spoken by characters</p> <p>- `01_distinctiveness_energy.ipynb` does the heavy lifting of data wrangling, cleaning and preprocessing, plus implements energy distance bootstrapping and does exploratory analysis</p> <p>- `02_logodds_curves.R` calculates keyword curves for characters<br> <br> - `03_analysis_and_models.R` explores keyword curves and does Bayesian models</p>
supplementary data for Bemelmans et al., 2023, High-resolution InSAR reveals localised pre-eruptive deformation inside the crater of Agung volcano, Indonesia.
<p>This repository contains the supplementary materials for the paper "High-resolution InSAR reveals localised pre-eruptive deformation inside the crater of Agung volcano, Indonesia." to be published in JGR: Solid Earth.</p> <p>The dataset contains files assiciated with the StaMPS time series processing. Each dataset has its own folder containing:</p> <ol> <li>*_data.csv : data file containing latitude, longitude, incidence angle, heading and LOS displacement for each acquistion (date is listed in the column name in the format yyyymmdd).</li> <li>parms.mat : parameter file used for StaMPS processing of that dataset</li> </ol> <p>The dataset also contains input and results from the GBIS modelling (/GBIS_results/). the *.inp files are the input files for each model inversion where the letter ('M','T','P','Y', or 'D') refer to the Mogi (point), McTigue (sphere), penny-shaped crack, Yang (ellipsoid), and dyke (also sill) model used for that run. folders with the same name as the *.inp file contain the inversion results (invert_*.mat), a summary table (summary_*.txt) and several figures showing the distribution and convergence of the model inversion.</p> <p>The input for the GBIS inversions is stored in /GBIS_results/INSAR_input/</p> <p>the file <a href="https://zenodo.org/api/files/f30be116-1e2f-4d52-8fcf-a54e11ab691f/matlab_functions.zip?versionId=490de786-f245-45b5-92bb-d2ae0d50be56">matlab_functions.zip </a>contains matlab functions used for data processing, visualisation, storage and conversion.</p> <p>the file <a href="https://zenodo.org/api/files/f30be116-1e2f-4d52-8fcf-a54e11ab691f/GBISv1_1_MJWB.zip?versionId=cec83c81-a0b7-4e4a-8aa8-ac81e32b8772">GBISv1_1_MJWB.zip </a>contains GBIS code adapted by the author to perform statistical analysis of the model inversion, perform region-of-interest based subsampling and store modeled results as shapefiles for further processing.</p> <p> </p>
Optimizing Sparse Matrix-Matrix Multiplication for the GPU supplementary data
<p>This contains the matrices for the SpGEMM tests presented in "Optimizing Sparse Matrix-Matrix Multiplication for the GPU", by Steven Dalton, Nathan Bell, and Luke N. Olson.</p> <p>Each A matrix from Table 3 has an companion matrix P in the directory. The storage scheme appends "_P" to the end of the A matrix filename.<br> </p>
Supplementary data for the manuscript titled 'Energy metabolism and aerobic respiratory chain of Vitreoscilla sp. C1: Comparison with beta-proteobacteria'
<p>This dataset contains the supplementary data files for the manuscript titled, 'Energy metabolism and aerobic respiratory chain of Vitreoscilla sp. C1: Comparison with beta-proteobacteria.' </p>
Supplementary data for Saintilan et al. 2023
<p>Supplementary Data 1: Surface Elevation Table data for Tidal Marshes, including elevation rate, elevation deficit, elevation capital, losses and gains of water area within 5 kilometres, losses and gains of tidal marsh within 5 kilometres.</p> <p>Supplementary Data 2: Area change in coral islands. </p>
Supplementary data for "Critically Evaluated Atomic Data for Au IV Spectrum"
<p>Transition data for computing opacity of Au IV in the kilonova ejecta have been provided. These files are a part of the article, "Critically Evaluated Atomic Data for Au IV Spectrum" submitted to ApJS journal. The files named as "Au4_Levels_Opacity.txt" and "Au4_Lin_Opacity.txt" describe the energy levels of Au IV spectrum and its radiative line parameters for E1-type of transitions, respectively.</p>
Supplementary Data for "Prediction of solar wind speed by applying convolutional neural network to potential field source surface (PFSS) magnetograms"
