bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study of ablation phase in double-wire Z-pinch based on optical Thomson scattering
Authors: Wang Wei , Wu Jian , Jiang Zhiyuan , Lu Yuanbo , Wang Zhenyu , Zhao Yiming , Shi Huantong , Chen Li , Li Xingwen , Qiu Aici 
Published: April 2024

Abstract
Measurement of plasma parameters during the ablation phase in the Z-pinch is crucial for investigating the dynamic behaviors. In this study, optical Thomson scattering was employed to measure the temperature and velocity of the ablation plasma in a double-wire Z-pinch. The scattering spectra profiles were fitted using a model that considered the velocity distribution. The experimental results revealed the energy evolution of ablation plasma, the establishment of the global magnetic field and the development of axial non-uniformities. The precursor plasma was found to play a key role in strengthening the global magnetic field. A resistive layer near the wire core with a size of 1.5 mm was observed in the ablation plasma after the precursor plasma column formed. The plasma underwent rapid heating in this layer, the electron temperature rises from 17 eV to 22 eV. Upon leaving this layer, electron the temperature is stable at around 22 eV. The radial distribution of the ablation rate increases and decreases, indicating the axial motion of the ablation plasma, which could be caused by the tilt motion of the stream and the secondary modulation of the natural wavelength.
Design and development of a variable structure gripper with electroadhesion
Authors: An Shunan , Xiang Chaoqun , Ji Cuicui , Liu Shilong , He Lei , Li Lijie , Wang Yanjie 
Published: April 2024

Abstract
Soft grippers are a novel kind of front-end actuators for robotics that offer great benefits such as easy control, superior grabbing capability, and close contact with the environment. They have vast application possibilities in numerous industries such as agricultural picking, item sorting, and medical rehabilitation. In this paper, a soft gripper with a variable structure and electrostatic adsorption is proposed. The gripper includes three fingers uniformly dispersed in the shape of a circle, which can adapt to varying sizes of grabbing objects by dynamically modifying the opening angle of the fingers. Aimed at addressing the existing issue of lacking multi fingers soft pneumatic grippers (SPGs) in grabbing tiny flat items, it is enhanced by embedding an electroadhesion (EA) films at the bottom of the soft pneumatic fingers of the gripper. It is simulated that the diameter adjustment range of this gripper is 0–482 mm, and the angle adjustment range is 0–180° via ABAQUS simulation. Finally, the adaptive grabbing capacity of the soft gripper was validated via experiments. The trials reveal that the gripper can grab items of different sizes by altering the opening angle of the fingers and the maximum load of the gripper can reach 10.91 N during specific grasping operations. The findings confirm that the SPGs with variable structure and EA described in this paper has a high gripping range and the capacity to grab thin flat items. We believe that its excellent gripping performance will encourage different uses of this gripper in everyday life and industry.
Insight into single-helix intelligent shape memory polymer cables: modeling and optimization under finite sliding contact
Authors: Enferadi Alireza , Ostadrahimi Alireza , Li Guoqiang , Baniassadi Majid , Baghani Mostafa 
Published: April 2024

Abstract
This pioneering study focuses on the finite element analysis (FEA) of thermomechanical properties of shape memory polymer (SMP) wire ropes and their components under both small- and finite-sliding contact deformation. To validate the FEA, we need to validate both geometric modeling and non-linear material behavior. Owing to intricate geometry, as well as excessive wire interactions in the structure, this part is studied by simulating a 1 × 37 steel wire rope and then comparing it with existing experimental data. To evaluate the response of non-linear material behavior, we employ the available numerical results to model the thermomechanical property of an SMP rectangular bar under a uniaxial test and then verify both constrained and unconstrained recovery behavior. After rigorous validation, two configurations of 1 × 7 and 1 × 27 SMP cables are modeled based on the thermo-visco-hyperelastic constitutive framework for acrylate polymer systems. Upon exerting an axially tensile load on these 1 × 7 and 1 × 27 SMP wire ropes, the response of force and shape recovery, as well as the normal and shear stress distributions, are measured under constrained and unconstrained conditions. For a deeper physical understanding, the influences of different temperature rates (5 and 1 °C min−1), inter-wire sliding frictional coefficient (0.1–0.6), and multiple-shape programming on the stress-strain-temperature relations of these SMP cables are also investigated. Furthermore, based on optimizing two cable factors of diameter and helix angle, and using the design of experiments method, the specific energy of a 1 × 6 SMP cable is maximized. Under different thermomechanical loadings, this study tries to cast light on the remarkable features and possible potential applications of these newly developed SMP actuators which may foster unparalleled advancements in various industries.
Investigation and measurement of square strip line antenna design and characteristic mode analysis for 5G/WiFi/WLAN applications
Authors: Albargi Hasan B , Bhatt Pranav , Borisagar Komal R , Kotak Nirali , Jalalah Mohammed , Almawgani Abdulkarem H M , Lavadiya Sunil , Patel Shobhit K 
Published: April 2024

