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Annexes to the external scientific report on the cumulative dietary exposure assessment of pesticides that have acute effects on the nervous system using MCRA software - Input and output data sets
<p>Retrospective dietary exposure assessments were conducted for two groups of pesticides that have acute effects on the nervous system: </p> <ol> <li>brain and/or erythrocyte acetylcholinesterase inhibition (CAG-NAN);</li> <li>functional alterations of the motor division (CAG-NAM).</li> </ol> <p>The pesticides considered in this assessment were identified and characterised in the scientific report on the establishment of cumulative assessment groups of pesticides for their effects on the nervous system (<a href="https://doi.org/10.2903/j.efsa.2019.5800">here</a>).</p> <p>The exposure calculations used monitoring data collected by Member States under their official pesticide monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Regarding the selection of relevant food commodities, the assessment included water, foods for infants and young children and 30 raw primary commodities of plant origin that are widely consumed within Europe.</p> <p>Exposure estimates were obtained with Monte Carlo Risk Assessment (MCRA) software using a 2-dimensional Monte Carlo simulation, which is composed of an inner-loop execution and an outer-loop execution. Variability within the population is modelled through the inner-loop execution and is expressed as a percentile of the exposure distribution. The outer-loop execution is used to derive 95% confidence intervals around those percentiles (reflecting the sampling uncertainty of the input data).</p> <p>Furthermore, calculations were carried out according to a tiered approach. While the first-tier calculations (Tier I) use very conservative assumptions for an efficient screening of the exposure with low risk for underestimation, the second-tier assessment (Tier II) includes assumptions that are more refined but still conservative. For each scenario, exposure estimates were obtained for different percentiles of the exposure distribution and the total margin of exposure (MOET, i.e. the ratio of the toxicological reference dose to the estimated exposure) was calculated at each percentile.</p> <p>The input and output data for the exposure assessment are reported in the following annexes:</p> <ul> <li>Annex A.1 – Input data for the exposure assessment of CAG-NAN</li> <li>Annex A.2 – Input data for the exposure assessment of CAG-NAM</li> <li>Annex B.1 – Output data from the Tier II exposure assessment of CAG-NAN</li> <li>Annex B.2 – Output data from the Tier II exposure assessment of CAG-NAM</li> </ul> <p>Further information on the data, methodologies and interpretation of the results are provided in the external scientific report on the cumulative dietary exposure assessment of pesticides that have acute effects on the nervous system using MCRA software (<a href="https://doi.org/10.2903/sp.efsa.2019.en-1708">here</a>).</p> <p>The results reported in this assessment only refer to the exposure and are not an estimation of the actual risks. These exposure estimates should therefore be considered as documentation for the final scientific report on the cumulative risk assessment of dietary exposure to pesticides for their effects on the nervous system (<a href="https://www.efsa.europa.eu/en/consultations/call/public-consultation-scientific-report-cumulative">here</a>). The latter combines the hazard assessment and exposure assessment into a consolidated risk characterisation, including all related uncertainties.</p>
Annexes to the external scientific report on the cumulative dietary exposure assessment of pesticides that have chronic effects on the thyroid using MCRA software - Input and output data sets
