Risk mapping of wildlife-vehicle collisions across thestate of Montana,USA:a machine-learning approach forimbalanced data along rural roads

Wildlife-vehicle collisions(WVCs)with large animals are estimated to cost the USA over 8 billion USD in property damage,tens of thousands of human injuries and nearly 200 human fatalities each year.Most WVCs occur on rural roads and are not collected evenly among road segments,leading to imbalanced data.There are a disproportionate number of analysis units that have zero WVC cases when investigating large geographic areas for collision risk.Analysis units with zero WVCs can reduce prediction accuracy and weaken the coefficient estimates of statistical learning models.This study demonstrates that the use of the synthetic minority over-sampling technique(SMOTE)to handle imbalanced WVC data in combination with statistical and machine-learning models improves the ability to determine seasonal WVC risk across the rural highway network in Montana,USA.An array of regularized variables describing landscape,road and traffic were used to develop negative binomial and random forest models to infer WVC rates per 100 million vehicle miles travelled.The random forest model is found to work particularly well with SMOTE-augmented data to improve the prediction accuracy of seasonal WVC risk.SMOTE-augmented data are found to improve accuracy when predicting crash risk across fine-grained grids while retaining the characteristics of the original dataset.The analyses suggest that SMOTE augmentation mitigates data imbalance that is encountered in seasonally divided WVC data.This research provides the basis for future risk-mapping models and can potentially be used to address the low rates of WVCs and other crash types along rural roads.

Violent collisions can reveal hexadecapole deformation of nuclei

A new observable in heavy ion collision experiments was identified to be sensitive to the hexadecapole deformation of the colliding nuclei.Such deformation is difficult to measure in traditional nuclear electric transition measurements,as it is often overwhelmed by the nuclear quadrupole deformation.This opens the door to gain new insight into nuclear structure with experiments that were designed to study hot and dense nuclear matter.

Investigating the elliptic anisotropy of identified particles in p-Pb collisions with a multi-phase transport model

The elliptic azimuthal anisotropy coefficient(v_(2))of the identified particles at midrapidity(|η|<0.8)was investigated in p-Pb collisions at√s_(NN)=5.02 TeV using a multi-phase transport model(AMPT).The calculations of differential v_(2)based on the advanced flow extraction method of light flavor hadrons(pions,kaons,protons,andΛ)in small collision systems were extended to a wider transverse momentum(p_(T))range of up to 8 GeV/c for the first time.The string-melting version of the AMPT model provides a good description of the measured p_(T)-differential v_(2)of the mesons but exhibits a slight deviation from the baryon v_(2).In addition,we observed the features of mass ordering at low p_(T)and the approximate number-of-constituentquark(NCQ)scaling at intermediate p_(T).Moreover,we demonstrate that hadronic rescattering does not have a significant impact on v_(2)in p-Pb collisions for different centrality selections,whereas partonic scattering dominates in generating the elliptic anisotropy of the final particles.This study provides further insight into the origin of collective-like behavior in small collision systems and has referential value for future measurements of azimuthal anisotropy.

Electromagnetic fields in ultra-peripheral relativistic heavy-ion collisions

Ultra-peripheral heavy-ion collisions(UPCs)offer unique opportunities to study processes under strong electromagnetic fields.In these collisions,highly charged fast-moving ions carry strong electromagnetic fields that can be effectively treated as photon fluxes.The exchange of photons can induce photonuclear and two-photon interactions and excite ions.This excitation of the ions results in Coulomb dissociation with the emission of photons,neutrons,and other particles.Additionally,the electromagnetic fields generated by the ions can be sufficiently strong to enforce mutual interactions between the two colliding ions.Consequently,the two colliding ions experience an electromagnetic force that pushes them in opposite directions,causing a back-to-back correlation in the emitted neutrons.Using a Monte Carlo simulation,we qualitatively demonstrate that the above electromagnetic effect is large enough to be observed in UPCs,which would provide a clear means to study strong electromagnetic fields and their effects.

