bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probing the local thermal expansion coefficient of single liquid sn nanoparticles using EELS in STEM
Authors: Kryshtal A. , Khshanovska O. 
Published: February 2025

Abstract
We investigated the local coefficient of thermal expansion (CTE) along the diameter of a 190 nm Sn nanoparticle supported on a thin Si₃N₄ substrate. The surface and volume plasmon energies of the liquid Sn nanoparticle were measured as a function of temperature using spatially resolved valence electron energy loss spectroscopy in a scanning transmission electron microscope. We found that the slope of the volume plasmon energy versus temperature gradually increased near the surface, revealing a thermal expansion gradient in liquid nanoparticles. This effect was confined to a 3 nm-thick surface layer, where the CTE was over 1.5 times larger than that of the nanoparticle core. Meanwhile, the CTE of the core was found to be smaller than the reference value for liquid Sn, which is attributed to mechanical constraints imposed by the thin Si₃N₄ substrate. We demonstrated that temperature-induced changes in surface plasmon energy provide insights into the CTE of the outmost surface layer of Sn nanoparticles.
Development of a field‐programmable gate array‐based real‐time generic solver for power electronics circuits with arbitrary configurations
Authors: Chen Yuan , Liu Jiadai , Ding Hui , Zhang Yi 
Published: February 2025

AbstractUsing a field‐programmable gate array (FPGA) as the core computational engine, this paper proposes a digital real‐time electromagnetic transient simulator for a generic power electronic system. The LC switching model is employed for constant network conductance representation. The fully paralleled and pipelined design for network solutions and component computation accomplished the highest performance and efficiency on the FPGA. A customised 48‐bit floating‐point data format is proposed to achieve high simulation precision. This dedicated design is necessary for power electronic simulation. A typical power electronic transformer, which is a heavy computation burden for real‐time simulation, demonstrates the effectiveness of the proposed simulator.
SeqBMC: Single‐cell data processing using iterative block matrix completion algorithm based on matrix factorisation
Authors: Lejun Gong , Like Yu , Xinyi Wei , Shehai Zhou , Shuhua Xu 
Published: February 2025

AbstractWith the development of high‐throughput sequencing technology, the analysis of single‐cell RNA sequencing data has become the focus of current research. Matrix analysis and processing of downstream gene expression after preprocessing is a hot topic for researchers. This paper proposed an iterative block matrix completion algorithm, called SeqBMC, based on matrix factorisation. The algorithm is used to complete the missing value of the gene expression matrix caused by the defect of sequencing technology. The gene frequency of the matrix is used to block the matrix, and then the matrix factorisation algorithm is used to complete the small matrix after the block, and then the biological zeros that may exist in the block matrix are retained. Experimental results show that the matrix completion algorithm can significantly improve the classification performance of the gene expression matrix after completion with 86.81% F1 score, which is conducive to the recognition of cell types in sequencing data. Moreover, this completion method can be completed only by the machine learning method without too much prior knowledge related to biology and has good effects. Compared with ALRA, SeqBMC increased 5.47% accuracy and 5.03% F1 score. It indicates that SeqBMC has significant advantages in the matrix completion of single‐cell RNA sequencing data.
Characteristics of non-thermal low-frequency Ar–N2 plasma and its application in microbial decontamination
Authors: Wali Niaz , Xiao W W , Rehman N U , Din Qayam ud , Wang C Y , Ma J T , Zhong W J , Yang Q W 
Published: February 2025

Abstract
Traditional methods to generate non-thermal Ar–N2 plasma at low pressure conditions have predominantly utilized radiofrequency and direct current power supplies. These techniques have proven efficiency in various applications, including surface modification and microbial decontamination. However, high operational costs and the complex equipment have provoked interest in alternative approaches. This study investigates the characteristics and efficacy of Ar–N2 plasma generated under vacuum conditions using a low-frequency alternating current power supply at 6 and 9 kHz. The plasma was produced in a capacitively coupled system, with key parameters such as electron density, electron temperature, and the electron energy distribution function (EEDF) were assessed using a single Langmuir probe. Results indicate that the increased driving frequency from 6 to 9 kHz led to a decrease in electron temperature, and electron density at higher pressure, when nitrogen was introduced into the argon plasma. EEDF is shifted from a bi-Maxwellian to a Maxwellian-like shape with increased frequency at fixed power and gas pressure. Additionally, a significant degradation of Xanthomonas campestris pv. vesicatoria from

