bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fine-grained fault diagnosis of photovoltaic systems based on DMAD-GAN and IFD-FGIF
Authors: Qiao Juanjuan , Qi Yongsheng , Liu Liqiang , Li Yongting , Luo Zhihong 
Published: December 2024

Abstract
In the field of photovoltaic (PV) system monitoring, fault detection faces two critical challenges: data imbalance and fault diversity, as well as incomplete complex fault information. To tackle these issues, this paper proposes a dual-mechanism anomaly detection with generative adversarial network (DMAD-GAN) and an integrated fault diagnosis with fine-grained information fusion (IFD-FGIF). DMAD-GAN utilizes GAN to integrate dual mechanisms for anomaly detection in PV datasets, with coordinate-space attention enhancing the perception of subtle features and differences in PV panels. The anomaly scoring mechanism utilizes an improved loss function to compute anomaly scores, assessing the degree of anomaly for each sample. In the IFD-FGIF method, t-SNE is used to visualize features for fault pre-classification to determine the presence of new faults. A fine-grained information fusion module is designed, leveraging ResNet50 to extract features from fault key areas and original images. This module integrates fine-grained features, original features, and fine-grained attributes. Fault attributes and categories are determined using an attribute classifier and Euclidean distance. If a new fault is identified during pre-classification, the network undergoes transfer learning to recognize and adapt to the new fault. The experimental results demonstrate that the proposed method outperforms other networks, achieving an anomaly detection accuracy of 95.86%. The fault fine-grained recognition accuracy is 95.62%. The accuracy of fine-grained information fusion has improved by 4%, and unsupervised learning of new faults has been successfully achieved. The proposed method can enhance the intelligent operation and maintenance capability of PV power plants, reduce false alarm rates in fault detection, and minimize operational risks caused by potential faults, thus effectively shortening downtime and lowering maintenance costs.
MLDM: a multi learning domain model for fault identification of centrifugal fan
Authors: Wang Ruijun , Fan Zhixia , Liu Yuan 
Published: December 2024

Abstract
In centrifugal fan fault diagnosis, the influence of multiple noise sources causes the collected fault signals to contain interference of different modes. Therefore, the difficulty of capturing fault characteristics greatly increases in this situation. In this article, a multi learning domain model scheme is proposed based on signal processing technology and artificial intelligence methods. The Haar wavelet convolution extraction module in the scheme is used to synchronously map features at different frequency scales, while the lightweight multi-scale feature enhancement module enhances feature extraction at different time scales. Meanwhile, upsampling is employed to enhance the expression of fault features. In addition, applying information rectification learning to feature maps extracted at each level allows for spatial representation and selection of extracted fault features, providing a basis for final decision-making. This scheme performs multi-level and multi-scale analysis on fault signals, jointly extracting time, frequency, and spatial information to improve the robustness and generalization ability of the model. Conduct experimental verification using data from the same type of centrifugal fan and rotor. The experimental results show that the recognition accuracy of the proposed model is about 93% for fan data at SNR = −4 dB, which has certain competitiveness compared to other excellent models.
Research on deterioration state evaluation of hydropower units based on successive variational mode decomposition and Mahalanobis distance
Authors: Wei Jiafu , Cao Chaofan , Yu Qing , Lu Na , Guo Jiang 
Published: December 2024

Abstract
In order to better acquire the real-time operating status of hydropower units and realize early fault warning, a deterioration state evaluation method for hydropower units based on successive variational mode decomposition (SVMD) and Mahalanobis distance (MD) is proposed. In the offline stage, SVMD is optimized with dispersion entropy as the fitness function, and historical health data is used to obtain a health baseline. In the online stage, the real-time monitoring signal is input into the optimized SVMD model first. The features of the intrinsic mode functions are then extracted. Subsequently, synthetic detection index and detection index are utilized for feature parameter selection. Finally, a degradation indicator is constructed based on Gaussian mixture model and MD, and the degradation curve is drown to evaluate the real-time deterioration state of the unit. Experimental results demonstrate that the proposed method can effectively characterize the real-time operating status of hydropower units, identify abnormal changes of the unit 4 d in advance, and issue timely warning.
Parameterized ZNCC image correlation for rotary-angle measurement
Authors: Wei Wang , Yang Wenyi , Li Chujun , Yuan Guixin , Xia Yang 
Published: December 2024

