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Dataset results
453 results for “Dynamic dataset”
Restart uncertainty relation for monitored quantum dynamics. DataSet
<p>Source Data Set for the publication entitled: Restart uncertainty relation for monitored quantum dynamics.</p>
Variability of Earth's ionospheric outflow in response to the dynamic terrestrial exosphere - dataset and plotting script
<p>This dataset contains all the information discussed and displayed in the paper titled "Variability of Earth's ionospheric outflow in response to the dynamic terrestrial exosphere". The attached Jupyter notebook contains the necessary software to produce the same plots that were used to conduct the analysis.</p>
Datasets for the submitted manuscript entitled as "Thermodynamic and Dynamic Changes in Japan Sea Polar Air Mass Convergence Zone and its Associated Heavy Snowfall Under Warmer Climate"
<p>These are datasets for the submitted manuscript entitled as "Thermodynamic and Dynamic Changes in Japan Sea Polar Air Mass Convergence Zone and its Associated Heavy Snowfall Under Warmer Climate". The thirteen cases of WRF domain 2 simulation in historical and PGW experiments were uploaded, respectively. </p>
Dataset for "Evolutionary Dynamics and Mechanisms of Chain-style Landslide Dam Failure Hazard: Insights from Experimental Field Research"
<p>Yang et al. (2024) Dataset for "Evolutionary Dynamics and Mechanisms of Chain-style Landslide Dam Failure Hazard: Insights from Experimental Field Research", Journal of Geophysical Research-Earth Surface.</p> <p>The data that support the findings of this study are available on request from the corresponding author upon reasonable request.</p>
Dataset for "Advances in Docking Protocols for PPIs: Insights from AlphaFold2 and Molecular Dynamics Refinement"
<p>Dataset files used in 'Advances in Docking Protocols for PPIs: Insights from AlphaFold2 and Molecular Dynamics Refinement' (https://github.com/SysBioUAB/docking_benchmark)</p>
Dataset for: Dynamic transition and Galilean relativity of current-driven skyrmions
<p>This data repository contains the experimental data utilised to produce the figures shown in the article "Dynamic transition and Galilean relativity of current-driven skyrmions" by Max Birch, Ilya Belopolski, Yukako Fujishiro, Minoru Kawamura, Akiko Kikkawa, Yasujiro Taguchi, Max Hirschberger, Naoto Nagaosa and Yoshinori Tokura.</p> <p>All data are in the typical .dat file format from a Quantum Design PPMS. The data are organised according to each main/extended/supplementary figure in the article. This means that same data files may appear in more than one figure folder. Files are labelled according to which device was measured, with additional information on the sample environment (temperature/field/current etc) included where relevant.</p>
Dataset for "Constructing many-body dissipative particle dynamics models of fluids from bottom-up coarse-graining"
<ul> <li>The trajectory files used for processing time correlation functions, as reported in the original paper, are provided here.</li> <li>The analysis tools can be found in the following GitHub repository: <a href="https://github.com/jaehyeokjin/ManyBodyDPD/tree/main/Time-Correlation" target="_new" rel="noopener">ManyBodyDPD/Time-Correlation</a>. These tools are designed to work with the two trajectory files included in this repository.</li> </ul>
Dataset for: Dynamically patterning X-ray beam by a femtosecond optical laser
<p>This record contains the image and plot data for the paper "Dynamically patterning X-ray beam by a femtosecond optical laser".</p>
Supporting Dataset for the study "Influence of Floodplains and Groundwater Dynamics on the Present-Day Climate simulated by the CNRM Model"
<p>This archive contains the data used in the study "Influence of Floodplains and Groundwater Dynamics on the Present-Day Climate simulated by the CNRM Model" submitted to <a href="https://www.earth-system-dynamics.net/">Earth System Dynamics</a>.</p> <p> </p>
A fMRI dataset in response to large number of short natural dynamic facial expression videos
<p><span>Facial expression is among the most natural methods for human beings to convey their emotional information in daily life. Although </span>the neural mechanism of facial expression has been extensively studied employing lab-controlled images and a <span>small number of</span> lab-controlled video stimuli, how the human brain processes <span>natural</span> facial expressions still needs to be investigated. <span>T</span>o our knowledge<span>,</span> this type of data <span>specifically</span> <span>on </span><span>large number of </span><span>natural</span> <span>facial expression videos</span> is currently missing. <span>W</span>e describe <span>here </span>the <span>natural </span>Facial Expressions Dataset (NFED), a fMRI dataset <span>including </span>responses to 1,320 short (<span>3-second</span>) <span>natural</span> facial expression video clips. <span>These video clips is </span><span>annotated</span> <span>with three types of labels: emotion, gender, and ethnicity</span><span>, along with accompanying metadata</span>. We validate that the dataset has good quality within and across participants and, notably, can capture temporal and spatial stimuli features. NFED provides researchers with fMRI data for understanding of the visual processing of large number of <span>natural </span> <span>facial expression videos.</span></p>
