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1,651 results for “Plane”
Raw data from the manuscript "Full-aperture extended-depth oblique plane microscopy through dynamic remote focusing"
<p>The repository contains all the raw data from the manuscript titled "Full-aperture extended-depth oblique plane microscopy through dynamic remote focusing" (https://doi.org/10.1117/1.JBO.29.3.036502).<br> The data consists in 3D stacks acquired with the method described in the manuscript. Since raw images are acquired along a diagonal plane, and are stretched in one direction, the dataset also includes a Python script to perform an affine transform projecting the stack on cartesian coordinates.</p> <p>Samples imaged include sub-resolution microbeads in agarose gel, a fixed slice of mouse kidney (fluocells prepared slide #3, invitrogen), and 3 to 5 days post fertilization Tg(kdrl:eGFP)s843 Zebrafish.</p>
Dataset for the study Late development of audio-visual integration in the vertical plane
<p>It is not clear how multisensory skills develop and how visual experience impacts on multisensory spatial development. Conflicting results show that visual calibration precedes multisensory integration for the audio-visual spatial bisection task (Gori et al., 2012a, 2012b) while in other tasks such as spatial localization, visual calibration occurs after multisensory development (Rohlf et al., 2020). Results in blind individuals can say something about the role of vision on perceptual development. Scientific evidences show that blind individuals have impairments in bisecting the auditory space (Gori et al., 2014) but not in localizing auditory sources (Lessard et al., 1998). Such results suggest that sensory calibration and impairment are linked. We studied the development of audio-visual multisensory localization in the vertical plane in sighted individuals from 5 years to adulthood to address this hypothesis. We hypothesize that typical children would show late audio-visual integration for the vertical plane, preceded by visual dominance. Unimodal and bimodal audio-visual thresholds and PSEs were measured and compared with the Bayesian optimal-integration model (maximum likelihood estimation). Results show that the development of multisensory integration in the vertical plane is not evident at 5 years, suggesting visual dominance for vertical audio-visual localization. These results support the idea that multisensory perception in the vertical domain depends on sensory calibration. We discuss these scientific results proposing that the process of cross-sensory calibration is task-specific and highlighting the importance of linking the impairment and development to better determine how our brain works.</p> <p>Data are in textual tab delimited format. Columns report for each subject: age, age_bin, condition, jnd.</p> <p> </p>
High-precision Aftershock Locations and Fault Planes of the 2016-2017 Central Italy Sequence
<p>The earthquake catalog includes high-precision hypocenter relocations for 390,334<br> earthquakes recorded during the 2016-2017 Amatrice (Central Italy) <br> earthquake sequence. The relative locations were computed by double-difference inversion of a <br> combination of INGV phase picks and cross-correlation differential <br> times measured from correlated seismograms with correlation coefficients > 0.7.</p> <p>Planes of normal faults (idx=1-5) are derived from PCA analysis of 2 months of aftershock <br> locations in the CAT4 catalog following large events. Surfaces of detachment faults (idx=7-10) are derived from mapping out the location of correlated earthquakes. </p> <p>Citation: Waldhauser, F., Michele, M., Chiaraluce, L., Di Stefano, R., & Schaff, D. P. (2021). Fault planes, fault zone structure and detachment fragmentation resolved with highprecision aftershock locations of the 2016-2017 central Italy sequence. Geophysical Research Letters, 48, e2021GL092918. https://doi.org/10.1029/2021GL092918</p>
A Fully-Parameterized Object-Side Light Field Dataset and Theory for Using Entrance and Exit Pupils as Natural Light Field Reference Planes for an Unfocused Plenoptic Camera
<p>We describe a dataset of light fields with full object-side parameterizations. The dataset contains PNG and ESLF files for all 32 images. 12 of them additionally contain depth maps and point clouds.</p>
