bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics
Authors: Chen Peiwen , Zhu Wenliang , Yu Chaogang , Sun Ningyuan , Xue Wenshen 
Published: September 2023

AbstractTo study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process.
Outage performance prediction of cooperative vehicle network based on sparrow search algorithm based on back‐propagation neural network
Authors: Li Ya , Zhang Yu , Tian Xinji , Liu Ruipeng 
Published: September 2023

AbstractWith the support of the sixth‐generation mobile networks (6G) technology, the Internet‐of‐Vehicle (IoV) can realize the perception and monitoring of vehicle road information. However, due to the change of network topology and various environment, the reliable performance of the communication link is facing challenges. For the sake of improving communication quality, a cooperative vehicular network (CVN) system is established, which adopts cooperative communication and multiple input multiple output (MIMO) technology. According to the signal‐to‐noise ratio (SNR) threshold of relay vehicles, using hybrid decode‐amplify‐forward (HDAF) protocol and combining with antenna selection, the analytical expression of outage probability (OP) with Meijer‐G function is obtained. For predicting the OP accurately, the sparrow search algorithm based on back‐propagation neural network (SSA‐BPNN) is put forward. The simulation results show that the cascade order of the channels has a negative effect on the OP. Meanwhile, the prediction accuracy of SSA‐BPNN is 64.8% higher than that of BPNN, and 98.96% greater than that of general regression neural network, and the convergence rate is faster than ICS‐BPNN.
Reinforcement learning for the traveling salesman problem: Performance comparison of three algorithms
Authors: Wang Jiaying , Xiao Chenglong , Wang Shanshan , Ruan Yaqi 
Published: September 2023

AbstractTravelling salesman problem (TSP) is one of the most famous problems in graph theory, as well as one of the typical nondeterministic polynomial time (NP)‐hard problems in combinatorial optimization. Reinforcement learning (RL) has been widely regarded as an effective tool for solving combinatorial optimization problems. This paper attempts to solve the TSP problem using different reinforcement learning algorithms and evaluated the performance of three RL algorithms (Q‐Learning, SARSA, and Double Q‐Learning) under different reward functions, ε‐greedy decay strategies, and running times. A comprehensive analysis and comparison of the three algorithms mentioned above were conducted in the experiment. First, the experimental results indicate that the Double Q‐Learning algorithm is the best algorithm. Among the eight TSP instances, the Double Q‐Learning algorithm outperforms the other two algorithms in five instances. Additionally, it has shorter runtimes compared to the SARSA algorithm and similar runtimes to the Q‐Learning algorithm across all instances. Second, upon analysing the results, it was found that using the reward strategy contributes to obtaining the best results for all algorithms. Among the 24 combinations of 3 algorithms and 8 instances, 17 combinations achieved the best results when the reward strategy was set to .
The role of supernovae inside AGN jets in UHECR acceleration
Authors: Bosch-Ramon V. 
Published: September 2023

Context. Jets of active galactic nuclei are potential accelerators of ultra high-energy cosmic rays. Supernovae can occur inside these jets and contribute to cosmic ray acceleration, particularly of heavy nuclei, but that contribution has been hardly investigated so far.
Aims. We carried out a first dedicated exploration of the role of supernovae inside extragalactic jets in the production of ultra high-energy cosmic rays.
Methods. We characterized the energy budget of supernova-jet interactions, and the maximum possible energies of the particles accelerated in those events, likely dominated by heavy nuclei. This allowed us to assess whether these interactions can be potential acceleration sites of ultra high-energy cosmic rays, or at least of their seeds. For that, we estimated the cosmic ray luminosity for different galaxy types, and compared the injection rate of cosmic ray seeds into the jet with that due to galactic cosmic ray entrainment.
Results. Since the supernova is fueled for a long time by the luminosity of the jet, the energy of a supernova-jet interaction can be several orders of magnitude greater than that of an isolated supernova. Thus, despite the low rate of supernovae expected to occur in the jet, they could still provide more seeds for accelerating ultra high-energy particles than cosmic ray entrainment from the host galaxy. Moreover, these interactions can create sufficiently efficient accelerators to be a source of cosmic rays with energies ≳10 EeV.
Conclusions. Supernova-jet interactions can contribute significantly to the production of ultra high-energy cosmic rays, either directly by accelerating these particles themselves or indirectly by providing pre-accelerated seeds.
Statistical validation of ionospheric electron density profiles retrievals from GOES geosynchronous satellites
Authors: Zakharenkova Irina , Cherniak Iurii , Gleason Scott , Hunt Douglas , Freesland Douglas , Krimchansky Alexander , McCorkel Joel , Ramsey Graeme , Chapel Jim 
Published: September 2023

