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Parameters for the modelization of operator, worker, and bystander exposure to pesticides in market gardening areas in Burkina Faso using three international exposure assessment models.
<p>Parameters used for the modelization of operator, worker, and bystander exposure to pesticides in market gardening areas in Burkina Faso using the following exposure assessment models:</p> <p>EFSA 2014: EFSA, 2014. Guidance on the assessment of exposure of operators, workers, residents and bystanders in risk assessment for plant protection products. EFSA J. 12, 3874. doi:10.2903/j.efsa.2014.3874</p> <p>HAIR2010: Kruijne, R., Deneer, J.W., Lahr, J., Vlaming, J., 2011. HAIR2010 Documentation: calculating risk indicators related to agricultural use of pesticides within the EU 205.</p> <p>WHO 2011: WHO, 2011. Generic risk assessment model for indoor and outdoor space spraying - WHO Pesticide Evaluation Scheme 1–72.</p> <p><br> This work was realized in the framework of the research component "Pesticides" (1.2.4) of the 3E program funded by the Swiss Agency for Development and Cooperation (SDC).</p> <p><br> Details on algorithm adaptations, scenario definitions and model outputs are available in the PhD thesis of Dr. Edouard Lehmann available from 2018 at https://infoscience.epfl.ch/</p>
Three-Point Correlation Multipoles with AP
<p>This repository contains the backbones for the computation of 3PCF theoretical predictions.</p> <p>See attached code</p> <p> </p>
FIGURE 3. A in Distinguishing between three modern Ellobius species (Rodentia, Mammalia) and identification of fossil Ellobius from Kaldar Cave (Iran) using geometric morphometric analyses of the first lower molar
FIGURE 3. A) Kaldar Cave location. B) Entrance from the south of Kaldar Cave.
FIGURE 1 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 1. Phylogenetic tree of Aulacophilinus
FIGURE 62 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 62. Collecting localities of Aulacophilus weiri.
FIGURE 48 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 48. Collecting locality of Aulacophilinus solitarius.
FIGURE 51 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 51. Collecting localities of Aulacophilus tegularis.
FIGURE 46 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 46. Collecting locality of Aulacophilinus rennellensis.
FIGURE 47 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 47. Aulacophilus solitarius: female clypeus and mandibles.
FIGURE 37 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 37. Collecting localities of Aulacophilinus pyrrhicus.
FIGURE 23 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 23. Collecting locality of Aulacophilinus carinatus.
FIGURE 29 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 29. Collecting localities of Aulacophilinus mandibulatus.
FIGURE 9 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 9. Collecting localities of Aulacophilinus amblygnathus.
FIGURE 17 in A Revision of the Wasp Genus Aulacophilinus Lomholdt, 1980 with Descriptions of Three New Species (Hymenoptera: Crabronidae)
FIGURE 17. Collecting localities of Aulacophilinus caliginosus.
