bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mode-selective photon-added two-mode squeezed vacuum state and its entanglement properties
Authors: Li Heng-Mei , Wang Zhen , Cai Jian-Wen , Yuan Hong-Chun , Xu Xue-Xiang 
Published: July 2024

Abstract
A class of non-Gaussian entangled states is introduced by applying the nonlocal single-photon addition to two-mode squeezed vacuum state and the properties of entanglement are numerically investigated according to linear entropy and Einstein–Podolsky–Rosen (EPR) steering. After the nonlocal single-photon addition operation, Wigner function of the generated state appears some negative region and loses its Gaussian property in phase space. In essence, non-Gaussian entangled states are generated after applying nonlocal single-photon addition. Additionally, by studying the linear entropy and EPR steering, we find that single-photon addition can enhance their entanglement degree and non-Gaussian steering can be witnessed in a large range of squeezing parameter for the second-order quadratures, which may provide a well application in the fields of quantum information processing.
Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task
Authors: Chung Ryan S , Martin del Campo Vera Roberto , Sundaram Shivani , Cavaleri Jonathon , Gilbert Zachary D , Leonor Andrea , Shao Xiecheng , Zhang Selena , Kammen Alexandra , Mason Xenos , Heck Christi , Liu Charles Y , Kellis Spencer S , Lee Brian 
Published: July 2024

Abstract

Objective. Traditionally known for its involvement in emotional processing, the amygdala’s involvement in motor control remains relatively unexplored, with sparse investigations into the neural mechanisms governing amygdaloid motor movement and inhibition. This study aimed to characterize the amygdaloid beta-band (13–30 Hz) power between ‘Go’ and ‘No-go’ trials of an arm-reaching task. Approach. Ten participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a direct reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-corrected Z tests were used to assess significant modulations of beta power between the Response and fixation (baseline) phases in the ‘Go’ and ‘No-go’ conditions. Main results. In the ‘Go’ condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p ⩽ 0.0499). In the ‘No-go’ condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the response phase (p ⩽ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the ‘Go’ and ‘No-go’ conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders. Significance. This study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.
Adaptive EMG decomposition in dynamic conditions based on online learning metrics with tunable hyperparameters
Authors: Mendez Guerra Irene , Barsakcioglu Deren Y , Farina Dario 
Published: July 2024

Abstract

Objective. Developing neural decoders robust to non-stationary conditions is essential to ensure their long-term accuracy and stability. This is particularly important when decoding the neural drive to muscles during dynamic contractions, which pose significant challenges for stationary decoders. Approach. We propose a novel adaptive electromyography (EMG) decomposition algorithm that builds on blind source separation methods by leveraging the Kullback–Leibler divergence and kurtosis of the signals as metrics for online learning. The proposed approach provides a theoretical framework to tune the adaptation hyperparameters and compensate for non-stationarities in the mixing matrix, such as due to dynamic contractions, and to identify the underlying motor neuron (MN) discharges. The adaptation is performed in real-time (∼22 ms of computational time per 100 ms batches). Main results. The hyperparameters of the proposed adaptation captured anatomical differences between recording locations (forearm vs wrist) and generalised across subjects. Once optimised, the proposed adaptation algorithm significantly improved all decomposition performance metrics with respect to the absence of adaptation in a wide range of motion of the wrist (80∘). The rate of agreement, sensitivity, and precision were

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90
%

in

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80
%

of the cases in both simulated and experimentally recorded data, according to a two-source validation approach. Significance. The findings demonstrate the suitability of the proposed online learning metrics and hyperparameter optimisation to compensate the induced modulation and accurately decode MN discharges in dynamic conditions. Moreover, the study proposes an experimental validation method for EMG decomposition in dynamic tasks.
Extraction of nonlinearity in neural networks with Koopman operator
Authors: Sugishita Naoki , Kinjo Kayo , Ohkubo Jun 
Published: July 2024

Abstract
Nonlinearity plays a crucial role in deep neural networks. In this paper, we investigate the degree to which the nonlinearity of the neural network is essential. For this purpose, we employ the Koopman operator, extended dynamic mode decomposition, and the tensor-train format. The Koopman operator approach has been recently developed in physics and nonlinear sciences; the Koopman operator deals with the time evolution in the observable space instead of the state space. Since we can replace the nonlinearity in the state space with the linearity in the observable space, it is a hopeful candidate for understanding complex behavior in nonlinear systems. Here, we analyze learned neural networks for the classification problems. As a result, the replacement of the nonlinear middle layers with the Koopman matrix yields enough accuracy in numerical experiments. In addition, we confirm that the pruning of the Koopman matrix gives sufficient accuracy even at high compression ratios. These results indicate the possibility of extracting some features in the neural networks with the Koopman operator approach.
Design and Implementation of Precise Position Control for High-Power Stepper Motors and Grating Rulers Based on STM32
Authors: Qin Xin , Song Zeyu , Fan Weijie , Tian Bo 
Published: July 2024

