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274 results for “collisions”
Post-50 Ma evolution of India-Asia collision zone from paleomagnetic and GPS data: Greater India indentation to eastward Tibet flow
<p>Review of paleomagnetic data from Tibet and N Indochina, supporting the paper "Post-50 Ma evolution of India-Asia collision zone from paleomagnetic and GPS data: Greater India indentation to eastward Tibet flow".</p>
Dataset from: Improved multispecies Dougherty collisions
<p>The Dougherty model Fokker-Planck operator is extended to describe nonlinear full-f collisions between multiple species in plasmas. Simple relations for cross-species primitive moments are developed which obey conservation laws, and reproduce familiar velocity and temperature relaxation rates. This treatment of multispecies Dougherty collisions, valid for arbitrary mass ratios, avoids unphysical temperatures and satisfies the H-theorem unlike an analogous Bhatnagar-Gross-Krook operator. Formulas for both a Cartesian velocity-space and a gyroaveraged operator are provided for use in Vlasov as well as long-wavelength gyrokinetic models. We present an algorithm for the discontinuous Galerkin discretization of this operator, and provide results from relaxation and Landau damping benchmarks.</p>
Hotspots in the grid: Avian sensitivity and vulnerability to collision risk from energy infrastructure interactions in Europe and North Africa
<p>Wind turbines and power lines can cause bird mortality due to collision or electrocution. The biodiversity impacts of energy infrastructure (EI) can be minimised through effective landscape-scale planning and mitigation. The identification of high-vulnerability areas is urgently needed to assess potential cumulative impacts of EI while supporting the transition to zero-carbon energy.</p> <p>We collected GPS location data from 1,454 birds from 27 species susceptible to collision within Europe and North Africa and identified areas where tracked birds are most at risk of colliding with existing EI. Sensitivity to EI development was estimated for wind turbines and power lines by calculating the proportion of GPS flight locations at heights where birds were at risk of collision and accounting for species' specific susceptibility to collision. We mapped the maximum collision sensitivity value obtained across all species, in each 5x5 km grid cell, across Europe and North Africa. Vulnerability to collision was obtained by overlaying the sensitivity surfaces with density of wind turbines and transmission power lines.</p> <p>Results: Exposure to risk varied across the 27 species, with some species flying consistently at heights where they risk collision. For areas with sufficient tracking data within Europe and North Africa, 13.6% of the area was classified as high sensitivity to wind turbines and 9.4% was classified as high sensitivity to transmission power lines. Sensitive areas were concentrated within important migratory corridors and along coastlines. Hotspots of vulnerability to collision with wind turbines and transmission power lines (2018 data) were scattered across the study region with highest concentrations occurring in central Europe, near the strait of Gibraltar and the Bosporus in Turkey.</p> <p>Synthesis and Applications: We identify the areas of Europe and North Africa that are most sensitive for the specific populations of birds for which sufficient GPS tracking data at high spatial resolution were available. We also map vulnerability hotspots where mitigation at existing EI should be prioritised to reduce collision risks. As tracking data availability improves our method could be applied to more species and areas to help reduce bird-EI conflicts.</p>
Modeling Crash Severity and Collision Types Using Machine Learning
<p>Traffic safety analysis is the fundamental step for reducing economic, social, and environmental cost incurred due to traffic accidents. The essence of traffic safety is understanding the factors affecting crash occurrence, injury severity and collision type and their underlying relationships and predict-prevent future crash instances. Crash injury severity studies in past have utilized numerous statistical, econometric and Machine Learning (ML) and Artificial Intelligence (AI) tools to extract the underlying relationship between the crash causal factors and the consequent severity or collision type. The study aims to explore the Multi-Label Classification (MLC) tool from the domain of Artificial Intelligence (AI) for classification problems in the setting of traffic safety. MLC finds its application primarily in protein function, semantic scene, and music categorization problems. In the real world, multiple heterogenous subjective factors decide the extent of damage/severity of a particular crash instance. Theoretically, the traffic collision type and crash severity type can be correlated, and thus, it is intuitive to model them simultaneously. The ability of MLC to categorize an entity under analysis to more than one labels, correlated or uncorrelated, provides the approach an edge over the single-class (binary) or multi-class classification approach. The MLC based classification model was calibrated and tested using the historical crash data extracted for the state of Texas. The selection of study area was based on a link-level unsupervised principal component analysis-based clustering approach. Similar clustering approach was also tested at the county-level to understand the spatial behavior and thus transferability of the MLC approach to other key cities in the state. The performance of the proposed approach was tested, compared, and quantified with the conventional binary/multi-class classification tools used in the traffic safety domain. Inferences from the preliminary numerical analysis indicates that the proposed multi-label classification approach has promising performance compared to the traditional classification approaches, specifically found in traffic safety literatures.</p>