Selected word frequencies for 20 short stories by three authors: Arthur Conan Doyle, Ernest Hemingway, Jack London
<p>Selected word frequencies for 20 short stories by three authors: Arthur Conan Doyle, Ernest Hemingway, Jack London. </p>
Genome sequence resources from three isolates of the apple canker pathogen Neonectria ditissima infecting forest trees
<p><em>Neonectria ditissima</em> is a generalist ascomycete plant pathogen causing canker diseases on a variety of hardwood tree species and can cross-infect many of them. The fungus enters the plants through wounds throughout the year. <em>N. ditissima</em> is considered a major threat to apple production responsible for the fruit tree canker disease which damages trees and causes rotting of fruits in storage. Nearby forests and shelter belts can serve as source of inoculum for well-managed apple orchards. Thus, knowledge about the <em>N. ditissima</em> isolates infecting different host species is essential for designing integrated pest management strategies. Here, we describe the genomes of three <em>N. ditissima</em> isolates, Nd_iso34, Nd_iso35, and Nd_iso36, infecting European beech, American tulip tree, and American beech, respectively. We obtained genome assemblies of ca. 45 megabases for all isolates, covering 94% of the <em>N. ditissima</em> reference annotation, and 97% of the universal single-copy orthologs (BUSCOs). We conclude that these genome assemblies are a highly relevant resource considering the scarcity of genomic data available for <em>N. ditissima</em>.</p>
Dataset of Room Impulse Responses from Baffled Microphone Arrays and Sound Sources at Three Elevations
<p>This data set contains a collection of impulse responses (stored in SOFA format) from <em>spherical microphone arrays</em> (<strong>SMA</strong>s), <em>equatorial microphone arrays</em> (<strong>EMA</strong>s), and <em>non-spherical microphone arrays</em> (<strong>XMA</strong>s). Thereby, impulse response sets are provided for each array type at various spatial resolutions, for a loudspeaker sound source at three source elevations, and in four diverse acoustic environments (see <strong>DATA</strong> section for a full description).</p> <p>The original purpose of the microphone array data is the binaural rendering in the <em>spherical harmonics</em> (<strong>SH</strong>) domain into ear signals for high-fidelity reproduction of the acoustic scenario via headphones. Therefore, <em>binaural room impulse responses</em> (<strong>BRIR</strong>s) for 360 horizontal head orientations of a <em>G.R.A.S KEMAR</em> acoustic dummy head are provided as a reference for each scenario.</p> <p>Please contact the authors for questions or additional information regarding the room setups and utilized measurement devices.</p> <p> </p> <p><strong>======<br> DATA<br>======</strong></p> <p>This archive contains the processed impulse response sets of various measurement configurations, as described in this section.</p> <p>Directory "resources/ARIR_processed/":</p> <ul> <li>Post-processed SMA and EMA impulse responses <ul> <li><strong>"_SMA*_"</strong> or <strong>"_EMA*_"</strong> in the file name</li> <li>In SOFA format with <em>"SingleRoomSRIR"</em> convention</li> <li>From 1x <em>DPA 4060</em> microphone flush mounted in a wooden spherical scattering body with an 8.5 cm radius</li> <li>High-resolution data (measured sequentially on VariSphear turntable with two degrees-of-freedom rotations): <ul> <li>Hall: <strong>1202</strong> <strong>channels</strong> (Lebedev grid) for maximum SH order 29</li> <li>Others: <strong>2702</strong> <strong>channels</strong> (Lebedev grid) for maximum SH order 44</li> </ul> </li> <li>Lower-resolution data via subsampling in the SH domain (arbitrary sampling grids and lower target orders can be achieved): <ul> <li>SH order 29: <strong>1742 channels</strong> (t-design grid) for SMA; <strong>59</strong> <strong>channels</strong> (equiangular grid) for EMA</li> <li>SH order 12: <strong>314</strong> <strong>channels</strong> (t-design grid) for SMA; <strong>25</strong> <strong>channels</strong> (equiangular grid) for EMA</li> <li>SH order 8: <strong>146</strong> <strong>channels</strong> (t-design grid) for SMA; <strong>17</strong> <strong>channels</strong> (equiangular