Abstract
Two novel compact low-profile dual-band plasmonic antennas designed using Characteristic Mode Analysis (CMA) and parametric analysis are presented in this study. The plasmonic antennas contain microstrip line-fed strip-loaded patches and partial ground planes. The final proposed antennas cover the two bands ranging from 2.4–2.5 GHz and 5–6 GHz. Plasmonic antennas offer nearly omnidirectional patterns at the desired frequency ranges. Additionally, a detailed parametric study of almost all the design parameters is performed to display the effect of varying those parameters on the resonance frequency at both bands. The parametric study for both antennas has been carried out to optimize the antenna and get better-enhanced results. Then the fabricated antenna is analyzed for the same. The comparison results of fabrication show nearly similarity results to the simulated results. The designed antenna can be applicable for 5G/ Wi-Fi/WLAN applications.
The Goldstone Apple Valley Radio Telescope (GAVRT) Search for Extra Terrestrial Intelligence (SETI)
Authors: Gorjian Varoujan , Levin Steven , Arballo John , Timmaraju Virisha , Dorcey Ryan , Kreuser-Jenkins Nancy , Lamb Lisa , Lazio Joseph , Webb-Mack Zoe 
Published: April 2024

Abstract
This paper reports the results from a student-led Search for Extraterrestrial Intelligence (SETI), also known as technosignatures, targeting the plane of the Milky Way as a part of the Goldstone Apple Valley Radio Telescope (GAVRT) collaboration between the Lewis Center for Educational Research (LCER) and the Jet Propulsion Laboratory. Students associated with LCER submit analytic reports of spectral data targeting specific regions of the Milky Way, identifying interference, noise, and Candidate signals potentially originating from intelligent sources. GAVRT-SETI's search is guided by the assumption that a narrow-band radio signal (<1.5 Hz) from a fixed location in the sky, occurring across multiple observation periods, is unlikely to be caused by instrument noise or by a natural source. Thus, we searched the reported data for similar signals occurring during different observation periods within the same region of sky. No such signals were found. However, our analysis of the frequency distribution of Candidates suggests that at least a few percent of the Candidates are associated with low-level radio-frequency interference.
MSLTE: multiple self-supervised learning tasks for enhancing EEG emotion recognition
Authors: Li Guangqiang , Chen Ning , Niu Yixiang , Xu Zhangyong , Dong Yuxuan , Jin Jing , Zhu Hongqin 
Published: April 2024