Dataset for "Self-assembly of dodecagonal and octagonal quasicrystals in hard spheres on a plane"
<p>This dataset contains supplementary data for the publication:<br> <em>Self-assembly of dodecagonal and octagonal quasicrystals in hard spheres on a plane</em><br> E. Fayen, M. Impéror-Clerc, L. Filion, G. Foffi, and F. Smallenburg</p> <p> </p> <p><strong>Contents:</strong><br> The folder Data contains subfolders for each of the simulations performed for the construction of Fig. 3 of the main paper. Each folder name contains the size ratio q, the fraction of large particles x_L, and the packing fraction e in the file name. Note that the fraction of large particles x_L is related to the quantity x_S used in the paper via x_L = 1 - x_S.</p> <p>For simulations that were run for longer times, an additional folder with the same naming convention is included in the subfolder Long.</p> <p>Each simulation subfolder includes:</p> <p>- A coordinate file "last.sph" representing the final configuration of the simulation in plain text format. In this file, the first line specifies the number of particles, the second line the box size and non-additivity parameter Delta, and the remaining lines the coordinates of the particles. Each line containing coordinates consists of a letter indicating particle species (a or b), three spatial coordinates (with the z-coordinate always zero), and the particle radius. All lengths are given in units of the large-particle diameter.</p> <p>- An image of the final particle configuration "snapshot.png".</p> <p>- An image representing the associated scattering pattern, obtained by taking the Fourier transform of the particle coordinates and plotting the result as a function of the 2D wave vector on a logarithmic color scale.</p> <p> </p> <p>Additionally, the main folder contains a set of HTML files ("table_q*.html") that provide an overview of the snapshots and scattering patterns for each size ratio (specified in the file name). The HTML table for each size ratio uses the images from the "Data" and "Data/Long" subfolders as appropriate, and depends on the included "SAtable.css" and "SAtable.js" files. Within each table, clicking on one of the entries will enlarge the associated images.<br> <br> </p>
MESA model files and data for: 'Stellar Neutrino Emission Across The Mass-Metallicity Plane'
<p>Example MESA model files and stellar evolution tracks for download from "Stellar Neutrino Emission Across The Mass-Metallicity Plane".</p>
A Free Database of Head-Related Impulse Response Measurements in the Horizontal Plane with Multiple Distances (MAT-Version)
<p>Head related impulse response measurements with the KEMAR dummy head performed in an anechoic chamber with a resolution of 1°. The impulse responses are provided for different distances and are accompanied by headphone compensation filters.</p> <p>This entry stores the measurements in the MAT format for use in Matlab/Octave. The measurements are identical to the once stored in the SOFA format available at <a href="https://doi.org/10.5281/zenodo.55418">https://doi.org/10.5281/zenodo.55418</a></p>
A Free Database of Head-Related Impulse Response Measurements in the Horizontal Plane with Multiple Distances
<p>Head related impulse response measurements with the KEMAR dummy head performed in an anechoic chamber with a resolution of 1°. The impulse responses are provided for different distances and are accompanied by headphone compensation filters.</p> <p>For details have a look at README.md.</p> <p>The same measurement can be downloaded as MAT files at <a href="https://doi.org/10.5281/zenodo.4459911">https://doi.org/10.5281/zenodo.4459911</a></p> <p>This dataset is further described in (see the PDF file)</p> <p>H. Wierstorf, M. Geier, A. Raake, S. Spors - A Free Database of Head-Related<br> Impulse Response Measurements in the Horizontal Plane with Multiple Distances.<br> In 130th AES Conv. 2011, eBrief 6.</p> <p> </p>
Symmetry breaking in spin spirals and skyrmions by in-plane and canted magnetic fields
