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464 results for “Kinematics”
astroneb/WR_PN_Kinematic_Models: WR-PN-Kinematic-Models.1.3
<p><strong>Morpho-kinematic properties of Wolf-Rayet planetary nebulae. Supplementary Data</strong></p> <p><strong><a href="https://astroneb.github.io/WR_PN_Kinematic_Models/figure5/">Figure 5</a>.</strong> The interactive figure of the morpho-kinematic mesh models of the PNe M 3-30, Hb 4, IC 1297, Th 2-A, Pe 1-1, M 1-32, M 3-15, M 1-25, Hen 2-142, K 2-16, MGC 6578, M 2-42, NGC 6567 and NGC 6629.</p> <p><strong>Citation</strong></p> <pre><code class="language-bash">@article{Danehkar2021, author = {{Danehkar}, A.}, title = {Morpho-kinematic properties of Wolf-Rayet planetary nebulae}, journal = {ApJS}, volume = {260}, number = {1}, pages = {14}, year = {2022}, doi = {10.3847/1538-4365/ac5cca} }</code></pre> <p><strong>Learn More</strong></p> <p>GitPage: <a href="https://astroneb.github.io/WR_PN_Kinematic_Models/">https://astroneb.github.io/WR_PN_Kinematic_Models/</a></p>
LAMOST–Gaia–Kepler Stellar Kinematic catalog
<p>In the second part of the Planets Across the Space and Time (PAST) series, by combining the data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR4 and Gaia DR2 and then applying the revised kinematic methods from PAST I, we present a catalog of kinematic properties (i.e., Galactic positions, velocities, and the relative membership probabilities among the thin disk, thick disk, Hercules stream, and the halo) as well as other basic stellar parameters for 35,835 Kepler stars.</p> <p>The new version combing LAMOST DR8 and Gaia eDR3 will be released soon.</p>
Kinematic catalog of 2,174 planet host stars from Planet across space and time (PAST). I
<p>We present a catalog of kinematic properties (i.e., Galactic positions, velocities, and the relative membership probabilities among the thin disk, thick disk, Hercules stream, and the halo) as well as other basic stellar parameters (e.g., effective temperature, metallicity) for 2174 host stars of 2872 planets by combining data from Gaia DR2, LAMOST DR4, APOGEE DR16, RAVE DR5, and the NASA exoplanet archive by applying the revised kinematic methods from Planet across space and time (PAST). I.</p> <p>we will continue to update our catalogue with the release of new data in the future.</p> <p> </p>
Linear Kinematic Feature detected and tracked in sea-ice deformation simulationed by all models participating in the Sea Ice Rheology Experiment and from RGPS
<p>Linear Kinematic Features (LKFs) detected and tracked in sea-ice deformation fields simulated by sea-ice models participating in the Sea Ice Rheology Experiment (SIREx), a model intercomparison project of the Forum of Arctic Modeling and Observational Synthesis (FAMOS). These data are the basis of the feature-based evaluation of sea-ice deformation in Hutter et al., Sea Ice Rheology Experiment (SIREx), Part II: Evaluating linear kinematic features in high-resolution sea-ice simulations, Journal of Geophysical Research: Oceans (2022). This paper also provides further details on the parameters of the LKF extraction.</p> <p>The LKF data sets in this archive are stored in a csv-files for each year (1997 and/or 2008), which use semi-colons as delimiters. Each row corresponds to a pixel that was identified as LKF and the following information for this pixels is stored: Start Year, Start Month, Start Day, End Year, End Month, End Day, LKF No., Parent LKF No., lon, lat, ind_x, ind_y, divergence rate, shear rate. All pixels belonging to the same LKF have the same LKF number. Tracked LKFs are linked by the parent LKF number, where "0" denotes LKFs that newly formed. Detailed information on all variables is provided in the additional notes.</p>
Studying kinematic linkage of finger joints: Experiment data
<p>Experimental data from <em>"<a href="https://doi.org/10.7717/peerj.14051">Studying kinematic linkage of finger joints: estimation of kinematics of distal interphalangeal joints during manipulation</a>", </em>available at PeerJ.</p> <p>Experiment data containing both hands joint angles of 9 subjects while performing 20 activities of daily living (ADLs) and free motion tasks.</p> <ul> <li>ADL_M.xlsx: Jont angles during manipulation phase of ADLs.</li> <li>ADL_R.xlsx: Jont angles during reaching and release phases of ADLs.</li> <li>FMT1-FMT2.xlsx: Joint angles during free motion tasks.</li> <li>LATERALITY.txt: Laterality of participants.</li> </ul> <p>Jont angles and sign criteria considered as in <a href="http://doi.org/10.1038/s41597-019-0175-6">Human hand kinematic data during feeding and cooking tasks</a></p> <p> </p>
Problems Using Data Gloves with Strain Gauges to Measure Distal Interphalangeal Joints' Kinematics (Experimental data)