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was observed following the antimicrobial treatment, suggesting its potential applications in agriculture, material processing, and sterilization.
Intuitive, phenomenological approach to test methods for approval purposes of trained models using the example of predicting loudness classes from EEG-data
Authors: Koch Christian 
Published: February 2025

Abstract
Machine learning (ML) models will soon be found in devices of critical structures or even in high-risk applications. Arranging the Artificial Intelligence Act of European Union, requirements and a methodology for an approval of measurement devices by a regulatory authority or a state institution need to be developed. In this study, using the example of loudness classification from electroencephalography measurement data, phenomenological methods were developed for the evaluation of ML models in the context of an approval process. A schedule of six sequential steps is proposed that can be used as a flowchart in such a process. After identifying the relevant features (step 1) performance measures and benchmarks were defined (step 2). In the following performance evaluation (step 3) the influence of the input data on the model’s output was determined. The range and characteristics of the input data at which the device operates correctly were identified and quantitative descriptors were determined for the full range of operating conditions specified in standards or regulations for approval (step 4). Perturbation-based techniques were developed and adapted to define corner cases and to create new test data that identify the areas of the input data where performance falls below a certain threshold (step 5). The newly found test data were finally applied in step 6, and it could be shown that the data can reveal weak points in the models. All processes can and must be used without knowledge of the models, as an independent test of a finished device is always carried out during a type approval. Thus, this study contributes to the still very nascent field of type approval development for measuring devices, software and methods containing machine or deep learning.
Lifetime analysis of hydraulic directional valves in a contaminated fluid condition based on internal leakage due to wear
Authors: Tao Wangfang , Ren Yan , Tang Hesheng , Xiang Jiawei 
Published: February 2025

Abstract
As an important part of the hydraulic system, hydraulic oil pollution will seriously affect the performance and the lifetime of the hydraulic component. Therefore, the pollution of hydraulic oil is crucial to the lifetime of the hydraulic component. In this study, an assessment model with internal leakage flow as a parameter is proposed. A Life assessment hydraulic test system is built. The test is conducted using hydraulic fluids containing test dust. It evaluates the effect of the contaminated fluid on the degradation of the internal leakage performance and reduction of lifetime. The results show that the internal leakage flow of the hydraulic directional valve, classified under ISO 4406 cleanliness level 21/19/17, increased from 6 ml to 68 ml following a test lasting 120 h. It verifies the lifetime based on the internal leakage flow is described by a logarithmic function. The hydraulic directional valve has a pressure loss of 0.8 MPa higher in port A than in port B at an operating pressure of 15 MPa. This paper provides a reference for further study on the effect of wear due to internal leakage failure on lifetime and improvement of service life of hydraulic directional valves.
Box-Cox enabled oscillatory sparse decomposition for frog feature extraction of high-speed railway turnout
Authors: Tang Miao , Shi Juanjuan , Qin Hangyuan , Huang Weiguo , Shen Changqing , Zhu Zhongkui 
Published: February 2025