<p>The influence of in-plane and canted magnetic fields on spin spirals and skyrmions in atomic bilayer<br> islands of palladium and iron on an Ir(111) substrate is investigated by scanning tunneling microscopy<br> at low temperatures. It is shown that the spin spiral propagation direction is determined by the island’s<br> border which can be explained by equilibrium state calculations on a triangular lattice.Wefind a<br> different response of spin spirals to in-plane magnetic fields for a propagation direction parallel to the<br> applied field as compared to perpendicular, which originates from their cycloidal nature. As a result,<br> the spin spiral propagation direction may be reorientated by in-plane fields. Furthermore, it is<br> demonstrated that also skyrmions are distorted in canted fields which allows to determine the sense of<br> magnetization rotation as enforced by the interfacial Dzyaloshinskii–Moriya interaction.</p>
Kuopio gait dataset: motion capture, inertial measurement and video-based sagittal-plane keypoint data from walking trials
<p>This dataset contains motion capture (3D marker trajectories, ground reaction forces and moments), inertial measurement unit (wearable Movella Xsens MTw Awinda sensors on the pelvis, both thighs, both shanks, and both feet), and sagittal-plane video (anatomical keypoints identified with the OpenPose human pose estimation algorithm) data.<br>The data is from 51 willing participants and collected in the HUMEA laboratory in the University of Eastern Finland, Kuopio, Finland, between 2022 and 2023. All trials were conducted barefoot.</p> <p>The file structure contains an Excel file containing information of the participants, data folders under each subject (numbered 01 to 51), and a MATLAB script.</p> <p>The Excel file has the following data for the participants:</p> <ul> <li><strong>ID</strong>: ID of the participants from 1 to 51</li> <li><strong>Age</strong>: age of the participant in years</li> <li><strong>Gender</strong>: biological sex as M for male, F for female</li> <li><strong>Leg</strong>: the participant's dominant leg, identified by asking which foot the participant would use to kick a football; R for right, L for left</li> <li><strong>Height</strong>: height of the participant in centimeters</li> <li><strong>Invalid_trials</strong>: list of invalid trials in the motion capture data (MOCAP) data, usually classified as such because the participant did not properly step on the middle force plate</li> <li><strong>IAD</strong>: inter-asis distance in millimeters, the distance between palpated left and right anterior superior iliac spine, measured with a caliper</li> <li><strong>Left_knee_width</strong>: width of the left knee from medial epicondyle to lateral epicondyle in millimeters, palpated and measured with a caliper</li> <li><strong>Right_knee_width</strong>: same as above for the right knee</li> <li><strong>Left_ankle width</strong>: width of the left ankle from medial malleolus to lateral malleolus in millimeters, palpated and measured with a caliper</li> <li><strong>Right_ankle_width</strong>: same as above for the right ankle</li> <li><strong>Left_thigh_length</strong>: the distance between the greater trochanter of the left femur and the lateral epicondyle of the left femur in millimeters, palpated and measured with a measuring tape</li> <li><strong>Right_thigh_length</strong>: same as above for the right thigh</li> <li><strong>Left_shank_length</strong>: the distance between the medial epicondyle of the femur and the medial malleolus of the tibia in millimeters, palpated and measured with a measuring tape</li> <li><strong>Right_shank_length</strong>: same as above for the right shank</li> <li><strong>Mass</strong>: mass in kilograms, measured on a force plate just before the walking measurements</li> <li><strong>ICD</strong>: inter-condylar distance of the knee of the dominant leg, measured from low-field MRI</li> <li><strong>Left_knee_width_mocap</strong>: distance between reflective MOCAP markers on the medial and lateral epicondyles of the knee in millimeters, measured from a static standing trial; -1 for missing (subject did not have those markers)</li> <li><strong>Right_knee_width_mocap</strong>: same as above for the right knee</li> </ul> <p>The folders under each subject (folders numbered 01 to 51) are as follows:</p> <ul> <li><strong>imu</strong>: "Raw" inertial measurement unit (IMU) data files that can be read with Xsens Device API (included in Xsens MT Manager 4.6, which may be unavailable these days, not sure). You won't need this if you use the data in the imu_extracted folder.