<p>Experimental data from <em>"Problems Using Data Gloves with Strain Gauges to Measure Distal Interphalangeal Joints’ Kinematics", </em>available in Sensors.</p> <p> </p> <p><strong>"PHASE I - STATIC POSTURES, FREE MOTION AND GRASPING TASKS.xlsx" </strong> contains raw data of CyberGlove data glove of 22DoF while performing experiments detailed in Phase I.</p> <p>Jonts labelled as in <a href="https://www.nature.com/articles/s41597-019-0175-6">Human hand kinematic data during feeding and cooking tasks</a>. </p> <p>Task order detailed in "PHASE I TASK ORDER.txt".</p> <p>Subjects' hand length detailed in "PHASE I SUBJECT DATA.txt".</p> <p> </p> <p><strong>"PHASE II - SOLLERMAN HAND FUNCTION TEST.xlsx" </strong> contains joint angles recorded using CyberGlove data glove of 22DoF while performing experiments detailed in Phase II.</p> <p>Jont angles and sign criteria considered as in <a href="https://www.nature.com/articles/s41597-019-0175-6">Human hand kinematic data during feeding and cooking tasks</a>.</p> <p>Subjects' hand length and laterality detailed in "PHASE II SUBJECT DATA.txt".</p> <p> </p> <p>For further information please contact authors (rodaa@uji.es).</p>
Supplementary files: A Comparative Study of Active Rock Glaciers Mapped from Geomorphic- and Kinematic-Based Approaches in Daxue Shan, Southeast Tibetan Plateau
<p>Supplement of "A Comparative Study of Active Rock Glaciers Mapped from Geomorphic- and Kinematic-Based Approaches in Daxue Shan, Southeast Tibetan Plateau". The supplementary files provide the outlines and parameters of the rock glaciers inventoried by InSAR-assist kinematic-based approach in the Daxue Shan, Southeast Tibet Plateau. </p> <p>Based on the Sentinel-1A ascending SAR images acquired between 2015 and 2019, we derived a five-year-long LOS mean velocity map of the study area. We then compiled a rock glacier inventory by synergistically interpreting the InSAR-derived surface displacements and geomorphic features based on Google Earth images.</p>
Interception of virtual throws reveals predictive skills based on the visual processing of throwing kinematics - Dataset
<p>Dataset consists of a list of Matlab structures, one for each of the 21 participants. For each participant all the recorded trials are reported ("trials" field). For each trial, the dataset reports information about the associated experimental condition and the kinematics of the ball and the racket trajectories. Information about the experimental condition are specified in the "info" field, which provides the experimental phase (Training and Experimental), the visibility (AllVisible, ThrowerOnly, BallOnly), the target (1, 2, 3, 4), and the thrower ID (1, 2, 3, 4). The kinematics data, starting from the time of ball release, are given in the field "trajectories", which provides the time vector (in seconds), and the corresponding 3D positions of the racket and the ball (in meters) in the reference frame shown in Figure 1 of the paper.</p>
Synchronously recorded gait kinematic data with Inertial Measurement Units and a photogrammetry system for a validation assessment
<h3>Description</h3> <p>A gait database of 32 healthy adult subjects was built , volunteers were between 20 and 63 y.o. (33.64 ± 12.44) and 71.88% were females. Every individual underwent a barefoot walking test recorded simultaneously with Inertial Measurement Units (IMUs) and the photogrammetry system Vicon. The dataset contains the kinematic gait information of the hip, knee, and ankle joints in the three planes of motion: sagittal, frontal, and transversal. </p> <p>The signals recorded by the IMUs are referred to as I(t) and were captured with a sampling frequency of 50 Hz, and those recorded by the photogrammetry system are called V(t) and were captured with a sampling frequency of 100 Hz. To perform a comparative study of both systems, the V(t) signals must be resampled to 50 Hz. Then, the delay between the two signals must be corrected to align them. Finally, gait cycles can be extracted for each pair of trials following the data information provided, obtaining a pair of waveforms for each gait cycle [I(t), V(t)]. A total of 268 synchronous gait cycles [I(t), V(t)] can be recovered and analyzed in the three planes of motion per limb.</p> <h3>Data information</h3> <ul> <li><em>raw_data</em>: folder containing the 32 subjects raw kinematic signals recorded with IMUs (sampling frequency 50 Hz) and photogrammetry system (sampling frequency 100 Hz) synchronously.<br> <ul> <li>For IMUs records: <ul> <li>Z: sagittal plane.</li> <li>X: frontal plane.</li> <li>Y: transversal plane.</li> </ul> </li> <li>For photogrammetry system records: <ul> <li>X: sagittal plane.</li> <li>Y: frontal plane.</li> <li>Z: transversal plane.</li> </ul> </li> </ul> </li> </ul> <ul> <li><em>captures_information.xlsx</em>: table containing the delay correction and the samples corresponding to the events of the gait cycles. The delay correction is the number of samples for which each photogrammetry signal V(t), after being resampled to 50 Hz, must be moved to be completely aligned with its synchronous IMUs signal couple I(t). <ul> <li>If the delay is positive (+) the V(t) signal must be delayed by adding zeros at the beginning.</li> <li>If the delay is negative (-) the V(t) signal must be moved forward by removing zeros at the beginning.</li> </ul> </li> </ul>
Analysis code and data for the morphometrics and kinematics of tube feet
