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274 results for “collision”
Dataset to "Modeling Collision-Coalescence in Particle Microphysics: Numerical Convergence of Mean and Variance of Precipitation in Cloud Simulations Using University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1 " by Zmijewski, Dziekan & Pawlowska
<p>The archive contains datasets, run scripts, time series and plotting scripts used when preparing the paper: P. Zmijewski, P. Dziekan and H. Pawlowska "Modeling Collision-Coalescence in Particle Microphysics: Numerical Convergence of Mean and Variance of Precipitation in Cloud Simulations Using University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1 " submitted to Geoscientific Model Development in March 2023.</p>
A dataset of seabird collision and displacement vulnerability factors relatively to marine wind farms in Portugal
<p>The implementation of marine wind farms has grown considerably along northern European's northern Atlantic coasts (e.g. Baltic and North Sea) and a boom in these infrastructures is expected to take place along Europe's entire Atlantic and Mediterranean coasts. Accordingly, the Portuguese government has recently proposed priority sites for the construction of wind farms along the mainland coast. We used sensitivity mapping (Garthe & Hüppop, 2004) to assess which areas along the Portuguese coast are most sensitive for seabirds and to what extent the proposed sites for wind farm construction overlap with these areas.</p><p>This dataset contains the base data to estimate a seabird Species Sensitivity Index (SSI) (following Bradbury et al., 2014, Certain et al., 2015), including scores for 11 species-specific ecological and behavioural factors related with seabird species' (i) vulnerability to collision with wind farms (4 factors), (ii) vulnerability to displacement due to disturbance by wind farms and associated maintenance (3 factors), and (iii) conservation status (4 factors). </p><p>We reviewed the literature to mine and compile data on these factors for 34 seabird species that regularly occur along the Portuguese mainland coast. We updated factor scores, particularly for those factors that have been studied in greater detail in recent years using tracking technologies (Clairbaux & Jessopp, 2021). However, in many cases empirical data were unavailable and we used the scores presented in previous sensitivity mapping studies (Garthe & Hüppop, 2004; Bradbury et al., 2014; Certain et al., 2015; Wade et al., 2016; Serratosa & Allinson, 2022).</p>
Experimental absorption spectra used in "Spectral profile of ro-vibrational transitions of HCl broadened by He, Ar and SF6: testing the β-correction to the Hartmann-Tran profile and the speed dependent (complex) hard collision model"
<p>Experimental absorption spectra used in the article entitled <strong>"Spectral profile of ro-vibrational transitions of HCl broadened by He, Ar and SF<sub>6</sub>: testing the β-</strong><strong>correction to the Hartmann-Tran profile and the speed dependent (complex) hard collision model", </strong>to be published in the Journal of Quantitative Spectroscopy and Radiative Transfer. Accepted 19 March 2024.</p> <div> <div> <div> <div> <h3><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jqsrt.2024.108977" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.jqsrt.2024.108977</a></h3> </div> </div> </div> </div> <p> </p> <p>Comma separated ASCII files with 1 header line.</p> <p>First column is wavenumber in cm-1</p> <p>The rest of the columns contain the napierian absorbance at the total pressure given in the header. </p> <p>Mind the units!: pressure of Ar-mixtures is expressed in Torr, pressure of He- and SF6-mixtures is expressed in mbar</p> <p> </p>
FastNLO interpolation tables for NLO pQCD predictions of Inclusive Jet Production in $pp$ collisions at $\sqrt{s}=200$ and $510$~GeV
<p>This is generated using the NLOJet++ interface using jet pT for renormalization and factorization scale.</p> <p><strong>run12pp200_R050.tab:</strong></p> <p>\sqrt{s} = 200 GeV<br> anti-kT R=0.5<br> |eta| bins: 0.0 0.5 0.9<br> pT bins (GeV): 6.9 8.2 9.7 11.5 13.6 16.1 19.0 22.5 26.6 31.4 37.2 44.0 52.0</p> <p><strong>run12pp510.tab:</strong></p> <p>\sqrt{s} = 510 GeV<br> anti-kT R=0.5<br> |eta| bins: 0.0 0.5 0.9<br> pT bins (GeV): 8.0 10.0 13.0 17.0 21.0 26.0 32.0 39.0 47.0 57.0 68.0 80.0</p> <p><em>This research was supported in part by Lilly Endowment, Inc., through its support for the Indiana University Pervasive Technology Institute.</em></p> <p>If you use this, please cite: D. Britzger, T. Kluge, K. Rabbertz, F. Stober, M. Wobisch, arXiv:1109.1310</p>
