bluuebunny/crossref_metadata_2025_split huggingface dataset:
Atomic layer deposition assisted fabrication of large-scale metal nanogaps for surface enhanced Raman scattering
Authors: Cheng Tangjie , Zhu Zebin , Wang Xinxin , Zhu Lin , Li Aidong , Jiang Liyong , Cao Yanqiang 
Published: March 2023

Abstract
Metal nanogaps can confine electromagnetic field into extremely small volumes, exhibiting strong surface plasmon resonance effect. Therefore, metal nanogaps show great prospects in enhancing light–matter interaction. However, it is still challenging to fabricate large-scale (centimeter scale) nanogaps with precise control of gap size at nanoscale, limiting the practical applications of metal nanogaps. In this work, we proposed a facile and economic strategy to fabricate large-scale sub-10 nm Ag nanogaps by the combination of atomic layer deposition (ALD) and mechanical rolling. The plasmonic nanogaps can be formed in the compacted Ag film by the sacrificial Al2O3 deposited via ALD. The size of nanogaps are determined by the twice thickness of Al2O3 with nanometric control. Raman results show that SERS activity depends closely on the nanogap size, and 4 nm Ag nanogaps exhibit the best SERS activity. By combining with other porous metal substrates, various sub-10 nm metal nanogaps can be fabricated over large scale. Therefore, this strategy will have significant implications for the preparation of nanogaps and enhanced spectroscopy.
Magnetic biosensors for identification of SARS-CoV-2, Influenza, HIV, and Ebola viruses: a review
Authors: GhaderiShekhiAbadi Parvaneh , Irani Mohammad , Noorisepehr Mohammad , Maleki Ali 
Published: March 2023

AbstractInfectious diseases such as novel coronavirus (SARS-CoV-2), Influenza, HIV, Ebola, etc kill many people around the world every year (SARS-CoV-2 in 2019, Ebola in 2013, HIV in 1980, Influenza in 1918). For example, SARS-CoV-2 has plagued higher than 317 000 000 people around the world from December 2019 to January 13, 2022. Some infectious diseases do not yet have not a proper vaccine, drug, therapeutic, and/or detection method, which makes rapid identification and definitive treatments the main challenges. Different device techniques have been used to detect infectious diseases. However, in recent years, magnetic materials have emerged as active sensors/biosensors for detecting viral, bacterial, and plasmids agents. In this review, the recent applications of magnetic materials in biosensors for infectious viruses detection have been discussed. Also, this work addresses the future trends and perspectives of magnetic biosensors.
Modulation transfer function (MTF) evaluation for x-ray phase imaging system employing attenuation masks
Authors: Havariyoun Glafkos , Massimi Lorenzo , Hagen Charlotte , Endrizzi Marco , Olivo Alessandro 
Published: March 2023

Abstract

Objective. Attenuation masks can be used in x-ray imaging systems to increase their inherent spatial resolution and/or make them sensitive to phase effects, a typical example being Edge Illumination x-ray phase contrast imaging (EI-XPCI). This work investigates the performance of a mask-based system such as EI-XPCI in terms of Modulation Transfer Function (MTF), in the absence of phase effects. Approach. Pre-sampled MTF measurements, using an edge, were performed on the same system implemented without masks, with non-skipped masks and finally with skipped masks (i.e. masks in which apertures illuminate every other pixel row/column). Results are compared to simulations and finally images of a resolution bar pattern acquired with all the above setups are presented. Main results. Compared to the detector’s inherent MTF, the non-skipped mask setup provides improved MTF results. In comparison to an ideal case where signal spill-out into neighbouring pixels is negligible, this improvement takes place only at specific frequencies of the MTF, dictated by the spatial repetition of the spill-out signal. This is limited with skipped masks, which indeed provide further MTF improvements over a larger frequency range. Experimental MTF measurements are supported through simulation and resolution bar pattern images. Significance. This work has quantified the improvement in MTF due to the use of attenuation masks and lays the foundation for how acceptance and routine quality control tests will have to be modified when systems using masks are introduced in clinical practice and how MTF results will compare to those of conventional imaging systems.
Attractive study of the physical properties of silver iron oxide nanoparticles for biomedical applications
Authors: El-Bassuony Asmaa A H , Abdelsalam H K 
Published: March 2023