Abstract
High-speed railway turnouts are susceptible to failures due to the intricate structure. The interaction forces between wheels and rails reflect the health condition of turnouts. Hence, force signal analysis emerges as a robust technique for the turnout health assessment. A crucial aspect of this analytical process is the accurate identification of signal segments within the measured force data that are originated specifically from turnouts. This identification is vital as the locations of force signals measured often misalign with the recorded positions of the turnout. Given the sparsity of the force impacts induced by the frogs of turnouts, this paper proposes a Box-Cox enabled oscillatory sparse decomposition (BC-OSD) method. Given the sparse and low oscillatory nature of signal segments produced by frogs, the BC-OSD proves effective in isolating frog-generated features from complex force signals. BC-OSD employs Oscillatory Sparse Decomposition to partition the signal into two segments based on their oscillatory properties. The integration of the Box-Cox Sparse Measures enables the algorithm to adaptively adjust its performance of subbands selection based on the actual signal characteristics. The decomposition outcome relies upon the chosen parameters; thus, a systematic discussion on the parameter selection for processing wheel–rail force signals is provided. The efficacy of the proposed method is validated through the analysis of measured wheel–rail force signals.
MSSSHANet: Hyperspectral and multispectral image fusion algorithm based on multi-scale spatial-spectral hybrid attention network
Authors: Zhang Xingyue , Chen Mingju , Liu Feng , Li Senyuan , Rao Jie , Song Xiaofei 
Published: February 2025

Abstract
In order to solve the problems of scale difference, inconspicuous spatial feature expression, redundancy, and overlapping of spectral feature information in hyperspectral and multispectral image fusion, a fusion algorithm based on multi-scale space-spectrum hybrid attention network is designed in this paper. The algorithm enhances the capability of shallow feature extraction through the multi-scale mechanism, uses the space-spectrum hybrid attention mechanism to mine the correlation between deep space and spectrum, designs a cross-spectrum fusion module to realize the effective reconstruction of spatial and spectral information, and uses the loss function to constrain the difference between the fused image and the reference image in terms of color, detail edge, and spatial structure. Experiments were conducted on PaviaUniversity, IndianPines, and hyperspectral image of Natural Scenes2004 datasets, and compared to algorithms such as ResTFNet, spatial spectral reconstruction network, MoGDCN, DBSR, and Fusformer. The proposed algorithm, MSSSHANet, performs better in spectral curve smoothness, spectral difference value, root mean squared error, peak signal to noise ratio, Erreur Relative Globale Adimensionnelle de Synthèse, and Spectral Angle Mapper value, which plays an active role in improving fusion quality. However, the generalization ability of the proposed algorithm in special remote sensing tasks needs to be verified, and future research will focus on data preprocessing optimization and the development of time-spatial-spectral integration fusion technology.
A sensor signal processing method based on Hankel dynamic mode decomposition
Authors: Wang Gerui , Wu Jiang , Chen Xiaoge , Du Yixin 
Published: February 2025

Abstract
Modal identification and extraction of monitoring signals are of great significance for aero-engine condition monitoring and health management. Empirical mode decomposition (EMD) method and variational mode decomposition (VMD) method have wide applications in time–frequency signal analysis, but EMD method is very sensitive to noise and sampling frequency. The accuracy of the VMD method relies on the input parameter settings. The dynamic mode decomposition (DMD) method is considered as a high-dimensional data-driven method which can predict the short-term behavior. However, the one-dimensional data decomposed by the DMD method only contains one mode. In this paper, the DMD method based on Hankel reconstruction (HDMD) is applied to the signal sequence to investigate its capability and potential as a signal processing method. First, multi-frequency, similar-frequency, and variable-frequency-variable-amplitude signals are constructed and resolved by various methods. It is shown that the HDMD method is more robust to noise, has a higher frequency resolution, and is capable of uncovering potential frequency trends compared to the EMD method and the VMD method. In addition, this paper applies the HDMD method to identify the measured signals of the aero-engine. It is shown that the HDMD method can accurately decompose the frequency modes of the core components. Compared with the EMD and VMD methods, the HDMD method can reveal the pattern of the engine frequency when it varies within a small range, which is more applicable to the analysis of the actual signals.
RUL prediction integrating feature distribution change point identification and martingale
Authors: Li Yanfeng , Duan Xia , Ren Weibo , Dong Lei , Chen Zhongxin , Du Wenhua , Wang Junyuan 
Published: February 2025

