bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of ultra-short pulse reflectometry on the Experimental Advanced Superconducting Tokamak (EAST)
Authors: Li Xiaoliang , Chen Ran , Xu Guosheng , Domier Calvin , Liu Xianzi , Zhang Yiwei , Zhou Tianfu , Zhu Yilun , Yu Guanying , Qiu Shasha , Yu Hai , Luhmann Neville C. 
Published: July 2024

Microwave reflectometry is an invaluable diagnostic tool for measuring electron density profiles in large fusion devices. Density fluctuations near the plasma cutoff layer, particularly those that are time-varying on the timescale of the reflectometry measurement, can result in distortions in phase and/or amplitude of the reflected waveform, which present challenges to the accuracy of the reconstructed profile. The ultra-short pulse reflectometry (USPR) technique eliminates the time-varying issue in that reflectometry data are collected on a nanosecond timescale, essentially freezing the fluctuations in place. An X-mode dedicated 32-channel USPR system has been developed and installed on the EAST, covering the operation frequency range from 52 to 92 GHz. This system enables high-resolution density profile measurements in the plasma pedestal and scrape-off layer, with resolutions reaching 5 mm and 1 μs, respectively. Laboratory testing of the system performance has been conducted, demonstrating the potential of the USPR technique to provide accurate and high-temporal-resolution density profiles in challenging plasma environments.
Cyanonaphthalene and cyanonaphthyl radicals: Vibrational structures via computed negative ion photoelectron spectra and thermochemistry of 1- and 2-cyanonaphthalene
Authors: White Nolan J. , Vargas Lucia A. , Tunstall Wyatt W. , Koku Hannadige Abeysooriya Dushmantha N. , Gichuhi Wilson K. 
Published: July 2024

A double harmonic oscillator model is applied to compute the negative ion photoelectron spectra (NIPES) of the 1- and 2-cyanonaphthalene (CNN) radical anions. The computed Franck–Condon factors utilize optimized structures and harmonic vibrational frequencies obtained using density functional theory with the B3LYP 6-311++G (2d,2p) basis set while considering the mode-mixing Duschinsky effects. To test the accuracy of our model, the NIPES of α and β naphthyl radical anions were computed, and a strong agreement between the slow electron velocity-map ion imaging spectra and the predicted spectra was found. The adiabatic electron affinities (EAs) of the ground singlet states (S0) in 1-CNN and 2-CNN are 0.856 and 0.798 eV, respectively. The origin of the lowest-lying triplet (T1) states in 1-CNN and 2-CNN is found to be 3.226 and 3.266 eV, resulting in singlet–triplet energy splittings (ΔEST) of 2.370 and 2.468 eV, respectively. Both the NIPES for electron detachment to the S0 and T1 states exhibit well-resolved vibrational features, allowing for the assignment of several vibrational fundamental frequencies. Following deprotonation, several isomers are formed, with the most stable deprotonated radical anions in 1-CNN and 2-CNN, corresponding to the removal of the most acidic proton, with EAs of 2.062 and 2.16 eV. The rich spectroscopic and thermochemical data obtained in the current study make the CNN radical anions and their deprotonated species interesting systems for investigation in gas-phase, negative-ion experiments.
Conformal sulfidation of HKUST-1 for constructing porous Cu2S/CuO octahedrons realizing highly sensitive non-enzymatic glucose detection
Authors: Liao Yanxin , Sun Shupei , Du Qian , Shi Nianfeng , Yin Guangfu , Huang Zhongbing , Liao Xiaoming 
Published: July 2024

