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Effect of Bi/Si Ratio of BiBSi Glass on Its Structure, Properties and Laser Sealing Shear Strength for Vacuum Glazing

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 13-24页

作者： LIU Wei JIAO Jinxu LUO Dusha ZHOU Junjie SHI Lifen wang Weiwei LI Changqing wang Peng XIONG Dehua LI Hong State Key Laboratory of Silicate Materials for Architectures Wuhan University of TechnologyWuhan 430070China Silica-Based Materials Laboratory of Anhui Province CNBM Research Institute for Advanced Glass Materials Group Co.LtdBengbu 233018China State Key Laboratory of Advanced Technology for Float Glass CNBM Research Institute for Advanced Glass Materials Group Co.LtdBengbu 233018China

The low-melting glass of Bi2O_(3)-B2O_(3)-SiO_(2)(BiBSi)system was used for the first time for laser sealing of vacuum *** the condition of constant boron content,how the structure and properties vary with Bi/Si ratio in low-melting glass was *** addition,the relationships between laser power,low-melting glass solder with different Bi/Si ratios and laser sealing shear strength were *** results show that a decrease in the Bi/Si ratio can cause a contraction of the glass network of the low-melting glass,leading to an increase of its characteristic temperature and a decrease of its coefficient of thermal *** laser sealing,the copper ions in the low-melting glass play an endothermic role.A change in the Bi/Si ratio will affect the valence state transition of the copper ions in the low-melting *** absorbance of the low-melting glass does not follow the expected correlation with the Bi/Si ratio,but shows a linear correlation with the content of divalent copper *** greater the concentration of divalent copper ions,the greater the absorbance of the low-melting glass,and the lower the laser power required for laser *** shear strength of the low melting glass solder after laser sealing was tested,and it was found that the maximum shear strength of Z1 glass sample was the highest up to 2.67 MPa.

关键词： Bi2O_(3)-B2O_(3)-SiO_(2)(BiBSi) Bi/Si ratio low-melting glass laser sealing vacuum glazing

A novel flexible nerve guidance conduit promotes nerve regeneration while providing excellent mechanical properties

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Neural Regeneration Research 2025年第7期20卷 2084-2094页

作者： Tong Li Quhan Cheng Jingai Zhang Boxin Liu Yu Shi Haoxue wang Lijie Huang Su Zhang Ruixin Zhang Song wang Guangxu Lu Peifu Tang Zhongyang Liu Kai wang Department of Orthopedics the Fourth Medical Center of Chinese PLA General HospitalBeijingChina Department of Training and Sports Medicine Characteristic Medical Center of Chinese People’s Armed Police ForceTianjinChina Medical School of Chinese PLA BeijingChina Key Laboratory of Bioactive Materials for the Ministry of Education College of Life SciencesNankai UniversityTianjinChina Department of Orthopedics Tianjin HospitalTianjinChina Department of Rehabilitation Medicine Er Quan Hospital of PAPWuxiJiangsu ProvinceChina

Autografting is the gold standard for surgical repair of nerve defects>5 mm in length;however,autografting is associated with potential complications at the nerve donor *** an alternative,nerve guidance conduits may be *** ideal conduit should be flexible,resistant to kinks and lumen collapse,and provide physical cues to guide nerve *** designed a novel flexible conduit using electrospinning technology to create fibers on the innermost surface of the nerve guidance conduit and employed melt spinning to align ***,we prepared disordered electrospun fibers outside the aligned fibers and helical melt-spun fibers on the outer wall of the electrospun fiber *** presence of aligned fibers on the inner surface can promote the extension of nerve cells along the *** helical melt-spun fibers on the outer surface can enhance resistance to kinking and compression and provide *** novel conduit promoted nerve regeneration and functional recovery in a rat sciatic nerve defect model,suggesting that it has potential for clinical use in human nerve injuries.

