bluuebunny/crossref_metadata_2025_split huggingface dataset:
Post-editing neural machine translation in specialised languages
Authors: Kübler Natalie , Martikainen Hanna , Mestivier Alexandra , Pecman Mojca 
Published: October 2024

Abstract
This study focuses on phraseology in specialised texts and on students’ difficulties pertaining to
phraseology in post-editing neural machine translation output. It is undertaken within the corpus-based methodological
framework that we have developed for several purposes, one of which being to assess the impact of corpus use on
translation and post-editing. The objective of the study is to propose a descriptive analysis of typical student
errors related to phraseology in order to design tailored pedagogical materials. We aim to show that, with consistent
training in querying corpora and in interpreting results in an appropriate manner, students can manage to improve
their productions when translating specialised texts or when post-editing machine translation output.
The middle construction and some machine translation issues
Authors: Gutiérrez Macarena Palma 
Published: October 2024

Abstract
This paper aims at exploring the colloconstructional analysis of multiword units (MWU) in machine
translation regarding the middle construction in terms of compositional cospecification (Yoshimura, 1998; Yoshimura & Taylor, 2004). For
that purpose, I examine the Adverb + Verb collocation focusing on the predicates cut and
drive, collocated with quality-oriented adjuncts (Heyvaert,
2003) and incorporating Inanimate Subject entities (Patients, Enablers and Instruments). The number of
instances examined is 500+. The data analysed reveals that apart from the generalised Qt-Qc pattern
in shift of semantic importance, other patterns (namely, Qc-Qc) can be found by virtue of the
prototype effects of the construction (cf. Taylor, 1995), thus, providing a
potential source of disambiguation in the computational treatment of MWU in machine translation.
A single dielectric nanoparticle for refractive index sensing
Authors: Peng Ruiguang , Wen JingDa , Zhao Qian 
Published: October 2024

Abstract
Refractive index sensing has great application potential in a wide range of chemical and biomedical fields, however, these sensors usually require large-area and fabrication-intense arrays of unit cells. Here, we propose an ultracompact sensor based on a single dielectric nanoparticle for refractive index sensing with a footprint smaller than 2 µm2 and numerically investigate its sensing performance. A single-mode resonance rather than multimodes interaction is adopted for the spectroscopic feature of refractometric sensing. The elaborate resonator geometry facilitates the excitation of the gapped-vortex mode and enables the exposure of electric hotspots outside the dielectric. Such design enhances the coupling to the sensing medium, thus exhibiting high sensitivity at the level of 345 nm RIU–1 with a figure of merit of 12.78 per RIU. The single-particle nanostructure together with the single-mode resonance exhibits robust sensing performance to dimension deviations. Importantly, a thin annular beam is employed as the illumination to increase the excitation efficiency of the single-mode resonance, which significantly improves the modulation depth without relying on the near-field coupling of array nanostructures. This work provides a miniaturization platform for the dielectric sensors and other application fields based on enhanced light-matter interaction.
Charge transfer induced phase transition in Li2MnO3 at high pressure
Authors: Khangal Ajinkya P , Patel Nishant N , Mishra Ajay K 
Published: October 2024

Abstract
Efficient and better energy storage materials are of utmost technological importance to reduce energy dependence on the fossil fuels. Li2MnO3 is one such material having potential to meet most of the requirements for energy storage. This material has been synthesized using solid state synthesis route. High pressure structural and vibrational studies on this material have been carried out upto ∼22 and 26 GPa respectively. These investigations show occurrence of a hitherto unknown second order phase transition to a new low symmetry phase whose symmetry is constrained to be monoclinic with space group P21/n at pressure of ∼2.3 GPa in Li2MnO3. The bulk modulus and its derivative determined by fitting the P–V data with third order Birch–Murnaghan equation of state are 113.3 ± 13.1 GPa and 4.1 ± 1.2 respectively. Mode Grüneisen parameter calculated for all the Raman modes show positive values which indicates the absence of any soft mode in this material. A microscopic mechanism based on bond-charge transfer is invoked and applied to understand the spectroscopic changes occurring in this material which also manifests second order structural phase transition. Enhancement in covalent character of Li–O bonds in the Li–O polyhedra is inferred based on the spectroscopic observation and above mechanism.
Fluorescence microscopic image enhancement method based on multi-saliency guided filtering fusion
Authors: Hu Qiu , Zeng Haiwei , Miao Yanzi , Wang Kehui , Wu Shuangle , Li Wenhui , Zhang Zhiwang 
Published: October 2024

