Microscopic Scenario Research Articles

Assessing Traffic-Flow Safety at Various Levels of Autonomous-Vehicle Market Penetration

This study analyzes the impact of autonomous-vehicle (AV) market-penetration rates on traffic-flow safety using a genetic algorithm. We set up a microscopic traffic-simulation scenario on a 640 m section of the US I-101 freeway using VISSIM, a microscopic traffic-simulation software. The results of analyzing the number of conflicts according to the introduction rate of autonomous vehicles showed that the number of conflicts increased as the introduction rate increased up to 30%, and then decreased from 40% or more. In this study, it was assumed that autonomous vehicles can avoid dangerous situations, so it is judged that this is the result of an increase in the traffic volume of autonomous vehicles and a decrease in the traffic volume of conventional vehicles. When planning an exclusive lane for autonomous vehicles, it is judged that it is desirable to install two exclusive lanes on the left side until the introduction rate of autonomous vehicles reaches 30%. When the introduction rate of autonomous vehicles is 40–90%, the risk of accidents between autonomous vehicles and conventional vehicles decreases, and the traffic volume of autonomous vehicles is higher than that of conventional vehicles. Therefore, it is judged that it is desirable to operate a mixed road where autonomous vehicles and conventional vehicles can drive together rather than operating an exclusive lane for autonomous vehicles.

Using Probe Counts to Provide High-Resolution Detector Data for a Microscopic Traffic Simulation

Microscopic traffic simulations have become increasingly important for research targeting connected vehicles. They are especially appreciated for enabling investigations targeting large areas, which would be practically impossible or too expensive in the real world. However, such large-scale simulation scenarios often lack validation with real-world measurements since these data are often not available. To overcome this issue, this work integrates probe counts from floating car data as reference counts to model a large-scale microscopic traffic scenario with high-resolution detector data. To integrate the frequent probe counts, a road network matching is required. Thus, a novel road network matching method based on a decision tree classifier is proposed. The classifier automatically adjusts its cosine similarity and Hausdorff distance-based similarity metrics to match the network’s requirements. The approach performs well with an F1-score of 95.6%. However, post-processing steps are required to produce a sufficiently consistent detector dataset for the subsequent traffic simulation. The finally modeled traffic shows a good agreement of 95.1%. with upscaled probe counts and no unrealistic traffic jams, teleports, or collisions in the simulation. We conclude that probe counts can lead to consistent traffic simulations and, especially with increasing and consistent penetration rates in the future, help to accurately model large-scale microscopic traffic simulations.

A microscopic scenario on recovery mechanisms under waterlogging and submergence stress in rice.

Adaptive traits in rice responding to flooding, a compound stress, are associated with morpho-anatomical and physiological changes which are regulated at the genetic level. Therefore, understanding submergence stress tolerance in rice will help development of adapted cultivars that can help mitigate agricultural losses. Rice is an important dietary component of daily human consumption and is cultivated as a staple crop worldwide. Flooding is a compound stress which imposes significant financial losses to farmers. Flood-affected rainfed rice ecosystems led to the development of various adaptive traits in different cultivars for their optimal growth and survival. Some cultivars can tolerate hypoxia by temporarily arresting elongation and conserving their energy sources, which they utilize to regrow after the stress conditions subside. However, few other cultivars rapidly elongate to escape hypoxia using carbohydrate resources. These contrasting characters are regulated at the genetic level through different quantitative trait loci that contain ERF transcription factors (TFs), Submergence and Snorkels. TFs can simultaneously activate the transcription of various genes involved in stress and development responses. These TFs are of prime importance because the introgressed and near-isogenic lines showed promising results with increased submergence tolerance without affecting yield or quality. However, the entire landscape of submergence tolerance is not entirely depicted, and further exploration in the field is necessary to understand the mechanism in rice completely. Therefore, this review will highlight the significant adaptive traits observed in flooded rice varieties and how they are regulated mechanistically.

