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1,548 results for “Trajectories”
Choline acetyltransferase (ChAT) - Amyloid beta peptides complex Molecular dynamics Trajectories
<p>In silico molecular dynamics study was performed for the choline acetyltransferase (ChAT) - Abeta peptides complex. The molecular docking of Aβ<sub>40 </sub>and Aβ<sub>42</sub> on ChAT suggested three most probable binding clusters for both the Aβ peptides. Thus generating ChAT-Aβ<sub>40</sub> Cluster-0, ChAT-Aβ<sub>40</sub> Cluster-1, ChAT-Aβ<sub>40</sub> Cluster-2 for Aβ<sub>40</sub> peptide on ChAT, likewise ChAT-Aβ<sub>42</sub> Cluster-0, ChAT-Aβ<sub>42</sub> Cluster-1, ChAT-Aβ<sub>42</sub> Cluster-2 were generated for Aβ<sub>42</sub> peptide on ChAT.</p> <p>Each of the folders contains the topology file with a ‘.gro’ extension and a trajectory file with ‘.xtc’ extension generated from the 100 ns molecular dynamics performed for each of the clusters mentioned above that were generated from the molecular docking. The folders are named as follows:</p> <ol> <li>ChAT_AB40_Cluster_0: Containing the topology file (ab40_0.gro) and the trajectory file (ab40_0.xtc)</li> <li>ChAT_AB40_Cluster_1: Containing the topology file (ab40_1.gro) and the trajectory file (ab40_1.xtc)</li> <li>ChAT_AB40_Cluster_2: Containing the topology file (ab40_2.gro) and the trajectory file (ab40_2.xtc)</li> <li>ChAT_AB42_Cluster_0: Containing the topology file (ab42_0.gro) and the trajectory file (ab42_0.xtc)</li> <li>ChAT_AB42_Cluster_1: Containing the topology file (ab42_1.gro) and the trajectory file (ab42_1.xtc)</li> <li>ChAT_AB42_Cluster_2: Containing the topology file (ab42_2.gro) and the trajectory file (ab42_2.xtc</li> </ol>
Adolescents' mental health and maladaptive behaviors before the Covid-19 pandemic and one-year after: analysis of trajectories over time and associated factors
<p>The database reports data about psychopathological indexes in a sample of adolescent students (N=153) assessed before Covid-19 pandemic (T0, November 2019-January 2020) and one year after (T1, April-May 2021).</p>
Video-Trajectory Robot Dataset
<p>This dataset consists of color and depth videos of Panda robot motions and their corresponding joint and Cartesian trajectories. The dataset also includes the trajectories of a receiver robot for the purpose of an object handover. Each motion sample comprises 6 files (RGB video, depth video and 4 giver/receiver trajectories in time series form). Total number of motion samples: 38393.</p> <p>Structure: MPEG-4 videos of robot motion and corresponding Python serialized (or “pickled”) files, containing joint and Cartesian trajectories. Dataset is divided into four parts: simulation dataset (PandaHandover_Sim.zip), real train dataset (PandaHandover_Real_Train.zip), real validation dataset (PandaHandover_Real_Val.zip), real test dataset (PandaHandover_Real_Test.zip). Extract using 7-Zip or similar software. Video files (.avi) can be opened using VLC media player or any other video player that supports MPEG-4 codec. The .pkl files can be loaded using Python (>=3.7) and the Python library Pandas (>=1.1.3).</p>
Video-Trajectory Hand Dataset
<p>This dataset consists of color and depth videos of human worker motions and their corresponding Cartesian trajectories of the worker’s hand, captured using OptiTrack motion capture system. Each motion sample comprises 4 files (RGB video, depth video, a Cartesian trajectory of worker’s hand and a label of the motion, representing one of four possible goals from 1 to 4). Total number of motion samples: 811.</p> <p>Structure: MPEG-4 videos of human worker motion and corresponding NumPy array files, containing Cartesian trajectories and a label of the motion. Dataset is in a .zip archive. Extract using 7-Zip or similar software. Video files (.avi) can be opened using VLC media player or any other video player that supports MPEG-4 codec. The .npy files can be loaded using Python (>=3.7) and the Python library NumPy (>=1.19.2).</p>
Molecular dynamics trajectories of protein folding
