bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep transfer learning in machinery remaining useful life prediction: a systematic review
Authors: Chen Gaige , Kong Xianguang , Cheng Han , Yang Shengkang , Wang Xianzhi 
Published: October 2024

Abstract
As a novel paradigm in machine learning, deep transfer learning (DTL) can harness the strengths of deep learning for feature representation, while also capitalizing on the advantages of transfer learning for knowledge transfer. Hence, DTL can effectively enhance the robustness and applicability of the data-driven remaining useful life (RUL) prediction methods, and has garnered extensive development and research attention in machinery RUL prediction. Although there are numerous systematic review articles published on the topic of the DTL-based approaches, a comprehensive overview of the application of DTL in the RUL prediction for different mechanical equipment has yet to be systematically conducted. Therefore, it is imperative to further review the pertinent literature on DTL-based approaches. This will facilitate researchers in comprehending the latest technological advancements and devising efficient solutions to address the cross-domain RUL prediction challenge. In this review, a brief overview of the theoretical background of DTL and its application in RUL prediction tasks are provided at first. Then, a detailed discussion of the primary DTL methods and their recent advancements in cross-domain RUL prediction is presented. Next, the practical application of the current research is discussed in relation to the research object and its open-source data. More importantly, several challenges and further trend are further presented to conclude this paper in the end. We have reason to hope this work can offer convenience and inspiration to researchers seeking to advance in the field of RUL prediction.
The unsupervised bearing fault diagnosis method based on the dual-framework Siamese network
Authors: Qu Xiaotian , Liu Yongqiang , Deng Feiyue , Yingying Liao , Qing Chengwei 
Published: October 2024

Abstract
Aiming at the problem of insufficient bearing fault samples in practical engineering, an unsupervised bearing fault diagnosis method with double frame twin network is proposed in this paper. This method only uses the source domain data to diagnose the target domain data, and can minimize the problem of domain difference. The concrete method is firstly to carry on continuous wavelet transform to the rolling bearing signal, and the processed signal is used as the input feature of convolutional neural network. The twin network structure is optimized and Manhattan distance is used as the loss function in the training process. The proposed CM network is applied to the diagnosis of inner ring fault, outer ring fault and normal state of rolling bearing. The results show that CM network can achieve over 90% accuracy on SQ variable speed vibration signal data set (SQV), Shijiazhuang Railway University data set (STD) and Case Western Reserve University data set (CWRU), which is suitable for bearing fault diagnosis under different working conditions and provides a new direction for fault diagnosis. The PyTorch code is available at https://github.com/xiaotianqu/The-unsupervised-bearing-fault-diagnosis-method-based-on-the-dual-framework-Siamese-network.
Deep learning-based acoustic emission source localization in heterogeneous rock media without prior wave velocity information
Authors: Cui Yi , Chen Jie , Chen Ziyang , Pu Yuanyuan , Yu Bin , Jiang Wei 
Published: October 2024

Abstract
Acoustic emission (AE) source localization is crucial for monitoring but often relies on prior information, such as wave velocity and arrival time. This study introduces a novel method for locating AE sources in rocks without such information, addressing challenges posed by heterogeneous sensor arrays. Experiments involving pencil led break (PLB) tests on sandstone cubes collected AE waveforms and their coordinates. A ResNet-50 based deep learning model was developed to correlate the time-frequency spectra of AE with PLB locations, expressed as spatial Gaussian distributions. The model, achieved a 79% prediction accuracy for AE localization in complex environments. While there is room for improvement in training data quantity and diversity, the results validate the model’s effectiveness, particularly in coal mines and tunnel engineering.
An enhanced mobile localization algorithm integrating multiple AUKF models for mixed indoor environments
Authors: Jiang Yi , Gao Heng , Zhang Pengpeng , Hu Qing 
Published: October 2024