Abstract
Novel ratios of silver iron nanoparticles with the chemical formulas Ag2Fe2O4 with Ag/Fe ratio = 1/1 and Ag0.5Fe2.5O4 with Ag/Fe ratio = 1/5 were successfully synthesized using a flash auto-combustion technique at 400 °C. Structural properties were studied using XRD (x-ray diffraction), AFM (Atomic Force Microscopy), FESEM (Field Emission Scanning Electron Microscopy), and FTIR (Fourier transform infrared) analyses. The nanosize range determined from XRD analysis lies in 56.6–71.1 nm for Ag0.5Fe2.5O4 and Ag2Fe2O4 nanoparticles. The morphology was analyzed using AFM and FESEM to confirm that the particle size of both samples was spherical and nanosized with agglomeration. Fourier transform infrared (FTIR) analysis was performed to confirm nano-samples’ formation. Both samples were measured using a vibrating sample magnetometer to study their magnetism. By increasing the concentration of iron ions, the saturation magnetization (Ms) increased 5-fold for Ag0.5Fe2.5O4 nanoparticles compared with Ag2Fe2O4 nanoparticles. Moreover, there is a relation between saturation magnetization and antimicrobial activity, in which high (Ms) gives high antibacterial activity. Thus, Ag0.5Fe2.5O4 had a high (Ms) and high efficacy against the tested bacteria. However, Ag2Fe2O4 showed high activity against Candida albicans. Moreover, a high-frequency application was measured from the magnetic measurements, showing that both samples could be applied at a very high frequency (VHF) in the radio wave range. Finally, both samples could be antibacterial materials, particularly Ag0.5Fe2.5O4 nanoparticles. However, Ag2Fe2O4 nanoparticles are strongly recommended for antifungal activity against Candida albicans.
The investigation of interlayer (CeO2:PVC) effects on the dielectric features of Au-Si (MS) Schottky barrier diodes (SBDs) using the impedance spectroscopy method
Authors: Ganj Tohid , Rozati S M , Azizian-Kalandaragh Yashar , Pirgholi-Givi Gholamreza 
Published: March 2023

Abstract
In this research, Au-PVC-Si (MPS1), Au-(CeO2: PVC)-Si (MPS2) Schottky barrier diodes (SBDs) have been grown on n-type silicon (n-Si) with the aim of investigating the frequency dependence and the effect of polymer interlayer on dielectric parameters such as complex dielectric constant (ε = ε′–iε″), ac-conductivity (σ
ac), and complex electric-modulus (M = M′ + iM″). For this purpose, the mentioned parameters have been calculated by measuring C/G-f in wide-range frequency (100 Hz–1 MHz) at room temperature for all three diodes and how the effect of PVC and (CeO2: PVC) interlayer on dielectric parameters of Au-Si (MS) has been studied. In the low-frequency range, plot C-f shows a negative capacitance behavior (NC) that causes the dielectric constant to be negative in this frequency range. Such negative behavior can be described using capture and emissions of carriers at interface states. The results of examining the frequency dependence of dielectric parameters showed that these parameters are sensitive to the frequency, especially the low-frequency range, which is due to the surface polarization and interface states. Also, the conduction mechanism of samples was investigated through the slope of the lnσ
ac- lnω plot. The σ
ac value for all three diodes at low frequencies is almost independent of the frequency, which is related to dc conductivity (σ
dc). The slope value of the lnσ
ac- lnω plot in the high frequencies was smaller than the unit which can be described by the hopping mechanism. The presence of the PVC and (PVC: CeO2) interlayer in the metal-semiconductor junction has increased the dielectric constant and conductivity of MPS compared to MS-type SBDs.
Weakly Supervised Semantic Segmentation of PolSAR Image Based on Improved SEAM
Authors: Shao Qiqi , Yu Lingjuan , Guo Yuting , Xie Xiaochun , Zou Jianping , Li Liang 
Published: March 2023