<p>Molecular dynamics trajectories of protein folding are deposited for educational purposes.</p> <p>Currently, the following trajectories are available:</p> <ul> <li>Chignolin (five independent NVT simulations up to 1.5 micro-sec): <ul> <li>`movie.pse` is a PyMOL session file of MD trajectories. </li> <li>`movie.mp4` is a movie file that shows you how a protein folds during simulation.</li> <li>xtc files (Gromacs compressed format) and corresponding tpr files.</li> <li>gro files for movie making</li> </ul> </li> </ul> <p> </p> <p>Computational setting </p> <ul> <li>Amber ff99SB-ILDN for protein (Lindorff-Larsen, K. <em>et al.</em> Improved side-chain torsion potentials for the Amber ff99SB protein force field. <em>Proteins</em> <strong>78</strong>, 1950–1958 (2010))</li> <li>TIP3P water model</li> <li>0.1 M salt concentration </li> <li>NVT ensemble at 300 K with V-rescale thermostat (Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. <em>J. Chem. Phys.</em> <strong>126</strong>, 014101 (2007))</li> <li>Time step : 2 fs</li> <li>gromacs-2020.6</li> </ul>
The I-24 Trajectory Dataset
<p>This dataset was created by recording CAN and GPS data from a single vehicle driving on I-24. The dataset includes values for Time, Velocity, Acceleration, Space Gap, Lateral Distance, Relative Velocity, Longitude GPS, Latitude GPS, Score, TrackID, L_Approach, R_Approach, L_Adjacent, and R_Adjacent. Data are preprocessed for your convenience into individual westbound or eastbound trajectories with mile markers and other relevant data fields added, in the labeled directories.</p> <p> </p> <p>Nice, Matthew and Lichtle, Nathan and Gumm, Gracie and Roman, Michael and Vinitsky, Eugene and Elmadani, Safwan and Bunting, Matt and Bhadani, Rahul and Gunter, George and Kumar, Maya and McQuade, Sean and Denaro, Chris and Delorenzo, Ryan and Piccoli, Benedetto and Work, Dan and Bayen, Alex and Lee, Jonny and Sprinkle, Jonathan and Seibold, Benjamin</p>
Magellanic penguin's onland trajectory data
<p><span>Understanding how animals move in dense environments where vision is compromised is a major challenge. We used GPS and dead-reckoning to examine the movement of Magellanic penguins commuting through vegetation that precluded long-distance vision. Birds leaving the nest followed the shortest, quickest route to the sea (the 'ideal path' [<em>I-path</em>]) but return tracks depended where the birds left the water. Penguins arriving at the beach departure spot mirrored the departure. Most of those landing at a distance from the departure spot travelled slowly, obliquely to the coast at a more acute angle than a beeline trajectory to the nest. On crossing their<em> I-path</em>, these birds then followed this route quickly to their nests. This movement strategy saves birds distance, time and energy compared to a route along the beach and the into the colony on the <em>I-track</em> and saves time and energy compared to a beeline trajectory which necessitates slow travel in unfamiliar areas. This suggests that some animals adopt tactics that take them to an area where their navigational capacities are enhanced for efficient travel in challenging environments.</span></p>
Data from: Kinematic trajectories in response to speed perturbations in walking suggest modular task-level control of leg angle and length
Abstract Navigating complex terrains requires dynamic interactions between the substrate, musculoskeletal and sensorimotor systems. Current perturbation studies have mostly used visible terrain height perturbations, which do not allow us to distinguish among the neuromechanical contributions of feedforward control, feedback-mediated and mechanical perturbation responses. Here, we use treadmill belt speed perturbations to induce a targeted perturbation to foot speed only, and without terrain-induced changes in joint posture and leg loading at stance onset. Based on previous studies suggesting a proximo-distal gradient in neuromechanical control, we hypothesized that distal joints would exhibit larger changes in joint kinematics, compared to proximal joints. Additionally, we expected birds to use feedforward strategies to increase the intrinsic stability of gait. To test these hypotheses, seven adult guinea fowl were video recorded while walking on a motorized treadmill, during both steady and perturbed trials. Perturbations consisted of repeated exposures to a deceleration and acceleration of the treadmill belt speed. Surprisingly, we found that joint angular trajectories and center of mass fluctuations remain very similar, despite substantial perturbation of foot velocity by the treadmill belt. Hip joint angular trajectories exhibit the largest changes, with the birds adopting a slightly more flexed position across all perturbed strides. Additionally, we observed increased stride duration across all strides, consistent with feedforward