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6,623 results for “general”
Agriculture - General 2
<p>CABI (Centre for Agriculture and Biosciences International). CABI Bioscience Genetic Resource Collection. Occurrence dataset <a href="https://doi.org/10.15468/yr757j">https://doi.org/10.15468/yr757j</a> accessed via GBIF.org</p>
Agriculture - General 3
<p>CABI (Centre for Agriculture and Biosciences International). CABI Bioscience Fungus Collection. Occurrence dataset <a href="https://doi.org/10.15468/c9vdlf">https://doi.org/10.15468/c9vdlf</a> accessed via GBIF.org</p>
Agriculture - General: Animal Production and Health 8
<p>1992, invertebrate fauna inventory on peat swamps in The Netherlands using pyramidtraps Siepel H, Dimmers W (2016). Alterra (NL) - Entomofauna inventory in peat swamps. Version 1.1. Alterra, Wageningen UR. Occurrence dataset <a href="https://doi.org/10.15468/ibom6z">https://doi.org/10.15468/ibom6z</a> accessed via GBIF.org</p>
Agriculture - General: Animal Production and Health, Natural Resources and Environment 5
<p>2001 till 2002 and 2004, inventory of entomofauna in forestwalls banks, diches, road verges in The Netherlands using pitfalls and sweeping net</p> <p>Jagers op Akkerhuis G, Dimmers W (2016). Alterra (NL) - Comparison of entomofauna in four different habitats. Version 1.1. Alterra, Wageningen UR. Occurrence dataset <a href="https://doi.org/10.15468/mkoqqh">https://doi.org/10.15468/mkoqqh</a> accessed via GBIF.org</p>
Agriculture - General: Animal Production and Health, Natural Resources and Environment 6
<p>2007, 2011 and 2012, microarthropod fauna inventory in a nature restauration experiment (re-introduction) on a calcareous grassland and three reverence sites in the province of Limburg using pF-cores</p> <p>Smits N, Dimmers W (2016). Alterra (NL) - Microarthropods inventory in calcareous grasslands. Version 1.1. Alterra, Wageningen UR. Occurrence dataset <a href="https://doi.org/10.15468/28jocn">https://doi.org/10.15468/28jocn</a> accessed via GBIF.org</p>
Agriculture - General: Animal Production and Health, Natural Resources and Environment 4
<p>1993 till 2001, entomofauna inventory in cattle grazed versus non-grazed dune grassland using pitfalls</p> <p>van Wingerden W, Dimmers W (2016). Alterra (NL) - Entomofauna inventory in cattle grazed dune grassland. Version 2.1. Alterra, Wageningen UR. Occurrence dataset <a href="https://doi.org/10.15468/zp5oif">https://doi.org/10.15468/zp5oif</a> accessed via GBIF.org</p>
Agriculture - General: Animal Production and Health, Natural Resources and Environment 8
<p>2000-2003, microarthropod fauna inventory of arable land and grassland on sandy soil using pF-cores. Points of interest are biodiversity, nutrients and disease suppression</p> <p>Faber J, Dimmers W (2016). Alterra (NL) - Microarthropods inventory in grassland and arable land. Version 1.1. Alterra, Wageningen UR. Occurrence dataset <a href="https://doi.org/10.15468/fwvi7m">https://doi.org/10.15468/fwvi7m</a> accessed via GBIF.org</p>
Agriculture - General: biological diversity 2
<p>The records in this dataset are general records of different taxonomic groups submitted to the National Biodiversity Data Centre. This provides a temporary facility to store and make available data submitted to the Centre, until such time as subsets of the data can be added to a recognised national database. National Biodiversity Data Centre (2016). General Biodiversity Records from Ireland. Occurrence dataset <a href="https://doi.org/10.15468/w8q1jm">https://doi.org/10.15468/w8q1jm</a> accessed via GBIF.org</p>
Agriculture - General: biological diversity 5
<p>Dataset of Invasive species - initial compilation of aquatic invasive species National Biodiversity Data Centre (2016). National Invasive Species Database. Occurrence dataset <a href="https://doi.org/10.15468/pkjqbk">https://doi.org/10.15468/pkjqbk</a> accessed via GBIF.org</p>
बोधगया, बिहार. General view of the excavations on the north side of the main temple.