Abstract
Metal–organic frameworks (MOFs) are believed to be promising precursors for constructing novel and efficient catalysts for glucose sensing. Herein, HKUST-1 precursors are first fabricated using a one-pot hydrothermal approach, and then HKUST-1 is converted into porous Cu2S/CuO octahedrons through conformal sulfidation with the help of OH− ions. The as-obtained Cu2S/CuO composite can provide rich electrochemical active sites and promoted electric transfer kinetics. Benefiting from these combined merits, the as-fabricated Cu2S/CuO composite is confirmed to be a high-performance catalyst, with high sensitivities of 8269.45 and 4140.82 μA mM−1cm−2 in the corresponding ranges of 0.05 ∼ 0.6 mM and 0.6 ∼ 1.2 mM, respectively. Moreover, the as-prepared electrode materials possess good anti-interference ability, reproducibility and long-term stability. This work opens up new avenues for the design and preparation of transition metal sulfide composites.
A stretchable and self-powered strain sensor with elastomeric electret
Authors: Li Yanyu , Li Yifan , Gu Haoyu , Zhai Chongpu , Song Siyang , Zhang Shuwen , Xu Minglong 
Published: July 2024

Abstract
Stretchable deformation sensors play an important role in the perception and autonomy of soft robots. While various sensors have been reported, the mechanical sensor with self-powered capability and stretchability to suit extreme environment is urgently required. In this study, a stretchable, self-powered, sensitivity adjustable, and long-term stability strain sensor based on the stretchable electret is researched for deformation monitoring. This stretchable and self-powered sensor is composed of the dielectric elastomer with designed elastic modulus gradient and the stretchable electret with elastomeric and Nano-particles. The electro-mechanical capability of this designed sensor is researched and optimized by multi-objective optimization approach. The sensor exhibits self-powered capability, stretchability (tensile strain from 0% to 20%), tunable sensitivity (optimized from 5.7 to 5.9 pC mm−1), and stability, where electromechanical performance remains stable after 8000 stretching cycles. The feasibility of its autonomous sensing which promotes a wide range of potential application in soft robotics is demonstrated. This elastic modulus gradient-induced and net charge design significantly broadened the potential applications with large deformation and low-attached stiffness.
Compression and encryption for remote sensing image based on PSO-BP and 2D-MCCM
Authors: Li Pei-zhen , Feng Xiu-fang , Zhou Shuang , Yan Peng-fei , Zhang Hao 
Published: July 2024

Abstract
In response to the large size of remote sensing images and the limitations of existing image compression and encryption algorithms, this paper proposes a novel compression and encryption algorithm. The proposed algorithm utilizes a new type of memristive chaotic mapping in combination with PSO-BP neural networks and multi-threaded parallelism. Specifically, the proposed novel two-dimensional memristive chaotic mapping involves a combination of new memristors based on HP memristors and Cubic chaotic mapping. Compared to existing chaotic systems, this method exhibits stronger randomness and hyperchaotic characteristics. Additionally, to improve the reconstruction accuracy of compressed images, a traditional BP neural network with an added hidden layer is combined with the PSO algorithm for image compression and reconstruction. Furthermore, to enhance the encryption efficiency of remote sensing images, a multi-threaded parallel encryption method is employed, enabling simultaneous permutation within and among threads. Experimental results demonstrate that the proposed algorithm achieves good compression reconstruction accuracy, excellent encryption performance, and resistance to attacks.
Helmert variance component estimation for mixed additive and multiplicative random error model
Authors: Wang Leyang , Xiao Hao 
Published: July 2024

Abstract
With the development of surveying and mapping science, the object of measurement adjustment has been extended from a single observation of the same kind in the past to different precisions of the same kind, or different kinds of observations. There are additive and multiplicative errors related to electronic instrument measurements, which affect the quality of the adjustment results. A single additive error model is difficult to meet the accuracy requirements, so a mixed additive and multiplicative random error model (MAMREM) is needed. Aiming at the problem of inaccurate MAMREM stochastic model, this paper proposes Helmert Variance Component Estimation (VCE) to determine the weight matrix in different types of observations under MAMREM. In this paper, the formula and iterative algorithm of Helmert variance component estimation applied to MAMREM are derived, and the weights of different kinds of observations in the adjustment process are estimated. In order to verify the effectiveness of the method, the digital elevation model experiment and the side network experiment are used to verify the method. The results prove the effectiveness of the method.
A study on the motion characteristics of particle in shear flow of active nematic fluid between two plates
Authors: Li Zhenna , Ye Hao , Lin Jianzhong 
Published: July 2024