<p>Retrospective dietary exposure assessments were conducted for two groups of pesticides that have chronic effects on the thyroid: </p> <ol> <li>hypertrophy, hyperplasia and neoplasia of C-cells, i.e. affecting the parafollicular cells or the calcitonin system of the thyroid (CAG-TCP);</li> <li>hypothyroidism, i.e. affecting the follicular cells and/or the hormone system of the thyroid (CAG-TCF).</li> </ol> <p>The pesticides considered in this assessment were identified and characterised in the scientific report on the establishment of cumulative assessment groups of pesticides for their effects on the thyroid (<a href="https://doi.org/10.2903/j.efsa.2019.5801">here</a>).</p> <p>The exposure calculations used monitoring data collected by Member States under their official pesticide monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Regarding the selection of relevant food commodities, the assessment included water, foods for infants and young children and 30 raw primary commodities of plant origin that are widely consumed within Europe.</p> <p>Exposure estimates were obtained with Monte Carlo Risk Assessment (MCRA) software using a 2-dimensional probabilistic method, which is composed of an inner-loop execution and an outer-loop execution. Variability within the population is modelled through the inner-loop execution and is expressed as a percentile of the exposure distribution. The outer-loop execution is used to derive 95% confidence intervals around those percentiles (reflecting the sampling uncertainty of the input data).</p> <p>Furthermore, calculations were carried out according to a tiered approach. While the first-tier calculations (Tier I) use very conservative assumptions for an efficient screening of the exposure with low risk for underestimation, the second-tier assessment (Tier II) includes assumptions that are more refined but still conservative. For each scenario, exposure estimates were obtained for different percentiles of the exposure distribution and the total margin of exposure (MOET, i.e. the ratio of the toxicological reference dose to the estimated exposure) was calculated at each percentile.</p> <p>The input and output data for the exposure assessment are reported in the following annexes:</p> <ul> <li>Annex A.1 – Input data for the exposure assessment of CAG-TCP</li> <li>Annex A.2 – Input data for the exposure assessment of CAG-TCF</li> <li>Annex B.1 – Output data from the Tier II exposure assessment of CAG-TCP</li> <li>Annex B.2 – Output data from the Tier II exposure assessment of CAG-TCF</li> </ul> <p>Further information on the data, methodologies and interpretation of the results are provided in the external scientific report on the cumulative dietary exposure assessment of pesticides that have chronic effects on the thyroid using MCRA software (<a href="https://doi.org/10.2903/sp.efsa.2019.en-1707">here</a>).</p> <p>The results reported in this assessment only refer to the exposure and are not an estimation of the actual risks. These exposure estimates should therefore be considered as documentation for the final scientific report on the cumulative risk assessment of dietary exposure to pesticides for their effects on the thyroid (<a href="https://www.efsa.europa.eu/en/consultations/call/public-consultation-scientific-report-cumulative">here</a>). The latter combines the hazard assessment and exposure assessment into a consolidated risk characterisation, including all related uncertainties.</p>
Annexes to the scientific report on the cumulative dietary exposure assessment of pesticides that have chronic effects on the thyroid using SAS® software - Input and output data sets
<p>Retrospective dietary exposure assessments were conducted for two groups of pesticides that have chronic effects on the thyroid: </p> <ol> <li>hypertrophy, hyperplasia and neoplasia of C-cells, i.e. affecting the parafollicular cells or the calcitonin system of the thyroid (CAG-TCP);</li> <li>hypothyroidism, i.e. affecting the follicular cells and/or the hormone system of the thyroid (CAG-TCF).</li> </ol> <p>The pesticides considered in this assessment were identified and characterised in the scientific report on the establishment of cumulative assessment groups of pesticides for their effects on the thyroid (<a href="https://doi.org/10.2903/j.efsa.2019.5801">here</a>).</p> <p>The exposure calculations used monitoring data collected by Member States under their official pesticide monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Regarding the selection of relevant food commodities, the assessment included water, foods for infants and young children and 30 raw primary commodities of plant origin that are widely consumed within Europe.