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68 results for “Trajectory modeling”
Global-scale modeling of early factors and country-specific trajectories of COVID-19 incidence: a cross-sectional study of the first 6 months of the pandemic
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A non-equilibrium species distribution model reveals unprecedented depth of time lag responses to past environmental change trajectories
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Data from: Moving like a model: mimicry of hymenopteran flight trajectories by clearwing moths of Southeast Asian rainforests
Clearwing moths are known for their physical resemblance to hymenopterans, but the extent of their behavioural mimicry is unknown. We describe zigzag flights of sesiid bee mimics which are nearly indistinguishable from those of sympatric bees, whereas sesiid wasp mimics display faster, straighter flights more akin to those of wasps. In particular, the flight of the sesiids Heterosphecia pahangensis, Aschistophleps argentifasciata and Pyrophleps cruentata resembles both Tetragonilla collina and T. atripes stingless bees and, to a lesser extent, dwarf honey bees Apis andreniformis, whereas the sesiid Pyrophleps sp. resembles Tachysphex sp. wasps. These findings represent the first experimental evidence for behavioural mimicry in clearwing moths.
MD simulation trajectory and related files for POPC bilayer with 340mM NaCl (Berger model delivered by Tieleman, ffgmx ions, Gromacs 4.5)
<p>Equilibrated POPC lipid bilayer simulation ran with Gromacs 4.5, Berger force field delivered by Peter Tieleman (http://wcm.ucalgary.ca/tieleman/downloads), double bonds updated in http://dx.doi.org/10.1021/jp065424f, ffgmx parameters for ions, 50ns, T=298K, 128 POPC molecules, 7202 water molecules, 44 Na molecules, 44 Cl molecules. This data is used in the NMRLipids II project (nmrlipids.blospot.fi).</p>
MD simulation trajectory and related files for POPC bilayer with 340mM CaCl_2 (Berger model delivered by Tieleman, ffgmx ions, Gromacs 4.5)
<p>Equilibrated POPC lipid bilayer simulation ran with Gromacs 4.5, Berger force field delivered by Peter Tieleman (http://wcm.ucalgary.ca/tieleman/downloads) double bonds updated in http://dx.doi.org/10.1021/jp065424f, ffgmx parameters for ions, 50ns, T=298K, 128 POPC molecules, 7157 water molecules, 44 Na molecules, 88 Cl molecules. This data is used in the NMRLipids II project (nmrlipids.blospot.fi).</p>
Parcels-WAOM model data: Lagrangian particle trajectories
<p>This data set includes the results of Lagrangian particle tracking experiments with Parsels in Weddell and Ross seas. </p> <p>The following information for each particle is stored once a day: longitude (lon in files), latitude (lat), time (time), depth (z), temperature (temp), salinity (sal), ice draft (ice).</p> <p>Each *.zip archive contains one experiment in netcdf file for one of the seas (Weddell or Ross seas) and for one of four seasons during 20 years of simulations. </p>
UAS Trajectory Model Dynamics at different flight heights: An In-depth Analysis of PPK Georeferencing Results for an Urban Area
<p>In-depth analysis of the PPK georeferencing results when using three different Continuously Operating Reference Station (CORS) stations and one local base station.</p>
Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model - Data
<p>This repository contains the data and additional information for the paper 'Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model'. </p> <p>The following files are included:</p> <ul> <li>accuracy.zip: raw performance files for all models;</li> <li>plots.zip: additional plots;</li> <li>tuning.zip: tuning log files.</li> </ul>
Model Comparison Benchmark Datasets, Results, and Peptide MD Trajectory
<p>Contents of this database include:</p> <ul> <li>aib9.out.zip: zipped file containing raw output of the Aib9 OpenMM MD simulation</li> <li>aib9_openmm.zip: zipped folder containing all input files for the Aib9 OpenMM MD simulation, as well as the generated trajectory</li> <li>data_input.zip: zipped folder containing input datasets for the GMM and Aib9 numerical experiments</li> <li>data_output.zip: zipped folder containing output data and experimental results for three generative models (NS, CFM, DDPM) on the input datasets, included for posterity (file names do not synchronize with most recent repository naming conventions)</li> </ul> <p>The files are automatically retrieved and unzipped via the data_accessor notebook in the GitHub repository.</p> <p> </p>
Matlab files for: Mathematical Modelling of Polymer Trajectory during Electrospinning
<p>Matlab files used within this publication to be able to replicate the results.</p>
Particle trajectories generated by the eDNA fate and transport model for the Atlantic bottlenose dolphin (Tursiops truncatus) -- Part I