Abstract
In common closed-loop feedback stepper systems, grating ruler displacement sensors are often used for linear displacement detection. To improve the precision positioning of the motor platform and meet the requirements of high-precision automated measurement, this paper proposes a high-power stepper motor 57J1880-450 based on STM32. The control system uses a grating ruler measurement platform to feedback displacement to the processor for displacement compensation, aiming to achieve high-precision closed-loop control of the linear motion platform. Experimental results have shown that the designed linear motion platform has a high-precision positioning function and can be applied to some motion positioning control systems.
Research on the significance of coupling effects of multiple process parameters in 3D printing based on orthogonal experimental method
Authors: Zeng Lianghua , Wu Wenxiong 
Published: July 2024

Abstract
For the semi-cylindrical model, orthogonal experiments and range analysis methods are used to explore the effects of four process parameters, namely layer thickness, printing speed, nozzle temperature, and bottom plate temperature, on the cross-sectional profile error and height error of FDM type 3D printing. This paper summarizes the optimal process plan for various errors and the significance of their impact, providing a certain reference for the coupling mechanism and significance research of process parameters.
Optimization of Ultrasonic Motor Control Based on NARX Neural Network
Authors: Yang Chengju , Li Tianjian , Zhou Shen , Lin Tao 
Published: July 2024

Abstract
Compared with traditional motors, ultrasonic motors have the advantages of small size and no noise and are widely used in modern technological fields. This article proposes a neural network-based ultrasonic motor control method and optimizes it to address the difficulty of controlling ultrasonic motors. Firstly, the principle and equivalent circuit of ultrasonic motors are studied, and a phase-shifted PWM method suitable for driving ultrasonic motors is proposed. Secondly, to meet the nonlinear characteristics of ultrasonic motors, a NARX neural network that can be used for nonlinear systems is adopted for optimization control. Finally, an experimental platform was built for the experiment, and the results showed that the proposed H-bridge driving circuit has a wide input voltage range. After using the NARX neural network, the output voltage of the H-bridge circuit is more stable, which can provide a stable driving voltage for the ultrasonic motor. It can provide a certain reference value for the application of ultrasonic motors in modern technology.
Adaptive low voltage crossing strategy for symmetrical faults of networked inverters
Authors: Mu Longfei 
Published: July 2024

Abstract
Due to the inability of grid-following control methods to compensate for the comprehensive reduction in system inertia, strength, and short-circuit capacity caused by the decreased proportion of synchronous machines, the grid exhibits insufficient resilience to disturbances, leading to severe stability risks in terms of rotor angle, frequency, and voltage. Grid-forming inverters have emerged to address this issue. During symmetrical faults, the low-voltage ride-through of grid-forming inverters often involves freezing the reactive power loop, resulting in a direct output of higher voltage and reactive current. However, an increase in reactive power command leads to a sharp rise in the internal potential magnitude of grid-forming inverters. Upon clearance of the grid fault, the excessively high internal potential may cause a rapid, short-term increase in terminal voltage, potentially resulting in overvoltage, which is detrimental to the operation of grid-connected equipment. In response to this issue, this paper proposes an adaptive low-voltage ride-through control strategy for grid-forming inverters under symmetrical faults controlled by a virtual synchronous machine control method. Initially, a virtual synchronous machine control model is established. Limiting current is achieved through the construction of a fixed virtual impedance loop. The issues associated with fixed virtual impedance current limiting are analyzed, leading to the proposal of an adaptive virtual impedance control strategy. Finally, the feasibility of the proposed method is verified through simulation experiments.
Modified EPS Control and Topology Modification for Two-Stage Bidirectional AC-DC Converter for V2G Applications
Authors: Qu Yaohui , Lu Zhengmei , Qiu Wenhui , Xu Guo 
Published: July 2024