Multigroup Neutron Transport using a Collision-Based Hybrid Method Dataset
<p>G = 361 Energy Group dataset for the "Multigroup Neutron Transport using a Collision-Based Hybrid Method" paper (under review) by Whewell et al.</p> <p>Included is the total, scattering, and fission cross section matrices for the G = 361 uranium oxide problem and the energy group bounds for G = 361, 300, 240, 180, 150, 120, 90, 60, and 30.</p>
Decentralized Motion Planning with Collision Avoidance for a Team of UAVs under High Level Goals
<p>The video illustrates simulation and experimental results of a team of unmanned aerial vehicles executing Linear Temporal Logic (LTL) tasks. More specifically, given a certain LTL task over predefined regions of interest, each agent derives a high-level plan that satisfies the given task. Then, it executes the plan using a continuous controller that is based on decentralized navigation functions, which also guarantee inter-agent collision avoidance. The video shows one simulation and two experimental scenarios.</p>
State-resolved mutual neutralization of O$^+$ with $^1$H$^-$ and $^2$H$^-$ at collision energies below 100 meV
<p>The data files found here contain the data as obtained and displayed in : "State-resolved mutual neutralization of O$^+$ with $^1$H$^-$ and $^2$H$^-$ at collision energies below 100 meV" published in Physical Review A (2024). Each file contains an explanatory header. Header lines start with #.</p>
Dataset for Cenozoic India-Asia collision driven by mantle dragging the cratonic root
<p>Dataset for the paper:</p> <p>Cenozoic India-Asia collision driven by mantle dragging the cratonic root</p> <p>For more infomation, please look into the README file or contact Professor Lijun Liu at ljliu@mail.iggcas.ac.cn, thank you!</p>
Lithosphere removal (delamination) following continental collision: shape and complexity of observables predicted from 3D numerical models
<p>Upload contains most essential data files from the manuscript. The raw data amount to several TB and cannot be uploaded.</p> <p><strong>1 Model data</strong></p> <p><em>1.1 Models covered</em></p> <p>Relatively frequent output is available for the reference model (<em>R</em> in paper, see Table S2), prefixed <em>dp10</em>. Limited output is uploaded for models with geometric variations (<em>OSM -> dp19, TSM->dp26</em>).</p> <p><em>1.2 Types of data</em></p> <p>Most files are visualisation files (ending *.<em>vtr</em>). These are intended for loading into the visualisation software Paraview. Files starting with <em>comp_</em> contain the lithological composition field; other visualisation files hold the fields of selected physical parameters. Note that as of the design of the study, the maximum file size allowed for loading into Paraview is ca. 2 GB. This limits the number of fields available according to model size - larger models (geometrical variations) hold therefore less fields.</p> <p>Binary files with ending *.<em>prn</em> are saved model states, from which programs can be rerun.</p> <p>Time information mapping step numbers to years is provided in <em>times...txt</em>.</p> <p> </p> <p><strong>2 Software for reproduction</strong></p> <p>The numerical code is not in the public domain, and its use is restricted. A pre-compiled binary is provided and allows reproduction of the main/reference model. We present the input files; however, these cannot be changed freely (equivalent to software distribution), and changes will lead to termination of the program.</p> <p><em>2.1 Requirements, preparation and use</em></p> <p>The code is compiled on CentOS with gcc 4.8.2. There is no library dependency, apart from the intrinsic OpenMP and glibc (>= 2.17). The following requirements <em>must</em> be satisfied in order to run it:</p> <ul> <li>Linux OS (tested on CentOS and Fedora)</li> <li>> 160 GB shared memory</li> </ul> <p>The following provisions are recommended:</p> <ul> <li>16 cores</li> <li>high bandwidth storage</li> <li>storage space <em>O</em>(TB)</li> </ul> <p>To prepare, simply unzip the provided snapshot <em>clsd_reproduce_gcc_CentOS.zip</em> in an appropriate directory (cluster). The input file <em>init.t3c</em> sets the initial conditions; the input file <em>mode.t3c </em>controls solver and file output. <em>file.t3c</em> is the pointer to the last output step; if a model snapshot is available as binary dump (*.prn file), setting the pointer to its number allows restarting.</p> <p>For normal usage, create initial condition with executable <em>in3mg</em>, and subsequently run <em>i3mg</em>. This will create snapshots and *.vtr visualisation files.</p> <p> </p> <p>High-performance computing facilities, runtime (months), proper software environment, and training in use of the code, or in the use of the visualisation software, are not provided.</p> <p> </p>
Figure 2 in Identifying the hotspots of wildlife-vehicle collision on the Çankırı-Kırıkkale highway during summer
Figure 2. The distribution of accidentally killed mammals on the road course.