Abstract
The positioning technology based on ultra-wideband ranging has been widely applied in the field of indoor positioning due to its excellent localization capabilities. However, mixed line-of-sight (LOS) and non-LOS (NLOS) indoor environments severely constrain positioning accuracy. To address this issue, we propose an innovative algorithm based on the adaptive unscented Kalman filter (AUKF) and interactive multiple model (IMM), designed to significantly enhance positioning accuracy in mixed indoor environments by mitigating the impact of NLOS errors and inaccurate process noise. Firstly, recognizing the distinct characteristics of ranging errors in indoor environments, we develop LOS and NLOS ranging models separately. Based on these models, the unscented Kalman filters are constructed for LOS and NLOS environments to accurately simulate the mixed LOS/NLOS indoor environments. Secondly, determining the statistical characteristics of process noise is challenging, often leading to degraded filter performance. We address this issue by proposing an environment-based AUKF algorithm, which significantly enhances the robustness and accuracy of the positioning system. Finally, the environment-based AUKFs are integrated into the IMM framework to constrain NLOS errors and achieve precise positioning effectively. Simulations, open-source dataset validation and experimental results demonstrate that the proposed algorithm significantly enhances the accuracy and stability of mobile target positioning in mixed LOS/NLOS indoor environments.
Sensing offset analysis and compensation of a capacitive displacement transducer for space inertial sensors
Authors: Yang Xiaotian , Wang Chengrui , Hu Ming , Lu Jinfeng , Bai Yanzheng , Qu Shaobo , Zhou Zebing 
Published: October 2024

Abstract
Capacitive displacement transducers play a crucial role in inertial sensors especially for space gravitational wave detection missions. One of the major requirements for the displacement transducer is to have a lower sensing offset. The sensing offset will adversely affect the accuracy of the absolute position measurement of the test mass, providing erroneous data to the drag-free controller and leading to spacecraft mispositioning. Additionally, the offset could introduce multiplicative noise to the sensing output and the closed loop output of the inertial sensor. The asymmetry of the sensing bridge within the front-end electronics has been identified as the primary source of these offsets. This paper analyzes the requirements of the main parameters in the sensing bridge. A method is proposed to reduce the sensing offset by utilizing differentiated resonant capacitors while maintaining the ability to tune the resonant frequency and ensure a sufficiently low sensing noise level. Experimental results show that this approach can effectively reduce the residual sensing offset to (−15.7 ± 5.0) ppm, which satisfies the stringent requirement for space inertial sensors in the TianQin mission.
Performance degradation assessment of rolling bearings for electrostatic monitoring based on IDDAE and ADPC
Authors: Wei Xinyue , Li Dewen , Li Zihan , Cai Jing , Li Ai , Zhang Ying 
Published: October 2024

Abstract
To improve the early degradation detection capability of the electrostatic monitoring system for rolling bearings, a performance degradation evaluation method based on improved deep denoising autoencoder and adaptive density peak clustering (ADPC) is proposed in this paper. Firstly, the fusion of electrostatic charge signal features with conventional time-domain, frequency-domain and time–frequency-domain features constitutes the characteristic parameter set of the electrostatic monitoring system indicating the status of the bearings. Then, in order to improve the feature extraction ability of DAE, the deep network DDAE is constructed, and L1 regularisation and Dropout mechanism are applied to avoid overfitting in the deep network, so as to achieve non-linear mapping dimensionality reduction of high-dimensional features. Moreover, to eliminate the error caused by manually selecting the clustering centre, the parameters are adaptively determined by entropy value method and comprehensive optimisation search on the basis of DPC, thus avoiding the ‘chain effect’ that occurs in traditional DPC when data are incorrectly aggregated due to incorrect assignment of clustering centres. Consequently, an improved ADPC algorithm is used to establish a model to measure the health status of bearings, calculate the Mahalanobis distance (MD) between the test set and the cluster centre, and quantitatively characterize the degree of performance degradation of rolling bearings. Finally, combining the