Abstract
The two-stage Wiener process (WP) model has become a common method to describe the phased deterioration of bearings over time. However, this model ignores the correlation of feature data distribution structure and change points (CPs) between the two stages, as well as the limitations of maximum-likelihood estimation methods for WP model parameter estimation. Therefore, this paper proposes a remaining useful life prediction approach that integrates feature distribution CP identification and a martingale process. First, a two-step feature screening method adopting trend consistency and composite score is proposed to construct a health indicator, which accounts for the trend consistency of the same feature on different bearings and can avoid redundancy while containing sufficient degradation information. Next, a t-neighborhood granular mean-shift clustering method is proposed, which makes the divisibility of the feature distribution more obvious and can identify CPs sensitively, flexibly and stably. Finally, a martingale method is introduced so that the parameter estimation of the two-stage WP model depends on the entire degradation path, which overcomes the limitations of WP model parameter estimation and enables the model to better characterize the bearing degradation process.
Modeling fast ion losses due to tearing and internal kink perturbations in MAST-U
Authors: Liu Yueqiang , Rivero-Rodríguez J F , Blackmore S , Harrison J R , McClements K G ,   the MAST-U Team,   the Tokamak Exploitation Team
Published: February 2025

Abstract
Fast ion (FI) loss properties in the presence of tearing mode and internal kink perturbations are numerically investigated for discharges in the MAST-U spherical tokamak, utilizing the MARS-F magnetohydrodynamic stability code and the REORBIT test particle guiding-center orbit-following module. Tracing about 100 000 particle markers sampled from the equilibrium distribution of the neutral-beam injection induced FIs, it is found that about 10% out of the total strike the limiting surface (including the divertor surface) in MAST-U discharge 46943, assuming a maximum perturbation of 100 G inside the plasma (corresponding to ∼6 G at the Mirnov probe location at the outboard mid-plane). Detailed particle tracing, assuming a uniform initial distribution in the 2D phase space (at given radial locations), reveals that initially counter-current FIs launched near the plasma edge are subject to significant prompt losses, while almost all initially co-current ions remain well confined at the assumed perturbation level. Most lost FIs strike the lower-half of the limiting surface. Finite gyro-radius effects prevent lost ions from striking the top-outer corner of the super-X divertor chamber. A scan of the perturbation level (based on discharge 45163) reveals, not surprisingly, an approximately linear scaling of the particle loss fraction (for counter-current FIs) with respect to the perturbation amplitude.
A meshless method for thermal vibration analysis of curved-edge trapezoidal plates made of laminated materials
Authors: Hu Shuangwei , Zhong Rui , Wang Qingshan , Qin Bin 
Published: February 2025

Abstract
This paper reports a meshless method for stochastic vibration analysis of trapezoidal composite laminates with curvilinear bound. The basis functions used in this meshless method are Chebyshev polynomials, which are adapted to the defining domain of the Chebyshev polynomials by transforming the curved-edge plate into a square plate using a coordinate mapping technique. The developed vibration analysis model combines the first-order shear deformation theory (FSDT) and thermos-elasticity theory using the Hamiltonian variational principle. The displacement tolerance function of the square plate is approximated by a two-dimensional meshless Chebyshev-radial basis point interpolation method. Gaussian Lobato sampling points are used to discretize the square domain. The correctness and efficiency of the model is verified by comparison with finite element results and published literature. The effects of temperature, geometry, and stochastic loading on the vibration characteristics of curved edge trapezoidal plates are also carried out. The results show that the existing Chebyshev-radial basis point interpolation method can accurately and efficiently calculate the vibration characteristics of curved-edge trapezoidal plates under different boundary conditions.&#xD;
Parallel Cross-sectional Lamé Mode Rod Resonator with high effective electromechanical coupling coefficient and temperature stability
Authors: Li Haiyang , Zhou Jie , Xu Qinwen , Lin Binghui , Yang Tingting , Liu Zesheng , Zheng Yupeng , Huang Xiaoming , Liu Yan , Guo Shishang , Cai Yao , Sun Chengliang 
Published: February 2025

Abstract
Lamb wave resonators (LWR) have the advantages of high frequency, small size and lithographically defined resonant frequency. To solve the problems of low effective electromechanical coupling coefficient (