Abstract
Weakly supervised semantic segmentation (WSSS) has been widely studied in optical image field. Self-supervised equivariant attention mechanism (SEAM) effectively improves the WSSS results with the image-level labels. However, when it is directly used in the WSSS of polarimetric synthetic aperture radar (PolSAR) image, the performance is very poor. In this paper, an improved SEAM (ISEAM) is proposed for WSSS of PolSAR image, which uses the improved ResNet as the backbone network. The improvement mainly includes two aspects. First, the structure of ResNet is lightweight, which aims to match the characteristics of PolSAR dataset. Second, a squeeze-and-extraction (SE) attention mechanism is added into the backbone network, which aims to obtain channel-wise information. Experiments on Flevoland and San Francisco datasets show that the proposed ISEAM can achieve better performance than the original SEAM.
Review of Supernumerary Robotic Limbs
Authors: Zhang Kailing , Long Yi , Luo Xiaofeng 
Published: March 2023

Abstract
Supernumerary robotic limbs (SRLs) are the expansion of human body. It can provide extra limbs to enhance human ability. It is a novel way to assist the existing limbs using SRLs without prejudice to the normal activities of the user’s arm. It has great application prospects in the fields of military, industry, rehabilitation training and assistance in daily life. Based on the public research results of SRLs around the world, the development state of SRLs are summarized from the mechanical architecture, actuation mode, motion intention prediction and control strategy. The technical problems for SRLs are analyzed and their future technical development is given.
A stochastic convolution kernel transform-based model for evaluating bearing performance degradation
Authors: Zhu Qiuning , Liu Hongqi , Zhu Jiaming , Zhu Junhui 
Published: March 2023

Abstract
Bearing performance degradation assessment can effectively reduce the accuracy degradation and failure of robotic arms caused by bearing failures. Existing performance degradation models based on deep learning and machine learning models have not yet considered the enhancement of degradation assessment by fault-related decoupling in the signal. Therefore, this paper proposes a random convolution kernel transform-based bearing performance degradation assessment model, which enriches the characterization of bearing degradation trends by decomposing the VMD signal and extracting multi-dimensional sensitive features from the decomposed IMFs. The multi-scale characterization of bearing degradation is enriched by a large number of stochastic convolution kernel transforms. A ridge regression classifier is applied to balance accuracy and computational complexity to achieve an intelligent assessment of bearing degradation trends, and the effectiveness of the proposed method is verified on the XJTU-SY dataset, where the accuracy of the proposed method exceeds that of existing fault degradation trend assessment models.
Driving Style Recognition of Leading Vehicles based on Semi-supervised Gaussian Mixture Model
Authors: Song Qingjin , Li Wenyun , Pan Yirong , Leng Aocheng , Zhu Ren 
Published: March 2023

Abstract
Driving style recognition of leading vehicles is important to ensure driving safety and improve the efficiency of road traffic. Current supervised learning based methods achieve high recognition accuracy, but their annotations are labor-intensive and time-consuming in practical scenarios. Although unsupervised learning based methods do not require manual labeling, their recognition accuracy is still low. In order to reduce the labeling cost and improve the accuracy of driving style recognition simultaneously, we propose a driving style recognition method based on semi-supervised Gaussian mixture model. Firstly, the driving data is collected and pre-processed by OBD-II vehicle recorder, and 22-dimensional driving style feature parameters are selected and constructed. Secondly, the kernel principal component analysis method is used to reduce the dimensionality and obtain 6-dimensional discriminative principal components. Finally, the Gaussian mixture model is trained by utilizing both the labeled data and unlabeled data. Concretely, the model parameters are measured by the expectation maximization algorithm and the likelihood function. The simulation experimental results demonstrate that the proposed method can effectively improve the driving style recognition accuracy, as well as reduce the reliance on labeled data.
Component Detection of Overhead Transmission Line Based on CBAM-Efficient-YOLOv5
Authors: Wang Shukun , Gao Lin , Hu Tao , Fu Desu , Liu Wei 
Published: March 2023