Abstract
The motion characteristics of particle in shear flow of active nematic fluid between two plates are investigated numerically. The influence of activity intensity of active nematic fluids on the motion characteristics of particle is focused. The results showed that, when the activity intensity is high, the particle exhibits initially smooth trajectories and ultimately approximate Brownian motion. As the activity intensity increases, both the translational mean square displacement (MSDT) and rotational mean square displacement (MSDR) of the particle increase. The particle exhibits initially super-diffusive behavior and then normal diffusion. The unique vortex lattice mode in the flow plays a role in hindering particle motion, leading to a decrease in MSDT and MSDR. An increase in particle size will lead to a weakening of particle diffusion. In addition, there are topological defects in the active nematic fluid, and the number of topological defects N
def in the contractile system is greater than that in the extensible system, while the presence of particle has a smaller impact on N
def in the flow.
Highly sensitive photonic crystal fiber chemical sensor for detecting carbon disulfide and bromoform in the THz regime
Authors: Nasif Mohammad Abrar 
Published: July 2024

Abstract
In this study, an innovative photonic crystal fiber (PCF) designed specifically for the detection of carbon disulfide and bromoform liquid chemicals within the THz frequency range was introduced. The PCF’s structural design was achieved using the Finite Element Method (FEM) and Perfectly Matched Layer (PML) boundary conditions within COMSOL Multiphysics, ensuring precision through appropriate numerical parameters. Six distinct configurations were developed, incorporating circular, square, rectangular slotted, benzene-shaped circular, and two elliptical core designs, as well as an eight-elliptical core design. The PCF models were constructed utilizing the dielectric material TOPAS for accurate simulation and analysis. Various crucial parameters of the proposed PCF were examined across a wide THz spectrum spanning from 0.2 to 1.2 THz. The PCF model exhibited a peak output at the operating frequency of 0.8 THz for the square-shaped core design, achieving a relative sensitivity of 96.891% for bromoform and 95.603% for carbon disulfide. Remarkably low material losses of 0.0081104 cm−1 for bromoform and 0.006703 cm−1 for carbon disulfide were observed, along with a core power fraction of 93.107% for bromoform and 94.263% for carbon disulfide. The effective area was determined to be 1.77 × 10−07
μm2 for bromoform and 1.70 × 10−07
μm2 for carbon disulfide, while the confinement loss measured 2.25 × 10−17 dB/cm for bromoform and 4.76 × 10−17 dB/cm for carbon disulfide. These superior attributes strongly suggest that this model will be crucial in applications like supercontinuum generation, sensing, and biomedical imaging.
Enhanced plasmonic absorption using MIM ring resonator structures for optical detector applications
Authors: Salahandish Mohammad , Ghahramani Bigbaghlou Reza , Nasiri Hassan , Pourziad Ali 
Published: July 2024

Abstract
This study delves into the design and analysis of plasmonic absorbers utilizing Metal-Insulator-Metal (MIM) ring resonator devices to achieve heightened optical absorption efficiency. Various ring resonator topologies, namely SRR-L and Ring-L, are investigated with the objective of amplifying absorption capabilities. Moreover, the examination extends to the influence of modifying the inner radius of the ring, resulting in discernibly diverse absorption levels. Through the integration of these ring resonators, absorption peaks are effectively brought into proximity, thereby yielding a broad-band absorption spectrum. Our discoveries underscore the promising potential of these devices as proficient optical detectors. The simulations were performed in three dimensions utilizing CST Microwave Studio.
Alternating spin splitting of electronic and magnon bands in two-dimensional altermagnetic materials
Authors: Wang 王 Qian 乾 , Wu 邬 Da-Wei 大为 , Guo 郭 Guang-Hua 光华 , Long 龙 Meng-Qiu 孟秋 , Wang 王 Yun-Peng 云鹏 
Published: July 2024