grid) for EMA</li> <li>SH order 4: <strong>42</strong> <strong>channels</strong> (t-design grid) for SMA; <strong>9</strong> <strong>channels</strong> (equiangular grid) for EMA</li> <li>SH order 2: <strong>14</strong> <strong>channels</strong> (t-design grid) for SMA; <strong>5</strong> <strong>channels</strong> (equiangular grid) for EMA</li> <li>SH order 1: <strong>6</strong> <strong>channels</strong> (t-design grid) for SMA; <strong>3</strong> <strong>channels</strong> (equiangular grid) for EMA</li> </ul> </li> </ul> </li> <li>Post-processed XMA impulse responses <ul> <li><strong>"_XMA*_"</strong> in the file name</li> <li>In SOFA format with <em>"SingleRoomSRIR"</em> convention</li> <li>From 18x <em>Rode Lavalier GO</em> microphone mounted in an elastic band on a wooden head-shaped scattering body (7.5 cm to 10.5 cm radius)</li> <li>High-resolution data (measured simultaneously): <ul> <li><strong>18 channels</strong> for maximum SH order 8</li> </ul> </li> <li>Lower-resolution data via integer subsets of microphones: <ul> <li>SH order 4: <strong>9 channels</strong></li> <li>SH order 2: <strong>6 channels</strong></li> </ul> </li> <li>Anechoic: For 360 horizontal scattering body orientations (measured sequentially on a VariSphear turntable with azimuth in 1-degree steps)</li> <li>Rooms: For 36 horizontal scattering body orientations (measured sequentially on VariSphear turntable with azimuth in 10-degree steps)</li> </ul> </li> <li>Generated XMA calibration filters and equalization filters <ul> <li><strong>"_x_nm_"</strong> and <strong>"_e_nm_"</strong> in the file name</li> <li>In proprietary Matlab format</li> <li>Time-domain representation of filters in the respective orders of "real" spherical harmonics</li> </ul> </li> <li>Post-processed binaural impulse responses <ul> <li><strong>"_KEMAR_"</strong> in the file name</li> <li>In SOFA format with <em>"SingleRoomSRIR"</em> convention</li> <li>From <em>G.R.A.S KEMAR</em> dummy head with large pinna</li> <li>For 360 horizontal head orientations (measured sequentially on VariSphear turntable with azimuth in 1-degree steps)</li> </ul> </li> <li>Thereby, impulse response sets are included for five acoustic environments <ul> <li><strong>"Simulation_"</strong>: Anechoic simulation of a plane wave impinging from the frontal direction on the array (SMA and EMA only)</li> <li><strong>"Anechoic_"</strong>: Anechoic measurement of a <em>Genelec 8030A</em> loudspeaker at the same height of the array</li> <li>"<strong>LabDry_"</strong>: Room measurement in an acoustically damped laboratory of a <em>Genelec 8030A</em> loudspeaker at three different source heights (the direct floor reflection is attenuated with an additional porous absorber but otherwise identical to the following condition)</li> <li><strong>"LabWet_"</strong>: Room measurement in an acoustically damped laboratory of a <em>Genelec 8030A</em> loudspeaker at three different source heights (the direct reflection is not obstructed from the hard concrete floor, but otherwise identical to the former condition)</li> <li><strong>"Hall_"</strong>: Room measurement in a very reverberant hall of a <em>Genelec 8030A</em> loudspeaker at three different source heights</li> </ul> </li> <li>Thereby, the room impulse response sets are included for three relative source elevations (from placing the loudspeaker to varying heights on the same vertical axis) <ul> <li><strong>"_SrcHigh"</strong>: The source is located above the horizon of the receiver</li> <li>"<strong>_SrcEar"</strong>: The source and receiver are located at the same height</li> <li><strong>"_SrcLow"</strong>: The source is located below the horizon of the receiver</li> </ul> </li> <li>Additionally, anechoic impulse responses of the measurement loudspeaker and the utilized microphones are included <ul> <li><strong>"Anechoic_MicSMAnoTape_"</strong>: SMA measurement microphone without the applied tape (the source was compensated)</li> <li><strong>"Anechoic_MicSMAwithTape_"</strong>: SMA measurement microphone with the applied tape (the source was compensated)</li> <li><strong>"Anechoic_MicXMAmic19_"</strong>: XMA measurement microphone (the source was compensated)</li> <li><strong>"Anechoic_SrcFreeField_"</strong>: Measurement source (on-axis) (the influence of the utilized high-quality free-field measurement microphone can be neglected)</li> <li><strong>"Anechoic_SrcFreeField+MicSMAnoTape_"</strong>: Measurement source and SMA measurement microphone without the tape applied</li> <li><strong>"Anechoic_SrcFreeField+MicSMAwithTape_"</strong>: Measurement source and SMA measurement microphone with the tape applied</li> <li><strong>"Anechoic_SrcFreeField+MicXMAmic19_"</strong>: Measurement source and XMA measurement microphone</li> <li>Overall, the resulting impulse response sets contain the following compensations (including exact compensation of the phase/time behavior): <ul> <li>Anechoic KEMAR: Source</li> <li>Anechoic SMA/EMA/XMA: Source and array microphones</li> <li>Rooms KEMAR: None</li> <li>Rooms SMA/EMA/XMA: Array microphones</li> <li>There is the option to compensate for the source's on-axis response in the room measurement data. However, the direction-dependent directivity of the loudspeaker cannot be compensated. Therefore, we decided not to compensate for the source in the room measurement data since the on-axis frequency response of the utilized loudspeaker is reasonably flat.</li> </ul> </li> </ul> </li> </ul> <p> </p> <p><strong>===========<br> DATA_RAW<br>===========</strong></p> <p><strong>This archive is too large to be uploaded to Zotero (around 77.5 GB). Please get in touch with the authors to request the data.</strong></p> <p>The archive contains the raw acoustic data of all measurement configurations captured by the measurement scripts (see section <strong>CODE_AND_PLOTS</strong>). The data yields the final impulse responses (see section <strong>DATA</strong>), as described in this section.</p> <p>Directory "resources/ARIR_raw/":</p> <ul> <li>Subdirectories by room and source position containing the raw SMA, XMA, and KEMAR acoustic measurement data</li> <li>In proprietary Matlab format, separate for every measurement position of each configuration</li> <li>Each data file contains extensive metadata, e.g., describing the utilized hardware devices, input/output ports, and descriptions.</li> <li>Each data file contains the raw utilized exponential sweep signal and the resulting captured microphone signals. Each impulse response may be recomputed with alternative deconvolution and post-processing parameters.</li> </ul> <p>Directory "resources/ARIR_raw/Logs_temp_humidity/":</p> <ul> <li>Air temperature and humidity data were captured in 5-second intervals during all acoustic measurements</li> <li>In CSV format (automatically loaded and included in the final impulse response sets as part of the measurement post-processing; see section <strong>CODE_AND_PLOTS</strong>)</li> <li>This data is not further utilized at the moment but seemed worthwhile to capture since some acoustic measurements (particularly the high-resolution SMA data sets) were conducted over multiple hours.</li> </ul> <p> </p> <p><strong>==================<br> CODE_AND_PLOTS<br>==================</strong></p> <p>This archive contains the code required to gather the raw acoustic measurement data (see section <strong>DATA_RAW</strong>), the code to post-process and yield the final impulse response data (see section <strong>DATA</strong>), and the resulting plots as described in this section.</p> <p>Directory "dependencies/":</p> <ul> <li>Matlab and Python functions that are utilized in the code</li> <li>Additional dependencies of available open-source projects may be required for certain code functions. If so, the source and setup process for the necessary dependencies are documented in the code header.</li> </ul> <p>Directory "plots/":</p> <ul> <li>Plots that were exported (and that may be regenerated) by the following scripts to validate different stages of the data simulation, measurement, and subsampling.</li> </ul> <p>Shell script "x1_Start_Jupyter.sh":</p> <ul> <li>Prepare a Python environment with the required tools described as dependencies.</li> <li>Activate the prepared Python environment to perform impulse response measurements using Jupyter Notebooks setup for different acoustic settings.</li> </ul> <p>Python Jupyter notebook "x1a_Measure_Microphones.ipynb":</p> <ul> <li>Setup and test the utilized acoustic measurement hardware.