关键词： aligned fibers anti-kinking helical fibers nerve guidance conduit nerve regeneration peripheral nerve injury topological guidance

Macro-mechanics and Microstructure of Nanomaterial-modified Geopolymer Concrete: A Comprehensive Review

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 204-214页

作者： wang Tao FAN Xiangqian GAO Changsheng QU Chiyu The National Key Laboratory of Water Disaster Prevention Nanjing Hydraulic Research InstituteNanjing 210024China Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou 511458China School of Water Conservancy and Transportation Zhengzhou UniversityZhengzhou 450001China

We have described in detail the effects of nano-SiO_(2),nano-CaCO_(3),carbon nanotubes,and nano-Al_(2)O_(3) on geopolymer concrete from the perspectives of macro mechanics and *** existing research results show that the mechanism of nano-materials on geopolymer concrete mainly includes the filling effect,nucleation effect,and bridging effect,the appropriate amount of nano-materials can be used as fillers to reduce the porosity of geopolymer concrete,and can also react with Ca(OH)2 to produce C-S-H gel,thereby improving the mechanical properties of geopolymer *** optimum content of nano-SiO_(2) is between 1.0%and 2.0%.The optimum content of nano-CaCO_(3) is between 2.0%and 3.0%.The optimum content of carbon nanotubes is between 0.1%and 0.2%.The optimum content of nano-Al_(2)O_(3) is between 1.0%and 2.0%.The main problems existing in the research and application of nanomaterial-modified geopolymer concrete are summarized,which lays a foundation for the further application of nanomaterial in geopolymer concrete.

关键词： nanomaterials low carbon geopolymer concrete macro-mechanics microstructure

Malicious Document Detection Based on GGE Visualization

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Computers, Materials & Continua 2025年第1期82卷 1233-1254页

作者： Youhe wang Yi Sun Yujie Li Chuanqi Zhou Henan Province Key Laboratory of Information Security Information Engineering UniversityZhengzhou450000China

With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers has become particularly ***,detection methods based on document structure and behavioral features encounter challenges in feature engineering,these methods not only have limited accuracy,but also consume large resources,and usually can only detect documents in specific formats,which lacks versatility and *** address such problems,this paper proposes a novel malicious document detection method-visualizing documents as GGE images(Grayscale,Grayscale matrix,Entropy).The GGE method visualizes the original byte sequence of the malicious document as a grayscale image,the information entropy sequence of the document as an entropy image,and at the same time,the grayscale level co-occurrence matrix and the texture and spatial information stored in it are converted into grayscale matrix image,and fuses the three types of images to get the GGE color *** Convolutional Block Attention Module-EfficientNet-B0(CBAM-EfficientNet-B0)model is then used for classification,combining transfer learning and applying the pre-trained model on the ImageNet dataset to the feature extraction process of GGE *** shown in the experimental results,the GGE method has superior performance compared with other methods,which is suitable for detecting malicious documents in different formats,and achieves an accuracy of 99.44%and 97.39%on Portable Document Format(PDF)and office datasets,respectively,and consumes less time during the detection process,which can be effectively applied to the task of detecting malicious documents in real-time.

关键词： Malicious document visualization EfficientNet-B0 convolutional block attention module GGE image

Offload Strategy for Edge Computing in Satellite Networks Based on Software Defined Network

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Computers, Materials & Continua 2025年第1期82卷 863-879页

作者： Zhiguo Liu Yuqing Gui Lin wang Yingru Jiang Communication and Network Laboratory Dalian UniversityDalian116622China College of Environment and Chemical Engineering Dalian UniversityDalian116622China

Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable *** sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers,making it necessary to implement effective task offloading scheduling to enhance user *** this paper,we propose a priority-based task scheduling strategy based on a Software-Defined Network(SDN)framework for satellite-terrestrial integrated networks,which clarifies the execution order of tasks based on their ***,we apply a Dueling-Double Deep Q-Network(DDQN)algorithm enhanced with prioritized experience replay to derive a computation offloading strategy,improving the experience replay mechanism within the Dueling-DDQN ***,we utilize the Deep Deterministic Policy Gradient(DDPG)algorithm to determine the optimal resource allocation strategy to reduce the processing latency of *** results demonstrate that the proposed d3-DDPG algorithm outperforms other approaches,effectively reducing task processing latency and thus improving user experience and system efficiency.

关键词： Satellite network edge computing task scheduling computing offloading

SEFormer:A Lightweight CNN-Transformer Based on Separable Multiscale Depthwise Convolution and Efficient Self-Attention for Rotating Machinery Fault Diagnosis

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Computers, Materials & Continua 2025年第1期82卷 1417-1437页

作者： Hongxing wang Xilai Ju Hua Zhu Huafeng Li State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing210016China School of Computer Science and Engineering Nanyang Technological UniversitySingapore639798Singapore

Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain ***,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis ***,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault ***,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative *** complexity results in high computational costs and limited industrial *** tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault ***,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration ***,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global ***,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and *** study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.