Collisionless shock acceleration of protons in a plasma slab produced in a gas jet by the collision of two laser-driven hydrodynamic shockwaves

We have recently proposed a new technique of plasma tailoring by laser-driven hydrodynamic shockwaves generated on both sides of a gas jet[Marquès et al.,Phys.Plasmas 28,023103(2021)].In a continuation of this numerical work,we study experimentally the influence of the tailoring on proton acceleration driven by a high-intensity picosecond laser in three cases:without tailoring,by tailoring only the entrance side of the picosecond laser,and by tailoring both sides of the gas jet.Without tailoring,the acceleration is transverse to the laser axis,with a low-energy exponential spectrum,produced by Coulomb explosion.When the front side of the gas jet is tailored,a forward acceleration appears,which is significantly enhanced when both the front and back sides of the plasma are tailored.This forward acceleration produces higher-energy protons,with a peaked spectrum,and is in good agreement with the mechanism of collisionless shock acceleration(CSA).The spatiotemporal evolution of the plasma profile is characterized by optical shadowgraphy of a probe beam.The refraction and absorption of this beam are simulated by post-processing 3D hydrodynamic simulations of the plasma tailoring.Comparison with the experimental results allows estimation of the thickness and near-critical density of the plasma slab produced by tailoring both sides of the gas jet.These parameters are in good agreement with those required for CSA.

Production of the X(4014)as the Spin-2 Partner of X(3872)in e^(+)e^(-)Collisions

In 2021,the Belle collaboration reported the first observation of a new structure in theψ(2S)γfinal state produced in the two-photon fusion process.In the hadronic molecule picture,this new structure can be associatedwith the shallow isoscalar D*D* bound state and as such is an excellent candidate for the spin-2 partner of the X(3872)with the quantum numbers J^(PC)=2^(++)conventionally named X_(2).

Impact of initial fluctuations and nuclear deformations in isobar collisions

Relativistic isobar^(96)_(44)Ru+^(96)_(44)Ru and^(96)_(40)Zr+^(96)_(40)Zrcollisions have revealed intricate differences in their nuclear size and shape,inspiring unconventional studies of nuclear structure using relativistic heavy ion collisions.In this study,we investigate the relative differences in the mean multiplicityR_(<Nch>)and the secondR_(ε2)and third-order eccentricityR_(ε3)between isobar collisions using initial state Glauber models.It is found that initial fluctuations and nuclear deformations have negligible effects on R_(<Nch>)in most central collisions,while both are important for the R_(ε2)and R_(ε3),the degree of which is sensitive to the underlying nucleonic or sub-nucleonic degree of freedom.These features,compared to real data,may probe the particle production mechanism and the physics underlying nuclear structure.

Cosmological Redshift Caused by Head-On Collisions with CMB Photons, Not by Expansion of Space

The Big Bang model was first proposed in 1931 by Georges Lemaitre. Lemaitre and Hubble discovered a linear correlation between distances to galaxies and their redshifts. The correlation between redshifts and distances arises in all expanding models of universe as the cosmological redshift is commonly attributed to stretching of wavelengths of photons propagating through the expanding space. Fritz Zwicky suggested that the cosmological redshift could be caused by the interaction of propagating light photons with certain inherent features of the cosmos to lose a fraction of their energy. However, Zwicky did not provide any physical mechanism to support his tired light hypothesis. In this paper, we have developed the mechanism of producing cosmological redshift through head-on collision between light and CMB photons. The process of repeated energy loss of visual photons through n head-on collisions with CMB photons, constitutes a primary mechanism for producing the Cosmological redshift z. While this process results in steady reduction in the energy of visual photons, it also results in continuous increase in the number of photons in the CMB. After a head-on collision with a CMB photon, the incoming light photon, with reduced energy, keeps moving on its original path without any deflection or scattering in any way. After propagation through very large distances in the intergalactic space, all light photons will tend to lose bulk of their energy and fall into the invisible region of the spectrum. Thus, this mechanism of producing cosmological redshift through gradual energy depletion, also explains the Olbers’s paradox.