Data and code for Zheng et al. Contrasting coloured ventral wings are a visual collision avoidance signal in birds
<p>This repository contains codes and data for Zheng et al. Contrasting coloured ventral wings are a visual collision avoidance signal in birds. We have three folders, each containing one of the three datasets of contrast scores of avian ventral wings. These include the mean manual contrast ventral wing scores for 1780 species, a subset of 1745 diurnal species, 648 species with high-resolution museum ventral images, and the mean Root-Mean-Square (RMS) contrast ventral wing scores for the same 648 species. We tested the collision avoidance hypothesis for each dataset by assessing the relationships between the contrast scores and ecological traits. We used the Bayesian Generalized Linear Mixed Models in MCMCglmm with considering the phylogenetic relatedness among species and the uncertainties of 100 phylogenetic trees (downloaded in birdtree.org). We included body mass, flock size, coloniality (colonial vs. non-colonial breeding species), activity time (nocturnal vs. diurnal), the number of sympatric predators, and the interaction between coloniality and body mass as the predictors. In each folder, we included four files, including an R source file, a dataset containing the contrast scores and the ecological traits of the corresponding species, and a tree file containing 100 randomly sampled phylogenetic trees among these species. See the Methods of the paper for detail. </p>
Strand-switching mechanism of Pif1 helicase induced by its collision with a G-quadruplex embedded in dsDNA_data_NAR
<p>This document includes data corresponding to the paper entitled :"Strand-switching mechanism of Pif1 helicase induced by its collision with a G-quadruplex embedded in dsDNA" published in Nucleic Acid Research, 2022. The link to the zenodo depository of the homemade software to open the data is given in the readme.txt file as well as the way the data files are organized</p>
Code and Velocity Data for Sustained indentation in 2D models of continental collision involving whole mantle subduction
<p>Contains the Python code for all models and resolution tests using the <a href="https://www.underworldcode.org/intro-to-underworld">underworld geodynamics code</a> in "Sustained indentation in 2D models of continental collision involving whole mantle subduction" submitted to GJI</p>
S116 | REFCCS | Collision Cross Section (CCS) Values from Literature
<p>This is the collection associated with list S116 REFCCS Collision Cross Section Values from Literature on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>This dataset is an entry point for users to contribute collision cross section values from the literature for addition to the NORMAN SLE, SusDat and the PubChem Collision Cross Section annotations.</p>
Results of MD simulations of collision cascades in hcp Zr at 600 K.
<p>This is a database consisting of pre- and post-processing scripts, input files and results from molecular dynamics (MD) simulations of collision cascades in LAMMPS. The database is associated with the paper: <a href="https://arxiv.org/abs/2405.03332">Molecular dynamics simulations of neutron induced collision cascades in Zr</a>. The material studied was hcp Zr at the temperature of 600 K. A detailed description of the record can be found in the <code>pdf</code> file, as well as in Emacs <code>org</code> and Jupyter notebooks (<code>ipynb</code>). Files also include Python code describing how to access and process the data.</p>
Рис. 1. Птицы, погибшие от стоΛкновений с оконными стекΛами в г. Уссурийске осенью 2019 г. Фото Δ. А. БеΛяева Fig. 1. Birds that died as a result of window collisions in Ussuriysk in the autumn of 2019. Photo by D. A. Belyaev in Deaths Resulting From Bird Window Collisions In Ussuriysk (Primorsky Krai)
Рис. 1. Птицы, погибшие от стоΛкновений с оконными стекΛами в г. Уссурийске осенью 2019 г. Фото Δ. А. БеΛяева Fig. 1. Birds that died as a result of window collisions in Ussuriysk in the autumn of 2019. Photo by D. A. Belyaev