In this paper, we discuss a novel retrieval of ionospheric electron density profiles using the Radio Occultation (RO) technique applied to measurements captured by the Global Positioning System (GPS) receivers onboard two Geostationary Operational Environmental Satellites (GOES). The GOES satellites operate at ~35,800 km altitude and are primarily weather satellites that operationally contribute continuous remote-sensing data for real-time weather forecasting, as well as near-Earth environment monitoring and Sun observations. The GPS receivers onboard GOES-16 and GOES-17 satellites can track GPS signals propagated through the Earth’s atmosphere, and although the receivers are primarily designed for navigation and station-keeping maneuvers, these GPS measurements that traverse the Earth’s atmosphere can be used to retrieve the ionospheric electron density profiles. This process poses a range of technical challenges. GOES RO links are different from the traditional low Earth orbit (LEO) RO geometry since the receiver is located in an orbit that is higher in altitude than the GPS constellation of transmitters. Additionally, the GPS receivers onboard GOES satellites provide only single-frequency GPS L1 observations and have clocks much less stable than those typically used for RO measurements. The geographical distribution of the retrieved GEO-based RO profiles was found to be uniquely constrained and repeatable based on the relative geostationary fixed positions in the Earth-Centered Earth Fixed reference frame with respect to the GPS constellation orbiting at lower altitude, and significantly different from the coverage patterns of LEO-based RO missions. We demonstrate the successful application of the proposed RO profiling technique with a statistically significant set of GPS observations from GOES-16 and GOES-17 satellites over several years of data collection. This enabled us to retrieve more than 10,000 ionospheric electron density profiles with a maximum altitude of up to 1000–2000 km, much higher than any existing LEO-based RO mission. We demonstrate good performance of GEO-based RO measurements for properly specifying the vertical distribution of ionospheric plasma density by comparing the profiles dataset from the GOES RO experiment with independent reference observations – ground-based ionosondes and LEO-based RO missions, as well as model simulation results provided by the empirical International Reference Ionosphere model. Over multiple years of observations, statistical analysis of discrepancies between the ionospheric F2 layer peak parameters (peak density and height) derived from geosynchronous GOES observations and reference measurements was conducted. This analysis reveals a very good agreement between GOES RO electron density profiles and independent types of measurements in both the F2 peak and the profile shape.
The concept of “interaction” in debates on human–machine interaction
Authors: Schleidgen Sebastian , Friedrich Orsolya , Gerlek Selin , Assadi Galia , Seifert Johanna 
Published: September 2023

AbstractThe concept of “interaction” is central to debates on Human–machine interaction (HMI). At the same time, however, it is vague and ambiguous: “interaction” is understood in different ways within and between the scientific disciplines involved in debates on HMI. Ultimately, this makes it difficult to reasonably debate questions of ethics, politics, engineering, and the sciences regarding HMI. Against this background, we elaborate and analyze the different meanings and dimensions of the term “interaction” in the disciplines and discourses relevant to debates on modern HMI. For this purpose, we introduce a four-dimensional SMPC model, according to which “interaction” is specified with a view to its subjects, modes, purposes, and contexts. With this, we aim to provide a basis for a fruitful intra- and particularly interdisciplinary discourse on HMI.
Comparative first-principles structural and vibrational properties of rutile and anatase TiO2
Authors: Ghose Krishna K , Liu Yun , Frankcombe Terry J 
Published: September 2023

Abstract
The structural and vibrational properties of two polymorphs of TiO2, rutile and anatase, have been investigated by first-principles methods at different levels of exchange-correlational (XC) energy functionals in density functional theory (DFT). Reports in the literature to date are contradictory regarding the stability of the rutile phase using DFT XC-functionals more sophisticated than simple local-density approximation. Here the PBEsol generalized gradient approximation (GGA), TPSS meta-GGA, and HSE06 hybrid functionals have been employed to demonstrate the XC-functional effects on the calculated structural, phonon and thermodynamic properties of rutile and anatase TiO2. Lattice and elastic parameters correctly calculated with these XC-functionals show good agreement with the experimental values. Calculated phonon frequencies generated stable phonon dispersion relations for both rutile and anatase TiO2 when correctly converged, in agreement with the experimental observations. The phonon frequencies along high symmetry Brillouin zone paths and their corresponding phonon density of states showed sensitivity to different levels of XC-functional employed in phonon dispersion prediction. Nevertheless, the thermodynamic properties of rutile and anatase TiO2 estimated by harmonic approximations are in excellent experimental agreement and are effectively invariant to the level of theory employed in the DFT XC-functional.
Application of chaotic colony predation algorithm in electromagnetics
Authors: Hu Kui , Liu Yan , Zhao KunXia 
Published: September 2023

