bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thermally-driven large current-perpendicular-to-plane magnetoresistance in ultrathin flakes of vanadium diselenide
Authors: Firouzeh Seyedamin , Rahman Md Wazedur , Pramanik Sandipan 
Published: October 2022

Abstract
Current-perpendicular-to-plane magnetoresistance (CPP MR) in layered heterojunctions is at the heart of modern magnetic field sensing and data storage technologies. van der waals heterostructures and two-dimensional (2D) magnets opened a new playground for exploring this effect, although most 2D magnets exhibit large CPP MR only at very low temperatures due to their very low Curie temperatures. vanadium diselenide (VSe2) is a promising material since its monolayers can potentially act as room temperature ferromagnets. VSe2 multilayers have been predicted to exhibit CPP MR effects, although experimental work in this area remains scarce. In this work we investigate CPP MR in 1T-VSe2 ultrathin flakes, revealing a large (∼60%–70%), positive, linear, and non saturating CPP MR, which persists close to room temperature (∼250 K), in a relatively small magnetic field range of ±12 kG. The CPP MR has been found to increase with decreasing flake thickness. The CPP MR originates due to the intrinsic inhomogeneity in the CPP transport path, and exhibits unprecedented immunity against thermal fluctuations, leading to increasingly enhanced MR as temperature is increased, even significantly beyond the charge density wave transition temperature. The observed ‘thermally-driven’ MR features are remarkably robust and reproducible, and can offer a viable route for developing practical room temperature 2D based magnetic sensor technologies. Our results also suggest that harnessing similar effects in other 2D systems could result in large MR as well, thereby motivating further research on CPP transport in these systems, which has been relatively unexplored so far.
A novel performance trend prediction approach using ENBLS with GWO
Authors: Zhao Huimin , Zhang Panpan , Zhang Ruichao , Yao Rui , Deng Wu 
Published: October 2022

Abstract
Bearings are a core component of rotating machinery, and directly affect its reliability and operational efficiency. Effective evaluation of a bearing’s operational state is key to ensuring the safe operation of the equipment. In this paper, a novel prediction method of bearing performance trends based on the elastic net broad learning system (ENBLS) and the grey wolf optimization (GWO) algorithm is proposed. The proposed method combines the advantages of the ENBLS and GWO algorithms to achieve better prediction results. In order to solve the problem that traditional regression prediction algorithms may lead to unsatisfactory prediction results and long training time, we propose a performance trend prediction method based on ENBLS. To further improve the prediction accuracy, we utilize the GWO algorithm to optimize various parameters present in the model to improve the performance of the model. The bearing data of the whole life cycle from the 2012 IEEE PHM challenge are selected to verify the effectiveness of the proposed method. The results show that the proposed method has high prediction accuracy and stability.
Accurate determination of the elastic moduli of optimized cantilever beams by efficient time-averaged ESPI system
Authors: Ma Yinhang , Quan Chenggen , Yang Boshuo , Liu Liu , Lu Guangchen , He Xiaoyuan , Yang Fujun 
Published: October 2022

Abstract
Elastic moduli, including Young’s modulus, shear modulus, bulk modulus, etc, are key parameters that are used to characterize the ability of a solid material to resist various types of deformation. The moduli can be extracted from the natural frequencies of a cantilever beam. In this paper, the relationships between moduli and natural frequencies, for the first time, are quantified by the finite element method. The optimized three-dimensional proportion of the cantilever beam is selected to be implemented simple error compensation. Experimentally, to precisely obtain the natural frequencies of the cantilever beam, an efficient time-averaged electronic speckle pattern interferometry(ESPI) system has been developed. The efficiency and precision are reflected in the following aspects: firstly, according to the slender character of the cantilever beam, a large shear optical path arrangement is designed to facilitate isolation from environmental interference; secondly, a resonance search method, based on the moiré effect is employed to recognize the natural frequencies accurately and efficiently; thirdly, a novel dynamic phase-shifting method is proposed based on the arrangement of the large shear optical path for clearer visualization of the mode shape of the cantilever beam. The proposed methods are verified by three kinds of common materials. The results suggest that Young’s modulus and shear modulus derived from natural frequencies are higher than the known value, and the error compensation can significantly reduce the calculation error. Furthermore, the experiments carried out on the woven carbon fiber reinforced plastic laminates illustrate the potential of the proposed methods in the evaluation of elastic moduli of composites. Given that the exciter attached to the specimen surfaces can be replaced with some special counterparts, the proposed ESPI system has considerable potential to test the objects loaded in some extreme environments, e.g. at high temperatures or underwater, where contact detection methods are difficult to be implemented.
Position estimation and calibration for high precision human positioning and tracking using millimeter-wave radar
Authors: Xu Zhimeng , Wu Zhenbin , Li Dan , Chen Liangqin , Zhang Shanshan , Chen Zhizhang (David) 
Published: October 2022