changes in the control strategy. The speed perturbations mainly influenced the timing of stance and swing, with the largest kinematic changes in the strides directly following a deceleration. Our findings do not support the general hypothesis of a proximo-distal gradient in joint control, as distal joint kinematics remain largely unchanged. Instead, we find that leg angular trajectory and the timing of stance and swing are most sensitive to this specific perturbation, and leg length actuation remains largely unchanged. Our results are consistent with modular task-level control of leg length and leg angle actuation, with different neuromechanical control and perturbation sensitivity in each actuation mode. Distal joints appear to be sensitive to changes in vertical loading but not foot fore-aft velocity. Future directions should include in vivo studies of muscle activation and force-length dynamics to provide more direct evidence of the sensorimotor control strategies for stability in response to belt speed perturbations.
Postprocessed trajectory output for ice cloud microphysics - ICON and CLaMS-Ice models
<p>Postprocessed output from a trajectory module implemented in ICON v 2.3.0. The trajectories track density, temperature, pressure, specific humidity, cloud ice mass and number mixing ratios, cloud liquid mass and number mixing ratios, graupel mass and number mixing ratios, and ice sedimentation mass and number mixing ratios both into and out of the parcel. They are initiated over the Sichuan basin and allowed to flow for 51 hours westward during which the cross India into the Arabian Sea. This trajectory output is also used to run an offline microphysics box model, CLaMS-Ice. qih-Nih* files contain histograms of ice mass mixing ratio (qi) and ice crystal number concentration (Ni); het-hom-pre* files contain process tendencies from heterogeneous nucleation, homogeneous nucleation, and preexisting ice in CLaMS-Ice; qippmvNi-TRHi* files contain qi and Ni versus a range of cirrus temperatures and a range of supersaturations with respect to ice; qi_ppmv_abs* and Ni_abs* files contain probability distributions of qi and Ni differences over absolute time; and qi_ppmv_norm* and Ni_norm* files contain probability distributions of qi and Ni differences over normalized time. Suffixes in all cases indicate the cloud microphysical setup that the trajectory values were used to run with 1M = one-moment scheme, 2M = two-moment scheme, Tf = temperature fluctuation parameterization in CLaMS-Ice simulations, and noSHflux = no pseudo-mixing tendency included in CLaMS-Ice simulations.</p>
A simple method to describe the COVID-19 trajectory and dynamics in any country based on Johnson cumulative density function fitting
<p></p><p>A simple method is utilised to study and compare COVID-19 infection dynamics between countries based on curve fitting to publicly shared data of confirmed COVID-19 infections. The method was tested using data from 80 countries from 6 continents. We found that Johnson cumulative density functions (CDFs) were extremely well fitted to the data (R<sup>2</sup> > 0.99) and that Johnson CDFs were much better fitted to the tails of the data than either the commonly used normal or lognormal CDFs. Fitted Johnson CDFs can be used to obtain basic parameters of the infection wave, such as the percentage of the population infected during an infection wave, the days of the start, peak and end of the infection wave, and the duration of the wave's increase and decrease. These parameters can be easily interpreted biologically and used both for describing infection wave dynamics and in further statistical analysis. The usefulness of the parameters obtained was analysed with respect to the relation between the gross domestic product (GDP) per capita, the population density, the percentage of the population infected during an infection wave, the starting day and the duration of the infection wave in the 80 countries. We found that all the above parameters were significantly associated with GDP per capita, but only the percentage of the population infected was significantly associated with population density. If used with caution, this method has a limited ability to predict the future trajectory and parameters of an ongoing infection wave.</p><p></p>
Tests showing the projectile flight trajectory of 5, 7 and 8mm diameter steel spheres attached to either a detonator or a rear detonated C4 spherical explosive charge.