Abstract
The colony predation algorithm (CPA) is a new meta-heuristic algorithm that mimics the predation of animals to improve the radiation properties of antenna arrays. To overcome CPA’s problems of low accuracy and fast convergence, we propose an improved CPA called the chaotic colony predation algorithm (CCPA). The performance of CCPA was investigated in three parts. First, CCPA was tested with four benchmark functions. Then, CCPA was applied to equally spaced linear arrays to suppress the peak side-lobe level (PSLL) and place nulls in the desired directions. Finally, CCPA was used for a pattern synthesis of equally spaced linear arrays to reduce the PSLL under various constraints. Our results show that CCPA performed competitively with other well-known algorithms. Thus, CCPA is a promising option for solving electromagnetic optimization problems.
Terahertz emission with remarkable efficiency through spherical nanoparticles using dark-hollow-Gaussian beams
Authors: Malik Hitendra K , Sharma Dimple 
Published: September 2023

Abstract
Simultaneous tuning of Terahertz (THz) radiation with respect to its frequency, power and focus is still a challenge for the scientific community, because of which its use is lacking in several areas. To achieve such properties, the present work proposes monodisperse graphite nanoparticles (NPs) of spherical shape dispersed in two orthogonal directions with normal vector of their basal planes parallel and perpendicular to the electric field of the dark-hollow-Gaussian beams (DHGBs) used for the generation of THz radiation. The NPs are impinged upon by two DHGBs of slightly different frequencies, which exert a ponderomotive force on the conduction electrons of the NPs. The motion of these electrons under the action of high intensity laser beams constitutes a macroscopic nonlinear current that produces the THz radiation. The well-structured THz emission occurs with the efficiency reaching 10−2 when the NPs resonate with the beating frequency, and they are arranged in their parallel orientations with respect to the electric field of the lasers. The proposal and the obtained results will contribute to the THz science and technology along with their use in medical science and THz time-domain spectroscopy.
NeuSort: an automatic adaptive spike sorting approach with neuromorphic models
Authors: Yu Hang , Qi Yu , Pan Gang 
Published: September 2023

Abstract

Objective. Spike sorting, a critical step in neural data processing, aims to classify spiking events from single electrode recordings based on different waveforms. This study aims to develop a novel online spike sorter, NeuSort, using neuromorphic models, with the ability to adaptively adjust to changes in neural signals, including waveform deformations and the appearance of new neurons. Approach. NeuSort leverages a neuromorphic model to emulate template-matching processes. This model incorporates plasticity learning mechanisms inspired by biological neural systems, facilitating real-time adjustments to online parameters. Results. Experimental findings demonstrate NeuSort’s ability to track neuron activities amidst waveform deformations and identify new neurons in real-time. NeuSort excels in handling non-stationary neural signals, significantly enhancing its applicability for long-term spike sorting tasks. Moreover, its implementation on neuromorphic chips guarantees ultra-low energy consumption during computation. Significance. NeuSort caters to the demand for real-time spike sorting in brain-machine interfaces through a neuromorphic approach. Its unsupervised, automated spike sorting process makes it a plug-and-play solution for online spike sorting.
Plant-inspired rearrangement of liquid in a porous structure for controlled swelling
Authors: Sarokin Yauheni , Aabloo Alvo , Must Indrek 
Published: September 2023

Abstract
Soft robots can adapt to dynamic environments without prior knowledge of their properties. Plants inspire mechanisms for counterbalancing dynamic loads by locally modulating compliance through anisotropic humidity-responsive materials and structures. In addition to well-known passive bilayers, plants may also actively control swelling. The combination of robust hygroscopic material-level response and simple electrical control makes active swelling particularly attractive for technological implementation. However, dynamic swelling demands the development and optimisation of congruent pumping solutions. This work suggests electrohydrodynamic pumping, enabled by highly reversible ion immobilisation at capacitive electrodes, as a particularly suitable low-pressure, high-area liquid displacement solution for active swelling. Local pore fill ratio (PFR) modulation is used as a measure for dynamic liquid displacement and swelling. A method for highly localised (10 μm membrane thickness) assessment of the dynamic variation of PFR in a 400 μm laminate undergoing cross-plane electrokinetic liquid displacement is developed. Two modes for transient PFR modulation were identified: electrokinetic ion transfer and diffusive solvent redistribution, pronounced at high and low voltage scan rates, respectively. The strategic combination of these modes enables various compliance-modulation scenarios. The system contains (within a cycle) a constant amount of liquid in an open network of liquid-filled pores. 30%–75% PFR yielded the highest dynamic PFR modulation: a high amount of empty pores is beneficial, yet a too-low PFR compromises the continuous liquid pathway necessary for electrokinetic pumping. The dynamic nature of internal liquid rearrangement was characterised by relatively fast electrokinetics-driven fluxes (6.3% PFR change in 80 s), followed by a slow equilibration of concentration and PFR. At high scan rates, PFR decreased at positive polarisation, while both positive and negative polarity yielded a similar decrease at low scan rates (5 mV s−1). Localised control over the swelling gradient enables the design of systems that morphologically adapt to complex dynamic loading conditions.
Double-layered blood vessels over 3 mm in diameter extruded by the inverse-gravity technique
Authors: Duong Van Thuy , Nguyen Chanh Trung , Phan Huu Lam , Le Van Phu , Dang Thao Thi , Choi Cholong , Seo Jongmo , Cha Chaenyung , Back Sung Hoon , Koo Kyo-in 
Published: September 2023