Abstract

Objective. The instability of the EEG acquisition devices may lead to information loss in the channels or frequency bands of the collected EEG. This phenomenon may be ignored in available models, which leads to the overfitting and low generalization of the model. Approach. Multiple self-supervised learning tasks are introduced in the proposed model to enhance the generalization of EEG emotion recognition and reduce the overfitting problem to some extent. Firstly, channel masking and frequency masking are introduced to simulate the information loss in certain channels and frequency bands resulting from the instability of EEG, and two self-supervised learning-based feature reconstruction tasks combining masked graph autoencoders (GAE) are constructed to enhance the generalization of the shared encoder. Secondly, to take full advantage of the complementary information contained in these two self-supervised learning tasks to ensure the reliability of feature reconstruction, a weight sharing (WS) mechanism is introduced between the two graph decoders. Thirdly, an adaptive weight multi-task loss (AWML) strategy based on homoscedastic uncertainty is adopted to combine the supervised learning loss and the two self-supervised learning losses to enhance the performance further. Main results. Experimental results on SEED, SEED-V, and DEAP datasets demonstrate that: (i) Generally, the proposed model achieves higher averaged emotion classification accuracy than various baselines included in both subject-dependent and subject-independent scenarios. (ii) Each key module contributes to the performance enhancement of the proposed model. (iii) It achieves higher training efficiency, and significantly lower model size and computational complexity than the state-of-the-art (SOTA) multi-task-based model. (iv) The performances of the proposed model are less influenced by the key parameters. Significance. The introduction of the self-supervised learning task helps to enhance the generalization of the EEG emotion recognition model and eliminate overfitting to some extent, which can be modified to be applied in other EEG-based classification tasks.
Numerical simulation study on the embedding depth of anti slip piles in fully weathered granite landslides
Authors: Yu Peng , Zhang Jike , Jia Shixiang , Cao Lei , Zhao Lei 
Published: April 2024

Abstract
Taking the reinforcement project of the fully weathered granite landslide in Fanling as the research object, this study establishes a numerical slope model with anti-slide pile reinforcement, the most common means in slope reinforcement engineering, while considering the pile-soil interaction. Using the strength reduction method, the effects of different anti-slide pile embedment depth on the stability of the reinforced slope are discussed. The research results indicate the following findings. (1) The embedment depth is negatively correlated with the slope displacement. (2) When the embedment depth is more excellent than 7m, the slope Factor of safety is 2.032>2.0, which meets engineering safety requirements. (3) According to the changes in displacement and the factor of safety, the stress analyses of the pile body and the economic factors, the optimal embedment depth for the Fanling landslide are determined as 8 m. The results afford certain application and promotion values by providing theoretical references and technical guidance for similar anti-slide pile reinforced slope projects.
Hardware-Accelerated YOLOv5 Based on MPSoC
Authors: Liu Junjiang , Mao Mingyu , Gao Jianlong , Bai Jiangtao , Sun Dandan 
Published: April 2024

Abstract
This paper details the development of a hardware acceleration system for YOLOv5, focusing on flame detection as its primary application. The implementation leverages the APU and DPU functionalities integrated into the Zynq UltraScale+ MPSoC XCZU7EV core. The proposed solution addresses the challenge of achieving real-time target detection on mobile terminals, ensuring both real-time operation and ultralow power consumption of YOLOv5. Notably, our design approach facilitates the deployment of all target detection algorithms under TensorFlow for mobile devices. To optimize model efficiency, we employ saturated linear mapping quantization with calibration. This technique maps model weights, double bases, and activations from 32-bit to 8-bit, incurring only a 1.64% accuracy loss. The data flow design is realized through efficient data exchange between DDR, APU, and DPU, utilizing the AXI4 bus architecture. Image pre-processing and post-processing tasks are executed on the APU, while neural network inference occurs on the DPU. Our accelerated system demonstrates compelling experimental results: maintaining a detection speed of 56FPS, achieving an accuracy of 36.56% on the COCO2014 dataset, and exhibiting a total system power consumption of only 4.147W. Furthermore, the energy consumption ratio is measured at 15.41GOPS/W, surpassing the RTX A6000 graphics card by a factor of 55.
Study on Vibration Adjustment Mechanism of S-76D Helicopter Rotor System Based on HUMS System
Authors: Zheng Xiaofeng , Sun Ting 
Published: April 2024

Abstract
In recent years, helicopter maintenance technology has been developing rapidly and is transitioning from time-based periodic maintenance to condition-based maintenance. Helicopter Health and Usage Monitoring System (HUMS system) plays an important role in this process. The excitation forces originating from the helicopter rotor system are the primary cause of airframe vibration, and the HUMS system monitors the main rotor balance and trajectory data during each flight and provides an adjustment solution and predicts the vibration level in case of overruns. This paper summarizes the vibration measurement, cause analysis and vibration adjustment methods by studying the vibration adjustment mechanism of the S-76D helicopter rotor system, and provides solution for the same type of vibration problems of the helicopter.
Study on Preparation and Application Technology of Micro scale New Foam Ceramics for Power Equipment
Authors: Zhang Shiling , He Yongsheng , Lu Zongxiang , Deng Baojia 
Published: April 2024