Abstract
Aiming at addressing the issues of colour deviation and clarity reduction in digital pathological imaging systems caused by complex environmental interferences such as uneven slice thickness, sample jitter, and background noise, this paper proposes a multi-saliency-guided filtering fusion enhancement method that combines energy saliency and Gaussian saliency. Firstly, a series of Gamma correction and spatial linear saturation adjustments are applied to enhance the contrast and colour saturation of blurred images, resulting in a sequence of pseudo-exposure images with improved contrast and saturation. Then, the pseudo-exposure images are decomposed into base and detail layers, and the fusion rules of energy saliency and Gaussian saliency-guided filtering are applied to each layer separately. Finally, clear microscopic images are obtained through two-scale reconstruction. This method overcomes the limitations of conventional deblurring algorithms that rely on prior estimation of scene depth and complex depth mapping processes. Experimental results on a dataset of cytological bright-field microscopic imaging samples show that the clarity evaluation metrics, including peak signal-to-noise ratio, root mean square error, and structural similarity index, have significantly improved, indicating that the proposed method can effectively improve the colour fidelity of the samples while eliminating noise interference and enhancing the clarity of cellular texture structures.
Application of NiS modified WS2/TiO2 heterostructure in photocathodic protection
Authors: Wu Hanbing , Bai Zhiming , Cheng Hongmei , Zhou Zhengqing , Zhang Zhibo 
Published: October 2024

Abstract
Stainless steel, as a popular corrosion resistant material, is still vulnerable to pitting corrosion in the marine environment. Therefore, in order to ensure the safety of stainless steel in the marine environment, it is necessary to implement corresponding protective measures. Titanium dioxide (TiO2), as an N-type semiconductor with excellent photoelectric properties, is widely used in the field of cathodic protection. However, as a photogenerated cathodic corrosion protection material, TiO2 has the disadvantages of low conductivity and high carrier recombination rate. Therefore, WS2 and NIS were introduced in this paper to modify it. TiO2/WS2/NiS (TWN) composites with Type-Ⅱ heterojunction structure were prepared by hydrothermal method and titration method. The results reveal TWN5 showed the best photoelectrochemical (PEC) performance, and the photocurrent density was 69% higher than that of a pure TiO2 photoanode, and the photochemical and photocathodic protection performance was significantly better than that of pure TiO2. Under simulated ocean conditions, the self-corrosion potential of 304ss combined with TW5 and TWN5 photoanodes is reduced to −0.64 V and −0.7 V, respectively. The main reason is that the contact surfaces of WS2 and TiO2 formed a Type II heterostructure, which accelerates the separation and diffusion processes of photoinduced carriers. In addition, the plasmon resonance effect of NiS improves the ability to absorb visible light, and the metallic-like feature of NiS also promotes charge separation.
The influence of continuum lowering on the equilibrium composition of plasma: case study of laser-induced plasma on a WC–Cu target
Authors: Ristić Miroslav , Krstevski Nikola , Ranković Dragan , Marković Milica , Šajić Aleksandra , Kuzmanović Miroslav 
Published: October 2024

Abstract
The composition of the plasma obtained by laser ablation of cermet WC–Cu is calculated under the assumption of local thermodynamic equilibrium. Special attention is paid to the effect of lowering the ionization potential, the influence of which in the Saha equations is reflected both through the exponential Boltzmann term and through the partition functions of atomic and ionic species present in the plasma. The effects of these two terms are separated and quantified. It has been shown that the correction to the partition functions due to the reduction of the ionization potential is of greater importance than the correction to the Boltzmann term at higher temperatures for atomic species. It is thus necessary for the precise determination of the plasma composition, especially at higher temperatures. The effect of lowering the ionization potential on different types of atoms as well as on different ionic states is analyzed. The change of the partition function due to the lowering of ionization energy also affects the concentration of single charged ions in an amount comparable to the correction of the Boltzmann term.
Resonant solitary states in complex networks
Authors: Niehues Jakob , Yanchuk Serhiy , Berner Rico , Kurths Jürgen , Hellmann Frank , Anvari Mehrnaz 
Published: October 2024