Abstract
In view of the low efficiency of the staff who need to detect the insulator, grading ring, spacer and other components with their naked eyes when inspecting the transmission line manually, a CBAM Efficient YOLOv5 algorithm is proposed to realize the automatic detection of the above components. The algorithm improves the lightweight of YOLOv5, uses EfficientNet lightweight network to replace the original feature extraction network, and uses CBAM (Convolutional Block Attention Module) with both channel and spatial attention to replace SE (Sequence and Exception) attention module. Finally, a lightweight network model is obtained, in which the model size is reduced by 45.8%, the average precision is 95.2%, and the detection precision of all targets is improved to more than 90%. On the premise of meeting the precision requirements, it is easier to deploy in embedded equipment such as unmanned aerial vehicle, so as to improve the work efficiency of line patrol.
Exploring the Hysteresis Effect in SOC Estimation of Li-ion Batteries
Authors: Li Wenyun , Ruan Siqi , Bahitbek Ardah , Gao Zihuan , Turak Nuramina , Li Heng 
Published: March 2023

AbstractThe global energy crisis and serious environmental pollution make governments attach importance to the development of regenerating green energy. As the best battery system at present, lithium-ion battery has developed rapidly into a new generation of energy storage power. SOC estimation is an important indicator in the development of lithium-ion batteries. If SOC can be properly estimated, it will be pivotal to the investigation and exploitation of batteries, and a number of algorithms for SOC estimation have already emerged. This paper first introduces several current SOC estimation methods, and then explains the influencing factors and hysteresis effect of SOC. Then the SOC estimation value was obtained by open circuit voltage method, based on the mean value calculated by the random forest output OCV-SOC curve to reduce hysteresis effect. The effect of temperature on SOC was analysed by plotting the OCV-SOC profiles for charging and discharging at different temperatures. Finally, this paper is summarized and puts forward the improvement.
Line of Sight Tracking Method Based on Feedback Linearization and Command Planning
Authors: Guo Fengyu , Xie Cheng , Chen Songlin 
Published: March 2023

Abstract
When the target just enters the field of view of the optoelectronic tracking system, there is a big pointing deviation. If the closed-loop control is directly performed at this time, overshoot or even oscillation will occur, which will easily cause the target to leave the field of view again. At present, most control algorithms are concerned about enhancing the steady-state tracking precision of the system, but seldom consider the transient performance of the system. In this paper, a new definition of pointing deviation is given, in addition, the model of the line-of-sight (LOS) tracking system is realized. On this basis, a method based on feedback linearization is raised, which can compensate measurable disturbance. For both transient response and steady-state performance, a new LOS planning method is presented, which accomplishes the planning and design of the target motion trajectory on the imaging plane. It can be able to avoid the target departing from the field of view and speed up the system response based on fixed control parameters. Through the analysis of experimental results, it can be indicated that the LOS tracking method proposed in this paper can availably promote the transient performance of the system and is existent of real value.
Research on Hierarchical Clustering LEACH Protocol Optimization Algorithm Based on Chebyshev Distance
Authors: Zhu Yunyun , Zhu Li , Xiao Yu , Zha Minghu , Hu Tao , Xiang Mian 
Published: March 2023

Abstract
For the problems of premature death of cluster head nodes, short network life cycle and fast energy consumption in hierarchical clustering LEACH protocol in wireless sensor networks, an improved routing protocol K-means LEACH distance optimization algorithm based on LEACH is proposed in this paper. The improved routing algorithm takes into account the problems such as random selection of cluster heads and tedious calculation of distance formula in LEACH algorithm, so K-means clustering algorithm is introduced. The specific scheme is to first divide the data into K classes, then select the appropriate cluster heads, and introduce the Chebyshev distance formula on the basis of K-means clustering algorithm. From the comparative analysis of the simulation results, the K-means LEACH distance optimization algorithm compared to the original LEACH algorithm wireless network node life cycle by 64%, node energy consumption by 26%, which is conducive to improving the stability of WSN, reducing node energy consumption and extending the network survival time.
Human Motion Capture Based on MEMS Sensor
Authors: Dong Zhuangzhuang , Cheng Guangxin , Lou Qixin , Li Ding , Gao Na , Xu Yunong , Yu Xudong 
Published: March 2023