Abstract
For the two-stage bidirectional AC-DC converter applied to vehicle-to-grid (V2G), this paper studies the modulation strategy and the topology of the dual active bridge (DAB) converter in the DC-DC stage. Aiming at the problem of large circulating current due to the fixed internal phase shift under the traditional extended phase shift (EPS) control, this paper modified the EPS modulation strategy by deciding whether the internal phase shift is generated by the primary or secondary side based on the voltage gain, which realizes the high-efficiency power transfer under wide voltage gain. To realize the full load range zero voltage switching (ZVS) with junction capacitors taken into account, it is proposed to parallel an additional auxiliary inductor between the bridge arms of the DAB converter, and the operating mechanism and the improved effect are analyzed in detail. Finally, a simulation circuit was built using PSIM software to verify the correctness.
Numerical Simulation of Residual Stresses and Structural Vibration of Welding Repaired Blades
Authors: Zhang Ying , Luo Ruimin , Liang Shuai 
Published: July 2024

Abstract
Taking a typical aero-engine high-pressure compressor blade as the research object, the Gauss heat source was used to numerically simulate the repair process of blade surfacing welding. The temperature data and stress data of the blade were obtained when the heat source velocity was 1 mm/s, 2 mm/s, and 4 mm/s, respectively. The results showed that both the temperature and stress values decreased with the heat source velocity increasing. Then, the residual stress of the repaired blade is introduced into the modal analysis module as prestress, and the Campbell diagram is drawn to analyze the natural frequency and speed margin of the blade respectively. The results show that as the heat source speed increases, the frequencies of each order of the blade decrease. The speed margin of each resonance point is greater than 10%, and the modal dynamic stress corresponding to the resonance speed can be used as the primary criterion for blade failure.
An Approach to Remaining Life Estimation for Power Transformers with Biased Data
Authors: Zhou Hongyu , Yang Yiming , He Yu , Zhang Feiyu 
Published: July 2024

Abstract
Power transformers are among the most important equipment in power systems. Estimating the remaining life of transformers is an important issue for energy companies because of the need for planning maintenance and capital expenditures. Traditional methods fail to provide accurate results mainly because data is incomplete, and there is a significant lack of records of equipment scrapped before 2015. Given this, the study provides a new approach to life estimation for power transformers based on survival analysis. First, the data was selected from only the transformers that were still operating after 2015. Then, a Bayesian survival model with a truncated Weibull distribution is developed to fit the biased data. Parameters are, at last, estimated through maximum likelihood estimation. The experimental results indicate that the proposed method performs well.
Research and Application on High Precision Measurement Method of Large Mesh Antenna Surface
Authors: Pu Lihua , Ma Xiaofei , Liu Boxue , Duan Hao , Yang Le 
Published: July 2024

Abstract
The development process of large mesh antennas requires a significant investment of time and resources for iterative measurements and adjustments to achieve high precision in the large mesh reflector. In this paper, a novel measurement method for the precision of large mesh antenna surfaces is proposed to reduce the development process. Multiple measurement cameras have been utilized to set up a network system, enabling data integration for comprehensive analysis and computational calculations. In this approach, the implementation of a one-click and the rapid measurement function represent substantial advancements. The single measurement time has been successfully reduced from 40 minutes to 2 minutes, which addresses the challenge of high efficiency and precision measurement application on the complex mesh antenna surface. Then the optimization of calibration is accomplished through the meticulous measurement of network patterns, marker points, and reference bars to improve the precision accuracy on the foundation of rapid measurements, combined with the simulation analysis. The final results have been practically verified and successfully applied to model development, which provides a crucial reference for subsequent endeavors involving the rapid and automated measurement of similar antennas.
Thermal Design of Tile Type Active Phased Array Radar Antenna
Authors: Cai Sen , Han Yu , Tang Junhao , Shi Tongwu 
Published: July 2024

Abstract
Based on the structure and heat source distribution characteristics of the tile-type active phased array radar antenna, forced air cooling is adopted for its heat dissipation design. The heat dissipation path and fins of the main heating module of the antenna were designed and calculated, and the reliability of the thermal design was verified through software simulation and thermal testing.
Research on New Energy Transmission Line Fault Localization Method Based on APSVMD-NTEO
Authors: Pan Zhongfeng , Che Wencheng , Du Xiang , Wang Minzhen , Wang Hui , Xu Daming , Xu Wenlong , Zheng Wenyuan 
Published: July 2024