</li> <li><strong>imu_extracted</strong>: IMU data extracted from those data files using the Xsens Device API, so you don't have to. <ul> <li>The data is saved as MATLAB structs where the fields are named as a sensor ID (e.g., "B42D48"). The sensor IDs and their corresponding IMU locations are as follows: <ul> <li>pelvis IMU: B42DA3</li> <li>right femur IMU: B42DA2</li> <li>left femur IMU: B42D4D</li> <li>right tibia IMU: B42DAE</li> <li>left tibia IMU: B42D53</li> <li>right foot IMU: B42D48</li> <li>left foot IMU: B42D51 (except for subjects 01 and 02, where left foot IMU has the ID B42D4E)</li> </ul> </li> <li>Some of the data are just zeros as they couldn't be read from these sensors, but under each sensor, the fields "calibratedAcceleration", "freeAcceleration", "time", "rotationMatrix", and "quaternion" contain usable data. <ul> <li>time: Contains time stamps of the measurement at each frame recorded at 100 Hz, so if you remove the first value from all values in the time vector and divide the result by 100, you will get the time in seconds from the beginning of the walking trial.</li> <li>calibratedAcceleration and freeAcceleration: Contain triaxial acceleration data from the accelerometers of the IMU. freeAcceleration is just calibratedAcceleration without the effect of Earth's gravitational acceleration.</li> <li>rotationMatrix: Orientations of the IMU as rotation matrices.</li> <li>quaternion: Orientations of the IMU as quaternions.</li> </ul> </li> </ul> </li> <li><strong>openpose</strong>: Trajectories of the keypoints identified from sagittal plane video frames, saved as json files. <ul> <li>The keypoints are from the BODY_25 model of OpenPose (https://cmu-perceptual-computing-lab.github.io/openpose/web/html/doc/md_doc_02_output.html).</li> <li>Each frame in the video has its own json file.</li> <li>You can use the function in the script "OpenPose_to_keypoint_table.m" in the root folder to read the keypoint trajectories and confidences of all frames in a walking trial into MATLAB tables. The function takes as argument the path to the folder containing the json files of the walking trial.</li> </ul> </li> <li>Note that some subjects (11, 14, 37, 49) do not have keypoint and IMU data.</li> </ul> <p>The folders under each subject are divided into three ZIP archives with 17 subjects each.</p> <p>The script "OpenPose_to_keypoint_table.m" is a MATLAB script for extracting keypoint trajectories and confidences from JSON files into tables in MATLAB.</p> <p><br><strong>Publication in Data in Brief</strong>: <a href="https://doi.org/10.1016/j.dib.2024.110841" target="_blank" rel="noopener">https://doi.org/10.1016/j.dib.2024.110841</a></p> <p><br><strong>Contact</strong>: Jere Lavikainen, jere.lavikainen@uef.fi</p>
Improvement of frequency responses of an in-plane electro-thermal cantilever sensor for real-time measurement (Data)
<p>Origin projects, figures and COMSOL simulation used for the article "Improvement of frequency responses of an in-plane electro-thermal cantilever sensor for real-time measurement", published in <em>Journal of Micromechanics and Microengineering </em>on 05 Nov 2019.</p>
In-Plane and Out-of-Plane MEMS Piezoresistive Cantilever Sensors for Nanoparticle Mass Detection (Data)
<p>Origin projects, figures and LabVIEW software used for the article "In-Plane and Out-of-Plane MEMS Piezoresistive Cantilever Sensors for Nanoparticle Mass Detection", published in <em>Sensors </em>on 22 Jan 2020.</p>
BetaEddyOne: A long-lived 1.5 layer quasigeostrophic eddy on a beta plane, with Lagrangian particles
<p>BetaEddyOne is a yearlong simulation of a large, nonlinear oceanic eddy under 1.5 layer quasigeostrophic dynamics on a beta plane, initially located at 24˚N. The simulation is run at 512 x 256 resolution and is seeded with Lagrangian particles with one particle per grid point. </p> <p>This simulation is indended for use as a common test case for eddy-related diagnostics and analysis methods. It approximately replicates the eddy analyzed in detail in Early, Samelson, and Chelton (2011), <a href="https://doi.org/10.1175/2011JPO4601.1">https://doi.org/10.1175/2011JPO4601.1</a>. The simulation was created using the WaveVortexModel (Early, Lelong, and Sundermeyer, 2021, <a href="https://doi.org/10.1017/jfm.2020.995">https://doi.org/10.1017/jfm.2020.995</a>), the code for which is available on GitHub at <a href="https://github.com/Energy-Pathways-Group/GLOceanKit">https://github.com/Energy-Pathways-Group/GLOceanKit</a>. This particular simulation was created for use in the paper</p> <p>Lilly, J. M., J. Feske, B. Fox-Kemper, and J. J. Early (2024). Integral theorems for the gradient of a vector field, with a fluid dynamical application. <em>Proceedings of the Royal Society of London, Series A</em>. <strong>480</strong> (2293): 20230550, 1–30. <a href="https://doi.org/10.1098/rspa.2023.0550">doi 10.1098/rspa.2023.0550</a>.</p> <p>The figure shows a snapshot of the model's vertical vorticity. </p> <p> </p>