<p>बोधगया, बिहार. General view of the excavations on the north side of the main temple. British Museum 1897,0528,0.125 a. © ब्रिटिश म्यूजियम</p>
Rakhterā (रखतेरा or Rakhetrā, Ashoknagar). General view of the niche with foot prints near a large rock-cut image of Ādinātha.
<p><a href="https://siddham.network/object/vs1555/">OBIG1555</a> Rakhterā (रखतेरा or Rakhetrā, Ashoknagar). General view of the niche with foot prints near a large rock-cut image of Ādinātha.</p>
The Biodata of Legislative Candidates for Indonesian General Election 2019
<p>The dataset of biodata of Legislative Candidates for General Election 2019 is crawled from the Indonesian General Election Committee. We remove privacy information, such as the birth of data and home address. We only store the year of birth and the city of home. The dataset is in CSV file.</p>
Deo Barunark (देवबरनार्क Bhojpur district, Bihar). Ruined temple, general view.
<p>Deo Barunark (देवबरनार्क Bhojpur district, Bihar). Ruined temple, general view. Photograph by Henry Baily Wade Garrick in 1881-82.</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)
Data for: "Comprehensive sampling of coverage effects in catalysis by leveraging generalization in neural network models"
<p>This repository contains the raw data to reproduce the paper: "Comprehensive sampling of coverage effects in catalysis by leveraging generalization in neural network models". Within the .tar.gz file, you will find the directory structure described above.</p> <h2>Directory Structure</h2> <h3>`data`</h3> <p>Contains the data to reproduce all figures in the manuscript. Used primarily by the Jupyter Notebooks that plot the data from the paper.</p> <h3>`eval`</h3> <p>Contains the predicted energies according to a MACE model for the following systems and facets:<br>- covsplit (100, 111, 211, 331, 410, 711): The NN model is trained on low-coverage structures and tested on high-coverage structures for a single facet<br>- evencov (100, 111, 211, 331, 410, 711): The NN is trained on even coverages and tested on odd coverages for a single facet<br>- facet (100, 111, 211, 331, 410, 711): the NN is trained on the facet indicated by the folder name (e.g., facet-100 means that the model was trained on Cu(100)) and tested on all of the other facets.<br>- full: the model was trained on all facets and all coverages<br>- slopes (various versions and configurations): the models were trained with different body-order correlation (v) for the Cu(711) facet and tested only on the Cu(711) facet<br>- Rh111: Energies for the Rh(111) + CHOH + CO systems.</p> <h3>`mcmc`</h3> <p>Contains the data for MCMC (Markov Chain Monte Carlo) evaluations for two systems: Cu and Rh<br>- copper-mcmc-public.tar.gz<br>- rhodium-mcmc-public.tar.gz</p> <h3>`models`</h3> <p>Contains the weights and parameters of the best-performing MACE models trained in this work, as selected by the validation loss:</p> <p>File formats: `.model` and `_swa.model` relate to the first-stage of training and the second-stage of training.</p> <h3>`pyscripts`</h3> <p>Python scripts to perform the MCMC sampling given the custom configuration file `sample_cfg.json`.</p> <h3>`scripts`</h3> <p>Shell scripts for evaluation and training the MACE models, along with the hyperparameters used in doing so.</p> <p>- Evaluation scripts (eval-*.sh)<br>- Training scripts (train-*.sh)</p> <h3>`train`</h3> <p>Training, validation, and testing data for all Cu and Rh facets in this work, according to the naming scheme described above.</p> <p>- Rh111<br>- covsplit<br>- evencov<br>- facet<br>- full<br>- slopes</p>
RDF version of the data from Choi, JS. et al. Towards a generalized toxicity prediction model for oxide nanomaterials using integrated data from different sources (2018)