Abstract
Partially synchronized solitary states occur frequently when a synchronized system of networked oscillators with inertia is perturbed locally. Several asymptotic states of different frequencies can coexist at the same node. Here, we reveal the mechanism behind this multistability: additional solitary frequencies arise from the coupling between network modes and the solitary oscillator’s frequency, leading to significant energy transfer. This can cause the solitary node’s frequency to resonate with a Laplacian eigenvalue. We analyze which network structures enable this resonance and explain longstanding numerical observations. Another solitary state that is known in the literature is characterized by the effective decoupling of the synchronized network and the solitary node at the natural frequency. Our framework unifies the description of solitary states near and far from resonance, allowing to predict the behavior of complex networks from their topology.
Electromagnetic compatibility study of trackside antenna array miniaturization in the subway tunnel
Authors: Zhou Wen-Ying , Xu Jin-Jing , Lu Mai , Li Yu-Xin 
Published: October 2024

Abstract
To improve the compatibility of the subway tunnel’s electromagnetic environment and reduce the radiation impact of trackside antennas on subway workers. This paper proposes a miniaturized dual-band trackside antenna array by using metamaterial units. Its operation bandwidth is 2.33 ∼ 2.56 GHz and 3.24 ∼ 3.45 GHz, which could simultaneously satisfy the signal cover demands of the communications-based train control (CBTC) and the civil 5G wireless communication system. The proposed miniaturized antenna array has a maximum gain of 14.4 dBi and a maximum channel capacity of 13.9 bps Hz−1 at a signal-to-noise ratio (SNR) of 20 dB, which can effectively improve the quality of wireless communication systems. The number of trackside antennas with a single operation frequency band is reduced, and the distance between the antennas is enlarged at the same time. Besides that, we analyze the radiation impact on the tunnel electromagnetic environment of the proposed trackside antenna array. In particular, the electromagnetic dose absorbed by the human model of a tunnel worker is quantized. The results show that the electric field strength in the tunnel reduces by 4.11% at least after antenna array miniaturization, and the specific absorption rate (SAR) absorbed by the worker model’s trunk, skull, brain, heart, and liver is reduced by a maximum of 19.02%, 33.16%, 28.27%, 41.75%, and 74.54%, respectively, further lowering the human electromagnetic exposure risk. Therefore, a miniaturized trackside antenna array could reduce the interference from other radiation sources in the tunnel while providing a new idea for electromagnetic protection for subway workers.
Extraction of two-magnon scattering and detection of inverse spin Hall effect up to 40 GHz in low-damping Fe65Co35/Pt bilayer thin film
Authors: Koteswara Rao B S R , Sahu Savita , Basheed G A 
Published: October 2024

Abstract
We report an investigation of the inverse spin Hall effect (ISHE), as a measure of the pure spin current (J

S
), induced by spin pumping in a Fe65Co35/Pt bilayer using coplanar waveguide ferromagnetic resonance (CPW-FMR) in the in-plane (IP) geometry over the broadband microwave frequency range of 8–40 GHz. From the IP-FMR measurements, the defect-induced two-magnon scattering (TMS) contribution is evaluated by analyzing the frequency dependence of FMR linewidth using Arias and Mills approach [Arias R and Mills D L (1999 Phys. Rev. B 60, 7395), Mills D L and Arias R (2006 Physica B 384 147–151)]. Here, we have determined a very low Gilbert damping constant (α

G
) for Fe65Co35 bare film around 1.3 × 10−3, which is essential for the high spin current (>107 A/m2) generation. The enhanced value of α

G
≈3.2 × 10−3 obtained for Fe65Co35/Pt bilayer film is due to spin pumping damping, α

SP
= 1.9 × 10−3, confirmed by the ISHE induced DC voltage (V

DC
) signal measured across the edges of Pt layer. Out-of-plane (OP) angular ISHE measurements have been performed to disentangle spin pumping from spin rectification effects in the V

DC
signal. Further, we evaluated the effective spin-mixing conductance

g

eff

↑
↓

= 3.33 × 1019 m−2, which is higher than the values reported in FeCo-alloy-based bilayer systems. The present study aims to detect the J