Figure 1 in Identifying the hotspots of wildlife-vehicle collision on the Çankırı-Kırıkkale highway during summer
Figure 1. Study area.
Topography Response to Horizontal Slab Tearing and Oblique Continental Collision: 3D Thermomechanical Numerical Modelling
<p>This repository submission provides the 3D thermo-mechanical numerical modelling code I3ELVIS developed by the workgroup of Prof. Taras Gerya (ETH Zürich). The code is based on finite-difference and marker-in-cell methods (Gerya & Yuen, 2003, 2007; Gerya, 2019). The code solves the momentum, continuity, and energy equations on the fixed Eulerian grid and transports the physical properties by Lagrangian markers using the velocity field. The code also accounts for the major phase transitions in the Earth’s mantle and internal heat sources arising from adiabatic, radiogenic, and frictional heating. Partial melting and melt extraction processes are neglected for the sake of simplicity. A more detailed description of the code, including the governing equations and the adopted rheological model can be found in various published literature (Andrić-Tomašević et al., 2023; Boonma et al., 2023; Maiti et al., 2024). Interested users are recommended to contact Prof. Taras Gerya (taras.gerya@erdw.ethz.ch). </p> <p>The repository also provides input and output files to run and reproduce model results and manuscript figures of Maiti et al., 2024 (JGR Solid Earth). Paraview States for processing .vtr result files and visualizing the model output data. Matlab script to visualise the topography from .grd files. </p>
Deciphering Ball Milling Mechanochemistry via Molecular Simulations of Collision‐Driven and Liquid‐Assisted Reactivity
<p>The direct study of mechanical activation events in ball milling mechanochemistry is, at present, not directly accessible experimentally, which prompted us to examine it by theoretical modelling. We use molecular dynamics simulations to describe mechanical activation by fragmentation of crystal particles down to individual atoms, ions and ion pairs, and monitor subsequent product formation and agglomeration under neat and liquid-assisted conditions. We demonstrate that a small amount of the liquid additive facilitated product formation, while too much of it destabilised the product by stabilising the reactants. Our approach provides a fresh and detailed view of mechanochemistry that could allow for its theoretical optimisation including the targeted choice of a catalyst and its loading. </p>
Data and Code From Formation of Stripped Stars From Stellar Collisions in Galactic Nuclei
<p>This repository is for the paper "Formation of Stripped Stars From Stellar Collisions in Galactic Nuclei" by Charles F. A. Gibson. It is associated with manuscript number ApJ AAS55868.</p> <p>We include the MESA inlists, SPH input files, and the last SPH output file for the StarSmasher relaxations of the parent models in Table 1 and collisions from Tables 2 and 3.</p> <p>We also include the StarSmasher source code with the Stretchy HCP relaxation technique and the post processing codes used to generate MESA input from the StarSmasher output.</p> <p>Finally, we provide the MESA input files for the post-collision stellar evolution of the models shown in Figures 7 and 9.</p>
Simulations of planetary-scale collisions between rotating, differentiated bodies
<p>In the late stages of terrestrial planet formation, pairwise collisions between planetary-sized bodies act as the fundamental agent of planet growth. These collisions can lead to either growth or disruption of the bodies involved and are largely responsible for shaping the final characteristics of planets. Despite their critical role in planet formation, an accurate treatment of collisions has yet to be realized. Therefore, we simulated a new set of 10,700 smoothed-particle hydrodynamics (SPH) simulations of pairwise collisions between rotating, differentiated bodies. This dataset is an order of magnitude larger than any previous collision dataset and is intended to serve as a training dataset for machine learning models, so that accurate surrogate models for planetary-scale collisions can be developed.</p>
High-dimensional Anomaly Detection with Radiative Return in e+e- Collisions
<p>Numpy files of Pythia + Delphes simulated e+e- collisions used as DNN/PFN training inputs.</p>
Bird-building collisions increase with weather conditions that favor nocturnal migration and with inclement and changing weather