<ul> <li>"release" includes particle trajectories generated by the eDNA fate and transport model, which was driven by the hydrodynamics simulated with the realistic wind and tidal forcings.</li> <li>The python codes used to read the particle trajectories and get the particle counts in each model grid cell can be found in https://github.com/Jilian0717/eDNA_fate_transport_model/tree/main/particle_density</li> </ul>
Particle trajectories generated by the eDNA fate and transport model for the Atlantic bottlenose dolphin (Tursiops truncatus) -- Part II
<ul> <li>"release_no_wind" includes particle trajectories generated by the eDNA fate and transport model, which was driven by the hydrodynamics simulated without wind forcing. The purpose is to diagnose the influence of wind on particle distributions.</li> <li>The python codes used to read the particle trajectories and get the particle counts in each model grid cell can be found in https://github.com/Jilian0717/eDNA_fate_transport_model/tree/main/particle_density</li> </ul>
Air parcel trajectories data generated by MIMICA code and simulation results generated by a trajectory box model
<p>The dataset includes trajectories of air parcels extracted from the large-eddy (cloud-resolving model) simulations of the deep convective clouds from the Amazon based on the soundings retrieved on April 8, 2020, April 23, 2020, and April 27, 2020, over Manaus, Brazil, as well as the results of the chemical box model simulations quantifying the transport of some atmospheric trace gases abundant in the Amazon.</p>
Model 4 dataset for the manuscript "Improving trajectory calculations by FLEXPART 10.4+ using deep learning inspired single image superresolution"
<p>Model 4 dataset for the manuscript "Improving trajectory calculations by FLEXPART 10.4+ using deep learning inspired single image superresolution"</p>
Model 2 dataset for the manuscript "Improving trajectory calculations by FLEXPART 10.4+ using deep learning inspired single image superresolution"
<p>Dataset produced by the model 2 neural network for the manuscript "Improving trajectory calculations by FLEXPART 10.4+ using deep learning inspired single image superresolution"</p>
Air parcel trajectories dataset based on modeling of 16 deep convective clouds in the Amazon.
<p>The dataset contains trajectories of 16 deep convective cloud air parcels simulated with MIMICA code based on soundings retrieved over Manaus (Latitude: -3.1, Longitude: -60.0) during the wet season from April 1 until April 14, 2020 at 00 and 12 UTC.</p> <p> </p> <p>Parcel data contains values for coordinate (X, Y, Z), velocity components (U, V, W), potential temperature (PTIL), total water content (QT), water vapor (QV), condensate density (QC), precipitation density (QR), net precipitation change (QR_FLUX), relative humidity (RH), buoyancy (BUOY), temperature (T), pressure (P), resolved TKE (KRES), SGS TKE (SGS_TKE), turbulent diffusion (TDIFF) are provided for each parcel at every time step of the simulation.</p>
Mixed model-based deconvolution of cell-state abundances along a one-dimensional trajectory [csd-eQTL]
<p><strong>README:</strong></p> <p>The full summary data of the cell-state-dependent eQTLs for GTEx Esophagus Mucosa (n=497) are stored in the .parquet format.</p> <p>An example of the file name:</p> <p><strong>"GTEx_Esophagus_Mucosa_bin1.cis_qtl_pairs.1.parquet.gz"</strong> means the summary data of csd-eQTLs for bin1 of chromosome 1.</p>
MD simulation trajectories associated to the publication: Multi-eGO: model improvements towards the study of complex self-assembly processes
<p>The three tgz compressed files include the simulations data and resulting trajectories for the three systems discussed in the work. In particular: </p><ul><li>ab42.tgz includes a random_coil simulation, the multi-eGO simulation of the monomer performed in triplicate and the simulations performed with the original multi-eGO model.</li><li>ttr.tgz includes the randomcoil simulations for both the intramolecular as well as the intermolecular interactions at the three different concentrations, the simulation of the monomer performed in triplicate, and the aggregation kinetics performed in triplicate at the three reported concentrations</li><li>protein_g.tgz includes the reference GB1 simulation, a randomcoil simulation and the 200 multi-eGO folding simulations.</li></ul>
Data from: Moving like a model: mimicry of hymenopteran flight trajectories by clearwing moths of Southeast Asian rainforests
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Data from: Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits
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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.