</p> <p>Exposure estimates were obtained with SAS<sup>®</sup> software using a 2-dimensional probabilistic method, which is composed of an inner-loop execution and an outer-loop execution. Variability within the population is modelled through the inner-loop execution and is expressed as a percentile of the exposure distribution. The outer-loop execution is used to derive 95% confidence intervals around those percentiles (reflecting the sampling uncertainty of the input data).</p> <p>Furthermore, calculations were carried out according to a tiered approach. While the first-tier calculations (Tier I) use very conservative assumptions for an efficient screening of the exposure with low risk for underestimation, the second-tier assessment (Tier II) includes assumptions that are more refined but still conservative. For each scenario, exposure estimates were obtained for different percentiles of the exposure distribution and the total margin of exposure (MOET, i.e. the ratio of the toxicological reference dose to the estimated exposure) was calculated at each percentile.</p> <p>The input and output data for the exposure assessment are reported in the following annexes:</p> <ul> <li>Annex A.1 – Input data for the exposure assessment of CAG-TCP</li> <li>Annex A.2 – Input data for the exposure assessment of CAG-TCF</li> <li>Annex B.1 – Output data from the Tier I exposure assessment of CAG-TCP</li> <li>Annex B.2 – Output data from the Tier I exposure assessment of CAG-TCF</li> <li>Annex C.1 – Output data from the Tier II exposure assessment of CAG-TCP</li> <li>Annex C.2 – Output data from the Tier II exposure assessment of CAG-TCF</li> </ul> <p>Further information on the data, methodologies and interpretation of the results are provided in the scientific report on the cumulative dietary exposure assessment of pesticides that have chronic effects on the thyroid using SAS<sup>®</sup> software (<a href="https://doi.org/10.2903/j.efsa.2019.5763">here</a>).</p> <p>The results reported in this assessment only refer to the exposure and are not an estimation of the actual risks. These exposure estimates should therefore be considered as documentation for the final scientific report on the cumulative risk assessment of dietary exposure to pesticides for their effects on the thyroid (<a href="https://www.efsa.europa.eu/en/consultations/call/public-consultation-scientific-report-cumulative">here</a>). The latter combines the hazard assessment and exposure assessment into a consolidated risk characterisation, including all related uncertainties.</p>
Annexes to the scientific report on the cumulative dietary exposure assessment of pesticides that have acute effects on the nervous system using SAS® software - Input and output data sets
<p>Retrospective dietary exposure assessments were conducted for two groups of pesticides that have acute effects on the nervous system: </p> <ol> <li>brain and/or erythrocyte acetylcholinesterase inhibition (CAG-NAN);</li> <li>functional alterations of the motor division (CAG-NAM).</li> </ol> <p>The pesticides considered in this assessment were identified and characterised in the scientific report on the establishment of cumulative assessment groups of pesticides for their effects on the nervous system (<a href="https://doi.org/10.2903/j.efsa.2019.5800">here</a>).</p> <p>The exposure calculations used monitoring data collected by Member States under their official pesticide monitoring programmes in 2014, 2015 and 2016 and individual food consumption data from ten populations of consumers from different countries and from different age groups. Regarding the selection of relevant food commodities, the assessment included water, foods for infants and young children and 30 raw primary commodities of plant origin that are widely consumed within Europe.</p> <p>Exposure estimates were obtained with SAS<sup>®</sup> software using a 2-dimensional Monte Carlo simulation, which is composed of an inner-loop execution and an outer-loop execution. Variability within the population is modelled through the inner-loop execution and is expressed as a percentile of the exposure distribution. The outer-loop execution is used to derive 95% confidence intervals around those percentiles (reflecting the sampling uncertainty of the input data).