<p>Collisions with building windows are a top bird mortality source, but few studies have evaluated how bird-window collisions are influenced by the weather. By monitoring collisions daily at 21 buildings in Minneapolis, Minnesota, over 4 migration seasons, we show that weather influences the number of window collisions of nocturnal migrants in spring and fall, indicating that collisions may be forecastable based on weather conditions. Collisions increased with weather favoring migration, such as consecutive nights of south wind in spring and even short periods of north wind in fall. We also found evidence that spring and fall collisions increase with weather changes that impede migration, such as changes from fair conditions and tailwinds early in the night to headwinds near sunrise. Our study suggests complex weather effects never before considered in the context of bird collisions, including possible time lag effects of conditions two and three nights before collisions occur, effects of multi-day sequences of conditions, and interactions between conditions at different times of the night. More research is needed to determine if the accuracy of weather-based collision prediction systems improves by integrating such nuances and to clarify mechanisms through which these complex effects operate, such as influences of weather on migration intensity and collision avoidance behavior. Weather-based forecasts may allow refinement of collision mitigation approaches (e.g., reducing building lighting on certain nights or using temporary glass coverings or treatments). However, because challenges remain to communicating such temporally targeted actions and implementing them in a timely manner, other bird-friendly practices (e.g., season-long lighting reduction and permanent glass treatments) should continue to be prioritized.</p>
NL, Advanced Driving, Cooperative Collision Avoidance
<p>Use Case Category: <strong>Advanced Driving</strong><br> User Story: <strong>Cooperative Collision Avoidance</strong><br> Location: Dutch (NL) trial site</p> <p>According to 3GPP TS 22.186 R16, Advanced Driving “enables semi-automated or fully-automated driving. Longer inter-vehicle distance is assumed. Each vehicle and/or Road Side Unit (RSU) shares data obtained from its local sensors with vehicles in proximity, thus allowing vehicles to coordinate their trajectories or manoeuvres. In addition, each vehicle shares its driving intention with vehicles in proximity. The benefits of this use case group are safer traveling, collision avoidance, and improved traffic efficiency”.</p> <p>User Story: Cooperative Collision Avoidance</p> <p>This 5G-MOBIX Service will take place at an Intelligent Intersection of the A270 Motorway - N270 Highway between Eindhoven and Helmond (NL). This site has been used for several tests and trials on Automated Driving and/or C-ITC. In 5G-Mobix the current facilities to support CCAM will be upgraded to work on a 5G mobile connectivity platform.</p> <p>Cooperative Collision Avoidance (CoCA) targets to solve a challenging traffic situation on the motorway/highway environment. The Vehicle A (‘ego vehicle’, a foreign registered vehicle driving on the Dutch motorway/highway network) will make itself ‘visible’ and known to other traffic participants and to the infrastructure for Edge Computing through C-ITS messaging via 5G networks, and Cellular V2X (C-V2X) communication i.e. either LTE-based or 5G NR-based V2X. The Vehicle B (‘alter vehicle’, a Dutch registered vehicle) will submit similar information of its presence, speed and direction of movement to ‘ego vehicle’ and infrastructure as described above. Hence the ‘Edge Cloud’ infrastructure facilities can perform calculations and offload from the vehicles to the infrastructure and then return the suggested manoeuvring messages.</p> <p>At the intersection of A270-N270 roads, the most critical path for cooperative automated driving is the left turn over the direct traffic flow that has a right-of-way for driving in highly automated mode through the intersection. The ego vehicle that is approaching the intersection must be able to clear itself safely across the motorway/highway lanes to join the main traffic flow. When deemed necessary, the ego vehicle need to safely stop autonomously before crossing the motorway/highway and start driving only when its calculated trajectory path is safe and clear for autonomous manoeuvring. For this purpose, the ego vehicle must be able to utilise both its own trajectory and timing data and information from the road side sensors as well as the alter vehicle’s precise location, intended direction and speed to avoid collision.</p> <p>The target in 5G-Mobix is time-critical message exchange between CAVs using 5G technologies. These technologies include:</p> <p>· C-V2X based on LTE or 5G NR for direct communication between vehicles and 5G networks<br> · 5G NR enabled base stations (gNB)<br> · 5G core technologies like Edge Computing (‘Edge Cloud ‘) and Slicing<br> · Ultra-Reliable Low Latency Communication (uRLLC) to support time-critical communication.</p> <p>Currently the CAVs are capable to support direct communication between vehicles via ITS-G5 based solutions and/or 4G network-based communication for C-ITS message exchange. The ultimate solution is to use hybrid in-vehicle communication units that can communicate both directly between vehicles and over the network using 5G NR-V2X.</p>
Deep Subduction Versus Collision Cessation: The Fate of Continental Collisional Orogens
<p>Deep Subduction Versus Collision Cessation: The Fate of Continental Collisional Orogens</p>
Linearly and Nonlinearly Implicit Schemes for Energy-Stable Simulation of String Vibrations with Collisions: Refinement, Analysis, and Comparison
<p>Sound examples accompanying the manuscript submitted to the Journal of Sound and Vibration</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.