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principle, a repair method that can satisfy online monitoring and adapt to spurious fluctuations in different situations is established on a sliding window to obtain an improved index IMD that can accurately characterise the rolling bearing degradation process. The experimental results show that the proposed method can identify early bearing degradation earlier and has better monotonicity, robustness and tendency than other performance degradation assessment methods.
Laser-assisted synthesis and modification of 2D materials
Authors: Lee Yejun , Hong Sunhwa , Moon Issac , Kim Chan-Jin , Lee Yunseok , Hong Byung Hee 
Published: October 2024

Abstract
Two-dimensional (2D) materials with unique physical, electronic, and optical properties have been intensively studied to be utilized for the next-generation electronic and optical devices, and the use of laser energy in the synthesis and modification of 2D materials is advantageous due to its convenient and fast fabrication processes as well as selective, controllable, and cost-effective characteristics allowing the precise control in materials properties. This paper summarizes the recent progress in utilizations of laser technology in synthesizing, doping, etching, transfer and strain engineering of 2D materials, which is expected to provide an insight for the future applications across diverse research areas.
CRISPR-based strategies for sample-to-answer monkeypox detection: current status and emerging opportunities
Authors: Ahamed Md Ahasan , Politza Anthony J , Liu Tianyi , Khalid Muhammad Asad Ullah , Zhang Huanshu , Guan Weihua 
Published: October 2024

Abstract
The global health threat posed by the Monkeypox virus (Mpox) requires swift, simple, and accurate detection methods for effective management, emphasizing the growing necessity for decentralized point-of-care (POC) diagnostic solutions. The clustered regularly interspaced short palindromic repeats (CRISPR), initially known for its effective nucleic acid detection abilities, presents itself as an attractive diagnostic strategy. CRISPR offers exceptional sensitivity, single-base specificity, and programmability. Here, we reviewed the latest developments in CRISPR-based POC devices and testing strategies for Mpox detection. We explored the crucial role of genetic sequencing in designing crRNA for CRISPR reaction and understanding Mpox transmission and mutations. Additionally, we showed the integration of CRISPR-Cas12 strategy with pre-amplification and amplification-free methods. Our study also focused on the significant role of Cas12 proteins and the effectiveness of Cas12 coupled with recombinase polymerase amplification (RPA) for Mpox detection. We envision the future prospects and challenges, positioning CRISPR-Cas12-based POC devices as a frontrunner in the next generation of molecular biosensing technologies.
A simulation framework for preclinical proton irradiation workflow
Authors: Malimban Justin , Ludwig Felix , Lathouwers Danny , Staring Marius , Verhaegen Frank , Brandenburg Sytze 
Published: October 2024

Abstract

Objective. The integration of proton beamlines with x-ray imaging/irradiation platforms has opened up possibilities for image-guided Bragg peak irradiations in small animals. Such irradiations allow selective targeting of normal tissue substructures and tumours. However, their small size and location pose challenges in designing experiments. This work presents a simulation framework useful for optimizing beamlines, imaging protocols, and design of animal experiments. The usage of the framework is demonstrated, mainly focusing on the imaging part. Approach. The fastCAT toolkit was modified with Monte Carlo (MC)-calculated primary and scatter data of a small animal imager for the simulation of micro-CT scans. The simulated CT of a mini-calibration phantom from fastCAT was validated against a full MC TOPAS CT simulation. A realistic beam model of a preclinical proton facility was obtained from beam transport simulations to create irradiation plans in matRad. Simulated CT images of a digital mouse phantom were generated using single-energy CT (SECT) and dual-energy CT (DECT) protocols and their accuracy in proton stopping power ratio (SPR) estimation and their impact on calculated proton dose distributions in a mouse were evaluated. Main results. The CT numbers from fastCAT agree within 11 HU with TOPAS except for materials at the centre of the phantom. Discrepancies for central inserts are caused by beam hardening issues. The root mean square deviation in the SPR for the best SECT (90 kV/Cu) and DECT (50 kV/Al–90 kV/Al) protocols are 3.7% and 1.0%, respectively. Dose distributions calculated for SECT and DECT datasets revealed range shifts <0.1 mm, gamma pass rates (3%/0.1 mm) greater than 99%, and no substantial dosimetric differences for all structures. The outcomes suggest that SECT is sufficient for proton treatment planning in animals. Significance. The framework is a useful tool for the development of an optimized experimental configuration without using animals and beam time.
Hydrodynamic equations for a U(N) invariant superfluid
Authors: Zhang Yi-Cai , Zhang Shizhong 
Published: October 2024