Spectral- and spatial-based multi-focus image fusion method towards multi-layer nonwovens

In the microscopic imaging scenario where the object thickness exceeds the depth of field of the microscope, multi-focus image fusion (MFF) is an effective method to generate an all-in-focus image. However, for nonwoven fabric for which the captured image number is up to 100 or more, the existing methods often underperform in areas near the fiber edges, owing to image ghosting and noise accumulation caused by the platform moving. To address the above problem, this paper presents a method designed to fuse multi-layer micro-images based on the combination of spectral and spatial features of the images. Firstly, the spectral domain-based map is generated by decomposition and reconstruction of the high-frequency and low-frequency components of the images, aimed at obtaining the edge information. Simultaneously, the spatial domain-based fuse map is built through sharpness measurement, referring to visual perception. Finally, the two methods are combined via an optimized weight to obtain an all-in-focus fused image. Four groups of real-world data consisting of 100 multi-focus nonwoven images are utilized to verify the superiority of this method. The experimental results demonstrate that the proposed method can obtain satisfactory performance in terms of both human visual evaluation and objective evaluation compared with the image fusion framework based on the convolutional neural network, MFF, region-based image fusion algorithm and convolutional neural network state-of-the-art fusion methods.

Structure and Transport Properties of Poly(ethylene oxide)-Based Cross-Linked Polymer Electrolytes─A Molecular Dynamics Simulations Study

We present an extensive molecular dynamics (MD) simulation study of poly(ethylene oxide) (PEO) based densely cross-linked polymers, focussing on structural properties as well as the systems dynamics in the presence of lithium salt. Motivated by experimental findings for networks with short PEO strands we employ a combination of LiTFSI (Lithium bis(trifluoromethanesulfonyl)imide) and LiDFOB (Lithium difluoro(oxalato)borate). Recently, it has been shown that such multi-salt systems outperform classical single salt systems (Shaji et al., Energy Storage Materials, 2022, 44, 263). To analyse the microscopic scenario we employ an analytical model, originally developed for non-cross-linked polymer electrolytes or blends (Maitra et al., Phys. Rev. Lett., 2007, 98, 227802 and Diddens et al., J. Electrochem. Soc., 2017, 164, E3225-E3231). Excluding very short PEO strands, the local dynamics is only slightly restricted compared to linear PEO and is not significantly dependent on the network structure. The transfer of lithium ions between PEO chains and the motion along the polymer backbone may be controlled through the employed salt.

Impact of Deep Reinforcement Learning on Variable Speed Limit strategies in connected vehicles environments

The Variable Speed Limit (VSL) control is considered in the context of connected vehicles acting as moving sensors, while their obedience to speed limit is enforced by a mandatory Intelligent Speed Adaptation (ISA) system. The objective of this study is to extend spatially static differential VSL control by introducing novel VSL strategies that are based on spatially dynamic speed limit zones. The spatial configuration of speed limit zones requires a novel traffic state representation based on the set of consecutive matrices which encode each vehicle position and speed within the controlled motorway during the control time step. The actions for all proposed VSL strategies are computed by the same Deep Reinforcement Learning (DRL) approach based on the Deep Deterministic Policy Gradient (DDPG) architecture. The DDPG learning models contain integration of Convolution and Long Short-Term Memory (LSTM) known as ConvLSTM layers, along with the Convolution and Fully Connected layers. Thus, those models can learn complex spatio-temporal traffic dynamics based on proposed traffic state representation. The results show that proposed VSL strategies have achieved higher overall motorway throughput compared to one which is based on the static speed limit zones and baseline cases (no-control and Simple Proportional Speed Controller algorithm). Simultaneously, they achieved a minimal increase in the number of aggressive braking, while the average headway is increased. All proposed VSL control approaches are simulated and analyzed by using a synthetic microscopic motorway model and characteristic traffic scenario for urban motorways.

Ultradilute Quantum Liquid of Dipolar Atoms in a Bilayer.

We show that ultradilute quantum liquids can be formed with ultracold bosonic dipolar atoms in a bilayer geometry. Contrary to previous realizations of ultradilute liquids, there is no need for stabilizing the system with an additional repulsive short-range potential. The advantage of the proposed system is that dipolar interactions on their own are sufficient for creation of a self-bound state and no additional short-range potential is needed for the stabilization. We perform quantum MonteCarlo simulations and find a rich ground-state phase diagram that contains quantum phase transitions between liquid, solid, atomic gas, and molecular gas phases. The stabilization mechanism of the liquid phase is consistent with the microscopic scenario in which the effective dimer-dimer attraction is balanced by an effective three-dimer repulsion. The equilibrium density of the liquid, which is extremely small, can be controlled by the interlayer distance. From the equation of state, we extract the spinodal density, below which the homogeneous system breaks into droplets. Our results offer a new example of a two-dimensional interacting dipolar liquid in a clean and highly controllable setup.