Data files for the manuscript "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes"
<p>This depository contains the data of all DEM simulations used in the manuscript titled "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes" submitted to Soft Matter in July 2024.</p> <p>The data in the excel file are the measurements obtained after the coarse graining procedure.</p>
Data for "Impact of the Out-of-Plane Flow Shear on Magnetic Reconnection at the Flanks of Earth's Magnetopause"
<p>Data for Figures 3-8 in the paper (data for Figures 5 has been updated on 2024-09-20). The data is compatible with all data-analysis software. Here are the guidelines for reading and visualizing the data:</p> <p>(1) The filenames "noshear", "MA0p7", and "MA2p3" correspond to the simulation runs with no flow shear, Mach number M_A=0.7 flow shear, and M_A=2.3 flow shear.</p> <p>(2) The "upper" and "lower" mean upper and lower current sheet, corresponding to dusk-side and dawn-side reconnection respectively. For the "noshear" case, only the "upper" is considered.</p> <p>(3) Each data file (*.dat) is written in ASCII format and has multiple columns. The first row is the header.</p> <ul> <li>The first column is always the x-coordinates of the figure. </li> <li>For the line plots, all columns starting from the second column are the y-coordinates for different variables. The variables names can be found at the header. </li> <li>For the 2D image plots, the second column is the y-coordinates, and the third column is the value of the variable at a given (x,y) location. </li> </ul> <p>(4) The files "fig4_*_field_*.dat" are the magnetic potential in the x-y domain. The contour of this potential gives the in-plane field line configurations.</p>
Fermi-LAT transients in the Galactic plane
<p>It is a basic reproduction package for the paper titled "An update on Fermi-LAT transients in the Galactic plane, including strong activity of Cygnus X-3 in mid-2020" by Dmitry Prokhorov and Anthony Moraghan. This package includes data products for reproducing the main results of the paper, https://arxiv.org/abs/2209.12461. The description of data products is in the file, readme.txt. Please, feel free to contact Dmitry Prokhorov, email: d.prokhorov at uva.nl, if you have any questions about the data products. </p> <p>The paper is accepted for publication in MNRAS on November 18, 2022.</p> <p>The software used for this analysis is publicly available at https://zenodo.org/record/4739389 and Fermi-LAT data are publicly available at https://fermi.gsfc.nasa.gov/ssc/data/access/</p>
Maternal fetal ultrasound planes from low-resource imaging settings in five African countries
<p>This resource is a dataset of routinely acquired maternal-fetal screening ultrasound images collected in five centers of five countries in Africa (Malawi, Egypt, Uganda, Ghana and Algeria) that is associated to the journal article Sendra-Bacells et al. "Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries", <em>Scientific Reports</em>. The images correspond to the four most common fetal planes: abdomen, brain, femur and thorax. A CSV file is provided where image filenames are associated to plane types and patient number as well as the partitioning in training and testing splits as used in the associated publication.</p>
Fig. 2.26. Plane 5 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.26. Plane 5 of the specimen page at Zoosphere.net, showing the distribution of the specimen's species, as retrieved from GBIF. Image copyright MfN.
Fig. 2.24. Plane 3 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.24. Plane 3 of the specimen page at Zoosphere.net, showing the taxonomy of the specimen. Image copyright MfN.
Fig. 2.23. Plane 2 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections
Fig. 2.23. Plane 2 of the specimen page at Zoosphere.net, showing the specimen pictures. Image copyright MfN.
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.