</li> <li>Perform a series of acoustic measurements of all utilized microphones in an anechoic environment.</li> <li>Export the raw acoustic data and processed impulse responses.</li> </ul> <p>Python Jupyter notebook "x1b_Measure_BRIRs.ipynb":</p> <ul> <li>Setup and test the utilized acoustic measurement hardware.</li> <li>Generate a horizontal grid of measurement orientations for the VariSphear turntable according to the desired dummy head orientations.</li> <li>Perform a series of acoustic measurements of the dummy head at the pre-defined grid in anechoic and various room environments.</li> <li>Export the raw acoustic data and processed impulse responses.</li> </ul> <p>Python Jupyter notebook "x1c_Measure_SMAs.ipynb":</p> <ul> <li>Setup and test the utilized acoustic measurement hardware.</li> <li>Generate a spherical grid of measurement orientations for the VariSphear turntable according to the desired SMA sampling grid.</li> <li>Perform a series of acoustic measurements of the SMA microphone at the pre-defined grid in anechoic and various room environments.</li> <li>Export the raw acoustic data and processed impulse responses.</li> </ul> <p>Python Jupyter notebook "x1d_Measure_XMAs.ipynb":</p> <ul> <li>Setup and test the utilized acoustic measurement hardware.</li> <li>Generate a horizontal grid of measurement orientations for the VariSphear turntable according to the desired scattering body orientations.</li> <li>Perform a series of acoustic measurements of the XMA microphones at the pre-defined grid in anechoic and various room environments.</li> <li>Export the raw acoustic data and processed impulse responses.</li> </ul> <p>Matlab script "x1e_Simulate_SMAs.m":</p> <ul> <li>Simulate a plane wave impinging from an arbitrary direction on SMAs and EMAs with a desired sampling grid in an anechoic environment.</li> <li>The simulations are helpful to evaluate the rendering method and to investigate the influence of different sampling grids and equalization methods on the rendered binaural signals.</li> </ul> <p>Matlab script "x2_Gather_And_Plot_Measurements.m":</p> <ul> <li>Gather the stored single files with individually measured impulse responses and the according metadata into a combined data set.</li> <li>The initial impulse responses can be recomputed with pre- and post-processing parameters tuned towards the specific acoustic scenario, including compensation of provided source and receiver impulse responses.</li> <li>Many plots may be generated during the processing to validate the input and output data.</li> </ul> <p>Matlab script "x2a_Compare_Measurement_Lengths.m":</p> <ul> <li>Compare the length of the resulting impulse responses of designated measurement configurations.</li> <li>This may be helpful for the tuning of pre-processing and post-processing parameters of the measured impulse responses.</li> </ul> <p>Matlab script "x3_Subsample_Measurements.m":</p> <ul> <li>Spatially subsample a high-resolution directional impulse response data set into a different (lower-resolution) sampling grid in the spherical harmonics domain.</li> <li>This is suitable for array and HRIR data sets.</li> <li>The script also compares the subsampled data against a reference set if available. In the current data set, an evaluation is performed for an anechoic simulation and a room measurement of an SMA at SH order 8.</li> </ul> <p>Matlab script "x3a_Gather_XMA_Measurements.m":</p> <ul> <li> <p>Transform anechoic XMA measurement data from SOFA into the data format required by the processing scripts to calculate the respective calibration and equalization filters.</p> </li> </ul> <p>Readme file "x3b_Generate_XMA_Filters.txt":</p> <ul> <li>The code for this functionality follows the publication [1] but is currently not polished enough for publication. Please contact Jens Ahrens (jens.ahrens@chalmers.se) for questions regarding this functionality.</li> <li>[1] J. Ahrens, H. Helmholz, D. Lou Alon, and S. V. Amengual Garí, “Spherical Harmonic Decomposition of a Sound Field Using Microphones on a Circumferential Contour Around a Non-Spherical Baffle,” <em>IEEE/ACM Trans. Audio, Speech, Lang. Process.</em>, vol. 30, pp. 3110–3119, 2022, doi: 10.1109/TASLP.2022.3209940.