Рис. 2. ЗΑание ТЦ «Москва», гΑе быΛо найΑено наибоΛьшее чисΛо погибших от стоΛкновения птиц. Фото Δ. А. БеΛяева Fig. 2. The building of the "Moskva" shopping center, where the highest number of bird window collision deaths was registered. Photo by D. A. Belyaev in Deaths Resulting From Bird Window Collisions In Ussuriysk (Primorsky Krai)
Рис. 2. ЗΑание ТЦ «Москва», гΑе быΛо найΑено наибоΛьшее чисΛо погибших от стоΛкновения птиц. Фото Δ. А. БеΛяева Fig. 2. The building of the "Moskva" shopping center, where the highest number of bird window collision deaths was registered. Photo by D. A. Belyaev
Dataset for "On a Collision Course: Unveiling Wireless Attacks to the Aircraft Traffic Collision Avoidance System (TCAS)"
<p>The dataset associated with "On a Collision Course: Unveiling Wireless Attacks to the Aircraft Traffic Collision Avoidance System (TCAS)"</p>
Robot trajectory data for "Biohybrid Fly-Robot Interface system performs active collision avoidance"
<p>This dataset includes the videos of the trajectories of the biohybrid robot (Fly-Robot Interface), performing collision avoidance at the patterned wall corners (90 and 60 degrees). A python script for the manual tracking is also attached, as well as the processed coordinates of each individual robot trajectory, where two tracking markers were chosen on the front-left and front-right corners of the robot.</p> <p>Serial Number <20: the videos at 90-degree wall corner</p> <p>Serial Number >20: the videos at 60-degree wall corner</p>
Equation of state tables used in the paper: "Exploring the Catastrophic Regime: Thermodynamics and Disintegration in Head-On Planetary Collisions"
<p>The EoS (Equation of State) tables for iron and forsterite used in the paper "<span>Exploring the Catastrophic Regime: Thermodynamics and Disintegration</span><br><span>in Head-On Planetary Collisions</span>" are available here for use.</p> <p>These tables can be directly integrated into the SPH (Smoothed Particle Hydrodynamics) code <a href="https://swift.strw.leidenuniv.nl/">SWIFT</a> to conduct simulations of planetary giant impacts.</p> <p>The tables were generated using the GitHub repository maintained by Sarah T. Stewart, specifically for <a href="https://github.com/ststewart/aneos-iron-2020">iron</a> and <a href="https://github.com/ststewart/aneos-forsterite-2019">forsterite</a>.</p> <p>All tables were created with the tension regions of the materials removed.</p> <p>Table "ANEOS_iron_S20_100gcc_denseTgrid_NOTension.txt" was generated with denser grid at temperate range 1e5 to 1e6 to using for impacts with target mass above 10 Earth mass.</p> <p>Table "ANEOS_forsterite_S19_80gcc_NOTension.txt" was generated with dense grid in both rho and temperate dimention.</p> <p>"ANEOS_iron_S20_100gcc_denseTgrid_NOTension.txt" and "ANEOS_forsterite_S19_80gcc_NOTension.txt" were generated to deal with extreme cases that impact speeds and target masses are very high. </p> <p>Most of the simulations were run with "ANEOS_forsterite_S19.txt" and "ANEOS_iron_S20.txt".</p> <p> </p>
Supplementary data for "Collision-induced absorptions by pure CO2 in the infrared: New measurements in the 1150–4500 cm−1 spectral range and empirical modeling for applications" published in Icarus. https://doi.org/10.1016/j.icarus.2024.116265
<p>Supplementary data for the paper entitled ""Collision-induced absorptions by pure CO2 in the infrared: New measurements in the 1150–4500 cm−1 spectral range and empirical modeling for applications" published in <em>Icarus</em>. https://doi.org/10.1016/j.icarus.2024.116265</p> <p>These data files contain the coefficients needed to compute the shape of a pure CO2 CIA band at a given temperature (see Eq. (3)) of the paper https://doi.org/10.1016/j.icarus.2024.116265</p> <p>"CIA_shape_coeff.dat" involves a CIA band shape without dimer signatures </p> <p>"CIA_dimer_shape_coeff.dat" involves a CIA band shape with dimer signatures </p> <p>"CIA_Fermi_doublet_shape_coeff.dat" involves the Fermi doublet band shape</p> <p>First column is wavenumber in cm-1, the rest of the columns contain the coefficients.</p>
Simulated pp collisions at 13 TeV with 2 leptons + 1 b jet final state and selected benchmark Beyond the Standard Model signals