Abstract
High-accuracy rotary-angle measurement is critical for precise positioning and control of robots, machine arms, and machine tools in industry. Image-based measurement is a very promising technology for angle positioning owing to its simple system, low cost, and good robustness to environments. Image correlation, such as the zero-mean normalized cross correlation (ZNCC) method, can obtain high accuracy image-positioning results, but their efficiency is too low to directly use in industries. This paper proposes to measure the absolute rotary angle using a parameterized ZNCC (PZNCC) image correlation method. The PZNCC expresses the ZNCC coefficient by the image-shift parameters explicitly, so that the precise match point corresponding to the global ZNCC maximum can be efficiently obtained and no image-resampling process is required. As a result, PZNCC is approximately 5 times faster than the classic inverse compositional Gauss–Newton algorithm. Experiments show that rotary angle measurement based on PZNCC can obtain absolute angle positions with an accuracy of 1.16 arcsec (RMSE).
Exploring hydrogen adsorption and release in 2D M2C-MXenes: structural and functional insights
Authors: Xu Wenzhen , Sun Liang , Zhai Wenyan , Yang Jia , Jiang Tao , Peng Jianhong 
Published: December 2024

Abstract
Two-dimensional M2C-MXenes, characterized by their lightweight nature, tunable surface structures, and strong affinity for hydrogen, hold significant promise for addressing various challenges in hydrogen energy utilization. This study focuses on investigating the hydrogen adsorption and desorption properties, as well as the stability of hydrogenated compounds in 19 pure M2C-MXenes nanosheets. The results indicate that hydrogen adsorption on M2C primarily occurs through weak physisorption, with Mn2C and Fe2C from the fourth period, and Ag2C and Cd2C from the fifth period exhibiting the lowest adsorption energies. In contrast, hydrogen atoms are adsorbed on M2C primarily through chemisorption, leading to the potential dissociation of H2 molecules into two hydrogen atoms. Among the M2C-MXenes, Ti2C, and Zr2C in the d4
and d5
, respectively, demonstrate the most stable hydrogen atom binding. Hydrogen evolution is most facile on Cu2C and Ag2C surfaces. Two types of stacking configurations, face-centered cubic and hexagonal close-packed, are observed for hydrogenated M2C surfaces (e.g. Co2C and Zr2C), showing excellent thermodynamic stability. This work elucidates the hydrogen utilization performance of pure M2C-MXenes nanosheets and guides future research aimed at achieving high hydrogen storage capacities through the functional tuning of MXenes.
Internal transport barrier triggered by phase synchronization of zonal flow with energetic particle modes
Authors: Ghizzo A , Del Sarto D , Sama N J , Biancalani A 
Published: December 2024

Abstract
The suppression of the microturbulence associated to the emergence of a spontaneous internal transport barrier has been recently demonstrated in a system showing a possible amplification of the zonal flow component in the low-frequency regime (Ghizzo and Del Sarto 2023 Nucl. Fusion
63 104002). We use here numerical experiments performed with a ‘particles modes’ model based on a double average over the fast cyclotron phase and over the bounce (or transit) phase to show the major role played by energetic particles and shear flows in this scenario. ‘Particle modes’ are meant here as classes of particles, identified by some adiabatic invariant after a gyro-average procedure, which are associated to the description of some specific linear modes of the plasma. The introduction of energetic circulating ions or shear flows into the system makes a larger number of particle modes being involved in the synchronization process. A global synchronization of the Fourier modes of the turbulent spectrum can be this way achieved. This process allows for a bifurcation towards self-organization, which is associated to the emergence of a staircase-like structure. This is known to be an essential element in the modification of the zonal flow pattern in phase space during the suppression of microturbulence in tokamaks.
Continuous natural fiber-reinforced shape memory polymer biocomposites: design and fabrication for sustainable self-folding architectural applications
Authors: Hassan Asmaa , Dahy Hanaa 
Published: December 2024