Abstract
In this paper, we develop an appropriate set of hydrodynamic equations for a U(N) invariant superfluid that couple the dynamics of superflow and magnetization. In the special case when both the superfluid and normal velocities are zero, the hydrodynamic equations reduce to a generalized version of Landau–Lifshitz equation for ferromagnetism with U(N) symmetry. When both velocities are non-zero, there appears couplings between the superflow and magnetization dynamics, and the superfluid velocity no longer satisfies the irrotational condition. On the other hand, the magnitude of magnetization is no longer a constant of motion as was the case for the standard Landau–Lifshitz theory. In comparison with the simple superfluid, the first and second sounds are modified by a non-zero magnetization through various thermodynamic functions. For U(2) invariant superfluid, we get both (zero-) sound wave and a spin wave at zero temperature. It is found that the dispersion of spin wave is always quadratic, which is consistent with microscopic analysis. In the appendix, we show that the hydrodynamic equation for a U(N) invariant superfluid can be obtained from the general hydrodynamic equation with arbitrary internal symmetries.
Terahertz laser-fabricated all-polymer hole arrays with high-quality quasi-bound states in the continuum
Authors: Shen Yanchun , Wu Feng , Liu Dejun 
Published: October 2024

Abstract
Dielectric metasurfaces promise to realize ultrahigh-quality (Q) resonances due to their ultralow material absorption. Most of them are silicon-based metasurfaces, requiring complex fabricated steps and thus suffering high costs. Laser etching processing has simple steps accompanied by low time consumption and exemplary processing efficiency. Here, an all-polymer metasurface based on hole arrays fabricated by laser processing has been proposed and investigated. Such metasurfaces achieve sharp quasi-bound states in the continuum (quasi-BICs) via breaking structural symmetry, form two annular circulation electric fields in different directions, and thus allow strong coupling between holes. Owing to the low refractive index of polymer, the calculated Q-factor reaches 9555 while the diameter discrepancy is 4 μm. Simulated results proved that the Q-factors of quasi-BICs can be further improved by reducing the film thickness and refractive indices of materials, which can be predicted by the fitting equation. Also, the fields in holes can be enhanced by reducing the film refractive index. These results in simulations and experiments provide an alternative method for designing high-Q resonators in terahertz regions.
Effect of silver nanoparticles on the photostability and aging of CsPbBr3 nanocrystals
Authors: Krukov Vitali , Patsinko Olga , Ramanenka Andrei A , Kulakovich Olga , Canımkurbey Betül , Gaponenko Sergey V 
Published: October 2024

Abstract
Perovskite nanocrystals may become a promising replacement for current phosphors in light-emitting diodes (LEDs) and screens, but the question of the stability of their optical properties remains open. One way to solve this problem could be to use plasmonic nanoparticles. In this work, we investigate the combination of all-inorganic perovskite nanocrystals synthesized by the hot-injection method with spherical Ag nanoparticles (mean diameter 53 nm). 3-fold enhancement of photoluminescence (PL) has been implemented in hybrid ‘silver-CsPbBr3-polymethyl methacrylate’ structures. The presence of silver nanoparticles reduces the likelihood of Auger processes and forms a possible silver bromide barrier layer which prevents photoinduced ion migration in the perovskite-polymer film. Plasmonic enhancement of PL partially presents during long-term samples storage within 75 days. This work may be useful in the creation of perovskite LEDs using remote phosphor technology.
Low-energy (0–9 eV) electron interaction with gas phase 1,3-dichlorobenzene: an experimental and theoretical study
Authors: Abdoul-Carime H , G F de Miranda E , Varella M T do N 
Published: October 2024