Abstract
Unconventional antiferromagnetism dubbed as altermagnetism was first discovered in rutile structured magnets, which is featured by spin splitting even without the spin–orbital coupling effect. This interesting phenomenon has been discovered in more altermagnetic materials. In this work, we explore two-dimensional altermagnetic materials by studying two series of two-dimensional magnets, including MF4 with M covering all 3d and 4d transition metal elements, as well as TS2 with T = V, Cr, Mn, Fe. Through the magnetic symmetry operation of RuF4 and MnS2, it is verified that breaking the time inversion is a necessary condition for spin splitting. Based on symmetry analysis and first-principles calculations, we find that the electronic bands and magnon dispersion experience alternating spin splitting along the same path. This work paves the way for exploring altermagnetism in two-dimensional materials.
Thermal pairing treatment within the path integral formalism
Authors: Fellah M. , Allal N.H. , Oudih M. R. 
Published: July 2024

Abstract
A method for the treatment of pairing correlations at finite temperature is proposed within the path integral formalism, based on the square root extraction of the pairing term in the Hamiltonian of the system. Gap equations and expressions for the pairing gap parameter Δ, energy E, and heat capacity C are established. The formalism is first tested using the Richardson model, which enables comparison with an exact solution. The results obtained using this formalism are also compared with the finite temperature BCS (FTBCS) results. An improvement over the FTBCS model is noted, especially at low temperatures. Indeed, the agreement between the Δ values of this study and the exact values is good at low temperatures. This leads to better agreement between the values of E and C of this model and the exact values than with the FTBCS values. However, a critical value of temperature remains. Subsequently, realistic cases are considered using single-particle energies of a deformed Woods-Saxon mean-field for the nuclei

Dy and

Yb. In the framework of the current approach, pairing effects persist beyond the FTBCS critical temperature. Moreover, at low temperatures, a good agreement between the model and semiexperimental values of the heat capacity is observed, and a clear improvement compared to the FTBCS method is noted. This is no more the case at higher temperatures.
A Remote Intelligent Check and Discharge Test System for Substation Battery Pack Based on Raspberry Pi
Authors: Zhang Liang , Gong Zemin , Lei Wei , Ni Pang 
Published: July 2024

Abstract
Regular check and discharge test of the battery pack is an effective means to ensure the normal state of the battery and timely detect outdated batteries. However, conventional manual check and discharge test methods are costly, cumbersome, and inefficient in maintenance. This article introduces a remote intelligent check and discharge test system for a substation battery pack based on Raspberry Pi. The system monitors the battery status in real-time, allowing operators to detect battery faults on time through the front-end management interface. At the same time, remote check and discharge tests can be carried out, greatly ensuring battery safety and solving the shortcomings of conventional manual methods.
A New Method for Traveling Wave Localization in Wide Area Power Grid Based on Trusted Zone Identification of Fault Lines
Authors: Wan Wanglong , Qin Zheng , Deng Minggao 
Published: July 2024

Abstract
Aiming at the problem of dead zones in fault localization of wide area power grids, which makes it difficult to improve localization accuracy, a new method based on the trusted zone of fault lines for precise localization of wide area traveling waves is proposed. The algorithm is based on the principle of dual terminal positioning, which determines the fault line in the network through the action status of the circuit breaker, and determines the calculation area of network positioning based on the fault line, obtaining a set of dual terminal positioning calculation paths based on the fault line; Then, calculate the reliable localization zone of the faulty line under all dual end localization calculation paths and use it to determine whether the localization result of the path is reliable. For calculation paths with unreliable results, identify the second traveling wave of the fault point for calculation; Finally, all credible positioning results obtained are linearly fitted to obtain the final accurate positioning result. Simulation and practical application results have shown that this algorithm does not require finding the shortest path for traveling wave transmission, and can effectively improve the accuracy of wide area traveling wave positioning. It has high reliability, strong adaptability, and a positioning error of less than 100m.
EAPTON: Event-based Antinoise Powerlines Tracking with ON/OFF Enhancement
Authors: Zhao Jiannan , Zhang Wenyuan , Wang Yang , Chen Shaonan , Zhou Xiang , Shuang Feng 
Published: July 2024