Abstract
The growing demand for sustainable building materials has driven the search for innovative solutions that minimize environmental impact while enhancing architectural functionality. Nature’s adaptability to environmental changes, such as the mimosa plant’s sensitivity to temperature and touch, has inspired the development of shape memory materials like shape memory polymers (SMPs). These materials change shape in response to external stimuli, offering promising solutions for responsive and eco-friendly applications. This study investigates the use of SMP biocomposites (SMPBCs) reinforced with continuous flax fibers for sustainable architectural applications. The main aim is to enhance the mechanical and shape memory properties of these materials, focusing on design exploration, fabrication methods, and performance evaluation for architectural use. Combining material science with digital fabrication techniques, particularly tailored fiber placement, this research integrates flax fiber into thermo-responsive epoxy-based SMPs. Origami-inspired designs, including rigid and curved folding origami, were explored using a moldless fabrication technique to optimize the SMPBCs’ performance and facilitate the creation of complex three-dimensional structures. The study began with initial prototypes of simple origami shapes, followed by three architectural prototypes representing distinct origami types. Curved folding origami enhances shape memory performance by enabling larger deformation, which increases strain energy storage and allows more effective recovery. Further exploration of single and multi degree of freedom (SDOF and MDOF) designs for architectural applications revealed that curved SDOF prototypes achieved the highest shape recovery ratio (Rr
%) of 97%, while rigid MDOF prototypes showed the lowest Rr
of 60% and 70%. All prototypes provided a high shape fixity ratio of nearly 100%. Moreover, initial load tests on the permanent shapes demonstrated their ability to support over 240 times their weight. This research advances sustainable architecture by showing how SMPBCs with optimal geometric designs can enable self-shaping and multifunctional applications, paving the way for more adaptive, eco-friendly building materials.
Strain-induced interstitial anionic electrons and superconductivity of monolayer BaCu
Authors: Zhou Tong , Guan ZhiYao , Cui Tian , Li Da 
Published: December 2024

Abstract
Recently, a novel electride, BaCu, which contains no light elements, has been both predicted and synthesized. This material adds to the list of inorganic two-dimensional (2D) interlayer electrides, including Ca2N and Y2C. However, the electride properties of the BaCu monolayer are not known, and its characteristics have not been thoroughly investigated. Here, our first-principles calculations indicated that the BaCu monolayer is a weak electride with few interstitial anionic electrons (IAEs). Notably, biaxial tensile strain can significantly alter the electronic properties of the BaCu monolayer, leading to the increase of IAEs. This strain causes a redistribution of charge from the Ba and Cu atoms to the IAEs. Additionally, the biaxial tensile strain induces superconductivity in the BaCu monolayer, and a notable increase in the critical superconducting transition temperature (T
c) to 0.2 K at 10% strain is observed. The coupling between the vibrations of the Cu atoms and IAEs plays a crucial role in this superconductivity. Our findings provide valuable insights into the relationship between the IAEs and superconductivity in the 2D electrides.
Quantum advantages in

(n,d)

↦

1

random access codes
Authors: Ambainis Andris , Kravchenko Dmitry , Sazim Sk , Bae Joonwoo , Rai Ashutosh 
Published: December 2024

Abstract
A random access code (RAC), corresponding to a communication primitive with various applications in quantum information theory, is an instance of a preparation-and-measurement scenario. In this work, we consider (n, d)-RACs constituting an n-length string, constructed from a d size set of letters, and send an encoding of the string in a single d-level physical system and present their quantum advantages. We first characterize optimal classical RACs and prove that a known classical strategy, called majority-encoding-identity-decoding, is optimal. We then construct a quantum protocol by exploiting only two incompatible measurements (the minimal requirement) and show the advantages beyond the classical one. We also discuss the generality of our results and whether quantum advantages are valid for all types of