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) and high temperature coefficient of frequency (TCF) in the application of LWR, a method of etching off the AlN film not covered by the top interdigital transducers (IDTs) is proposed to form a Parallel Cross-sectional Lamé Mode Rods Resonator (PCLMRR). The formed rods confine more longitudinal electric field and weaken the lateral capacitance between lateral rods. PCLMRR takes advantage of the high

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of one order Cross-sectional Lamé Mode Resonator (CLMR) and the low impedance of array structure. The complexity of manufacturing PCLMRR has been reduced by etching grooves using the same mask of IDTs. For the same thickness of AlN film, the critical dimension for PCLMRR in photolithography is twice of CLMR, reducing the demand for photolithography resolution. Compared to plate LWR with a trade-off between TCF and

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, the PCLMRR adjusts the electric field, capacitance and stress-free boundaries, resulting in a higher

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and lower TCF simultaneously. The variation of quality factor (Q) with temperature in PCLMRR is also smaller than that of the plate LWR due to the groove cutting the heat flow off and raising the thermal relaxation time.
Ultra-low fluence irradiation with energetic heavy ion pulsed beam using a modified electrostatic raster scanner
Authors: Graham Joseph T , Olivares José , Tavora Vicente Garcia , Pérez Esther Enríquez , Padhi Santanu Kumar , Crespillo Miguel , López Gastón García 
Published: February 2025

Abstract
A method for performing low fluence pulsed irradiations with energetic heavy ions is presented. A raster scanner, placed upstream from a sample target chamber, is externally driven by a voltage pulse generated by a function generator. The configuration is similar to an electrostatic chopper, where a voltage difference across the scanner’s electrodes sweeps the beam across the sample, placed slightly off center from the beam axis, resulting in a short irradiation pulse on the sample and a low particle fluence. Such a system was developed at the Centre for Micro Analysis of Materials (CMAM) facility and characterized using 9 MeV F and 18 MeV Cl ions. The system can generate pulses of a few microseconds duration, depending on ion energy and charge state. A diagnostic method for measuring the fluence on the samples by counting etched ion tracks is described. A fluence on the order of 106 cm−2 was obtained by this method. This method could be adopted by other tandem ion accelerator facilities through simple and inexpensive modifications of existing beam handling instruments.
Thermal-noise-resistant entanglement and steering via dark-mode engineering in multimode optomechanical system
Authors: Ge Ping-Chi , Yu Yikyung , Wu Hao-Tian , Han Xue , Wang Hong-Fu , Zhang Shou 
Published: February 2025

Abstract
We propose a scheme for generating thermal-noise-resistant entanglement and Einstein-Podolsky-Rosen (EPR) steering in a multimode optomechanical system by breaking the dark mode effect. Here, the dark mode is broken by coupling an auxiliary cavity to one of the mechanical modes. Under this condition, strong entanglement and one-way EPR steering between two mechanical modes are achieved through the cooperative interaction of an optical parametric amplifier and a squeezed vacuum field. Furthermore, our results demonstrate that breaking the dark mode effect significantly enhances the robustness of steady-state entanglement and asymmetric EPR steering against thermal noise. We further provide a physical interpretation of the generation and suppression of the dark mode effect. This work offers a promising approach for creating macroscopic quantum resources that are resistant to noise, with potential applications in quantum information processing.
First results of an evaluation of 100Gb/s Ethernet as a future HEP readout link
Authors: Stümpert Valentin , Klekotko Adam , Perro Alberto , Sigaud Christophe Gabriel , Montesinos Daniel Hernandez , Martina Francesco , Vichoudis Paschalis , Baron Sophie , Biereigel Stefan 
Published: February 2025

Abstract
This work presents first results from a feasibility study to qualify commercial 100 Gb/s Ethernet as a readout link for future high-energy physics detectors. The motivation for this work is to examine the possibility of reading out future detector front-ends directly via commercial, high bandwidth, cost-optimized data centers, without the need of the intermediate custom-link/hardware layer used for this purpose thus far. In an attempt to determine how well 100 Gb/s Ethernet is adapted to the readout of such systems, this paper examines the protocol on aspects such as unidirectional operation and radiation hardness. Initial work towards a complete demonstrator system is also presented.