Abstract
In this paper, a context-based human target detection and position estimation algorithm, as well as a position calibration algorithm based on radar irradiation angle are proposed to improve the positioning accuracy, which is limited by the sparse and easily submerged characteristics of the point cloud generated by millimeter-wave radar, which leads to difficulty in achieving high-precision positioning. Furthermore, an indoor target positioning and tracking system is built using 77 GHz millimeter-wave radar to verify the proposed algorithms. The experimental results indicate that the proposed algorithms can improve the positioning accuracy both in single-person and multi-person positioning scenarios, with median positioning errors 8.7 cm (36.7% decrease) and 12.95 cm (average) respectively. Therefore, the proposed sensing method is considered as a very promising technique for designing a high precision human trajectory tracking and positioning radar system.
CdO-supported ZrO2 heterojunctions: facile synthesis and rapid visible-light oxidation of atrazine herbicide with superb recyclability
Authors: Basaleh A S , Shawky Ahmed , Mahmoud M H H 
Published: October 2022

Abstract
The advancement in ceramic oxide-based photocatalysis has got much attention recently for environmental issues. Atrazine (AZ) is one of the major used herbicides in agricultural and related industries. This work familiarizes a polymeric-assisted sol-gel preparation of high surface area zirconium oxide (ZrO2) supported with cadmium oxide nanoparticles at minor content (0.5−2.0 wt%). Exploration of the synthesized heterostructures revealed the enhancement of visible-light absorbance and reduction of bandgap energy to 2.76 eV keeping the same crystalline form and high surface area of 170 m2 g‒1. The prepared photocatalysts were used to degrade AZ in water at a concentration of 231.8 μM (50 ppm). The 1.5%-introduced CdO to ZrO2 revealed the best-performed photocatalyst for complete oxidation of AZ within 40 at an optimized dose of 1.6 g l–1. This novel ceramic photocatalyst showed a chemical and structural ability to keep 98.5% of its initial efficiency after five regenerated cycles. The construction of p–n heterojunction between the p-type ZrO2 and the n-type CdO contributed to the comprehensive photocatalytic competence toward the efficient charge separation and photooxidation process.
Active shape model registration of ocular structures in computed tomography images
Authors: Liu Yuxuan , Ota Mitsuki , Han Runze , Siewerdsen Jeffrey H , Liu T Y Alvin , Jones Craig K 
Published: October 2022