(
n
,
d
)

↦

1

RACs.
Efficient hardware implementation of ROM-free LFM waveform generation for real-time reconfigurable software-defined radar
Authors: Bellabas A , Mesloub A , Ghezali B , Ziani T , Maali A 
Published: December 2024

Abstract
This paper presents a novel method for generating Linear Frequency Modulation (LFM) waveforms. Conventional Look-Up table (LUT)-based method requires large storage resources, especially in high-resolution, multi-mode radar systems. To address this issue, we propose a ROM-free, real-time LFM waveform generator. It uses the fourth-order Runge-Kutta (RK-4) method to solve differential equations for the in-phase and quadrature components. The proposed approach dynamically generates LFM waveforms using only parameters such as pulse width, bandwidth, and sampling rate, eliminating the need for pre-calculated waveforms and LUTs. This method completely removes storage requirements, enabling faster synthesis times and achieving minimal latency. The generator's performance is validated through simulation and FPGA implementation using a full hardware description language. Results confirm its effectiveness, making it a strong candidate for advanced radar systems that demand high performance with limited hardware resources.
Exploring the dynamics of overtaking interactions of electron acoustic solitons in beam-driven unmagnetized plasmas: application in the auroral region
Authors: Shohaib Muhammad , Masood W , Jahangir R 
Published: December 2024

Abstract
This study explores the propagation of nonlinear electron acoustic waves (EAWs) in an unmagnetized plasma consisting of dynamical inertial cold electrons, hot electrons following (r, q) distribution, a warm electron beam, and background ions. The fluid equations representing the plasma system are reduced to Kadomtsev–Petviashvili (KP) equation for EAWs by using the reductive perturbation technique. Our findings reveal that several key factors significantly influence the propagation and interaction properties of electron acoustic solitary waves (EASWs). These factors include the spectral indices r and q of the generalized (r, q) distribution, the concentrations of cold, hot, and beam electrons, as well as the temperature ratios among these electron populations. Additionally, we investigate the possible types of overtaking interactions between two Kadomtsev–Petviashvili (KP) solitons. The spatial regime for the interaction of two solitons is found to vary depending on the effect of plasma parameters on a single soliton behavior. This comprehensive analysis provides valuable insights into the complex interactions between EASWs, which are relevant for understanding phenomena in laboratory, space, and astrophysical plasmas.
A novel intensity-based phase unwrapping method for highly discontinuous topology
Authors: Yi Jingya , Wei Sheng , Song Mengsa , Tang Yu , Wen Zhiqing , Chen Weilin 
Published: December 2024

Abstract
The analysis of the phase of highly discontinuous surfaces presents significant challenges in the field of fringe projection profilometry. This research proposes a novel phase unwrapping technique based on an illumination attenuation model to efficiently resolve the phase of discontinuous objects. The study begins by analyzing the attenuation characteristics of light intensity with distance. Using the phase height model in the fringe projection profilometry system, the unwrapped light intensity-phase difference distribution map is then computed. A phase mask is subsequently employed to segment discontinuous regions, enabling phase unwrapping within each distinct section. The phase jump order, derived from the light intensity-phase difference, guides the integration of sub-regions to construct the global unwrapped phase map. This method achieves effective phase unwrapping in regions with discontinuities without increasing system complexity or requiring additional projection images. Furthermore, this method is particularly effective for isolated regions exhibiting phase jumps. The effectiveness of the proposed phase unwrapping algorithm is validated through both simulations and experimental evaluations.
Mechanical analysis and function matrix projective synchronization of El-Nino chaotic system
Authors: Shukla Vijay K , Joshi Mahesh C , Mishra Prashant K , Xu Changjin 
Published: December 2024