Abstract
With the proposal of a new type of power system in China, the new environment-friendly insulating medium micro nano foam ceramic is urgently needed to replace SF6, epoxy resin and other insulating materials in the GIS/GIL key power equipment. The new material technology can prepare: foam ceramic design method. Preparation method of foam ceramics and the functional modulation of micro/nano structures. The electrical performance of the foam ceramics was improved. Achievable: the stable performance of micro/nano structures under the high field strength. Excellent thermal conductivity under high current action. It has local replacement function in insulation material applications such as SF6 and epoxy resin. Detectable: Starting from the electrical performance of the UHV hybrid insulation material system, UHF technology and photo-acoustic spectroscopy technology are applied to the high sensitivity detection of the decomposition products and partial discharges of foam ceramics, focusing on types of fluorocarbon decomposition gases, making use of strong correlation between the decomposition products and the partial discharge detection data, and combining the multi-source data fusion algorithm to achieve the prediction of insulation structure data sequence and online detection of the latent faults for the special GIS/GIL.
Spatial-Temporal Graph Deviation Neural Networks for Anomaly Detection in Time Series
Authors: Guo Ziyu , Kong Weiyang , Liu Yubao 
Published: April 2024

Abstract
Anomaly detection in time series data (e.g., sensor data) is becoming a fundamental research problem that has various applications. Due to the complex inter-sensor relationships, it is challenging to detect anomalous events such as system faults and attacks hidden the high-dimensional time series. Recent advancements in deep learning approaches such as Graph Neural Networks (GNN) have greatly improved anomaly detection performance in time series data. However, existing methods usually use separate components to capture spatial and temporal dependence relationship and ignore the heterogeneities in spatial-temporal data which motivates us to capture them together. In this paper, we propose a novel approach STGDNN (short for Spatial-Temporal Graph Deviation Neural Networks) that learns the spatial-temporal dependence relationship together in structure learning of graph neural networks. In addition, we use the learned spatial-temporal graph structure and attention weights to explain the detected anomalies. The experiments on three real world datasets show our superiority in detection accuracy, anomaly diagnosis, and model interpretation compared with state-of-the-art methods.
Portable ratiometric fluorescence detection of Cu2+ and thiram
Authors: Zhang Jiazhen , Jia Yicong , Tong Xuan , Zhou Hangyu , Zhang Le , Yang Yue , Ji Xu 
Published: April 2024

Abstract
Food contaminants pose a danger to human health, but rapid, sensitive and reliable food safety detection methods can offer a solution to this problem. In this study, an optical fiber ratiometric fluorescence sensing system based on carbon dots (CDs) and o-phenylenediamine (OPD) was constructed. The ratiometric fluorescence response of Cu2+ and thiram was carried out by the fluorescence resonance energy transfer (FRET) between CDs and 2,3−diaminophenazine (ox-OPD, oxidized state o-phenylenediamine). The oxidation of OPD by Cu2+ resulted in the formation of ox-OPD, which quenched the fluorescence of CDs and exhibited a new emission peak at 573 nm. The formation of a [dithiocarbamate-Cu2+] (DTC-Cu2+) complex by reacting thiram with Cu2+, inhibits the OPD oxidation reaction triggered by Cu2+, thus turning off the fluorescence signal of OPD-Cu2+. The as-established detection system presented excellent sensitivity and selectivity for the detection of Cu2+ and thiram in the ranges of 1 ∼ 100 μM and 5 ∼ 50 μM, respectively. The lowest detection limits were 0.392 μM for Cu2+ and 0.522 μM for thiram. Furthermore, actual sample analysis indicated that the sensor had the potential for Cu2+ and thiram assays in real sample analysis.
Effect of sodium dodecyl sulfate (SDS) on the co-deposition and frictional behavior of carbon nanotube/nickel composite layer
Authors: Liu Yingnan , Yang Ping , Li Yuxin , Xiao Yi , Shu Baipo 
Published: April 2024