A wealth distribution model with a non-Maxwellian collision kernel

A non-Maxwellian collision kernel is employed to study the evolution of wealth distribution in a multi-agent society.The collision kernel divides agents into two different groups under certain conditions. Applying the kinetic theory of rarefied gases, we construct a two-group kinetic model for the evolution of wealth distribution. Under the continuous trading limit, the Fokker–Planck equation is derived and its steady-state solution is obtained. For the non-Maxwellian collision kernel, we find a suitable redistribution operator to match the taxation. Our results illustrate that taxation and redistribution have the property to change the Pareto index.

Transverse momentum balance of dijets in Xe+Xe collisions at the LHC

We present a theoretical study of the medium modifications of the p_(T)balance (x_(J)) of dijets in Xe+Xe collisions at■.The initial production of dijets was carried out using the POWHEG+PYTHIA8 prescription,which matches the next-toleading-order (NLO) QCD matrix elements with the parton shower (PS) effect.The SHELL model described the in-medium evolution of nucleus–nucleus collisions using a transport approach.The theoretical results of the dijet xJin the Xe+Xe collisions exhibit more imbalanced distributions than those in the p+p collisions,consistent with recently reported ATLAS data.By utilizing the Interleaved Flavor Neutralisation,an infrared-and-collinear-safe jet flavor algorithm,to identify the flavor of the reconstructed jets,we classify dijets processes into three categories:gluon–gluon (gg),quark–gluon (qg),and quark–quark (qq),and investigated the respective medium modification patterns and fraction changes of the gg,qg,and qq components of the dijet sample in Xe+Xe collisions.It is shown that the increased fraction of qg component at a small x_(J)contributes to the imbalance of the dijet;in particular,the q_(1)g_(2)(quark-jet-leading) dijets experience more significant asymmetric energy loss than the g_(1)q_(2)(gluon-jet-leading) dijets traversing the QGP.By comparing the■of inclusive,■ dijets in Xe+Xe collisions,we observe■.Moreover,ρ_(Xe),P_(b),the ratios of the nuclear modification factors of dijets in Xe+Xe to those in Pb+Pb,were calculated,which indicates that the yield suppression of dijets in Pb+Pb is more pronounced than that in Xe+Xe owing to the larger radius of the lead nucleus.

MD Simulation of Diffusion Behaviors in Collision Welding Processes of Al-Cu, Al-Al, Cu-Cu

To investigate the effects of material combinations and velocity conditions on atomic diffusion behavior near collision interfaces,this study simulates the atomic diffusion behavior near collision interfaces in Cu-Al,Al-Al and Cu-Cu combinations fabricated through collision welding using molecular dynamic(MD)simulation.The atomic diffusion behaviors are compared between similar metal combinations(Al-Al,Cu-Cu)and dissimilar metal combinations(Al-Cu).By combining the simulation results and classical diffusion theory,the diffusion coefficients for similar and dissimilar metal material combinations under different velocity conditions are obtained.The effects of material combinations and collision velocity on diffusion behaviors are also discussed.The diffusion behaviors of dissimilar material combinations strongly depend on the transverse velocity,whereas those of the similar material combinations are more dependent on the longitudinal velocity.These findings can provide guidance for optimizing welding parameters.

Virtual Assembly Collision Detection Algorithm Using Backpropagation Neural Network

As computer graphics technology continues to advance,Collision Detection(CD)has emerged as a critical element in fields such as virtual reality,computer graphics,and interactive simulations.CD is indispensable for ensuring the fidelity of physical interactions and the realism of virtual environments,particularly within complex scenarios like virtual assembly,where both high precision and real-time responsiveness are imperative.Despite ongoing developments,current CD techniques often fall short in meeting these stringent requirements,resulting in inefficiencies and inaccuracies that impede the overall performance of virtual assembly systems.To address these limitations,this study introduces a novel algorithm that leverages the capabilities of a Backpropagation Neural Network(BPNN)to optimize the structural composition of the Hybrid Bounding Volume Tree(HBVT).Through this optimization,the research proposes a refined Hybrid Hierarchical Bounding Box(HHBB)framework,which is specifically designed to enhance the computational efficiency and precision of CD processes.The HHBB framework strategically reduces the complexity of collision detection computations,thereby enabling more rapid and accurate responses to collision events.Extensive experimental validation within virtual assembly environments reveals that the proposed algorithm markedly improves the performance of CD,particularly in handling complex models.The optimized HBVT architecture not only accelerates the speed of collision detection but also significantly diminishes error rates,presenting a robust and scalable solution for real-time applications in intricate virtual systems.These findings suggest that the proposed approach offers a substantial advancement in CD technology,with broad implications for its application in virtual reality,computer graphics,and related fields.