Abstract
This study explores the mechanical aspects of the El-Nino system by transforming it into a Kolmogorov type system, characterized by four types of torques known as internal, inertial, dissipation, and external. Five scenarios by varying these torques to identify the factors that lead to chaos and their physical significance are also investigated. The interactions between kinetic, potential, and Hamiltonian energies are analyzed and depicted as how these energies interact with system parameters. The study also emphasizes the benefits of conservative chaos over dissipative chaos. Particularly, it has more applications like secure communications and pseudo-random number generation. The role of force interactions and exchanges, including Casimir energy in the generation of chaos is also identified. The transition from regular to irregular orbits, and then to more chaotic states is investigated through Casimir function. It concludes that all four types of torques are necessary to induce chaos in the El Niño chaotic system. Additionally, function matrix projective synchronization between identical El-Nino chaotic systems has achieved.
Bloch sphere representation for Rabi oscillation driven by Rashba field in the two-dimensional harmonic confinement system
Authors: Arai Kaichi , Tojo Tatsuki , Takeda Kyozaburo 
Published: December 2024

Abstract
We studied the dynamical properties of Rabi oscillations driven by an alternating Rashba field applied to a two-dimensional (2D) harmonic confinement system. We solve the time-dependent (TD) Schrödinger equation numerically and rewrite the resulting TD wavefunction onto the Bloch sphere (BS) using two BS parameters of the zenith (θ
B) and azimuthal (ϕ
B) angles, extracting the phase information ϕ
B as well as the mixing ratio θ
B between the two BS-pole states. We employed a two-state rotating wave (TSRW) approach and studied the fundamental features of θ
B and ϕ
B over time. The TSRW approach reveals a triangular wave formation in θ
B. Moreover, at each apex of the triangular wave, the TD wavefunction passes through the BS pole, and the state is completely replaced by the opposite spin state. The TSRW approach also elucidates a linear change in ϕ
B. The slope of ϕ
B vs. time is equal to the difference between the dynamical terms, leading to a confinement potential in the harmonic system. The TSRW approach further demonstrates a jump in the phase difference by π when the wavefunction passes through the BS pole. The alternating Rashba field causes multiple successive Rabi transitions in the 2D harmonic system. We then introduce the effective BS and transform these complicated transitions into an equivalent ‘single’ Rabi one. Consequently, the effective BS parameters

θ

B

eff

and

ϕ

B

eff

exhibit mixing and phase difference between two spin states α and β, leading to a deep understanding of the TD features of multi-Rabi oscillations. Furthermore, the combination of the BS representation with the TSRW approach successfully reveals the dynamical properties of the Rabi oscillation, even beyond the TSRW approximation.
Enhancing entanglement and steering in a hybrid atom–optomechanical system via Duffing nonlinearity
Authors: Dong 董 Ling-Hui 凌晖 , Wu 武 Xiao-Jie 晓捷 , Bai 白 Cheng-Hua 成华 , Wu 武 Shao-Xiong 少雄 
Published: December 2024

Abstract
We introduce a novel scheme for achieving quantum entanglement and Einstein–Podolsky–Rosen (EPR) steering between an atomic ensemble and a mechanical oscillator within a hybrid atom–optomechanical system. The system comprises an optical cavity, a two-level atomic ensemble and a mechanical resonator that possesses Duffing nonlinearity. The interaction between these components is mediated by the cavity mode, which is driven by an external laser. Our findings indicate that optimizing the coupling strengths between photons and phonons, as well as between atoms and the cavity, leads to maximal entanglement and EPR steering. The amplitude of the driving laser plays a pivotal role in enhancing the coupling between photons and phonons, and the system maintains robust entanglement and EPR steering even under high dissipation, thereby mitigating the constraints on initial conditions and parameter precision. Remarkably, the Duffing nonlinearity enhances the system’s resistance to thermal noise, ensuring its stability and entanglement protection. Our analysis of EPR steering conditions reveals that the party with lower dissipation exhibits superior stability and a propensity to steer the party with higher dissipation. These discoveries offer novel perspectives for advancing quantum information processing and communication technologies.