<p>These videos are the results of an experimental campaign carried out in the department of Propellant, Explosives and Blast Engineering of the Royal Military Academy in Brussels to study the flight trajectory of a projectile (steel sphere (5 or 7 or 8mm diameter)) attached to either a detonator or a rear detonated C4 spherical explosive charge. The projectile is accelerated by the blast wave generated by the explosive. The projectile initial trajectory is hidden by the flash of the detonation. After its passage through the opaque gas cloud, the first appearance of the projectile is captured and an almost straight trajectory can be tracked until the end of the field of view of the high speed camera. The test campaign reveals the capability of the projectiles to maintain an oriented path until impact on a target placed at 910mm stand of distance from the center of the explosion. </p>
Viral Communication: Trajectories of Experience through the Pandemic - A Qualitative Longitudinal Dataset
<p>Here, we present a dataset collected within a longitudinal interview study that has been conducted as part of a larger project (i.e., Viral Communication), exploring (changing) public attitudes and behaviours through the course of the pandemic in Germany. From a nationally representative survey, forty participants were purposively sampled on the basis of gender, age and socioeconomic status for the interviews. Each participant was interviewed three times within a 10 month time frame (between December 2020 and September 2021), with the exception of two dropouts from the study. The semi-structured interviews were developed to further elaborate on some of the responses in the survey instrument and to provide additional insights into topics and controversies surrounding the Covid-19 pandemic in Germany, such as information/misinformation, trust/distrust, compliance, vaccination, and conspiracy beliefs. </p> <ul> <li>Interviews Phase I (December 2020): 40 Interviews</li> <li>Interviews Phase II (April 2021): 38 Interviews</li> <li>Interviews Phase III (September 2021): 38 Interviews</li> </ul>
MD simulation trajectory of DOG/POPE bilayer and related files
<p>Raw simulation trajectory data of pre-equiblirated DOG/POPE bilayer and related files from all-atom molecular dynamics simulations. Simulations have been performed with GROMACS-2018.6 with Lipid17 forcefield and TIP3P water model. The trajectory is 0-2100 ns, and we have disregarded the first 100 ns in our analysis.</p> <p>The system in the trajectory consists of 12 DOG, 116 POPE and 6400 water molecules. Temperature 310 K, pressure 1 bar.</p>
MD simulation trajectory of SDG/SDPE bilayer and related files
<p>Raw simulation trajectory data of pre-equiblirated SDG/SDPE bilayer and related files from all-atom molecular dynamics simulations. Simulations have been performed with GROMACS-2018.6 with Lipid17 force field and TIP3P water model. The trajectory is 0-2100 ns, and we have disregarded the first 100 ns in our analysis.</p> <p>The system in the trajectory consists of 12 SDG, 116 SDPE and 6400 water molecules. Temperature 310 K, pressure 1 bar.</p>
MD simulation trajectory of SDG/POPE bilayer and related files
<p>Raw simulation trajectory data of pre-equiblirated SDG/POPE bilayer and related files from all-atom molecular dynamics simulations. Simulations have been performed with GROMACS-2018.6 with Lipid17 forcefield and TIP3P water model. The trajectory is 0-2100 ns, and we have disregarded the first 100 ns in our analysis.</p> <p>The system in the trajectory consists of 12 SDG, 116 POPE and 6400 water molecules. Temperature 310 K, pressure 1 bar.</p>
Do Go Chasing Waterfalls: Enoyl Reductase (FabI) in Complex with Inhibitors Stabilizes the Tetrameric Structure and Opens Water Channels - full trajectories of SaFabI and EcFabI monomers and G112/113V mutants