S
injected by low-damping Fe65Co35 thin films, leading to the realization of energy-efficient spintronic devices.
Dynamic quantum secret sharing with identity verification based on quantum walks
Authors: Feng Lu , Zhou Ri-Gui , Zhang Xiao-Xue 
Published: October 2024

Abstract
A dynamic quantum secret sharing protocol with authentication is proposed based on quantum walks. The protocol can share specific secrets and also update the secret information periodically based on the existing quantum walks structure. Participants can be added or removed while keeping the original secret unchanged. This is more flexible in practical applications. Before the secrets are shared, each participant is authenticated to ensure the legitimacy of all participants’ identities. In addition, the protocol uses single photons as quantum resources, avoiding the complex preparation of entangled states, which makes the protocol more advantageous and potential in practical applications. Security analyses show that the protocol is resistant to collusion attack and other common attacks.
Development of a novel automated algorithm for patient dosimetry in computed tomography: a step towards the facilitation of size-specific dose estimates and organs dosimetry estimations in a busy clinical workflow
Authors: Sekkat Hamza , Khallouqi Abdellah , Madkouri Youssef , El Atifi Wiam , Rhouch Imane , El rhazouani Omar , Tahiri Zakaria , Talbi Mohammed , Halimi Abdellah 
Published: October 2024

Abstract
Accurate dosimetry in computed tomography (CT) is essential for patient safety and effective radiation management. This study presents the development of an automated algorithm designed to enhance patient dosimetry by facilitating size-specific dose estimates (SSDE) and organ dose estimations. Utilizing a Python-based script, the proposed method integrates advanced image preprocessing, contour detection, and mathematical calculations to quantify key metrics from CT images. This automated approach addresses the limitations of manual measurement techniques. A retrospective analysis was conducted on CT axial images from examinations acquired with an 80-detector scanner. The algorithm processes DICOM images, converts pixel values to Hounsfield Units, applies Gaussian smoothing, windowing, and thresholding, followed by morphological operations to refine segmentation. It measures the water equivalent diameter (Dw) and estimates both region SSDE and organ doses, incorporating tissue attenuation. Validation was performed using an adult anthropomorphic ATOM phantom, with organ doses measured by optically stimulated luminescence dosimeters. The results demonstrated the algorithm’s potential in estimating SSDE and organ doses. Validation of the automated method revealed strong correlations for Dw and SSDE between the proposed method and manual measurements of five expert reviewers ranging from 0.86 to 0.99 for determination coefficient. Comparative analysis of organ doses showed close agreement between results from experimental setup against the proposed algorithm. The automated algorithm estimated brain dose with a mean of 21.8 mGy, while measurements from the ATOM phantom and CT Expo indicated 19.74 mGy and 23.05 mGy, respectively. For lung doses, the automated algorithm estimated 12.5 mGy compared to 11.0 mGy from the ATOM phantom and 13.1 mGy from CT Expo. Liver doses were measured at 12.7 mGy by the automated method, versus 12.1 mGy from the ATOM phantom and 11.1 mGy from CT Expo. This study shows the potential of automated image analysis techniques in enhancing dosimetry accuracy in CT examinations.
Atmospheric neutron single event effects for multiple convolutional neural networks based on 28-nm and 16-nm SoC
Authors: Zhao 赵 Xu 旭 , Du 杜 Xuecheng 雪成 , Ma 马 Chao 超 , Hu 胡 Zhiliang 志良 , Yang 杨 Weitao 卫涛 , Zheng 郑 Bo 波 
Published: October 2024

Abstract
The single event effects (SEEs) evaluations caused by atmospheric neutrons were conducted on three different convolutional neural network (CNN) models (Yolov3, MNIST, and ResNet50) in the atmospheric neutron irradiation spectrometer (ANIS) at the China Spallation Neutron Source (CSNS). The Yolov3 and MNIST models were implemented on the XILINX 28-nm system-on-chip (SoC). Meanwhile, the Yolov3 and ResNet50 models were deployed on the XILINX 16-nm FinFET UltraScale+MPSoC. The atmospheric neutron SEEs on the tested CNN systems were comprehensively evaluated from six aspects, including chip type, network architecture, deployment methods, inference time, datasets, and the position of the anchor boxes. The various types of SEE soft errors, SEE cross-sections, and their distribution were analyzed to explore the radiation sensitivities and rules of 28-nm and 16-nm SoC. The current research can provide the technology support of radiation-resistant design of CNN system for developing and applying high-reliability, long-lifespan domestic artificial intelligence chips.
Deep learning-based spike sorting: a survey
Authors: Meyer Luca M , Zamani Majid , Rokai János , Demosthenous Andreas 
Published: October 2024