<p>These are supplementary data for the paper "Prediction of solar wind speed by applying convolutional neural network to potential field source surface (PFSS) magnetograms". They are:</p> <p>- Python code to construct a neural network model</p> <p>- Saved optimal models (for 8-fold validation)</p> <p>- Selected y-label data (solar wind speed) and corresponding dates, which we eliminate the data identified as ICME</p>
Supplementary Data for: "The principles of SARS-CoV-2 inter-variant competition are exemplified in the pre-Omicron era of the Colombian epidemic"
<p>Supplementary data files, including BEAST XMLs and logs from the study "The principles of SARS-CoV-2 inter-variant competition are exemplified in the pre-Omicron era of the Colombian epidemic".</p>
Cantwell basin supplementary data
<p>Detrital zircon sample data and locations from the Cantwell basin, Denali National Park and Preserve, Alaska</p>
Supplementary Data: Simple, but not simplified: A new approach for optimising beyond-Standard Model physics searches at the Large Hadron Collider
<p><strong>Supplementary Data</strong></p> <p><em>Simple, but not simplified: A new approach for optimising beyond-Standard Model physics searches at the Large Hadron Collider</em></p> <p>This record contains the full dataset generated for the study "<em>Simple, but not simplified: A new approach for optimising beyond-Standard Model physics searches at the Large Hadron Collider</em>". It contains the following files:</p> <ul> <li>data_cross_sections_full_exact.csv - a CSV file with the soft breaking parameters M1, M2, mu and tanb, the neutralino/chargino masses, the cross sections for neutralino-neutralino, chargino-neutralino and chargino-chargino production at the LHC operating at a CM energy of 13 TeV, and the branching ratios of the unstable charginos/neutralinos. </li> <li>benchmark_points.zip - this zip file contains the SLHA files for the four benchmark points as shown in the paper, together with the prospino output for the cross section. </li> </ul> <p> </p>
AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments - Supplementary Data
<p><strong>Introduction</strong></p> <p>In this zip, we release the auxiliary data that is beneficial to execute the implementation of AVLEN described in our paper AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments by Sudipta Paul, Amit K Roy-Chowdhury, and Anoop Cherian, NeurIPS, 2022.</p> <p><strong>At a Glance</strong></p> <ul> <li>The size of the unzipped data is 4.6G</li> <li>The unzipped folder contains: (i) a README.md file and (ii) ./AVLEN-data folder. The latter contains the following zip files. Please see the AVLEN code to see how to unzip these files into their respective folders. <ul> <li>ckpt.119.pth -- 61M </li> <li>connectivity.zip -- 1.4M </li> <li>pretrained_weights.zip -- 1.7G</li> <li>ResNet-152-imagenet.zip -- 2.9G</li> <li>semantic_audionav_dialog_approx.zip -- 2.7M</li> <li>soundspaces.zip -- 479K</li> <li>speaker_model_weights.zip -- 51M</li> </ul> </li> </ul> <p><strong>Other Resources</strong></p> <p>For the implementation of AVLEN that uses the data shared here, please visit <a href="https://www.merl.com/publications/TR2022-131">MERL TR2022-131</a>.</p> <p><strong>Citation</strong></p> <p>If you use AVLEN in your research, please cite our paper:</p> <pre><code>@InProceedings{paul2022avlen, title={AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments}, booktitle={Advances in Neural Information Processing Systems}, author={Paul, Sudipta and Roy-Chowdhury, Amit and Cherian, Anoop}, volume={35}, pages={6236--6249}, year={2022} }</code></pre> <p><strong>Copyright and License</strong></p> <p>The AVLEN dataset is released under CC-BY-SA-4.0 license.</p> <p>All data:</p> <pre><code>Created by Mitsubishi Electric Research Laboratories (MERL), 2023 SPDX-License-Identifier: CC-BY-SA-4.0</code></pre> <p> </p>
Supplementary data for "Fault-tolerant quantum algorithm for symmetry-adapted perturbation theory"