Abstract
Given the new energy transmission line fault, traveling wave head detection difficulties, wave speed uncertainty, positioning errors, and other problems, this paper proposes a new Teager energy operator based on adaptive parameter selection variational mode decomposition (APSVMD) and new energy transmission line fault location method (NTEO). The envelope fuzzy entropy is introduced to select the key parameters of SVM, and the sampling range of the Teager energy operator (TEO) is improved to effectively improve the capture accuracy of the wave head. In terms of fault location, by improving the double-ended traveling wave method, the uncertainty of wave speed and the effect of actual line length error is eliminated, and the ranging error is reduced.
Working mode division and shift schedule extraction of a parallel hybrid power system
Authors: Wang Zexing , He Hongwen , Zhang Yang , Ji Shuang , Duan Zhihui 
Published: July 2024

Abstract
For hybrid electric vehicles, working mode division and shift schedule are two decisive factors affecting vehicle fuel economy. This paper introduces a method for vehicle working mode division and shift schedule determination on the basis of optimal system efficiency. The key index named ‘fuel-electricity conversion efficiency’ is defined and calculated. Via this method, unreasonable gear modes in specific working modes are excluded and the mode transition map and upshifting curves in each working mode are extracted. The simulation results demonstrate that, with the application of the single-motor multi-mode parallel hybrid power system, the proposed mode transition and shifting strategy can increase vehicle fuel economy by 12.99%.
Optimal Capacity Planning of a PV-Battery-Hydrogen System for Microgrid in Grid-Connected Mode
Authors: Xu Zhanpeng , Chen Fuxin , Yang Xuefan , Lu Qinfen 
Published: July 2024

Abstract
To improve the overall economy of the microgrid during the design and planning stage, a microgrid capacity configuration model containing photovoltaic, batteries, and hydrogen storage is proposed in this paper. The model of each equipment unit and the system control method are considered comprehensively. Demand response is utilized for load management, relieving pressure on the generation and storage sides. The configured capacity of each device is obtained by solving the optimization model using an improved particle swarm algorithm. The validity of the model is verified by using case simulations, and the impact of demand response on the allocation results and the influence of the algorithm on the optimization are also analyzed.
Operation optimization of cogeneration microgrid based on deep reinforcement learning
Authors: Sun Huiyu 
Published: July 2024

Abstract
The deep Q learning method is adopted to transform the microgrid model into the Markov decision model to realize the coordinated management and energy optimization of the microgrid. For the problem of the Markov decision model, we cleverly divide the working state of the gas turbine into different gears to meet its requirements. To reduce the fitting difficulty and improve the result accuracy and convergence stability, a linear penalty term was added to the reward function. Considering the operating and environmental costs, in addition to the purchase and sale price of a large power grid, peak and valley electricity price and operation constraints, we further reduce the peak and valley difference and reduce the operating cost. Finally, the output of the battery and the output of the distributed power supply are obtained through simulation verification. Through the peak-shifting and valley-filling function of the battery, it can effectively deal with the fluctuation of peak and valley electricity prices, reducing the peak and valley difference of electric heating load, and providing strong support for sustainable energy management.
Power Network Vulnerability Assessment Based on Electric Power System Cyber Security Simulation Platform
Authors: Chen Chenxi , Shi Kewei , Xiao Yizhao , Tang Fei , Gong Lianghua 
Published: July 2024

Abstract
This paper introduces a modeling approach for the integration of electric power and information networks, along with the creation of an electric power system network simulation platform. The system, achieved through the deep integration of computation, communication, and control technologies, offers new insights into power grid intelligence. The paper discusses the concept of power system vulnerability and presents a modeling scheme that effectively simulates and analyzes power systems. Using the Analytic Hierarchy Process (AHP), the impact of cyber attacks under different load conditions is evaluated, revealing that attacks have more severe consequences under heavy loads. In conclusion, this research contributes to enhancing the security and stability of power systems.
Research on the application of fiber-optical current sensor in power battery
Authors: Qiu Xiaowen , Li Guanlin , Wang Facheng , Chen Yadong , Meng Yi , Tie Jun , Li Chun 
Published: July 2024

Abstract
Compared with the total current, the current in each parallel branch will help to achieve better battery management for new energy vehicles. However, today, accurate measurement of branch current is very difficult because the space between branches in the power battery pack is very limited. In this study, the fiber-optic current mini-sensor is used to meet this challenge. A saddle-sensing fiber structure has been designed to achieve surface measurement in response to the specific interconnection of circuitry in battery packs. A computer simulation was used to validate the feasibility, and experimental testing showed positive results. The specific experiments confirmed that the relative error between the saddle fiber-optic current sensor and conventional fiber-optic loop current sensor does not exceed 0.0119%. It meets the requirements of the automotive industry standards.