Abstract
In this paper, the effects of sodium dodecyl sulfate (SDS) concentrations in the electroplating solution on the morphology, nucleation rate, nucleation mode, and frictional behavior of the CNT/Ni composite layers were investigated. The results showed that the electrodeposition of Ni was in a three-dimensional nucleation/growth mode. In addition, the x-ray diffraction (XRD) of the deposited layers showed that adding SDS changed the preferred growth direction of Ni from (2 0 0) to the (2 2 0) crystallographic plane. When the carbon nanotube (CNT) content was 0.1 g l−1, and the SDS content was 0.05 g l−1, the deposition potential was the most negative, increasing the number of Ni nucleation sites on the electrode and resulting in the grain size refinement of the deposited layer. It also reduced the friction coefficient of the composite simultaneously.
Development of CuO nanoparticles modified electrochemical sensor for detection of salbutamol
Authors: Koc Delice Tulay , Ak Azem Funda , Ozdemir Kazim , Alpat Senol 
Published: April 2024

Abstract
Metal oxide structures are being utilized in an increasing variety of applications. This study used cyclic and differential pulse voltammetry techniques to investigate the possible utilization of copper oxide (CuO) nanoparticles modified carbon paste electrode (CPE) for the redox reactions of salbutamol (SAL). The electrochemical performance of the SAL analyte in a complex matrix environment in Ventolin was evaluated in order to assess the appropriateness of the proposed sensor in a real sample environment. CuO nanoparticles were produced via a straightforward, cost-effective and efficient sol–gel method, and characterization studies of synthesized CuO nanoparticles were performed by scanning electron microscopy, x-ray Diffraction (XRD), and x-ray photoelectron spectroscopy. The synthesized CuO nanoparticles had a spherical shape and particle size was found to be 74 nm. The crystal size of the CuO particles was calculated to be 21.79 nm using the Debye–Scherrer equation. Under optimal conditions, differential pulse voltammetry demonstrated a linear response in the 50 nM to 100 μM range, with a salbutamol detection limit of 50 nM (S/N = 3). The SAL concentration (R
2 = 0.9971) was found to have a good correlation coefficient. The reproducibility of the biosensor was investigated and evaluated with a relative standard deviation of 3% (n = 8). The storage stability of CuO modified CPE for two weeks was evaluated based on the response of DP current measured at intervals every two days. According to the measurement results, the modified electrode exhibited good stability and reproducibility while maintaining 80% of its stability. It is also a rapid and dependable sensor candidate with a measurement time of approximately 20 s. The developed electrode has been utilized successfully to determine doping material with improved performance.
Reconfigurable screen-printed terahertz frequency selective surface based on metallic checkerboard pattern
Authors: Ahmad Redwan , Ropagnol Xavier , Trinh Ngoc Duc , Bois Chloé , Blanchard François 
Published: April 2024

Abstract
We employed the screen-printing method to fabricate terahertz (THz) frequency selective surfaces (FSSs) featuring an inductive metallic checkerboard (i-MCB) pattern based on conductive silver ink onto a flexible polyethylene terephthalate substrate, chosen for its excellent THz transmission properties below 1 THz [Jin et al 2006 J. Korean Phys. Soc.
49 513–17]. Analytical studies, along with simulations and experiments, were conducted to investigate the filtering characteristics of the printed FSSs, confirming their functionality as a band-pass filter. Subsequently, we demonstrated the reconfigurability of a two-layer system by vertically stacking two layers. This was achieved by systematically shifting the position of the second layer in the x or y-direction relative to the first layer. Experimental verification revealed a significant variation in normalized transmission, ranging from 94% to 6% at 0.15 THz for type-I:i-MCBs and 90% to 5% at 0.20 THz for type-II:i-MCBs, respectively. This study presents a simple scheme for a reconfigurable screen-printed i-MCB-FSS operating in the THz range. Consequently, our findings demonstrate that screen printing method can effectively be employed for the large-scale production of THz FSSs.