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Distributed fiber optic sensing system for vibration monitoring of 3D printed bridges

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Optoelectronics Letters 2025年第1期21卷 28-34页

作者： ZHAO Shuai ZHOU Ran LUO Mingming LIU Jianfei LIU Xiongfei ZHOU Tao school of Electronic information engineering Hebei University of Technology Tianjin Key Laboratory of Electronic Materials and Devices school of Civil engineering and Transportation Hebei University of Technology Tianjin Jinhang Institute of Technical Physics

The fiber optic sensing technology provides data support in structural health monitoring of the macro facilities, including design, construction, and maintenance of bridges, tunnels, ports and other infrastructures. In this paper, a distributed vibration sensing system is proved to be responsive to a single touch over a 1.8-m-long equivalent fiber segment, covering a vibration frequency from 5 Hz to 25 kHz. The sensing fiber was arranged as an S type layout on the bridge to recognize the standing state, windblown disturbance, and walking vibration. Moreover, the knocking and climbing events are recognized fiber laying spinning lines and hanging on the fences, respectively. The demonstration shows an accurate positioning and sensitive vibration monitoring applied on the automated three-dimensional(3D) printed bridge, which is applicable to all kinds of 3D printed facilities as intelligent sensory neuro-networks.

关键词： Spinning (fibers)

Congruent Feature Selection Method to Improve the Efficacy of Machine Learning-Based Classification in Medical Image Processing

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Computer Modeling in engineering & sciences 2025年第1期142卷 357-384页

作者： Mohd Anjum Naoufel Kraiem Hong Min Ashit Kumar Dutta Yousef Ibrahim Daradkeh Department of Computer engineering Aligarh Muslim UniversityAligarh202002India College of Computer science King Khalid UniversityAbha61413Saudi Arabia school of Computing Gachon UniversitySeongnam13120Republic of Korea Department of Computer science and information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer engineering and information College of Engineering in Wadi AlddawasirPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia

Machine learning(ML)is increasingly applied for medical image processing with appropriate learning *** applications include analyzing images of various organs,such as the brain,lung,eye,etc.,to identify specific flaws/diseases for *** primary concern of ML applications is the precise selection of flexible image features for pattern detection and region *** of the extracted image features are irrelevant and lead to an increase in computation ***,this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image *** process trains the learning paradigm using similarity and correlation-based features over different textural intensities and pixel *** similarity between the pixels over the various distribution patterns with high indexes is recommended for disease ***,the correlation based on intensity and distribution is analyzed to improve the feature selection ***,the more congruent pixels are sorted in the descending order of the selection,which identifies better regions than the ***,the learning paradigm is trained using intensity and region-based similarity to maximize the chances of ***,the probability of feature selection,regardless of the textures and medical image patterns,is *** process enhances the performance of ML applications for different medical image *** proposed method improves the accuracy,precision,and training rate by 13.19%,10.69%,and 11.06%,respectively,compared to other models for the selected *** mean error and selection time is also reduced by 12.56%and 13.56%,respectively,compared to the same models and dataset.

关键词： Computer vision feature selection machine learning region detection texture analysis image classification medical images

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in engineering & sciences 2025年第1期142卷 299-327页

作者： A.Robert Singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia school of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification

Advances in Graphene‑Based Electrode for Triboelectric Nanogenerator

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Nano-Micro Letters 2025年第1期17卷 378-403页

作者： Bin Xie Yuanhui Guo Yun Chen Hao Zhang Jiawei Xiao Maoxiang Hou Huilong Liu Li Ma Xin Chen Chingping Wong State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of TechnologyGuangzhou 510006People’s Republic of China school of Electromechanical engineering Guangdong University of TechnologyGuangzhou 510006People’s Republic of China school of Materials science and engineering Georgia Institute of TechnologyAtlantaGA 30332USA

With the continuous development of wearable electronics,wireless sensor networks and other micro-electronic devices,there is an increasingly urgent need for miniature,flexible and efficient nanopower generation *** nanogenerator(TENG)technology can convert small mechanical energy into electricity,which is expected to address this *** the core component of TENG,the choice of electrode materials significantly affects its *** metal electrode materials often suffer from problems such as durability,which limits the further application of ***,as a novel electrode material,shows excellent prospects for application in TENG owing to its unique structure and excellent electrical *** review systematically summarizes the recent research progress and application prospects of TENGs based on graphene *** precision processing methods of graphene electrodes are introduced,and the applications of graphene electrode-based TENGs in various scenarios as well as the enhancement of graphene electrodes for TENG performance are *** addition,the future development of graphene electrode-based TENGs is also prospectively discussed,aiming to promote the continuous advancement of graphene electrode-based TENGs.