<p>This data-set is comprised of simulated events of pp collisions at 13 TeV with 2 leptons + 1 bottom jet sinal state, with HT > 500 GeV. It includes the following samples</p> <ul> <li>Standard-Model background (bkg), generated at leading order includes the sub-samples Z+Jets, ttbar, WW, WZ, and ZZ. <ul> <li>The processes were generated in kinematic regions to ensure good statistics across the whole phase space. The sampling was carried out using event generation filters at parton level as follows <ul> <li>ttbar: pT <100 GeV; pT in [100, 250] GeV; pT > 250 GeV</li> <li>The scalar sum of the pT of outgoing particles for Z+Jet: ST < 250 Gev; ST in [250, 500] GeV; ST > 500 GeV</li> <li>W/Z pT for dibosons: pT < 250 GeV; pT in [250, 500] GeV; pT > 500 GeV</li> </ul> </li> </ul> </li> <li>Vector-like T-quarks with masses 1.0, 1.2, 1.4 TeV (hq1000, hq1200, hq14000) pair produced either through the Standard-Model gluon (wohg) or through a BSM 3TeV heavy gluon (hg3000)</li> <li>tZ production through a Flavour Changing Neutral Current (fcnc) vertex</li> </ul> <p>The samples are provided with both a full set of features, or with a sanitised set of features. The sanitised features remove some accumulation at zeros from non-reconstructed objects (i.e. missing values). All samples were generated using MadGraph5 2.6.5 and the detector was simulated using Delphes 3 with the default CMS card. For the Standard-Model background, both Pythia 8.2 (with CMS CUETP8M1 underlying event tune and NNPDF 2.3 parton distribution functions) (pythia) and Herwig 7 (herwig) hadronisations are provided to compare the background simulation. For the BSM signals only Pythia is provided.</p> <p>For the details of the generation and on the differences between the two feature sets please refer to <a href="https://link.springer.com/article/10.1140%2Fepjc%2Fs10052-020-08807-w">Finding new physics without learning about it: anomaly detection as a tool for searches at colliders</a> for more details. Each file provides a train:validation:split with the ratios 1:1:1 to ensure equal statistical description of the events at each step of the machine learning workflow.</p>
Local Earthquake Tomography Code and Data for study the Lithosphere Structure in the Collision Zone of the NW Himalayas
<p>The tomography model presented in the paper "Lithosphere Structure in the Collision Zone of the NW Himalayas Revealed by Local Earthquake Tomography" are obtained using the LOTOS code by Koulakov (2009). Here, we present the full version of the code with initial data and parameters used for calculating P and S velocity models beneath the NW Himalaya. This version of the code is adopted for the Windows OS and contains the entire program listing and the full project structure for Microsoft Visual Studio 2010 and Intel Visual Fortran. Detailed description of the code can be found at <a href="http://www.ivan-art.com/science/LOTOS">www.ivan-art.com/science/LOTOS</a></p>
Dataset for "Terrane collision-induced subduction initiation: Mode selection and implications for western Pacific subduction system"
<p>Numerical results for "<strong>Terrane collision-induced subduction initiation: Mode selection and implications for western Pacific subduction system</strong>".</p>
DTM files from wildlife–vehicle collisions using kernel density estimation (KDE)
<p>21 CSV files that contain the Digital Terrain Model (DTM) from wildlife–vehicle collisions (WVC) hotspots using kernel density estimation (KDE) in Spain between 2016 and 2021. Data source of each WVC record is the Spanish General Directorate of Traffic (DGT).</p> <p>The context is the Final Master's Degree Project 'Analysis and Predictive Modelling of Wildlife–Vehicle Collision on Interurban Roads in Spain' (Data Science Master’s Degree of Universitat Oberta de Catalunya - UOC).</p> <p>This dataset is the output of the KDE analysis and the <a href="https://github.com/alba620/analisis-prediccion-accidentes-trafico-animales">code repository</a> is available on GitHub.</p>
Data and code from: Three decades of wildlife-vehicle collisions in a protected area: main roads and long-distance commuting trips to migratory prey increase spotted hyena roadkills in the Serengeti
<p>This is the first release. Potential updates will be available on GitHub: <a href="https://github.com/MarwanNaciri/Three_decades_of_spotted_hyena_roadkill_in_a_protected_area">https://github.com/MarwanNaciri/Three_decades_of_spotted_hyena_roadkill_in_a_protected_area</a></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.