Dataset for "Dynamical Study of the Reaction of N+ Ions with O2 Neutrals"
<p>Dataset for "Dynamical Study of the Reaction of N+ Ions with O2 Neutrals"</p>
Dataset for "Reaction dynamics of the methoxy anion CH3O- with methyl iodide CH3I"
<p>Dataset for "Reaction dynamics of the methoxy anion CH3O- with methyl iodide CH3I"</p>
Dataset for "Imaging the ion-molecule reaction dynamics of O- + CD4"
<p>Dataset for "Imaging the ion-molecule reaction dynamics of O- + CD4"</p>
A fMRI dataset in response to large-scale short natural dynamic facial expression videos
<p>Facial expression is among the most natural methods for human beings to convey their emotional information in daily life. Although the neural mechanism of facial expression has been extensively studied employing lab-controlled images and a small number of lab-controlled video stimuli, how the human brain processes natural facial expressions still needs to be investigated. To our knowledge, this type of data specifically on large<span>-scale</span> natural facial expression videos is currently missing. We describe here the natural Facial Expressions Dataset (NFED), a fMRI dataset including responses to 1,320 short (3-second) natural facial expression video clips. These video clips is annotated with three types of labels: emotion, gender, and ethnicity, along with accompanying metadata. We validate that the dataset has good quality within and across participants and, notably, can capture temporal and spatial stimuli features. NFED provides researchers with fMRI data for understanding of the visual processing of large number of natural facial expression videos.</p>
Molecular dynamics analysis of iPP-polymorphs; a dataset of alpha and beta atomic structures
<p>This is the dataset corresponding to the publication in the <em>Polymer </em>journal:</p> <p>"Molecular dynamics analysis of iPP-polymorphs; Investigating thermal expansion and elastic properties"</p> <p>Authors:<strong> H.N. Chávez Thielemann, J.A.W. van Dommelen, L.E. Govaert, M. Hütter</strong></p> <p>Year: 2024</p> <p> </p> <p>The dataset presented here provides the chemical structures of iPP crystals, including COMPASS forcefield parameters, as follows:</p> <p>α structures were obtained by repeating the crystalline unit cell 4 times in a, 2 times in b, and 4 times in c (comprising 32 chains and 3456 atoms)</p> <ul> <li><strong><a href="https://zenodo.org/records/14048060/files/alpha2.zip?download=1">alpha2.zip</a>: </strong>α2 is the unit cell with perfect up-down alternation.</li> <li><a href="https://zenodo.org/records/14048060/files/alpha1.zip?download=1"><strong>alpha1.zip</strong></a>: α1 is an α2 but with 50% random up-down alternation.</li> </ul> <p>A X% of regio defects means that X% of the monomers are incorporated with the inverse head-tail order than in a perfect α2 case.<br>Thus, number of atoms and chains remain unvaried.</p> <ul> <li><a href="https://zenodo.org/records/14048060/files/d2p.zip?download=1"><strong>d2p.zip:</strong></a> α2 containing 2% of regio defects.</li> <li><strong><a href="https://zenodo.org/records/14048060/files/d4p.zip?download=1">d4p.zip:</a> </strong>α2 containing 4% of regio defects.</li> </ul> <p>Vacancy, 31 chains, 3348 atoms:</p> <ul> <li><strong><a href="https://zenodo.org/records/14048060/files/v1.zip?download=1">v1.zip:</a> </strong>contains the same α2 but with a vacancy, i.e. a complete chain is missing.</li> </ul> <p>β structures were obtained by repeating the crystalline unit cell 3 times in a, 2 times in b, and 4 times in c (comprising 36 chains and 3888 atoms)</p> <ul> <li><strong><a href="https://zenodo.org/records/14048060/files/beta2.zip?download=1">beta2.zip:</a> </strong>β2 structure is a monochiral domain, with purely right-handed chains.</li> <li><a href="https://zenodo.org/records/14048060/files/beta1.zip?download=1"><strong>beta1.zip:</strong></a> β1 structure comprises twelve left- and twenty-four right-handed chains.</li> </ul> <p> </p> <p>File names ended with <strong>_img</strong> indicates that supplementary images are provided for that structure.</p> <p>In most of the cases, the LAMMPS data files are accompanied by a PDB file for completeness.</p> <p>To download them all including extra files at once, then download the archive file <a href="https://zenodo.org/api/records/14048060/files-archive"><strong>14048060.zip</strong>.</a></p>
GazeMining: A Dataset of Video and Interaction Recordings on Dynamic Web Pages. Labels of Visual Change, Segmentation of Videos into Stimulus Shots, and Discovery of Visual Stimuli.