<p>The following IDs are related to trajectories:</p> <p>v36 = EcFabI apo, monomer<br> v42 = EcFabI + TCL complex, monomer<br> v43 = EcFabI + MUT complex, monomer<br> v44 = EcFabI + AFN complex, monomer<br> v35 = SaFabI apo, monomer<br> v45 = SaFabI + TCL complex, monomer<br> v46 = SaFabI + MUT complex, monomer<br> v47 = SaFabI + AFN complex, monomer<br> v52 = G112V EcFabI apo, tetramer<br> v53 = G112V EcFabI apo, monomer<br> v54 = G113V SaFabI apo, tetramer<br> v55 = G113V SaFabI apo, monomer</p>
Do Go Chasing Waterfalls: Enoyl Reductase (FabI) in Complex with Inhibitors Stabilizes the Tetrameric Structure and Opens Water Channels - full trajectories of SaFabI and EcFabI tetramers
<p>The following IDs are related to trajectories:</p> <p>v1 = EcFabI apo, tetramer<br> v2 = EcFabI + TCL complex, tetramer<br> v3 = EcFabI + MUT complex, tetramer<br> v39 = EcFabI + AFN complex, tetramer<br> v16 = SaFabI apo, tetramer<br> v17 = SaFabI + TCL complex, tetramer<br> v18 = SaFabI + MUT complex, tetramer<br> v40 = SaFabI + AFN complex, tetramer</p>
Salamanders reveal novel trajectories of amphibian MHC evolution
<p><span>Genes of the Major Histocompatibility Complex (MHC) code for immune proteins that are crucial for pathogen recognition in vertebrates. MHC research in non-model taxa has long been hampered by its genomic complexity that makes the locus-specific genotyping challenging. The recent progress in sequencing and genotyping methodologies allows an extensive phylogenetic coverage in studies of MHC evolution. Here, we analysed the peptide-binding region of MHC class I in 30 species of salamanders from six families representative of Urodela phylogeny. This extensive dataset revealed an extreme diversity of MHC-I in salamanders, both in terms of sequence diversity (ca. 3000 variants) and architecture (2-22 gene copies per species). The signal of positive selection was moderate and consistent between both peptide binding domains, but varied greatly between genera. Positions of positively selected sites mostly coincided with human Peptide Binding Sites, suggesting similar structural properties of MHC-I molecules across distant vertebrate lineages. Finally, we provided evidence for the common intra-exonic recombination at MHC-I and for the role of life-history traits in the processes of MHC-I expansion/contraction. Our study revealed novel evolutionary trajectories of amphibian MHC and it contributes to the understanding of the mechanisms that generated extraordinary MHC diversity throughout vertebrate evolution.</span></p>
Ab initio molecular dynamics trajectories of liquid water at the interface with hBN sheets
<p>Ab initio molecular dynamics trajectories of water confined between hBN sheets for different confinement widths and system sizes.</p> <p>This repository contains data supporting the findings of the paper: </p> <p>G. Tocci, M. Bilichenko, L. Joly, M. Iannuzzi, <em>Ab initio</em> nanofluidics: disentangling the role of the energy landscape and of density correlations on liquid/solid friction, Nanoscale, 12, 10994-11000 (2020). DOI: 10.1039/D0NR02511A.</p>
Ab initio molecular dynamics trajectories of liquid water at the interface with graphene sheets
<p>Ab initio molecular dynamics trajectories of water in contact with graphene sheets for different confinement widths and system sizes</p> <p>This repository contains data supporting the findings of the paper: </p> <p>G. Tocci, M. Bilichenko, L. Joly, M. Iannuzzi, <em>Ab initio</em> nanofluidics: disentangling the role of the energy landscape and of density correlations on liquid/solid friction, Nanoscale, 12, 10994-11000 (2020). DOI: 10.1039/D0NR02511A.</p>
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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.