The Supportive Role of NSC328382, a P2X7R Antagonist, in Enhancing the Inhibitory Effect of CRID3 on NLRP3 Inflammasome Activation in Rats with Dextran Sodium Sulfate-Induced Colitis.

PurposeThe NLRP3 inflammasome is a substantial component of the inflammation process. The complex pathogenesis of and the implication of a vast number of components in the inflammasome-activation pathway prompted us to search for compounds that have a wide therapeutic index and act at the level of multiple cellular targets. Although CRID3 blocks NLRP3 with high specificity in the laboratory, clinical trials of the compound reported weaker potency.MethodsWe used NSC328382, a P2X7R antagonist, as an adjunctive therapy and generated a strategy to potentiate the effects of CRID3 in rats with DSS-induced colitis.ResultsNSC328382/CRID3 combined therapy exhibited a significantly increased efficacy compared with either of the monotherapies. NSC328382/CRID3 was more efficient in 1) attenuating colon shortening and disease activity; 2) improving goblet cell density and both the macroscopic and microscopic scenario of the injured colon; 3) improving the antioxidant defense mechanisms of the inflamed colon against oxidative stress; and 4) mitigating the inflammation state by downregulating the proinflammatory cytokines. Pyroptotic cell death was also conspicuously restrained. Additionally, NSC328382 interrupted the MyD88/NF-κB axis. Moreover, NSC328382/CRID3 exhibited the ability to alter Th1/Th2 dominance.ConclusionThe clinical application of NSC328382/CRID3 may result in the generation of a novel approach for the treatment of IBDs.

Using coarse-grained molecular dynamics to understand the effect of ionic liquids on the aggregation of Pluronic copolymer solutions.

This study is aimed to enhance the understanding of the interaction between ionic liquids (ILs) and non-ionic Pluronic triblock copolymers in aqueous two-phase micellar systems (ATPMS) used for the selective separation/purification of hydrophobic biomolecules. The ILs allow a precise control of the cloud point phase separation temperature (CPT), particularly important when the stability of the molecule is highly dependent on temperature. The effect of choline-based ILs, with two different counter-anions, chloride and hexanoate, was evaluated using molecular dynamics simulations (MD) for F-68 and L-35 Pluronic aqueous solutions. The simulations revealed the role played by the anions during the Pluronic self-assembly, with choline chloride hindering Pluronic aggregation and the choline hexanoate favouring micelle formation and coalescence, in agreement with the experimental data. A detailed study of the accessible surface area of Pluronic showed a progressive dehydration of the Pluronic hydrophilic micelle corona in choline hexanoate mixtures promoting inter-micelle interactions and, consequently, micelle coalescence. With the addition of choline hexanoate, it was observed that the hydrophilic segments, which form the micelle corona, twisted towards the Pluronic micelle core. The electrostatic interaction is also shown to play a key role in this IL-Pluronic aqueous solution, as the hexanoate anions are accommodated in the Pluronic micelle core, while the choline cations are hosted by the Pluronic micelle corona, with the ions interacting with each other during the self-assembly process. In addition, a comparison study of F-68 and L-35 aqueous solutions shows that the IL impact depends on the length of the Pluronic hydrophilic segment. This work provides a realistic microscopic scenario of the complex interactions between Pluronic copolymers and ILs.

Verification of z-Scaling in p + p, $$\bar {p} + p$$ and Au + Au Collisions at RHIC, Tevatron and LHC

Experimental data on transverse momentum spectra of charged hadrons, strange particles, top quark and jets produced in $$p + p$$ and $$\bar {p} + p$$ collisions obtained at RHIC, Tevatron, and LHC are analyzed in the framework of $$z$$-scaling approach. The concept of the $$z$$-scaling based on fundamental principles of self-similarity, locality, and fractality of hadron interactions is verified over a wide range of collision energy and transverse momentum for different particle species. General properties of the data $$z$$-presentation are reviewed. A microscopic scenario of constituent interactions developed within the $$z$$-scaling scheme is used to study the dependence of momentum fractions and recoil mass on the collision energy, transverse momentum and mass of produced inclusive particle, and to estimate the constituent energy loss. Results of analysis in the framework of $$z$$-scaling of the negative particle spectra in $${\text{Au}} + {\text{Au}}$$ collisions obtained by the STAR Collaboration in the first phase of the Beam Energy Scan program at RHIC are presented. New indication on self-similarity of fractal structure of nuclei and fragmentation processes is found.