Abstract

Purpose. The goal of this work is to create an active shape model segmentation method based on the statistical shape model of five regions of the globe on computed tomography (CT) scans and to use the method to categorize normal globe from globe injury. Methods. A set of 78 normal globes imaged with CT scans were manually segmented (vitreous cavity, lens, sclera, anterior chamber, and cornea) by two graders. A statistical shape model was created from the regions. An active shape model was trained using the manual segmentations and the statistical shape model and was assessed using leave-one-out cross validations. The active shape model was then applied to a set of globes with open globe injures, and the segmentations were compared to those of normal globes, in terms of the standard deviations away from normal. Results. The active shape model (ASM) segmentation compared well to ground truth, based on Dice similarity coefficient score in a leave-one-out experiment: 90.2% ± 2.1% for the cornea, 92.5% ± 3.5% for the sclera, 87.4% ± 3.7% for the vitreous cavity, 83.5% ± 2.3% for the anterior chamber, and 91.2% ± 2.4% for the lens. A preliminary set of CT scans of patients with open globe injury were segmented using the ASM and the shape of each region was quantified. The sclera and vitreous cavity were statistically different in shape from the normal. The Zone 1 and Zone 2 globes were statistically different than normal from the cornea and anterior chamber. Both results are consistent with the definition of the zonal injuries in OGI. Conclusion. The ASM results were found to be reproducible and accurately correlated with manual segmentations. The quantitative metrics derived from ASM of globes with OGI are consistent with existing medical knowledge in terms of structural deformation.
Development of a more accurate Geant4 quantum molecular dynamics model for hadron therapy
Authors: Sato Yoshi-hide , Sakata Dousatsu , Bolst David , Simpson Edward C , Guatelli Susanna , Haga Akihiro 
Published: October 2022

Abstract

Objective. Although in heavy-ion therapy, the quantum molecular dynamics (QMD) model is one of the most fundamental physics models providing an accurate daughter-ion production yield in the final state, there are still non-negligible differences with the experimental results. The aim of this study is to improve fragment production in water phantoms by developing a more accurate QMD model in Geant4. Approach. A QMD model was developed by implementing modern Skyrme interaction parameter sets, as well as by incorporating with an ad hoc α-cluster model in the initial nuclear state. Two adjusting parameters were selected that can significantly affect the fragment productions in the QMD model: the radius to discriminate a cluster to which nucleons belong after the nucleus–nucleus reaction, denoted by R, and the squared standard deviation of the Gaussian packet, denoted by L. Squared Mahalanobis’s distance of fragment yields and angular distributions with 1, 2, and the higher atomic number for the produced fragments were employed as objective functions, and multi-objective optimization (MOO), which make it possible to compare quantitatively the simulated production yields with the reference experimental data, was performed. Main results. The MOO analysis showed that the QMD model with modern Skyrme parameters coupled with the proposed α-cluster model, denoted as SkM*
α, can drastically improve light fragments yields in water. In addition, the proposed model reproduced the kinetic energy distribution of the fragments accurately. The optimized L in SkM*
α was confirmed to be realistic by the charge radii analysis in the ground state formation. Significance. The proposed framework using MOO was demonstrated to be very useful in judging the superiority of the proposed nuclear model. The optimized QMD model is expected to improve the accuracy of heavy-ion therapy dosimetry.
Divertor plasma detachment: roles of plasma momentum, energy, and particle balances
Authors: Krasheninnikov S I , Kukushkin A S , Pshenov A A 
Published: October 2022

AbstractContrary to statements from some recent papers, the bifurcation of the scrape-off layer and divertor plasma parameters, as described within a 1D model, does exist. The analysis of both numerical simulations and experimental data shows that the real physical reasons that can cause a strong reduction of the plasma particle flux to the targetjdare impurity radiation loss and volumetric plasma recombination. Fitting the parameter describing the ‘plasma momentum removal’, based on the results of 2D numerical simulations, then using this fit in subsequent analytic expressions forjd, and finally interpreting the evolution ofjdas the result of elastic plasma-neutral interactions break the causality principle and lead to a wrong physical picture of divertor plasma detachment.
Kinetic plasma dynamics in a radial model of a Hall thruster with a curved magnetic field
Authors: Marín-Cebrián Alberto , Domínguez-Vázquez Adrián , Fajardo Pablo , Ahedo Eduardo 
Published: October 2022