关键词： CNN-Transformer separable multiscale depthwise convolution efficient self-attention fault diagnosis

IoT Empowered Early Warning of Transmission Line Galloping Based on Integrated Optical Fiber Sensing and Weather Forecast Time Series Data

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Computers, Materials & Continua 2025年第1期82卷 1171-1192页

作者： Zhe Li Yun Liang Jinyu wang Yang Gao State Grid Henan Electric Power Company Electric Power Scientific Research Institute State Grid Henan Electric Power CompanyZhengzhou450052China

Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power *** early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false *** address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather ***,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused ***,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network ***,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this ***,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.

关键词： Optical fiber sensing multi-source data fusion early warning of galloping time series data IoT adaptive weighted learning irregular time series perception closed-loop attention mechanism

Unmasking Social Robots’Camouflage:A GNN-Random Forest Framework for Enhanced Detection

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Computers, Materials & Continua 2025年第1期82卷 467-483页

作者： Weijian Fan Chunhua wang Xiao Han Chichen Lin School of Data Science and Intelligent Media Communication University of ChinaBeijing100024China School of Computer and Cyber Sciences Communication University of ChinaBeijing100024China Institute of Communication Studies Communication University of ChinaBeijing100024China State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing100024China

The proliferation of robot accounts on social media platforms has posed a significant negative impact,necessitating robust measures to counter network anomalies and safeguard content *** robot detection has emerged as a pivotal yet intricate task,aimed at mitigating the dissemination of misleading *** graphbased approaches have attained remarkable performance in this realm,they grapple with a fundamental limitation:the homogeneity assumption in graph convolution allows social robots to stealthily evade detection by mingling with genuine human *** unravel this challenge and thwart the camouflage tactics,this work proposed an innovative social robot detection framework based on enhanced HOmogeneity and Random Forest(HORFBot).At the core of HORFBot lies a homogeneous graph enhancement strategy,intricately woven with edge-removal techniques,tometiculously dissect the graph intomultiple revealing ***,leveraging the power of contrastive learning,the proposed methodology meticulously trains multiple graph convolutional networks,each honed to discern nuances within these tailored *** culminating stage involves the fusion of these feature-rich base classifiers,harmoniously aggregating their insights to produce a comprehensive detection *** experiments on three social robot detection datasets have shown that this method effectively improves the accuracy of social robot detection and outperforms comparative methods.

关键词： Social robot detection graph neural networks random forest homophily heterophily

Collaborative Trajectory Planning for Stereoscopic Agricultural Multi-UAVs Driven by the Aquila Optimizer

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Computers, Materials & Continua 2025年第1期82卷 1349-1376页

作者： Xinyu Liu Longfei wang Yuxin Ma Peng Shao School of Computer and Information Engineering Jiangxi Agricultural UniversityNanchang330045China

Stereoscopic agriculture,as an advanced method of agricultural production,poses new challenges for multi-task trajectory planning of unmanned aerial vehicles(UAVs).To address the need for UAVs to perform multi-task trajectory planning in stereoscopic agriculture,a multi-task trajectory planning model and algorithm(IEP-AO)that synthesizes flight safety and flight efficiency is *** on the requirements of stereoscopic agricultural geomorphological features and operational characteristics,the multi-task trajectory planning model is ensured by constructing targeted constraints at five aspects,including the path,slope,altitude,corner,energy and obstacle threat,to improve the effectiveness of the trajectory planning *** combined with the path optimization algorithm,an Aquila optimizer(IEP-AO)based on the interference-enhanced combination model is proposed,which can help UAVs to improve the trajectory search capability in complex operation space and large-scale operation tasks,and jump out of the locally optimal trajectory path region timely,to generate the optimal trajectory planning plan that can adapt to the diversity of the tasks and the flight ***,four simulated flights with different operation scales and different scene constraints were conducted under the constructed real 3Dimension scene,and the experimental results can show that the proposedmulti-task trajectory planning method canmeet themulti-task requirements in stereoscopic agriculture and improve the mission execution efficiency and agricultural production effect of UAV.

关键词： Stereoscopic agriculture unmanned aerial vehicle multi-task interference model Aquila optimizer