<p><strong>Recording setup</strong><br> Recordings have been taken place on 12th March 2019. Gaze data has been recorded with a Tobii 4C eye tracker with Pro license at 90 Hz. Resolution of the viewport was set to 1024x768. The display had a size of 24 inches and a resolution of 1680x1050 pixels. We polled the DOM tree every 50 milliseconds for fixed elements. We recorded the Web browsing of four participants, who followed the protocol as stored under "Dataset_visual_change/Instructions.doc".</p> <p><strong>Description of the dataset</strong><br> The dataset consists of following three subsets.</p> <p><em>1. Dataset_visual_change</em><br> The recordings of each participant p1-p4 on twelve Web sites are in the corresponding directories. For each Web site, there are nine to eleven files:</p> <ul> <li><site>.json: datacast</li> <li><site>.webm: video recording</li> <li><site>.features.csv: computer-vision features per observation</li> <li><site>.features_meta.csv: meta information about features</li> <li><site>.labels-l<X>.csv: labels of observations</li> <li><site>_meta.csv: meta information about recording</li> <li><site>_scroll_cache.csv: cache of estimated scrolling</li> <li><site>_scroll_cache_map.csv: mapping of observations to scroll cache entries</li> <li><site>_times.csv: timestamps of frames in the video recording</li> <li><site>_layer_pixels.csv: first row is the pixel count of root layer, second row is pixel count of all fixed elements</li> </ul> <p><em>2. Dataset_stimuli</em><br> Stimulus shots and visual stimuli computed with the framework. Value-based, edge-based, signal-based, and SIFT-based features have been used. The labels of the first participant's session had been used to train a random forest classifier with 100 trees for visual change classification, using the named features. The discovery has been performed on each Web site from the dataset and<br> the results are placed in the respective directories. Inside each directory, there is one directory for the detected shots and one for the discovered stimuli. In the shots directory, there is one overview as <participant>_<site>.csv file. For each shot, there are four further files:</p> <ul> <li><participant>_<site>_<shot>.png: stitched frame of the stimulus shot</li> <li><participant>_<site>_<shot>-blind.csv: frames from animations that are not contributing to the stitched frame</li> <li><participant>_<site>_<shot>-gaze.csv: gaze data (in stitched frame space)</li> <li><participant>_<site>_<shot>-mouse.csv: mouse data (in stitched frame space)</li> </ul> <p>The shots have been merged to stimuli, which are placed in the stimuli directory. The stimuli are grouped per layer (scrollable, fixed elements, etc.) and meta information is available in <layer_index>-<xpath>-meta.csv files. Furthermore, there are directories per layer, storing the discovered stimuli. Each discovered visual stimulus is represented by four files:</p> <ul> <li><stimulus_id>.png: stitched frame of the visual stimulus</li> <li><stimulus_id>-gaze.csv: gaze data (in stitched frame space)</li> <li><stimulus_id>-mouse.csv: mouse data (in stitched frame space)</li> <li><stimulus_id>-shots.csv: contained stimulus shots</li> </ul> <p><em>3. Dataset_evaluation</em><br> We have performed two evaluations of the visual stimuli discovery. One computational estimating the quality of stimuli. One case-study of an expert's task. There are two respective directories with the annotation data.</p> <p><strong>Changelog</strong><br> [1.0.2] Add counts of layer pixels per participant.<br> [1.0.1] Change to CC0 license.<br> [1.0.1] Add labels of third annotator "l3".<br> [1.0.0] Initial release.</p>
Dataset of "Electron holography details the Tagish Lake parent body and implies early planetary dynamics of the Solar System"
<p>Input files for iSALE-2D of the paper "Electron holography details the Tagish Lake parent body and implies early planetary dynamics of the Solar System" by Y. Kimura et al.<br> <br> Please note that usage of the iSALE-2D is not fully open source; it is distributed on a case-by-case basis to academic users in the impact community, strictly for noncommercial use. Scientists interested in using or developing iSALE code may apply at the iSALE Web page (http://www.isale-code.de). </p>
Molecular Dynamics Dataset - Dynamics of GLP-1R peptide agonist engagement are correlated with kinetics of G protein activation
<p>Molecular dynamics simulations of the glucagon-like peptide receptor (GLP-1R) in complex with Gs protein and four different agonist peptides: GLP-1, exendin-4, oxyntomodulin, and exendin-P5. </p> <p>For each system, the .xtc file is the result of the merging of 4 replicas of 500 ns for a total of 2 microseconds (8 microseconds considering all four GLP-1R complexes). The original MD trajectories have been stripped of water, ions and phosphatidylcholine atoms before the upload. The CHARMM36 force field was used.</p>
GISD30: global 30-m impervious surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform
<p>A novel and accurate global 30 m impervious surface dynamic dataset (GISD30) for 1985 to 2020 was produced using the spectral generalization method and time-series Landsat imagery, on the Google Earth Engine cloud-computing platform.</p>
dataset Master Thesis Optimising parity game solvers using dynamic SCC maintenance
<p>Complete dataset of my Master Thesis Optimising parity game solvers using dynamic SCC maintenance</p>
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.