Abstract
Dichlorobenzene used widely in industry for the synthesis of complex products, such as polymers. The processes using this compound require, as the initial step, the breakage of the C–Cl bond. In this work, we study the interaction of electrons with 1,3 dichlorobenzene molecules not only below 2 eV [M Mahmoodi-Darian et al 2001 J. Phys. Chem. A 113 11923–14929] but also at higher energies, i.e., up to 10 eV. In this investigated energy range, the electron induces the cleavage of the C–Cl bond producing essentially a Cl− anion and the chlorobenzene radical via dissociative electron attachment. The experimental measurements are completed with quantum scattering treatments providing the resonant states and also the integral scattering cross sections. These outcomes may potentially contribute to elaborate synthesis strategies using electrons (i.e., cold plasma, surface plasmon resonance, …).
Supression of shielding effect of large area field emitter cathode in radio frequency gun environment
Authors: Sathya A T , Sarkar Shreya G , Bakhtsingh R I , Mondal Jayanta 
Published: October 2024

Abstract
Utilisation of large area field emitters (LAFE) cathodes for rf gun injector hold promise for delivering compact, high power and high brightness electron beam for advanced accelerator technologies. LAFEs subjected to DC electric fields posses significant challenges due to the shielding effect which restricts emission from central emitters and decreases the overall current density. Mitigating the shielding effect of LAFE in rf gun environment is essential for meeting the desired beam quality requirement in an accelerator. The current distribution of LAFE under DC conditions depend on its various geometrical parameters such as emitter height, inter-emitter distance, aspect ratio, number of emitters. Additionally, in rf gunsetup, LAFEs are subjected to variable macroscopic electric field at different emitter position which can potentially alter the current distribution compared to DC fields. In this work, we have systematically studied the shielding effect properties of LAFE in rf gun environment under the influence of various LAFE parameters. A semi-analytical approachhas been adopted to estimate the current distribution which combines the analytically calculated field enhancement factor (γ) and numerically calculated applied rf field values. This new methodology was first validated using COMSOL simulation and then employed for field emission performance estimation of a LAFE cathode integrated in a½ cell S-band (2856 MHz) rf gun. The simulation results reveals that under favourable conditions, a Gaussian spatial distribution of beam can be obtained from LAFE thus countering the shielding effect typical in DC fields. By optimizing the LAFE parameters, the desired current and beam distribution pattern can be achieved. This study highlights the adoption of a promising approach for designing LAFE cathodes suitable for rf gun which can lead to advancement of field emission technologies for accelerator-related applications.
Structure-preserving analysis on chaotic characteristics of transverse vibration for embedded double-walled carbon nanotube
Authors: Hu Weipeng , Han Songmei , Wang Gangwei , Wazwaz Abdul-Majid 
Published: October 2024

Abstract
Analysing the ultra-high frequency vibrational characteristics of carbon nanotubes, especially on the chaotic characteristics, is a key scientific problem in the dynamic design of the carbon nanotube devices. Considering the van der Waals force between the inner layer and the outer layer of the embedded double-walled carbon nanotube, and the effects of the elastic medium as well as the effects of the simple harmonic external excitation, the coupling dybamic model describing the transverse vibration of the embedded double-walled carbon nanotube is presented. The generalized multi-symplectic formulations with an explicit multi-symplectic structure residual are deduced by introducing the dual momenta. The Preissmann approach, which has been proved to be a structure-preserving method that can be used to reproduce the chaotic characteristics of carbon nanotubes, is employed to discrete the generalized multi-symplectic formulations. The numerical results imply that, the transverse vibration of the embedded double-walled carbon nanotube subjected to the external excitation larger than the critical external excitation will enter the chaotic state through a period-doubling bifurcation path. In addition, the critical external excitation for the chaos of the inner layer carbon nanotube’s transverse vibration is larger than that of the outer layer carbon nanotube’s transverse vibration. The above findings reported in this paper provide some guidance for the dynamic design of the carbon nanotube devices directly.