</li> </ul> <p>Matlab script "x3c_Gather_XMA_Filters.m":</p> <ul> <li>Rename the files containing the computed calibration and equalization filters into a suitable convention for this collection of scripts.</li> <li>The generated name includes an incremental index to track different versions of provided filter sets.</li> </ul> <p>Matlab script "x3d_Compare_XMA_Filters.m":</p> <ul> <li> <p>Generate various time domain and frequency domain plots to compare different versions of the generated XMA calibration and equalization filters.</p> </li> </ul> <p> </p> <p><strong>================<br> DOCUMENTATION<br>================</strong></p> <p>This archive contains additional documentation of the setups and processes while conducting the acoustic measurements, as described in this section.</p> <p>Directory "documentation/":</p> <ul> <li>Various photographs of the different room, source, and receiver arrangements of the data set</li> <li>The room dimensions and source and receiver positions are documented in the form of the original measurement notes (this may be improved in the future).</li> </ul> <p> </p>
Simulations of POPC bilayers and monolayers at three different sizes. CHARMM36 with OPC water model
<p>Simulations of POPC bilayers and monolayers with the CHARMM36 force field and OPC water. Three system sizes are used: small ("s", 64 lipids), medium ("m", 256 lipids), and large ("l", 1024 lipids). All simulations are 1 µs long. The simulations are performed using GROMACS, and for each system the following are provided for bilayers (without "mono" in the name) and monolayers (with "mono" in the name):</p> <ul> <li>run input file (tpr)</li> <li>energy file (edr)</li> <li>trajectory file (xtc)</li> <li>checkpoint file (cpt) </li> <li>final structure (gro)</li> </ul> <p>Additionally, the following are shared by the monolayer and bilayer, and their naming convention follows the bilayer one.</p> <ul> <li>index file (ndx)</li> <li>topology file (top)</li> </ul> <p>The simulation parameter files (mdp) are provided separately for bilayers and monolayers. The molecular topologies (top) are included in TOP.tar.</p> <p>The CHARMM36 force field is obtained from http://mackerell.umaryland.edu/charmm_ff.shtml</p>
Simulations of POPC, SOPC, DOPC, and OMPC monolayers at three different sizes
<p>Simulations of lipid monolayers with the CHARMM36 force field and TIP3P water. Three system sizes are used: small ("s", 64 lipids), medium ("m", 256 lipids), and large ("l", 1024 lipids). All simulations are 1 µs long. The simulations are performed using GROMACS, and for each system the following are provided:</p> <ul> <li>index file (ndx)</li> <li>topology file (top)</li> <li>run input file (tpr)</li> <li>energy file (edr)</li> <li>trajectory file (xtc)</li> <li>checkpoint file (cpt) </li> <li>final structure (gro)</li> </ul> <p>The simulation parameter file (mdp) is common for all simulations. The molecular topologies (top) are included in TOP.tar.</p> <p>The CHARMM36 force field is obtained from http://mackerell.umaryland.edu/charmm_ff.shtml</p>
Toward three-dimensional DNA industrial nanorobots
<p>Nanoscale industrial robots have potential as manufacturing platforms, capable of automatically performing repetitive tasks to handle and produce nanomaterials with consistent precision and accuracy. We demonstrate a DNA industrial nanorobot, that fabricates a three-dimensional (3D) optically active, chiral structure from optically inactive parts. By making use of externally controlled temperature and ultraviolet (UV) light, our programmable robot, ~ 100 nanometers in size, grabs different parts, positions and aligns them so that they can be "welded", releases the construct and returns to its original configuration ready for its next operation. Our robot can also self-replicate its 3D structure and functions, surpassing single-step templating (restricted to two-dimensional (2D)) by using folding to access the third dimension and more degrees of freedom. Our introduction of multiple-axis precise folding and positioning as a tool/technology for nanomanufacturing will open the door to more complex and useful nano-micro devices.</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.