Abstract

Objective. Deep learning is increasingly permeating neuroscience, leading to a rise in signal-processing applications for extracellular recordings. These signals capture the activity of small neuronal populations, necessitating ‘spike sorting’ to assign action potentials (spikes) to their underlying neurons. With the rise in publications delving into new methodologies and techniques for deep learning-based spike sorting, it is crucial to synthesise these findings critically. This survey provides an in-depth evaluation of the approaches, methodologies and outcomes presented in recent articles, shedding light on the current state-of-the-art. Approach. Twenty-four articles published until December 2023 on deep learning-based spike sorting have been examined. The proposed methods are divided into three sub-problems of spike sorting: spike detection, feature extraction and classification. Moreover, integrated systems, i.e. models that detect spikes and extract features or do classification within a single network, are included. Main results. Although most algorithms have been developed for single-channel recordings, models utilising multi-channel data have already shown promising results, with efficient hardware implementations running quantised models on application-specific integrated circuits and field programmable gate arrays. Convolutional neural networks have been used extensively for spike detection and classification as the data can be processed spatiotemporally while maintaining low-parameter models and increasing generalisation and efficiency. Autoencoders have been mainly utilised for dimensionality reduction, enabling subsequent clustering with standard methods. Also, integrated systems have shown great potential in solving the spike sorting problem from end to end. Significance. This survey explores recent articles on deep learning-based spike sorting and highlights the capabilities of deep neural networks in overcoming associated challenges, but also highlights potential biases of certain models. Serving as a resource for both newcomers and seasoned researchers in the field, this work provides insights into the latest advancements and may inspire future model development.
Surrogate model of turbulent transport in fusion plasmas using machine learning
Authors: Li H. , Wang L. , Fu Y.L. , Wang Z.X. , Wang T.B. , Li J.Q. 
Published: October 2024

Abstract
The advent of machine learning (ML) has revolutionized the research of plasma confinement, offering new avenues for exploration. It enables the construction of models that effectively streamline the simulation process. While previous first-principles simulations have provided physics-based transport information, they have been inadequate fast for real-time applications or plasma control. In order to address this challenge, we introduce SExFC, a surrogate model based on the Gyro-Landau Extended Fluid Code (ExFC). An approach of physics-based database construction is detailed, as well the validity is illustrated. Through harnessing the power of ML, SExFC offers the capability to deliver rapid and precise predictions, facilitating real-time applications and enhancing plasma control. The proposed model integrates the recurrent neural network (RNN) algorithm, specifically leveraging the Gated Recurrent Unit (GRU) for iterative prediction of flux evolutions based on radial profiles. Therefore, the SExFC model has the potential to enable rapid and physics-based predictions that can be seamlessly integrated into future real-time plasma control systems.
The effects of zonal fields on energetic-particle excitations of reversed-shear Alfvén eigenmode: simulation and theory
Authors: Chen Liu , Liu Pengfei , Ma Ruirui , Lin Zhihong , Qiu Zhiyong , Wang Wenhao , Zonca Fulvio 
Published: October 2024

Abstract
By employing both nonlinear gyrokinetic simulation and analytical theory, we have investigated the effects of zonal (electromagnetic) fields on the energetic particle’s (EPs) drive of reversed-shear Alfvén eigenmodes (AEs) in tokamak plasmas. Contrary to the conventional expectation, simulations with zonal fields that are turned on and off in the EP dynamics while keeping the full nonlinear dynamics of the thermal plasma indicate that zonal fields further enhance the instability drive and thus lead to a higher saturation level. These puzzling simulation results can be understood analytically in terms of the general fishbone-like dispersion relation with the correspondingly different EP phase-space structures induced by the zonal fields. Analytical expressions for the zonal fields that are beat driven by the reversed-shear AEs are also derived, and shown to be in good agreement with the simulation results.