<p>Supplementary data belonging to "Fault-tolerant quantum algorithm for symmetry-adapted perturbation theory".</p> <p>The data includes geometries for the molecules in the paper as well as the Hamiltonian matrix elements, orbital coefficients and overlap matrices to reproduce the data in the paper.</p>
Trans-eQTL effects on risk of type 1 diabetes: a test of the sparse effector (omnigenic) hypothesis of complex trait genetics (supplementary data)
<p>This repository contains summary-level data generated by performing <a href="https://github.com/molepi-precmed/trans-qtls">Genomewide aggregated trans- effects (GATE) analysis</a> in case-control study of Type 1 Diabetes (T1D).</p>
Data and supplementary information: Effects of lithium on locomotor activity and circadian rhythm of honey bees
<p>Data and supplementary files for publication:</p><p>Erdem, B., Arslan, O.C., Sevin, S. Gozen, A. G., Agosto-Rivera, J. L., Tugrul, G., & Alemdar, H. (2023). Effects of lithium on locomotor activity and circadian rhythm of honey bees. <i>Scientific Reports</i>, <i>13,</i> 19861. https://doi.org/10.1038/s41598-023-46777-7</p><p> </p><p>AcuteExp_Dark_ActivityData.xlsx - Total LMA counts of acute experiment in dark condition.</p><p>AcuteExp_Light_ActivityData.xlsx - Total LMA counts of acute experiment in light condition.</p><p>ChronicExp_ActivityData.xlsx - Total LMA counts of the chronic experiment.</p><p>ChronicExp_MortalityData.xlsx - Mortality data of the chronic experiment.</p><p>ChronicExp_PeriodRhytmData.xlsx - Defines rhythmic and arrhythmic individuals and the circadian periods (h) of the rhythmic individuals in chronic experiment.</p><p>LD_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the 12 h light / 12 h dark condition.</p><p>DD_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the constant dark condition.</p><p>LL_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the constant light condition.<br>In the double-plotted actograms, NR indicates "non-rhythmic" individuals.</p>
Macroalgal deep genomics illuminate multiple paths to aquatic, photosynthetic multicellularity - Supplementary Data - ANNOTATIONS - Data S2
<p>Macroalgae are a polyphyletic group of multicellular aquatic organisms vital to global climate maintenance and have a wide variety of commercial applications. The lack of genomic datasets and poor physiological records preclude understanding their ecological roles and industrial potential. We <em>de novo</em> sequenced 121 macroalgal genomes from various climates spanning five major latitude parallels. The resultant genomic datasets illuminate the evolutionary mechanisms behind macroalgal diversification and specialization and reveal genetic bases for niche habitation facilitated by morphological complexity. Adhesome genes (e.g., cadherins, integrins, and lectins), extracellular matrix enzymes, and cytoskeletal organization regulating genes (e.g., spondins, Rho-type GTPases) predominantly distinguished macroalgal genomes from their microalgae correlates. Artificial neural networks could accurately classify an alga as micro- or macro- from set of significance-ranked genomic features (n = 251, entropy R<sup>2</sup> > 0.99) as well as adhesome gene sets (n = 110, entropy R<sup>2</sup> > 0.92). By deciphering the macroalgal adhesome, a clear picture of the genetic basis for the development and maintenance of complex algal tissues could be resolved in the three macroalgal phyla. Sequences from giant viruses were rampant in the macroalgal genomes and coded for zinc-finger transcription factors, ankyrins, Rieske proteins, and other exotic codomains. Lineage-specific retentions of transcription factors, cadherins, integrins, polysaccharide-acting enzymes, and receptor kinases, many with predicted viral origins, outline the divergent mechanisms facilitating multicellularity in these three macroalgal lineages. This work sheds new light on the evolution of multicellularity in three phyla (Rhodophyceae, Chlorophyceae, and Ochrophyceae v. Phaeophyceae) through the lens of large-scale genomics and paves the way for the genomic exploration of macroalgal biology.</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.