</p> <p>Furthermore, calculations were carried out according to a tiered approach. While the first-tier calculations (Tier I) use very conservative assumptions for an efficient screening of the exposure with low risk for underestimation, the second-tier assessment (Tier II) includes assumptions that are more refined but still conservative. For each scenario, exposure estimates were obtained for different percentiles of the exposure distribution and the total margin of exposure (MOET, i.e. the ratio of the toxicological reference dose to the estimated exposure) was calculated at each percentile.</p> <p>The input and output data for the exposure assessment are reported in the following annexes:</p> <ul> <li>Annex A.1 – Input data for the exposure assessment of CAG-NAN</li> <li>Annex A.2 – Input data for the exposure assessment of CAG-NAM</li> <li>Annex B.1 – Output data from the Tier I exposure assessment of CAG-NAN</li> <li>Annex B.2 – Output data from the Tier I exposure assessment of CAG-NAM</li> <li>Annex C.1 – Output data from the Tier II exposure assessment of CAG-NAN</li> <li>Annex C.2 – Output data from the Tier II exposure assessment of CAG-NAM</li> </ul> <p>Further information on the data, methodologies and interpretation of the results are provided in the scientific report on the cumulative dietary exposure assessment of pesticides that have acute effects on the nervous system using SAS<sup>®</sup> software (<a href="https://doi.org/10.2903/j.efsa.2019.5764">here</a>).</p> <p>The results reported in this assessment only refer to the exposure and are not an estimation of the actual risks. These exposure estimates should therefore be considered as documentation for the final scientific report on the cumulative risk assessment of dietary exposure to pesticides for their effects on the nervous system (<a href="https://www.efsa.europa.eu/en/consultations/call/public-consultation-scientific-report-cumulative">here</a>). The latter combines the hazard assessment and exposure assessment into a consolidated risk characterisation, including all related uncertainties.</p>
data set related to article Brainstem enlargement in preschool children with autism Results from an intermethod agreement study of segmentation algorithms
<p>This record contains raw data related to article Brainstem enlargement in preschool children with autism Results from an intermethod agreement study of segmentation algorithms</p>
Jammer data sets
<p>This compressed file contains 4 datasets which serve as an input for the jammer detector software: <a href="https://github.com/worldsensinginnovation/cipsec/tree/master/SDR%20Jammer%20detector">https://github.com/worldsensinginnovation/cipsec/tree/master/SDR%20Jammer%20detector</a> </p> <p>Each file corresponds to the capture of radiofrequency spectrum samples of a different jammer in the 2.4GHz band at 5 Msps. Each one starts with no jammer present for a few seconds, then the jammer appears for a few more seconds and at the end it dissapears until the file ends.</p> <p>jammer1: pulsed jammer</p> <p>jammer2: wideband jammer</p> <p>jammer3: continuous wave jammer</p> <p>jammer4: lmf jammer</p> <p>The duration of each dataset varies from file to file.</p>
HY+_HSVA‐08_UNI ST.ANDREWS - Data Storage Report and Data Set
<p>Data from the internal waves project according to data storage report</p>
MALICE: Vial Imaging and Label Extraction example image set
<p>48 images of Collection vials taken using Mirrored Angle Label Image Capture Extraction (MALICE). This data set is intended for development of automated cropping and label extraction solutions</p>
QLKNN10D training set
<p>This dataset contain a large-scale run of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. QuaLiKiz is used in many Fusion integrated modelling suites within Europe, and is openly available at <a href="http://qualikiz.com">qualikiz.com</a>. This dataset was generated with v2.4.0 'Big dataset edition' of QuaLiKiz, see <a href="https://gitlab.com/qualikiz-group/QuaLiKiz/-/tags/v2.4.0">https://gitlab.com/qualikiz-group/QuaLiKiz/-/tags/v2.4.0</a>. Note that GyroBohm fluxes were rescaled to match the normalizations of fluxes with a instead of R0, as is the case for v2.4.1 and later. The dataset was used to train neural network versions of QuaLiKiz, which when integrated in modelling suites allow for near-real time tokamak core transport simulations. Please check our <a href="https://doi.org/10.1088/0029-5515/55/9/092001">proof-of-principle</a> and <a href="http://doi.org/10.1088/0029-5515/55/9/092001">application in RAPTOR</a>, <a href="http://ocs.ciemat.es/EPS2019PAP/pdf/P1.1089.pdf">short paper</a> for <a href="http://ocs.ciemat.es/EPS2019PAP/html/contrib.html">the EPS 2019 conference</a>, and published in the Physics of Plasmas ICDDPS2 Special Issue <a href="https://aip.scitation.org/doi/10.1063/1.5134126">https://aip.scitation.org/doi/10.1063/1.5134126</a>. This paper is also available on arXiv <a href="https://arxiv.org/abs/1911.05617">https://arxiv.org/abs/1911.05617</a> and zenodo <a href="https://doi.org/10.5281/zenodo.3595558">10.5281/zenodo.3595558</a>.