Abstract
Event-based powerlines detection and tracking is a thriving research topic with significance in autonomous powerlines inspection, especially for payload-limited UAVs. Currently, event-based line detection methods are developed to address line detection in dynamic scenes, including UAV-based powerlines tracking. However, due to the motion sensitivity of event cameras, it is challenging to eliminate false line detection caused by clustered events from a complex background. Taking inspiration from animals’ motion vision, we propose the EAPTON algorithm to address the vulnerable robustness against complex backgrounds. In our method, the brightness increments (ON events) and decrements (OFF events) are separately processed in parallel pathways, which is prevalent in animals’ motion vision. To increase selective sensibility to powerlines, we utilize the feature that twin-born ON and OFF events will simultaneously arise on the bilateral side of the powerlines. We verified our algorithm in a simulated powerlines inspection scenario with background noise, it outperforms the SOTA algorithm in robustness. Surprisingly, we found that the relative motion type between UAV and the target (e.g., powerlines) is strongly correlated with the statistical asymmetry of the ON/OFF events, which provides a modal of visual cues for motion estimation in other robotic tasks and may shed a light on the explanation of why ON/OFF neural mechanism exists in numerous animals motion vision systems.
Application of Data Security Protection in Smart Grid Based on Computer Electronic Technology
Authors: Liu Xiangguo , Du Huijun , Wang Zhonglong , Chen Jianfei , Peng Jia , Liu Yue 
Published: July 2024

Abstract
With the continuous improvement of the intelligence level of the State Grid, data security protection in power system automation has become an important challenge for the development of power enterprises. In order to solve this problem, this article is based on the research of power system structure, data types, and the current development status of security protection, combined with computer electronics technology, to conduct in-depth research on data security protection in power system automation, and establish a security protection model based on its theoretical foundation. In order to verify the effectiveness of the model, this paper tested it from three dimensions: data security protection degree, risk processing efficiency, and response time, and compared it with traditional security protection models. The test results show that under different test cases, the maximum protection degree of the data security protection model proposed in this article reaches 95.16%, and the average protection degree is about 91.88%. From the specific test results, it can be seen that the application of data security protection in power system automation based on computer electronic technology has strong operability.
Photovoltaic Power Generation Related Physical Quantity Mining Method Based On Historical Time Series Data Analysis
Authors: Wang Yin , Liao Siyang , Shen Nuoqing 
Published: July 2024

Abstract
The impact of distributed photovoltaic grid-connected on distribution network security, power quality and system stability cannot be ignored. In order to better cope with the uncertainty and output of new energy output and understand the characteristics of distributed new energy power output, it is necessary to predict photovoltaic power. The historical time series data of photovoltaic power is large in dimension and quantity. If the data output is not carried out, a large amount of redundant data will affect the accuracy of photovoltaic prediction. Therefore, this paper proposes a feature selection method based on MIC most mutual information coefficient, which filters out the most relevant data of photovoltaic power generation from the original feature variables, and then performs the feature dimension reduction method of linear discriminant analysis (LDA) to map the high-dimensional data to a lower dimension space. Finally, using the prediction simulation example, using the long and short time neural network (LSTM) prediction comparison, the feature dimension reduction method of MIC feature selection and LDA effectively improves the accuracy of photovoltaic power generation prediction.
Research and Simulation of Partial Discharge Phenomenon Sensing Technology for Substation Inspection Robots
Authors: Yu Hongxi , Xu Liang , Yang Lu , Li Dongqi , Xu Ke , Li Li 
Published: July 2024

Abstract
This paper thoroughly investigates the phenomenon of partial discharge in substations and proposes a set of simulation experimental apparatus to replicate various types of partial discharge defects in switchgear. By modifying the switchgear, incorporating models for different types of partial discharge, and equipping various standard partial discharge sensors, accurate simulations of phenomena such as point discharge, suspended discharge, gap discharge, and particle discharge are achieved. Through this system, the effectiveness of different detection methods, such as ultrasonic, high-frequency, and transient voltage methods, is validated for various defect models. Furthermore, utilizing an indoor inspection robot guide rail, the paper simulates the environment of partial discharge in substations, enabling the validation of the robot’s partial discharge detection performance and typical patterns under different conditions. This work is dedicated to providing situational awareness technology for partial discharge phenomenon detection for substation inspection robots, so that the inspection robot can detect various abnormal partial discharge phenomena in transformers or other substation equipment through micro sensors to promote the stable operation of the substation.