Suppression of the outwards-dispersing branches in hour-glass magnetic spectra induced by nanoscale phase separation in La2−xSrxCoO4

Here, we reinvestigate the underlying charge and magnetic correlations in ${\mathrm{La}}_{2\ensuremath{-}x}{\mathrm{Sr}}_{x}{\mathrm{CoO}}_{4}$ within a combined study of muon spin relaxation ($\ensuremath{\mu}\mathrm{SR}$), x-ray photon correlation spectroscopy, synchrotron radiation single-crystal x-ray diffraction, and neutron-scattering measurements. For ${\mathrm{La}}_{2\ensuremath{-}x}{\mathrm{Sr}}_{x}{\mathrm{CoO}}_{4}$ around 1/3 hole-doping, the significant charge correlations that are responsible for the emergence of hour-glass magnetic spectra are found to be slowly fluctuating checkerboard charge ordering (CBCO) correlations with an onset temperature being independent of hole-doping. This reveals a local origin of the CBCO correlations in the rather ionic cobaltates, thus being distinct from the more covalent nickelates. Moreover, we report the observation of a very similar temperature dependence of the intensities of in-plane high- and low-energy excitations within the ${\mathrm{La}}_{2\ensuremath{-}x}{\mathrm{Sr}}_{x}{\mathrm{CoO}}_{4}$ hour-glass spectrum. This observation shows that nano phase separation is distinct from conventional phase separation and that there is a coupling between nanometer-sized undoped and hole-doped islands. Based on this, it is possible to propose a microscopic scenario for the suppression of the outwards-dispersing branches in hour-glass magnetic spectra.

Microscopic evolution of solid-hydrogen shells under the ultrafast dynamic compression

Starting from the same initial structure, solid-hydrogen shells were dynamically compressed at different implosion velocities by performing large-scale molecular dynamic simulations to explore their microscopic evolution under the ultrafast dynamic compression. The ultrafast dynamic compression is revealed to prohibit the solid shell from the structural phase transition, while the phase transition is first initiated at the inner surface of the shell. A faster compression generates a higher pressure in the shell at a given convergence ratio by preventing the hydrogen atoms from ejecting out of the solid-hydrogen shell to release pressure. These results provide a glimpse of the microscopic scenario of the solid-hydrogen shell at early times during the ultrafast dynamic compression, suggesting that the implosion velocity must be carefully determined to mitigate the growth of hydrodynamic instabilities on the inner surface of the solid-hydrogen shell.

Colossal barocaloric effects in plastic crystals

Refrigeration is of vital importance for modern society-for example, for food storage and air conditioning-and 25 to 30 per cent of the world's electricity is consumed for refrigeration1. Current refrigeration technology mostly involves the conventional vapour compression cycle, but the materials used in this technology are of growing environmental concern because of their large global warming potential2. As a promising alternative, refrigeration technologies based on solid-state caloric effects have been attracting attention in recent decades3-5. However, their application is restricted by the limited performance of current caloric materials, owing to small isothermal entropy changes and large drivingmagnetic fields. Here we report colossal barocaloric effects (CBCEs) (barocaloric effects are cooling effects of pressure-induced phase transitions) in a class of disordered solids called plastic crystals. The obtained entropy changes in a representative plastic crystal, neopentylglycol, are about 389 joules per kilogram per kelvin near room temperature. Pressure-dependent neutron scattering measurements reveal that CBCEs in plastic crystals can be attributed to the combination of extensive molecular orientational disorder, giant compressibility and highly anharmonic lattice dynamics of these materials. Our study establishes the microscopic mechanism of CBCEs in plastic crystals and paves the way to next-generation solid-state refrigeration technologies.