<p>Hydrostatic skeletons, such as an elephant trunk or a squid tentacle, permit the transmission of mechanical work through a soft body. Despite the ubiquity of these structures among animals, we generally do not understand how differences in their morphology affect their mechanical properties. Therefore, the present study used mathematical modeling, morphometrics, and kinematics to understand the transmission of force and displacement in the tube feet of the juvenile six-rayed star <em>Leptasterias</em> <em>sp.</em> An inverse-dynamic analysis revealed that the forces generated by the feet during crawling primarily serve to overcome the submerged weight of the body. This load was disproportionately generated by the feet at more proximal positions along each ray, which were used more frequently for crawling. Due to a combination of mechanical advantage and muscle mass, these proximal feet exhibited a greater capacity for force generation than the distal feet. However, the higher displacement advantage of the more elongated distal feet offer a superior ability to extend the feet into the environment. Therefore, the morphology of tube feet demonstrates a gradient in gearing along each ray that matches their role in behavior.</p>
Fig. 1 Landmarks used for the kinematic analyses. 1 upper jaw tip, 2 lower jaw tip, 3 in Flexibility is everything: prey capture throughout the seasonal habitat switches in the smooth newt Lissotriton vulgaris
Fig. 1 Landmarks used for the kinematic analyses. 1 upper jaw tip, 2 lower jaw tip, 3 hyoid (throat), 4 jaw joint, 5 nape, 6 dorsal trunk reference, 7 tongue tip (only digitized when visible)
Figure 2. (a) Representation of laser servo-driver for inverse kinematics analysis; (b) Representation of the lag angle, B, of the internal servomechanism (magnified version of the chin-rest).-Design of a Novel Servo-motorized Laser Device for Visual Pathways Diseases Therapy
<p>As the servo-driver will be attached in the chin-rest in a non-central area with respect to the<br> semispherical structure shown in Figure 1(a), it is necessary to calculate a lag angle, according to<br> the measurements from the chin-rest, see Figure 2(b). This was done using a hybrid formula based<br> on the law of cosines,</p>
DataSet from H. Merienne et al., "Walking kinematics in the polymorphic seed harvester ant Messor barbarus: influence of ant size and load carriage"
<p>DataSet from H. Merienne et al., “Walking kinematics in the polymorphic seed harvester ant Messor barbarus: influence of ant size and load carriage”</p>
A calibrated database of kinematics and EMG of the forearm and hand during activities of daily living
<p>KIN-MUS UJI Dataset contains 572 recordings with anatomical angles and forearm muscle activity of 22 subjects while performing 26 representative activities of daily living. This dataset is, to our knowledge, the biggest currently available hand kinematics and muscle activity dataset to focus on goal-oriented actions. Data were recorded using a CyberGlove instrumented glove and surface EMG electrodes, both properly synchronised. Eighteen hand anatomical angles were obtained from the glove sensors by a validated calibration procedure. Surface EMG activity was recorded from seven representative forearm areas. The statistics verified that data were not affected by the experimental procedures and were similar to the data acquired under real-life conditions.</p> <p> </p> <p><strong>Data Sets</strong>:</p> <p>Data are presented as a Matlab data structure (<em>.mat</em> file). This structure contains all the recorded kinematic and muscle activity data classified as: ADL, phase (reaching, manipulation or release) and subject. The fields contained in the structure are those detailed in the following scheme:</p> <ul> <li>Subject: subject ID;</li> <li>ADL: ADL ID;</li> <li>Phase: phase of movement. 1 corresponds to reaching; 2 corresponds to manipulation; 3 corresponds to releasing.</li> <li>Time: Time stamp</li> <li>Angles (18 columns): Calibrated anatomical angles</li> <li>Muscle activity (7 columns): Normalised signal for the seven representative spot areas, according to [1].</li> </ul> <p>RAW_EMG struct provides the raw sEMG data, without any filter and not resampled, so that researchers may choose to condition the signals as they please<strong>.</strong> The fields contained in this structure are those detailed in the following scheme:</p> <ul> <li>Subject: subject ID;</li> <li>ADL: ADL ID, according to Table 1;</li> <li>Time: Time stamp; this field corresponds with the time stamp of the previous structure.</li> <li>Raw EMG data (7 columns): Raw sEMG data without any filter and not resampled, for the seven representative spot areas according to [1].</li> </ul> <p>[1] Jarque-Bou, N. J., Vergara, M., Sancho-Bru, J. L., Alba, R.-S. & Gracia-Ibáñez, V. Identification of forearm skin zones with similar muscle activation patterns during activities of daily living. <em>J. NeuroEngineering Rehabil. </em>(2018).</p>
Kinematic and Paleoseismic Investigation of an Upper-Plate Fault on Chirikof Island: A Potential Tsunami-Seismic Hazard Source within the Alaska Subduction Zone
Open the record for dataset details and reuse information.