关键词： Triboelectric nanogenerator Precision processing Graphene electrode Self-powered sensor

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Unleashing the Potential of Electroactive Hybrid Biomaterials and Self‑Powered Systems for Bone Therapeutics

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Nano-Micro Letters 2025年第2期17卷 463-497页

作者： Shichang Liu Farid Manshaii Jinmiao Chen Xinfei Wang Shaolei Wang Junyi Yin Ming Yang Xuxu Chen Xinhua Yin Yunlei Zhou Honghui Hospital Xi’an Jiaotong UniversityXi’an 710018People’s Republic of China Department of Bioengineering Henry Samueli School of Engineering and Applied ScienceUniversity of California Los AngelesLos Angeles 90095USA Hangzhou Institute of Technology Xidian UniversityHangzhou 311231People’s Republic of China

The incidence of large bone defects caused by traumatic injury is increasing worldwide,and the tissue regeneration process requires a long recovery time due to limited self-healing *** bioelectrical phenomena have been well recognized as critical biophysical factors in bone remodeling and *** by bioelectricity,electrical stimulation has been widely considered an external intervention to induce the osteogenic lineage of cells and enhance the synthesis of the extracellular matrix,thereby accelerating bone *** ongoing advances in biomaterials and energy-harvesting techniques,electroactive biomaterials and self-powered systems have been considered biomimetic approaches to ensure functional recovery by recapitulating the natural electrophysiological microenvironment of healthy bone *** this review,we first introduce the role of bioelectricity and the endogenous electric field in bone tissue and summarize different techniques to electrically stimulate cells and ***,we highlight the latest progress in exploring electroactive hybrid biomaterials as well as self-powered systems such as triboelectric and piezoelectric-based nanogenerators and photovoltaic cell-based devices and their implementation in bone tissue ***,we emphasize the significance of simulating the target tissue’s electrophysiological microenvironment and propose the opportunities and challenges faced by electroactive hybrid biomaterials and self-powered bioelectronics for bone repair strategies.

关键词： Electroactive biomaterials Self-powered bioelectronics Bone regeneration Bone tissue

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Endoscopy-assisted lightweight diagnosis system based on transformers for colon polyp detection

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Optoelectronics Letters 2025年第1期21卷 57-64页

作者： FAN Weiming YU Jiahui JU Zhaojie school of Automation and Electrical engineering Shenyang Ligong University Department of Biomedical engineering Zhejiang University school of Computing University of Portsmouth

The integration of endoscopy has significantly propelled the diagnosis and treatment of gastrointestinal diseases, with colonoscopy establishing itself as the primary method for early diagnosis and preventive care in colorectal cancer(CRC). Although deep learning holds promise in mitigating missed polyp rates, modern endoscopy examinations pose additional challenges, such as image blurring and atomizing. This study explores lightweight yet powerful attention mechanisms, introducing the spatial-channel transformer(SCT), an innovative approach that leverages spatial channel relationships for attention weight calculation. The method utilizes rotation operations for inter-dimensional dependencies, followed by residual transformation, encoding inter-channel and spatial information with minimal computational overhead. Extensive experiments on the CVC-Clinic DB polyp detection dataset, addressing endoscopy pitfalls, underscore the superiority of our SCT over other state-of-the-art methods. The proposed model maintains high performance, even in challenging scenarios.