Fractality in hadron interactions: a conservation law and quantization of fractal dimensions

A microscopic scenario of constituent interactions in high energy collisions of hadrons and nuclei is studied. The concept is based on the z-scaling of inclusive spectra observed in a wide range of collision energies, multiplicity densities, momenta, and angles of detected particles. We bring arguments that, due to the fractality and self-similarity of the hadron interactions assumed in the z-scaling scheme, there exists a conservation law of a new quantity named “fractal cumulativity.” The conserved quantity is proportional to the corresponding fractal dimensions and is a simple function of the respective momentum fractions. Based on statistical ideas and entropy considerations we demonstrate that the fractal dimensions possess quantum character.

Role of hydrogen bonding in hysteresis observed in sorption-induced swelling of soft nanoporous polymers

Hysteresis is observed in sorption-induced swelling in various soft nanoporous polymers. The associated coupling mechanism responsible for the observed sorption-induced swelling and associated hysteresis needs to be unraveled. Here we report a microscopic scenario for the molecular mechanism responsible for hysteresis in sorption-induced swelling in natural polymers such as cellulose using atom-scale simulation; moisture content and swelling exhibit hysteresis upon ad- and desorption but not swelling versus moisture content. Different hydrogen bond networks are examined; cellulose swells to form water–cellulose bonds upon adsorption but these bonds do not break upon desorption at the same chemical potential. These findings, which are supported by mechanical testing and cellulose textural assessment upon sorption, shed light on experimental observations for wood and other related materials.

Distributed Optimal Traffic Lights Design for Large-Scale Urban Networks

In this paper, we deal with the problem of dynamical assignment of traffic light schedules in large-scale urban networks. We present a model for signalized traffic networks, based on the cell transmission model, and then a simplified model based on averaging theory. The control objective is to improve traffic, optimizing traffic indexes such as total travel distance and density balancing. We design a scheme that decides the duty cycles of traffic lights, by solving a convex program. The optimization is done in real time, at each cycle of traffic lights, so as to take into account variable traffic demands. The scalability problem is tackled through the synthesis of a distributed optimization algorithm; this reduces the computational load significantly, since the large optimization problem is broken into small local subproblems, whose size does not grow with the size of the network, together with iterative exchanges of messages with few neighbor subproblems. The performance of the proposed approach is evaluated via numerical simulations in two different scenarios: a macroscopic (MATLAB-based) Manhattan grid and a microscopic scenario (based on Aimsun simulator) reproducing a portion of the city of Grenoble, France.

New indication on scaling properties of strangeness production in pp collisions at RHIC

Experimental data on transverse momentum spectra of strange particles [Formula: see text] produced in [Formula: see text] collisions at [Formula: see text] obtained by the STAR and PHENIX collaborations at RHIC are analyzed in the framework of [Formula: see text]-scaling approach. The concept of the [Formula: see text]-scaling is based on fundamental principles of self-similarity, locality, and fractality of hadron interactions at high energies. General properties of the data [Formula: see text]-presentation are studied. Self-similarity of fractal structure of protons and fragmentation processes with strange particles is discussed. A microscopic scenario of constituent interactions developed within the [Formula: see text]-scaling scheme is used to study the dependence of momentum fractions and recoil mass on the collision energy, transverse momentum and mass of produced inclusive particle, and to estimate the constituent energy loss. We consider that obtained results can be useful in study of strangeness origin, in searching for new physics with strange probes, and can serve for better understanding of fractality of hadron interactions at small scales.

Advanced External Sulfate Attack Testing and Performance Specifications: Different Sample Geometries Testing

External sulfate attacks induce severe deterioration of concrete because of several phenomena: leaching, precipitation of expansive products, aggregates loss, and cracking. A new methodology has been developed to assess sulfate resistance of cement-based materials. We can actually estimate the nature of leached and precipitated minerals, and the microscopic volume variations due to each of the principal sulfate attack phenomena, from relatively simple monitoring parameters: sample mass, hydrostatic weighing, and the amount of leached hydroxide. Quantitative information is given on the mineralogical volume or mass variations, leading us to a phenomena decoupling and a better understanding of the sulfate attack mechanism. After we established the microscopic volume variation scenario, we defined a new performance criterion, the averaged density, capable to describe the tested sample performance variation according to the sample internal state indications given by this criterion. We applied the developed strategy on three different filled and hollow geometries in order to study the effect of the sample geometry on sulfate attack mechanism. The study shows almost the same degradation mechanism: the same microscopic volume variations entrained by the different sulfate attack phenomena. However the hollow tubes promote different precipitated mineral than the two others geometries, due to the different ionic and pH profiles between filled and hollow samples which affects the nature of formed sulfate minerals.