Abstract
A 1D particle-in-cell model of a Hall thruster discharge is used to analyze the effect of a curved magnetic topology in the radial plasma response and the plasma fluxes to dielectric walls. The kinetic solution shows a significant replenishment of the velocity distribution function tail and temperature isotropization for both negative (i.e. anode pointing) and positive curvatures. The new radial magnetic force is electron confining or expanding for, respectively, negative and positive curvatures, and this modifies significantly the electric and pressure radial forces. As a consequence, the plasma density near the wall and the degree of radial ion defocusing are affected: they are highly reduced for negative curvatures, the case of higher interest. For positive curvatures, the kinetic solution shows that the radial ion flow becomes supersonic within the plasma bulk, away from the Debye sheaths. An ancillary quasineutral fluid model is presented to explain this feature and other aspects of the kinetic solution. Some kinetic studies on additional phenomena complete the work.
Sensitivity of the negative ion beam extraction to initial plasma parameters by 3D particle modelling
Authors: Lindqvist Max , Wünderlich Dirk , Mimo Alessandro , Mochalskyy Serhiy , Revel Adrien , Nocentini Riccardo , Minea Tiberiu , Fantz Ursel 
Published: October 2022

Abstract
The ITER neutral beam injection system for heating and current drive requires Negative Ions (NI) produced in large ceasiated ion sources. Self-consistent 3D Particle-In-Cell Monte-Carlo Collision (PIC-MCC) modelling is necessary for simulating extraction of NI and the co-extraction of electrons in ITER-like ion sources. In the RF driven negative ion sources at the ELISE and BUG test facilities, the filter field is generated by a current drawn through the Plasma Grid (PG). The 3D PIC-MCC code ONIX has been used to study the role of electron temperature, plasma density and emission rate on the extracted currents, as well as the negative ion transport close to an extraction aperture of the PG in ELISE. The results are compared to a case with higher electron density, lower electron temperature and higher emission rate, corresponding to the typical working point of a filter field configuration generated by permanent magnets. It is shown that the current of co-extracted electrons is strongly influenced by the electron temperature and plasma density. Increasing T
e from 1 eV to 2 eV and decreasing the plasma density lead to an increase of co-extracted electrons by a factor 4 due to the increased electron flux towards the aperture and a deeper penetration of the extraction potential into the plasma. With reduced plasma density, the fraction of NI extracted directly after production on the PG increases. An additional parameter variation was conducted to study the effect of the emission rate of NI on the extracted currents. A reduced emission rate of NI from the PG from 550 Am−2 to 200 Am−2 reduces the extracted negative ion current by

∼
40

Am−2 due to a reduction of the number of directly extracted NI.
‘Classical’ coherent state generated by curved surface
Authors: Ding Weifeng , Wang Zhaoying 
Published: October 2022

Abstract
Analogous coherent states are deduced from classical optical fields on curved surface in this paper. The Gaussian laser beam, as a fundamental mode, cannot be adequately simulated by coherent states due to their inherent diffraction in flat space. But it differs when propagating on a surface with the uniform curvature, the constant Gaussian curvature surface (CGCS). By generalizing the method of Feynman path integral, an equivalent coherent states solution is demonstrated to describe the beam propagation. The temporal evolution of the Schrödinger equation is analogously translated into a spatial transmission in this derivation, and we obtain the expression of quantized momentum transmitted on curved surface, which is proportional to the square root of the Gaussian curvature K. In addition to that, a physical picture of beam propagation that is identical to the squeezed state is also built. We hope this research can offer a new view on the quantum field in curved space.
Linear pulse propagation with high-order dispersion
Authors: Runge Antoine F J , Long Qiang Y , Alexander Tristram J , de Sterke C Martijn 
Published: October 2022

Abstract
We present an approximate, but intuitively appealing theoretical study of the linear propagation of optical pulses in media with high-order dispersion. Our analysis, which is fully consistent with numerical simulations, is based on the pulses’ full-width at half maximum and shows that the effect of high-order dispersion differs significantly from that of the well-understood second order dispersion. For high dispersion orders m, the central part of the pulses, where the intensity is highest, evolve in the same way, independent of m, though at different rates, with a weak dependence on the initial pulse shape. We also find that all pulses, irrespective of initial pulse shape, eventually evolve to a sinc function. Our treatment allows us to find expressions for the characteristic dispersion lengths for high dispersion orders.
Near-field interference map due to a dipolar emission near the edge of a monocrystalline gold platelet
Authors: Abbasirad N , Barreda A , Arslan D , Steinert M , Chen Y-J , Huang J-S , Staude I , Setzpfandt F , Pertsch T 
Published: October 2022