Abstract
In order to realize the monitoring of human joint rehabilitation, a human motion capture and recognition system is constructed by using micro electro mechanical system (MEMS) sensor nodes. A two-stage extended Kalman filter algorithm is proposed for multi-sensor data fusion. The error matrix between the coordinate system of sensor node and the coordinate system of body was calculated by using the stationary posture calibration. The root mean squared error (RMSE) of the computed joint angle time series is less than 0.5°. The feature of joint angle time series was extracted and the support vector machine (SVM) classification model based on particle swarm optimization (PSO) was established. The experimental results show that the SVM algorithm optimized by PSO has better recognition effect than BP neural network. The average recognition rate can reach more than 97%. The human motion capture system designed in this paper can effectively realize human motion capture, recognition and joint rehabilitation monitoring.
Estimation of the Charge State in Lithium-ion Batteries Based on an Adaptive Particle Filter
Authors: Zhao Qianyue , Yang Huihui , Pan Yirong 
Published: March 2023

Abstract
Lithium-ion batteries have the advantages of high energy density, long life, and environmental friendliness, and are widely used as sources of energy in new energy vehicles. The charge state (SOC) of lithium-ion battery greatly represents the remaining service time of the battery, and in electric vehicles, it greatly determines the range of the electric vehicle. Therefore, how to estimate SOC from physical quantities such as end voltage and end current is crucial. This paper introduces the common lithium-ion battery charge state estimation method and its state model, and estimates the charge state based on the adaptive particle filter algorithm.
Self-avoiding walks and polygons confined to a square
Authors: Whittington S G 
Published: March 2023

Abstract
We prove several rigorous results about the asymptotic behaviour of the numbers of polygons and self-avoiding walks confined to a square on the square lattice. Specifically we prove that the dominant asymptotic behaviour of polygons confined to an L × L square is identical to that of self-avoiding walks that cross an L × L square from one corner vertex to the opposite corner vertex. We prove results about the sub-dominant asymptotic behaviour of self-avoiding walks crossing a square and polygons confined to a square and extend some results to self-avoiding walks and polygons in a hypercube in

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Culturally and Linguistically Informed Neuropsychological Evaluation Protocol for Primarily Spanish-Speaking Adults
Authors: Strutt Adriana M , Armendariz Victoria , Arias Franchesca , Diaz Santos Ana L , Zink Davor , Vuong Kevin Dat , Rossetti Maria Agustina 
Published: March 2023

Abstract

Objective
The Latina(o)/Hispanic (L/H) population represents the largest and fastest-growing ethnic group in the United States. Migration patterns have evolved and greater diversity (i.e., country of origin) is evident, highlighting the ever-changing heterogeneity of this community and the need for the field of neuropsychology to ensure equitable care for linguistically and culturally diverse communities. This paper aims to provide a flexible protocol of neuropsychological instruments appropriate for primarily Spanish-speaking adults residing in the United States.

Method
Spanish measures were selected based on availability, translations/cultural modifications, accompanying normative data sets, and clinician experience/acumen. Bilingual/bicultural providers of neuropsychological services to Spanish speakers across the training spectrum working at U.S.-based medical centers implemented a multimodal approach (i.e., literature search, clinical practice parameters, and focus groups) in the development of a multi-domain primary protocol that includes core and supplemental measures that are appropriate for individuals with varying linguistic proficiency and sociocultural demographic characteristics.

Results
A multi-domain, evidence-based, flexible neuropsychological protocol is presented. Recommendations for test selection based on sociocultural demographic factors and examples of clinical assessment practices are provided via a case illustration. Most instruments included may be applied across cultural and regional backgrounds.

Conclusion
Provision of neuropsychological services to primarily Spanish-speaking adults presents unique challenges. Existing Spanish measures and accompanying data rarely capture the heterogeneity of L/H individuals. Although Spanish has the largest number of neurocognitive instruments, relative to other languages, robust and representative norms continue to be scarce. Future studies should prioritize collecting normative data from educationally and geographically diverse samples.