Reflections on the Fischer-Tropsch synthesis: Mechanistic issues from a surface science perspective

The current paper presents a mechanistic view on important steps in the Fischer-Tropsch synthesis on cobalt catalysts, inspired by surface science studies. By revisiting the relation between activity and selectivity that results from the ASF assumption we highlight that knowledge about the number of growing chains as well as their residence time (∼growth rate) is of crucial importance to sketch a physically realistic scenario for FTS. This motivates further investigations into the microscopic scenario for FTS chain growth on fcc cobalt nanoparticles, by looking into the reaction mechanism in relation to surface structure and by determining the activation energies for key elementary steps. Such studies indicate that the modest activity of Co FTS catalysts might very well be attributable to the difficulty to remove chemisorbed oxygen from the metallic surface, rather than to dissociation of CO, which was found to proceed readily at step edge sites. Chain growth is envisaged to take place on the close-packed surfaces, with chain initiation via CH+CH to form acetylene, followed by hydrogenation to form ethylidyne, CCH3, a reaction that is shown to be promoted by co-adsorbed CO. Ethylidyne then couples with CH to form propyne, HCCCH3, etc. We propose that a fairly large number of surface sites is involved in the growth of a single chain. In such a “growth ensemble” multiple active step sites produce CHx monomer species that spill over onto the same close-packed coupling terrace, where one or only a few chains grow at the same time. In such a scenario diffusion of hydrocarbonaceous surface species is an essential step in the overall reaction sequence. We explore which factors need to be taken into account when considering of CxHy species under realistic reaction conditions. In addition, we note that the coupling reaction itself, via CH+CCnH2n+1, is a source of growing chain mobility.

Bridging soft-hard transport properties of quark-gluon plasmas with CUJET3.0

A new model of jet quenching in nuclear collisions, CUJET3.0, is constructed by generalizing the perturbative QCD based CUJET2.0 model to include two complementary non-perturbative features of the QCD confinement cross-over phase transition near $T_c\approx 160$ MeV: (1) the suppression of quark and gluon degrees of freedom and (2) the emergence of chromo-magnetic monopole degrees of freedom. Such a semi-Quark-Gluon-Monopole Plasma (sQGMP) microscopic scenario is tested by comparing predictions of the leading hadron nuclear modification factors, $R^h_{AA}(p_T>10{\rm GeV/c},\sqrt{s})$, and their azimuthal elliptic asymmetry $v^h_2(p_T>10{\rm GeV/c},\sqrt{s})$ with available data on $h=\pi,D,B$ jet fragments from nuclear collisions at RHIC($\sqrt{s}=0.2$ ATeV) and LHC($\sqrt{s}$=2.76 ATeV). The sQGMP model is shown to solve the long standing $R_{AA}$ vs $v_2$ puzzle by predicting a maximum of the jet quenching parameter field $\hat{q}(E,T)/T^3$ near $T_c$. The consistency of jet quenching with observed bulk perfect fluidity is demonstrated by extrapolating the sQGMP $\hat{q}$ down to thermal energy $E\sim 3 T$ scales and showing that the sQGMP shear viscosity to entropy density ratio $\eta/s \approx T^3/\hat{q}$ falls close to the unitarity bound, $1/4\pi$, in the range $(1-2)T_c$. Detailed comparisons of CUJET2.0 and CUJET3.0 reveal that the remarkably different $\hat{q}(T)$ could be consistent with the same $R_{AA}$ data and could only be distinguished by anisotropy observables. These findings demonstrate clearly the inadequacy of focusing on the jet path averaged quantity $<\hat{q}>$ as the only relevant medium property to characterize jet quenching, and point to the crucial roles of other essential factors, such as the chromo electric and magnetic composites of the plasma, the screening masses and the running couplings at multiple scales that all strongly influence jet energy loss.