Properties of collective flow and pion production in intermediate-energy heavy-ion collisions with a relativistic quantum molecular dynamics model

The relativistic mean-field approach was implemented in the Lanzhou quantum molecular dynamics transport model(LQMD.RMF). Using the LQMD.RMF, the properties of collective flow and pion production were investigated systematically for nuclear reactions with various isospin asymmetries. The directed and elliptic flows of the LQMD.RMF are able to describe the experimental data of STAR Collaboration. The directed flow difference between free neutrons and protons was associated with the stiffness of the symmetry energy, that is, a softer symmetry energy led to a larger flow difference. For various collision energies, the ratio between the π^(-) and π^(+) yields increased with a decrease in the slope parameter of the symmetry energy. When the collision energy was 270 MeV/nucleon, the single ratio of the pion transverse momentum spectra also increased with decreasing slope parameter of the symmetry energy in both nearly symmetric and neutron-rich systems.However, it is difficult to constrain the stiffness of the symmetry energy with the double ratio because of the lack of threshold energy correction on the pion production.

Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions.However,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world applications.In this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway driving.Within this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step.Thus,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical events.To construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy.Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data.The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios.The proposed risk assessment framework is promising for real-world applications.

A Secure Blockchain-Based Vehicular Collision Avoidance Protocol: Detecting and Preventing Blackhole Attacks

This work aims to examine the vulnerabilities and threats in the applications of intelligent transport systems,especially collision avoidance protocols.It focuses on achieving the availability of network communication among traveling vehicles.Finally,it aims to find a secure solution to prevent blackhole attacks on vehicular network communications.The proposed solution relies on authenticating vehicles by joining a blockchain network.This technology provides identification information and receives cryptography keys.Moreover,the ad hoc on-demand distance vector(AODV)protocol is used for route discovery and ensuring reliable node communication.The system activates an adaptive mode for monitoring communications and continually adjusts trust scores based on packet delivery performance.From the experimental study,we can infer that the proposed protocol has successfully detected and prevented blackhole attacks for different numbers of simulated vehicles and at different traveling speeds.This reduces accident rates by 60%and increases the packet delivery ratio and the throughput of the connecting network by 40%and 20%,respectively.However,extra overheads in delay and memory are required to create and initialize the blockchain network.

Diagnosing ratio of electron density to collision frequency of plasma surrounding scaled model in a shock tube using low-frequency alternating magnetic field phase shift

A non-contact low-frequency(LF)method of diagnosing the plasma surrounding a scaled model in a shock tube is proposed.This method utilizes the phase shift occurring after the transmission of an LF alternating magnetic field through the plasma to directly measure the ratio of the plasma loop average electron density to collision frequency.An equivalent circuit model is used to analyze the relationship of the phase shift of the magnetic field component of LF electromagnetic waves with the plasma electron density and collision frequency.The applicable range of the LF method on a given plasma scale is analyzed.The upper diagnostic limit for the ratio of the electron density(unit:m^(-3))to collision frequency(unit:Hz)exceeds 1×10^(11),enabling an electron density to exceed 1×10^(20)m^(-3)and a collision frequency to be less than 1 GHz.In this work,the feasibility of using the LF phase shift to implement the plasma diagnosis is also assessed.Diagnosis experiments on shock tube equipment are conducted by using both the electrostatic probe method and LF method.By comparing the diagnostic results of the two methods,the inversion results are relatively consistent with each other,thereby preliminarily verifying the feasibility of the LF method.The ratio of the electron density to the collision frequency has a relatively uniform distribution during the plasma stabilization.The LF diagnostic path is a loop around the model,which is suitable for diagnosing the plasma that surrounds the model.Finally,the causes of diagnostic discrepancy between the two methods are analyzed.The proposed method provides a new avenue for diagnosing high-density enveloping plasma.