Abstract
Point source excitation and point detection in the near-field provides new perspective to study the near-field optical phenomena of plasmonic nanostructures. Using the automated dual-tip scanning near-field optical microscope (SNOM), we have measured the optical near-field response of a dipolar emission near the edge of a monocrystalline gold platelet. The image dipole method was used to analytically calculate the interference pattern due to surface plasmon polaritons excited at the position of aperture tip and those reflected from edges of the gold platelet. The near-field enhancement was observed on the edges of the gold platelet. Our results verify that automated dual-tip SNOM is an intriguing technique for quantum plasmonic studies where deterministic coupling of quantum emitters and the detection of the near-field enhancement are of great interest.
On-line water quality inspection system: the role of the wireless sensory network
Authors: Okpara Enyioma C , Sehularo Boikanyo E , Wojuola Olanrewaju B 
Published: October 2022

Abstract
There is an increasing dependence on freshwater sources for various human activities because of population growth and rising industrialization across the globe. Meanwhile, the safety of available freshwater is threatened by the massive generation of waste from increasing domestic and industrial activities. The need for continuous assessment of the quality of the environmental water available has become a crucial research concern. The conventional techniques commonly used are not sufficient to meet the expanding demand for real-time, rapid, low-cost, reliable, and sensitive water quality monitoring (WQM). The use of wireless sensor networks (WSN) has been proposed by various researchers as a sustainable substitute for the traditional processes of monitoring water quality. In this work, an array of the literature on the practical applications of the networks in the assessment of vital water quality parameters such as pH, turbidity, temperature, dissolved oxygen (DO), chlorine content, etc., were surveyed and analyzed. Various technologies such as machine learning, blockchain, internet of things (IoT), deep reconstruction model, etc., were incorporated with WSN for real-time monitoring of water quality, data acquisition, and reporting for a broad range of water bodies. The survey shows that the networks are comparatively affordable and allow remote, real-time, and sensitive measurement of these parameters with minimal human involvement. The use of a low-power wide area network (LPWAN) was also introduced to solve a major problem of power supply often associated with the use of WSN. Recent developments also showed the capacity of WSN to assess simultaneously multiple water quality parameters from several locations using unmanned aerial vehicles (UAV). However, the networks rely on established parameters to indicate a compromise in water quality, but in most cases, fail to identify which pollutant species are responsible.
Limited impact of COVID-19 recovery packages on near-term CO2 emissions pathways
Authors: Gaucher Yann , Tanaka Katsumasa , Ciais Philippe , Boucher Olivier 
Published: October 2022

Abstract
Part of the economic recovery plans implemented by governments following COVID-19 is directed towards the energy transition. To understand the potential effects of these post-COVID green recovery packages on reductions of global greenhouse gas emissions until 2030, we investigated three different approaches. First, we analyzed simulation results of Integrated Assessment Models (IAMs) to infer the change in CO2 intensity of GDP that could result from post-COVID low-carbon investment plans. Second, we investigated the scenarios the International Energy Agency (IEA) provided based on a bottom-up energy system model. Combining the two approaches, we found that green recovery packages implemented and planned globally can lead to an emissions reduction of merely 1%–6% from the 2030 baseline levels at most. Third, we looked into the results of the Adaptative Regional Input-Output model, which simulates the dynamic effects of economic crisis and fiscal stimuli through supply chains following labor shortage. The third approach shows that the increase of activity driven by fiscal stimuli leads to a rebound of CO2 emissions even if they do not target carbon-intensive sectors. We conclude that green recovery packages targeting low-carbon technologies have a limited impact on near-term CO2 emissions and that demand-side incentives, as well as other policy efforts to disincentivize the use of fossil fuels, are also crucial for scaling up climate mitigation.