<p>This is an RDFied version of the dataset published in Choi, JS., Ha, M.K., Trinh, T.X. et al. Towards a generalized toxicity prediction model for oxide nanomaterials using integrated data from different sources. Sci Rep 8, 6110 (2018)</p> <p>The original dataset publication DOI: <a href="https://doi.org/10.1038/s41598-018-24483-z">https://doi.org/10.1038/s41598-018-24483-z</a></p> <p>The Original publication authors: Jang-Sik Choi, My Kieu Ha, Tung Xuan Trinh, Tae Hyun Yoon & Hyung-Gi Byun</p>
EERAdata D4.1 - General Building Stock Data for European Buildings
<p>This dataset fulfils the requirements for deliverable 4.1 of the EERAdata project and contains general data which models the building stock in three European cities - Andalusia, Copenhagen and Velenje. This dataset comprises local building data as well as research and scientific data. The dataset is still being built and will continue to be updated as more data is collected. A report describing this dataset in more detail has also been attached. </p>
Original .tif files for "Land snails can trap trematode cercariae in their shell: encapsulation as a general response against parasites?"
<p>In our article "Land snails can trap trematode cercariae in their shell: encapsulation as a general response against parasites?", we use photographic evidence to demonstrate the ability of snails to trap trematodes in their shells. Here we archive the tif files that make up our Figure 1 for this paper, for browsing at higher resolutions than on the published article.</p> <p>Below a (slightly edited) copy of the figure legend:</p> <p>"Backlit views of metazoan parasites trapped in the shell of Cornu aspersum: trematode cercariae (Fig1A.tif, Fig1B.tif, Fig1C.tif), and nematode (Fig1D.tif). Small cracks of the inner shell layer (Fig1B.tif) can be seen above the cercariae and were considered as indicative of damage on the shell after it covered cercariae. Note the accumulation of dark adhering cells around or above the parasites in both cases of cercariae (Fig1C.tif) and nematode (Fig1D.tif)."</p>
General Acyclicity and Cyclicity Notions for the Disjunctive Skolem Chase - Evaluation Material
<p>In this archive, we provide the (already normalized and translated) rule sets that we used for the evaluation<br> of MFA, DMFA, DMFA2, MFC, and DMFC in our paper "General Acyclicity and Cyclicity Notions for the Disjunctive Skolem Chase" at AAAI 2023.We also provide the raw result files and some basic scripts that we used<br> to produce and count the results.<br> Due to licensing restrictions we are not allowed to include all of our evaluation material.<br> <br> Please refer to the provided README.md for more information.</p>
GAP general purpose interatomic potential for iron
<p>A general purpose Gaussian Approximation Potential (GAP) [1,2] for iron. The training database has been computed at the PBE level of theory [3] using the VASP code [4-7]. Fitting of the potentials was done using QUIP/GAP [1,2,8].</p> <p>The potential uses 2-body (distance_2b), 3-body (angle_3b) and SOAP (soap_turbo) [9,10] descriptors, as implemented in the TurboGAP code [11].</p> <p>All files necessary to use the potential QUIP/GAP (compiled with the TurboGAP libraries) are in <em>QUIP_files.tar.gz</em>, all files to use with TurboGAP in <em>TurboGAP_files.tar.gz</em>. The database used to train the potential is in <em>training_database.tar.gz</em>.</p> <p>More details can be found in this publication:</p> <blockquote> <p>Searching for iron nanoparticles with a general-purpose Gaussian approximation potential</p> <p>Richard Jana, Miguel A. Caro</p> <p>https://doi.org/10.1103/PhysRevB.107.245421</p> </blockquote> <p>The authors are grateful to the Academy of Finland for financial support under projects #321713 (R. J. & M.A. C.) and #330488 (M.A. C.), and CSC -- IT Center for Science as well as Aalto University's Science-IT Project for computational resources.</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.