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1,548 results for “Trajectories”
Data from: Food availability affects adult survival trajectories depending on early developmental conditions
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Data from: Paleo-trajectories of forest savannization in the southern Congo
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Monitoring resistance and resilience using carbon trajectories: analysis of forest management-disturbance interactions
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Data from: Maternal and nourishment factors interact to influence offspring developmental trajectories in social wasps
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Timing of invasive species removal influences nonnative biotic resistance and trajectories of community reassembly
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Data from: Ontogenetic stage-specific quantitative trait loci contribute to divergence in developmental trajectories of sexually dimorphic fins between medaka populations
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Data-Two-dimensional numerical study on particle motion trajectories and deposition in a channel of partial diesel particulate filter
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Data from: Post-fire recovery in coastal sage scrub: seed rain and community trajectory
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Data from: Senescence or selective disappearance? Age trajectories of body mass in wild and captive populations of a small-bodied primate
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Data from: Genetic divergence between two phenotypically distinct bottlenose dolphin ecotypes suggests separate evolutionary trajectories
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Data from: Unique evolutionary trajectories in repeated adaptation to hydrogen sulphide-toxic habitats of a neotropical fish (Poecilia mexicana)
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Data from: Contrasting trajectories of morphological diversification on continents and islands in the Afrotropical white-eye radiation
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The evolutionary trajectory of drosophilid walking
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Dataset in support of: Recovering mixtures of fast diffusing states from short single particle trajectories
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Speed trajectory data from adaptive eco-driving applications
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Supplementary Methods: Multiple imputation of CVRF trajectories in detail
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Dataset on termite trajectories in experimental arenas under varying social context
<p>Here we present a dataset of trajectories of <em>Cornitermes cumulans</em> (Blattodea: Isoptera: Termitidae: Nasutitermitinae) termites confined in experimental arenas along with their nestmates. The assays consisted of tracking a focal termite worker inserted in groups composed of varying numbers of nestmates arranged in varying soldier: worker proportions. We captured, every 0.5 s along 6 hours, the cartesian locations of the focal termite, using a video camera coupled to the software Ethovision XT. This allowed us to build the full trajectory of each focal termite in each arena along the full extent of each assay. With more than 2 million data-points, the set of termite trajectories provided here is the largest published so far.</p> <p>The dataset containing the Cartesian coordinates for the trajectories of focal termite workers. From each assay, we obtained two data series: (i) the raw trajectory with a few steps eventually missed by the tracking software, (ii) a trajectory minimally processed to interpolate the missing steps and change the origin of the coordinate system to remove the negative values. The raw recordings are presented in .txt files with the readings separated by semicolons, and the data series minimally processed are presented in .csv files with readings separated by comma. Each data series is named with a simple code from S01 to S75 (S, series).</p> <p><strong>1. Raw data series:</strong><br> Each raw data series is composed of two parts: the header and the columns. The header contains the identity and the general conditions of the assay. The columns consist of the data collected at the rate of one sample every 0.5 seconds with a maximum of 43,155 Cartesian points gathered. Additional details are given below, to help better understanding and allow proper use of these data.</p> <p><em>1.1 Fields of the header</em></p> <ul> <li>Experiment: The name given to the assay. This name was always composed by the word ``cupim'' -- termite in Brazilian Portuguese -- plus the day and the month of the assay plus the part of the day in which the tracking was made. For example, the experiment ``Cupim28AbrilManha'' means an assay with termites tracked on the day 28 of April during the morning (``Manhã'' in Portuguese). </li> <li>Arena name: The arena from which the data is reported. </li> <li>Subject name: Name given by default (Subject 01) to the individual tracked. </li> <li>Start time: Date and start time of the tracking.</li> <li>Trial duration: Duration of the assay. For all the cases tracking lasted for 6 hours. </li> <li>Recording after: Time spent between the onset of the trial and the actual recording of the first X and Y position; 1.5 seconds for all the trials. </li> <li>Recording duration: Total time of the trial recordings (6 hours). </li> <li>Track: The actual name given by Ethovision XT software to the tracking file with .trk extension. </li> <li>Tracking source: Brand and model of the video camera used to track the individuals. </li> <li>Reference duration: Time programmed for the trial (6 hours). </li> <li>Reference time: Date and time of the trial as given by the hosting computer </li> <li>Missed samples: Percentage of samples missed. </li> <li>Subject not found: Percentage of times the individual was not detected by the video camera. </li> </ul> <p> </p> <p><em>1.2 Columns:</em></p> <ul> <li>Trial time: Collection time of each sample in seconds. </li> <li>Recording time: Time in seconds in which each pair of Cartesian coordinates were saved in the memory of the software. The first pair of points received the time 0 s.</li> <li>X center: X component of the Cartesian point in milimeters.</li> <li>Y center: Y component of the Cartesian point in milimeters.</li> <li>Area: Area in square millimeters of the focal termite each time it was detected by the software. The Cartesian coordinates were missed when the area detected became close to zero.</li> <li>Areachange: The change of the focal termite area, in pixels, between the current sample and the previous one.</li> <li>Elongation: A value in percentage to indicate how much the body of the individual stretches. If 0 the shape's of the individual is perfectly circular and 1 if the subject's body is a line. </li> <li>Distance moved: The distance traveled in milimeters by the individual from the previous X-Y coordinates to the current position. </li> <li>Velocity: The distance moved in milimeters by the individual per unit time in seconds.</li> </ul> <p>For additional information consult the Ethovision XT manual.</p> <p> </p> <p><strong>2. Data series minimally processed</strong><br> The data series processed to eliminate the gaps resulting from missed samples have two columns, each corresponding to the X or the Y coordinate describing the focal termite position in the arena at a given time. As mentioned above, the full identification of each data series as well as the conditions of the assay are given in the table 1 (pdf file) and also in the header of the raw data series. For all the cases, the first column of the .dat file corresponds to X-axis and the second one to Y-axis. </p>
Visually Inferring Elasticity from the Motion Trajectory of Bouncing Cubes
<p>Dataset relative to the following publication:</p> <p>Paulun, V.C., & Fleming, R. W. (2020). Visually Inferring Elasticity from the Motion Trajectory of Bouncing Cubes. <em>Journal of Vision, </em>20(6):6, 1–14, https://doi.org/10.1167/jov.20.6.6</p> <p>One folder contains the stimuli, another folder contains data from the main and control experiment.</p>
Trajectory and input files for "Coating of magnetic nanoparticles affects their interactions with model cell membranes"
<p>Input and output files, including trajectories, for the study published in BBA - General Subjects :</p> <p>"Coating of magnetic nanoparticles affects their interactions with model cell membranes"</p> <p>https://doi.org/10.1016/j.bbagen.2020.129671</p>
Complementary data to "Molecular dynamics trajectories for 630 drug-membrane potentials of mean force"
<p>Missing data from "Molecular dynamics trajectories for 630 drug-membrane potentials of mean force"</p> <p>Hoffmann, Christian; Centi, Alessia; Menichetti, Roberto; Bereau, Tristan (2020): Molecular dynamics trajectories for 630 drug-membrane potentials of mean force. figshare. Collection.</p> <p>https://doi.org/10.6084/m9.figshare.c.4641551.v1</p> <p>Includes:</p> <ul> <li>'bsResult.xvg' of DIM_P2-P3 in DLPC</li> </ul>
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.