关键词： Endoscopy

Near-perfect replication on amorphous alloys through active force modulation based on machine learning/neural network parameter prediction

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science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 181-191页

作者： Senkuan Meng Zheng Wang Ruisong Zhu Ruijie Liu Jiang Ma Lina Hu Weihua Wang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education) School of Materials Science and Engineering Shandong University College of Mechatronics and Control engineering Shenzhen University Songshan Lake Materials Laboratory Institute of Physics Chinese Academy of Sciences

As a microforming technique, micro/nano-structural replication possesses advantages of high precision and efficiency. With the remarkable superplasticity in the supercooled liquid region, amorphous alloys or metallic glasses(MGs) are regarded as ideal materials for miniature fabrication. However, due to the intrinsic metastable nature of supercooled liquids, the design of imprinting processes for MGs poses a challenge. In the past, process parameters have largely relied on trial-and-error *** this work, a low-frequency active force modulation system is employed to apply a stable, precise, and real-time feedback stress field for imprinting of MG samples. Low-frequency vibrations can facilitate the filling of microstructures on the template surface by reducing the effective viscosity of the supercooled liquid. With the dataset composed of orthogonal experiments, a machine learning strategy based on back-propagation(BP) neural networks was utilized to construct a 3D parameter space for temperature, stress, and time, and to predict the corresponding filling ratio. Furthermore, the optimal combination of imprinting process parameters was identified, and its filling ratio was experimentally validated to reach as high as 0.94. The near-perfect replication of microstructures confirms the superiority of the active force modulation system and the data-driven strategy of machine learning-assisted parameter design. At the same time, this one-step microforming process provides a new approach to addressing the accuracy-cost trade-off dilemma in precision manufacturing.

关键词： metallic glass amorphous alloy microforming imprinting machine learning

Dynamic behaviors of graphene platelets-reinforced metal foam piezoelectric beams with velocity feedback control

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applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 63-80页

作者： Jie CHEN Xinyue ZHANG Mingyang FAN school of Mathematics Statistics and Mechanics Beijing University of Technology College of Mechanical & Energy engineering Beijing University of Technology

Graphene platelets(GPLs)-reinforced metal foam structures enhance the mechanical properties while maintaining the lightweight characteristics of metal foams. Further bonding piezoelectric actuator and sensor layers on the surfaces of GPLs-reinforced metal foam beams enables active vibration control, greatly expanding their applications in the aerospace industry. For the first time, this paper investigates the vibration characteristics and active vibration control of GPLs-reinforced metal foam beams with surfacebonded piezoelectric layers. The constant velocity feedback scheme is used to design the closed-loop controller including piezoelectric actuators and sensors. The effects of the GPLs on the linear and nonlinear free vibrations of the beams are numerically *** Newmark-β method combined with Newton's iteration technique is used to calculate the nonlinear responses of the beams under different load forms including harmonic loads,impact loads, and moving loads. Additionally, special attention is given to the vibration reduction performance of the velocity feedback control on the responses of the beam.

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Continuous high-temperature rapid nanomanufacturing of electrocatalysts

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Nano Research 2025年第1期18卷 225-235页

作者： Xiaoyang Wang Ziyi Luo Baihua Cui Ziqi Fu Yanchang Liu Weidi Liu Jia Ding Jianrong Zeng Yanan ChenWenbin Hu school of Materials science and engineering Tianjin UniversityTianjin 300350China Australian Institute for Bioengineering and Nanotechnology The University of QueenslandSt.LuciaBrisbane 4072Australia Shanghai Synchrotron Radiation Facility Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai 201204China Shanghai Institute of applied Physics Chinese Academy of SciencesShanghai 201800China

Encapsulating metal nanoparticles in carbon shells(Metal@C)to enhance catalytic activity and stability has been certified ***,most existing methods for preparing Metal@C are complex,time-consuming,and lack of *** this study,a novel method that couples the high-temperature shock(HTS)with ultrasonic spray pyrolysis is reported,which can realize facile and scalable production of various Metal@C through the pyrolysis of glucose and metal chloride *** proposed HTS ultrasonic spray pyrolysis offers several advantages,including compact size,short reaction time(~120 ms),and uniform *** the Ni@C-40 nanocomposite as an example,the ultrasmall Ni nanoparticles(~10 nm)with thin carbon protective shells(~2 nm)are uniformly dispersed in the carbon matrix and applied for oxygen evolution reaction(OER)in alkaline *** Ni@C-40 optimized by tuning the thickness of carbon shell exhibits significantly enhanced OER activity with low overpotential of 242 mV at 10 mA·cm^(-2) and stability,which is attributed to the optimized interactions between Ni nanoparticles and carbon *** method also shows promise for continuous pyrolysis synthesis of various extreme materials at ultra-high temperatures using alternative electric heating materials.

关键词： ultrasonic spray pyrolysis high-temperature shock carbon shell oxygen evolution reaction Metal@C nanocomposite