Abstract
One of the most promising techniques for treating severe peripheral artery disease is the use of cellular tissue-engineered vascular grafts (TEVGs). This study proposes an inverse-gravity (IG) extrusion technique for creating long double-layered cellular TEVGs with diameters over 3 mm. A three-layered coaxial laminar hydrogel flow in an 8 mm-diameter pipe was realised simply by changing the extrusion direction of the hydrogel from being aligned with the direction of gravity to against it. This technique produced an extruded mixture of human aortic smooth muscle cells (HASMCs) and type-I collagen as a tubular structure with an inner diameter of 3.5 mm. After a 21 day maturation period, the maximal burst pressure, longitudinal breaking force, and circumferential breaking force of the HASMC TEVG were 416 mmHg, 0.69 N, and 0.89 N, respectively. The HASMC TEVG was endothelialised with human umbilical vein endothelial cells to form a tunica intima that simulated human vessels. Besides subcutaneous implantability on mice, the double-layered blood vessels showed a considerably lower adherence of platelets and red blood cells once exposed to heparinised mouse blood and were considered nonhaemolytic. The proposed IG extrusion technique can be applied in various fields requiring multilayered materials with large diameters.
Investigating the microstructure and mechanical properties of deposited metal with ENiCrFe-7 covered electrode
Authors: Zhu Haiyang , Yu Wei , Liu Kun , Weng Xiang , Li Xiaobing , Xu Changzheng , Zou Jiasheng 
Published: September 2023

Abstract
The effect of post weld heat treatment (PWHT) on microstructure and mechanical properties of deposited metal using ENiCrFe-7 covered electrode was investigated. The PWHT was conducted at 615 °C for 24 h. The results showed that three types of precipitates existed in both as-welded and PWHT deposited metals, i.e., NbC carbides, Al-Ti oxides in grains, and M23C6 carbides on grain boundaries. The M23C6 carbides coarsened after PWHT. The room temperature and elevated temperature (350 °C) tensile strength decreased by about 30 MPa, and elongation increased by about 3%–4% after PWHT. The tensile specimens presented ductile fracture feature and the dimples in PWHT condition were larger than that in as-welded condition. The hardness of deposited metal in as-welded condition was higher than that of PWHT condition. The impact toughness showed no significant change after PWHT. Both as-welded and PWHT impact specimens showed a mixed fracture mode with dominant ductile fracture and cleavage fracture.
Prediction of age-hardening behaviour of LM4 and its composites using artificial neural networks
Authors: Gowrishankar M C , Doddapaneni Srinivas , Sharma Sathyashankara , Hegde Ananda , Shettar Manjunath , Karthik B M 
Published: September 2023

Abstract
This research work highlights the prediction of hardness behaviour of age-hardened LM4 and its composites fabricated using a two-stage stir casting method with TiB2 and Si3N4. MATLAB - Artificial Neural Networks is used to predict the age-hardening behaviour of LM4 and its composites. Experiments (hardness and tensile tests) are conducted to collect data for training an ANN model as well as to investigate the effect of reinforcements and age-hardening treatment on LM4 and its composites. The results show that with an increment in the reinforcement wt%, there is an enhancement in hardness and ultimate tensile strength (UTS) values within the monolithic composites. As-cast hybrid composites display a 37 to 54% improvement in hardness compared to as-cast LM4. Heat-treated samples, specifically those treated with peak aging with MSHT and 100 °C aging, perform better than as-cast samples and other heat-treated samples in terms of UTS and hardness. Compared to as-cast LM4, MSHT, and 100 °C aged samples display an 85 to 202% increment in VHN. Hybrid composites perform better in terms of hardness, while composites with 3 wt% of TiB2 (L3TB) perform better in terms of UTS, peak aged (MSHT and 100 °C aging) L3TB display 68% increment in UTS when compared to as-cast LM4. ANN model is developed and trained with five inputs (wt% of TiB2, wt% of Si3N4, type of solutionizing, aging temperature, and aging time) and one output (VHN) using different algorithms and a different number of hidden neurons to predict the age hardening behaviour of composites. Among them, Lavenberg-Marquardt (LM) training algorithm with normalized data and 30 hidden neurons performs well and shows a least average error of 1.588364. The confirmation test confirms that the trained ANN model can predict the output with an average %error of 0.14 using unseen data.