A self-organization formation configuration based assignment probability and collision detection

The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-interest and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization interests can effectively complete the task formation.

Collision off-axis position dependence of relativistic nonlinear Thomson inverse scattering of an excited electron in a tightly focused circular polarized laser pulse

This paper presents a novel view of the impact of electron collision off-axis positions on the dynamic properties and relativistic nonlinear Thomson inverse scattering of excited electrons within tightly focused, circularly polarized laser pulses of varying intensities. We examine the effects of the transverse ponderomotive force, specifically how the deviation angle and speed of electron motion are affected by the initial off-axis position of the electron and the peak amplitude of the laser pulse. When the laser pulse intensity is low, an increase in the electron's initial off-axis distance results in reduced spatial radiation power, improved collimation, super-continuum phenomena generation, red-shifting of the spectrum's harmonic peak, and significant symmetry in the radiation radial direction. However, in contradiction to conventional understandings,when the laser pulse intensity is relatively high, the properties of the relativistic nonlinear Thomson inverse scattering of the electron deviate from the central axis, changing direction in opposition to the aforementioned effects. After reaching a peak, these properties then shift again, aligning with the previous direction. The complex interplay of these effects suggests a greater nuance and intricacy in the relationship between laser pulse intensity, electron position, and scattering properties than previously thought.

Age and geochemical evolution of granite magmatism in Olkhon region from Caledonian syncollisional ore-free granite to the rare metal granite and pegmatite of Middle Paleozoic intraplate setting

The detailed description of two granite complexes in the Olkhon subterrane is given.The Early Paleozoic Sharanur complex was formed by granitization of gneisses of the Olkhon series.It includes migmatites,granite-gneisses,granites and pegmatites of normal alkalinity;they belong to the type of syncollisional granites.The Middle Paleozoic Aya granite complex includes mother Aya massif of amazonite-bearing granites and several types of rare-metal pegmatites.They have elevated alkalinity,low of Ba,Sr,and high LILE and HFSE elements contents.The Aya pegmatites lie in northwest cracks of stretching and associated with the rise of the territory under the influence of the North Asian plume.These cracks and pegmatites mark the beginning of a new intraplate geodynamic setting.Two geochemical types are distinguished among the pegmatites of this complex.These are amazonite pegmatites of Li-F type with Ta mineralization and complex type pegmatite with Be-Rb-Nb-Ta and Li-F mineralization(the Ilixin vein).The Tashkiney pegmatite vein is similar to Ilixin,but lies in the gneisses of the Olkhon series.It shows high concentrations of Be,Nb,Ta,as well as W,Sn,but lacks Li and F,due to a greater depth and higher temperature of the melt crystallization of this pegmatite.

The study of intelligent algorithm in particle identification of heavy-ion collisions at low and intermediate energies

Traditional particle identification methods face timeconsuming,experience-dependent,and poor repeatability challenges in heavy-ion collisions at low and intermediate energies.Researchers urgently need solutions to the dilemma of traditional particle identification methods.This study explores the possibility of applying intelligent learning algorithms to the particle identification of heavy-ion collisions at low and intermediate energies.Multiple intelligent algorithms,including XgBoost and TabNet,were selected to test datasets from the neutron ion multi-detector for reaction-oriented dynamics(NIMROD-ISiS)and Geant4 simulation.Tree-based machine learning algorithms and deep learning algorithms e.g.TabNet show excellent performance and generalization ability.Adding additional data features besides energy deposition can improve the algorithm’s performance when the data distribution is nonuniform.Intelligent learning algorithms can be applied to solve the particle identification problem in heavy-ion collisions at low and intermediate energies.