Distinct population code for movement kinematics and changes of ongoing movements in human subthalamic nucleus
<p>The subthalamic nucleus (STN) is theorized to globally suppress movement through connections with downstream basal ganglia structures. Current theories are supported by increased STN activity when subjects withhold an uninitiated action plan, but a critical test of these theories requires studying STN responses when an ongoing action is replaced with an alternative. We perform this test in subjects with Parkinson's disease using an extended reaching task where the movement trajectory changes mid-action. We show that STN activity decreases during action switches, contrary to prevalent theories. Further, beta oscillations in the STN local field potential, which are associated with movement inhibition, do not show increased power or spiking entrainment during switches. We report an inhomogeneous population neural code in STN, with one sub-population encoding movement kinematics and direction and another encoding unexpected action switches. We suggest an elaborate neural code in STN that contributes to planning actions and changing the plans.</p>
Reproduction Package for the paper "The early evolution of young massive clusters. The kinematic history of NGC6611 / M16"
<p>This is a comprehensive reproduction package for the paper "The early evolution of young massive clusters. The kinematic history of NGC6611 / M16" by <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220708452S/abstract">Stoop et al. (2022)</a>.</p> <p>This reproduction package aims for open science, with the internal API designation of 'Gold'.</p> <p>This package aims to provide the raw data, and the software and scripts to produce the intermediate and end products. Software and scripts are also available to produce the figures and tables in the paper.</p> <p> </p>
Spatially resolved mock observations of stellar kinematics: full radiative transfer treatment of the simulated galaxies of the Auriga project
<p>We present realistic mock spectroscopic observations for state-of-the-art hydrodynamical simulations, using high spectral resolution stellar population models (FSPS) and full radiative transfer treatment with SKIRT. The dataset contains IFS-like spectroscopy of the stellar continuum for 10 (of the 30) galaxies in the Auriga Project at z=0. One galaxy at z=0.8 (Au 6) and another at z=3 (Au 29).</p>
Evaluating a Kinematic Data Glove with Pressure Sensors to Automatically Differentiate Free Motion from Product Manipulation (Experimental Data)
<p>Experimental data from <em>"Evaluating a kinematic data glove with pressure sensors to automatically differentiate free motion from product manipulation", </em>available at Applied Sciences.</p> <p>"DATA.zip" contains raw data collected using VMG30 and CyberGlove data gloves, in txt format. </p> <p>For further information please see the details in the manuscript or contact the corresponding author Alba Roda-Sales (rodaa@uji.es).</p>
Three-dimensional mandibular kinematics of mastication in the marsupial Didelphis virginiana
<p><span><em>Didelphis virginiana</em> </span>(the Virginia opossum) is often used as an extant model for understanding feeding behavior in Mesozoic mammaliaforms, primarily due to their morphological similarities, including an unfused mandibular symphysis and tribosphenic molars. However, the 3D jaw kinematics of opossum chewing have not yet been fully quantified. We used biplanar videofluoroscopy and the X-Ray Reconstruction of Moving Morphology workflow to quantify mandibular kinematics in four wild-caught opossums feeding on hard (almonds) and soft (cheese cubes) foods. These data were used to test hypotheses regarding the importance of roll versus yaw in chewing by early mammals, and the impact of food material properties (FMPs) on jaw kinematics. The magnitude of roll exceeds that of yaw, but both are necessary for tooth-tooth or tooth-food-tooth contact between complex occlusal surfaces. We confirmed the utility of the four vertical kinematic gape cycle phases identified in tetrapods but we further defined two more in order to capture non-vertical kinematics. Statistical tests support the separation of chew cycle phases into two functional groups: occlusal and non-occlusal phases. The separation of slow close into two (occlusal) phases gives quantitative kinematic support for the long-hypothesized multifunctionality of the tribosphenic molar.</p>
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Allen Brain Atlas
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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.
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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.
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