</p> <p>Related repositories:</p> <ul> <li>Training, plotting, filtering, and auxiliary tools <a href="https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop">https://gitlab.com/Karel-van-de-Plassche/QLKNN-develop</a></li> <li>QuaLiKiz related tools <a href="https://gitlab.com/qualikiz-group/QuaLiKiz-pythontools">https://gitlab.com/qualikiz-group/QuaLiKiz-pythontools</a></li> <li>FORTRAN QLKNN implementation with wrapper for Python and MATLAB <a href="https://gitlab.com/qualikiz-group/QLKNN-fortran">https://gitlab.com/qualikiz-group/QLKNN-fortran</a></li> <li>Weights and biases of 'hyperrectangle style' QLKNN <a href="https://gitlab.com/qualikiz-group/qlknn-hyper">https://gitlab.com/qualikiz-group/qlknn-hyper</a></li> </ul>
Constraining the Neutron Star Mass-Radius Relation and Dense Matter Equation of State with NICER. I. The Millisecond Pulsar X-Ray Data Set
<p>This deposit includes the cleaned, filtered and phase folded NICER event data set for the millisecond pulsar (MSP) PSR J0030+0451 in the 0.25-3 keV band. The data processing and filtering was performed using HEASoft 6.251 and NICERDAS version 5.0; the specific parameters and filtering criteria used are detailed in the ApJ Letter listed above. This event list was used to produce what is shown for PSR J0030+0451 in Figures 2, 3, and 4 in the accepted ApJ Letter listed above and was also used for the neutron star mass-radius and equation of state inference analyses presented in the companion papers (Miller et al. 2019, Riley et al. 2019, and Raaijmakers et al. 2019).</p> <p>The event file and its MD5 checksum is:<br> J0030+0451_merged_phase_0.25-3keV.fits (463bbac7203bb45bb02ea0deed49f083)<br> </p>
Reads and truth variant set for benchmarking variant calling/genotyping
<p><em>downsampled.fasta</em> is created by converting this file (ftp://<a href="http://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/AshkenazimTrio/HG002_NA24385_son/NIST_HiSeq_HG002_Homogeneity-10953946/HG002Run01-11419412/HG002run1_S1.bam">ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/AshkenazimTrio/HG002_NA24385_son/NIST_HiSeq_HG002_Homogeneity-10953946/HG002Run01-11419412/HG002run1_S1.bam</a>) to fasta and picking every second read (to get half the coverage and half the number of reads).</p> <p><em>The HG002_GRCh37_GIAB_highconf_CG</em>... file is created by picking variants on chromosome from this file (ftp://<a href="http://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/release/AshkenazimTrio/HG002_NA24385_son/NISTv3.3.2/GRCh37/HG002_GRCh37_GIAB_highconf_CG-IllFB-IllGATKHC-Ion-10X-SOLID_CHROM1-22_v.3.3.2_highconf_triophased.vcf.gz">ftp-trace.ncbi.nlm.nih.gov/giab/ftp/release/AshkenazimTrio/HG002_NA24385_son/NISTv3.3.2/GRCh37/HG002_GRCh37_GIAB_highconf_CG-IllFB-IllGATKHC-Ion-10X-SOLID_CHROM1-22_v.3.3.2_highconf_triophased.vcf.gz</a>).</p> <p> </p> <p><strong>These two files can be used in benchmarking variant calling/genotyping.</strong></p>
Data sets for " The nature of mean-field generation in three classes of optimal dynamos"
<pre>The tar archive Optimal_Dynamos.tar contains and index.html file with links to the run directories for each figure and the two tables of the paper "The nature of mean-field generation in three classes of optimal dynamos" by Axel Brandenburg (Nordita) and Long Chen (Durham University) with the temporary URL http://norlx51.nordita.org/~brandenb/tmp/long_chen. Corrections and updates are available on the active URL to this tar archive: https://www.nordita.org/~brandenb/projects/Optimal_Dynamos/</pre>
Generic sample set HC1
<p>A typical view of the samples ready to do SEM on them, along tweezers to compare size.</p>
Data sets for "MELISSA: System description and spectral features of pre‐ and post‐midnight F‐region echoes. Journal of Geophysical Research: Space Physics" by Rodrigues et al.
<p>Observations used in the study "Rodrigues, F. S., Zhan, W., Milla, M. A., Fejer, B. G., de Paula, E. R., Neto, A. C., et al ( 2019). MELISSA: System description and spectral features of pre‐ and post‐midnight <em>F</em>‐region echoes. <em>Journal of Geophysical Research: Space Physics</em>, 124. <a href="https://doi.org/10.1029/2019JA027445">https://doi.org/10.1029/2019JA027445</a>."</p> <p>The uploaded files include the RTI maps measured by the MELISSA radar system between 2014 and 2018 (.tif files). They also include values of SNR versus local time and height and the spectra presented in the manuscript (.mat files).</p> <p>Please, see README.txt for additional details.</p>
Fig. 8. Entactiniid radiolarians from the Kowala Quarry, set H−4 in Siliceous biota (radiolarians and sponges) and the Late Devonian biotic crisis: The Polish reference
Fig. 8. Entactiniid radiolarians from the Kowala Quarry, set H−4, early Famennian (Pa. crepida Zone), sample KM−1, all × 75. A–E. Haplentactinia aff. flagelifera. F. Polyentactinia cf. rudihispida. All SEM micrographs.
Fig. 7. Entactiniid radiolarians from the Kowala Quarry, set H−3 in Siliceous biota (radiolarians and sponges) and the Late Devonian biotic crisis: The Polish reference
Fig. 7. Entactiniid radiolarians from the Kowala Quarry, set H−3, earliest Famennian (Middle Pa. triangularis Zone), sample Kw−154, all × 75. A–C, E. Haplentactinia cf. rhinophyusa. D. Spongentactinella sp. F, G. Haplentactinia cf. inaudita. All SEM micrographs.
Fig. 4. Entactiniid radiolarians from the Kowala Quarry, set H−3 in Siliceous biota (radiolarians and sponges) and the Late Devonian biotic crisis: The Polish reference
Fig. 4. Entactiniid radiolarians from the Kowala Quarry, set H−3, earliest Famennian (Middle Pa. triangularis Zone), sample Kw−154, all × 150 except J × 240. A–C. Astroentactinia stellaepolus. D. Stigmospherostylus diversita. E, G. Astroentactinia stellata. F. Astroentactinia cf. crassata. H. Stigmospherostylus cf. micula. I, J. Helioentactinia cf. perjucunda.
Text-fig. 1. Geological setting and location of the fossil sites mentioned in this paper. Grey area indicates Cretaceous Basins. in Revision Of Protopteris And Oncopteris Tree Fern Stem Casts From The Late Cretaceous Of Central Europe
Text-fig. 1. Geological setting and location of the fossil sites mentioned in this paper. Grey area indicates Cretaceous Basins.
Fig. 5. Parsimony splits network constructed from a per and ITS2 concatenated sequence data set. Heterozygous specimens are indicated with A and B in Ecological and geographical speciation in Lucilia bufonivora: The evolution of amphibian obligate parasitism
Fig. 5. Parsimony splits network constructed from a per and ITS2 concatenated sequence data set. Heterozygous specimens are indicated with A and B. 'bufonivora_EUROPE_A' represents a consistent haplotype present in all 12 samples from Europe (Table 1), of which just two were heterozygous ('bufonivora_frog' and 'bufonivora_NLWi'). 'bufonivora_CAN' and 'elongata_CAN' are represented by two samples each, none of which were heterozygous. Scale bar represents expected changes per site.
Text-fig. 19. Geological position of the flora of Roudníky in the cores Ru 43 and Ru 60 and radiometric dating (from Bellon et al. 1998, adapted). 1 – xenolites intercalated with claystone, 2 – claystone, 3 – pyroclastite, 4 – tuffaceous claystone, 5 – olivine basalt, 6 – Quaternary cover. in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 19. Geological position of the flora of Roudníky in the cores Ru 43 and Ru 60 and radiometric dating (from Bellon et al. 1998, adapted). 1 – xenolites intercalated with claystone, 2 – claystone, 3 – pyroclastite, 4 – tuffaceous claystone, 5 – olivine basalt, 6 – Quaternary cover.
ScienceDex guides
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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.