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Rock fracture mechanism of buffer blasting with cushion layer at the borehole bottom

International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 325-334页

作者： Xinguang Zhu Chenxi Ding Zhe Sui Hong Su Xu Guo School of Civil and Resources Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory for Mechanics in Fluid Solid Coupling Systems Institute of MechanicsChinese Academy of SciencesBeijing 100190China School of Mechanics and Civil Engineering China University of Mining and Technology(Beijing)Beijing 100083China School of Chemical and Blasting Engineering Anhui University of Science and TechnologyHuainan 232001China

This study primarily investigates the rock fracture mechanism of bottom cushion layer blasting and explores the effects of the bottom cushion layer on rock *** involves analyses of the evolution patterns of blasting stress,characteristics of crack distribution,and rock fracture features in the ***,blasting model experiments were carried out using the dynamic caustics principle to investigate the influence of bottom cushion layers and initiation methods on the integrity of the bottom rock *** experimental results indicate that the combined use of bottom cushion layers and inverse initiation effectively protects the integrity of the bottom rock ***,the process of stress wave propagation and dynamic crack propagation in rocks was simulated using the continuum-discontinuum element method(CDEM)and the Landau explosion source model,with varying thicknesses of bottom cushion *** numerical simulation results indicate that with increasing cushion thickness,the absorption of energy generated by the explosion becomes more pronounced,resulting in fewer cracks in the bottom rock *** illustrates the positive role of the cushion layer in protecting the integrity of the bottom rock mass.

关键词： bottom cushion layer blasting crack propagation continuum-discontinuum element method dynamic stress intensity factor

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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

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GFRF R-CNN:Object Detection Algorithm for Transmission Lines

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Computers, Materials & Continua 2025年第1期82卷 1439-1458页

作者： Xunguang Yan Wenrui Wang Fanglin Lu Hongyong Fan Bo Wu Jianfeng Yu Shanghai Advanced Research institute Chinese Academy of SciencesShanghai201210China University of Chinese Academy of Sciences Beijing100049China Jingwei Textile Machinery Co. Ltd.Beijing100176China

To maintain the reliability of power systems,routine inspections using drones equipped with advanced object detection algorithms are essential for preempting power-related *** increasing resolution of drone-captured images has posed a challenge for traditional target detection methods,especially in identifying small objects in high-resolution *** study presents an enhanced object detection algorithm based on the Faster Regionbased Convolutional Neural Network(Faster R-CNN)framework,specifically tailored for detecting small-scale electrical components like insulators,shock hammers,and screws in transmission *** algorithm features an improved backbone network for Faster R-CNN,which significantly boosts the feature extraction network’s ability to detect fine *** Region Proposal Network is optimized using a method of guided feature refinement(GFR),which achieves a balance between accuracy and *** incorporation of Generalized Intersection over Union(GIOU)and Region of Interest(ROI)Align further refines themodel’s *** results demonstrate a notable improvement in mean Average Precision,reaching 89.3%,an 11.1%increase compared to the standard Faster *** highlights the effectiveness of the proposed algorithm in identifying electrical components in high-resolution aerial images.

关键词： Faster R-CNN transmission line object detection GIOU GFR

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Fractal autoencoder with redundancy regularization for unsupervised feature selection

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Science China(Information Sciences) 2025年

作者： Meiting SUN Fangyu LI Honggui HAN School of Information Science and Technology Beijing University of Technology beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Digital Community Ministry of Education beijing institute of Artificial Intelligence(beijing)

Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised feature selection has received increasing attention in recent years. However, existing unsupervised feature selection methods tend to prioritize selecting highly correlated features over exploring feature diversity. Thus, a regularized fractal autoencoder (RFAE) method is proposed to select informative features in an unsupervised way. Specifically, the fractal autoencoder network extends autoencoders to construct a correspondence neural network and a selection neural network. The correspondence neural network exploits interfeature correlations and the selection neural network selects the informative features. A redundancy regularization strategy consists of a redundancy elimination regularization term based on the dependency between features and a sparse regularization term based on the group lasso. The redundancy regularization strategy eliminates feature subset redundancy and enhances network generalization ability. Extensive experimental results on six publicly available datasets show that the proposed RFAE outperforms the compared methods regarding clustering accuracy and classification accuracy. Moreover, the proposed RFAE achieves acceptable computation efficiency.

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Cold-modeling study of a circulating fluidized bed reactor for flue gas desulfurization (FGD)

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Journal of Environmental Sciences 2000年第2期12卷 88-94页

作者： Qian, Feng Liu, Tong-Guang Zhang, Zhen-Fang Department of Chemical Engineering Beijing Institute of Light Industry Beijing 100037 China

Short residence time of the sorbent in the gas stream and formation of a dense layer of reaction product surrounding its surface influence the sulfur removal efficiency. A practical means of improving the process performance is to employ fluidized bed reaction in replacement of entrained bed reaction on normally used in cool side desulfurizaiton. This paper describes cold modeling study of a circulating fluidized bed reactor. Several aspects of the problem are discussed: fluidization behavior of CaO, attrition of the sorbent and solids entrainment from the fluidized bed. Mechanisms and key controlling parameters are identified, and an integral model based on rate of attrition and mass balance is developed for predicting steady state mass flows and particle size distributions of the system. A process flow scheme is finally presented for conducting desulfurization tests in the second stage of the study.

关键词： circulating fluidized bed reactor flue gas desulfurization cold modeling study CLC number: X701 Document code: A

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Electro-optic tuning in ferroelectric capacitor with photonic crystal nanobeam cavity

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Science China(Information Sciences) 2025年

作者： Tongtong WANG Yong ZHANG Danyang YAO Zhi JIANG Dongxin TAN Jie WEN Qiyu YANG Xuetao GAN Yan LIU Yue HAO Genquan HAN State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology School of MicroelectronicsXidian University Key Laboratory of light Field Manipulation and Information Acquisition Ministry of Industry and Information TechnologyShaanxi Key Laboratory of Optical Information Technology School of Physical Science and TechnologyNorthwestern Polytechnical University Hangzhou institute of Technology Xidian University

Silicon photonics has provided a platform for the convergency of photonic devices and electronic circuits, facilitating the development of optical telecommunications and optical interconnects on chip[1]. As the basic building block of optical communication systems, electro-optic tuning is expected to be more compact, high bandwidth, energy efficient, and allow for CMOS-compatible fabrication in the future[2]. Resonator-based electro-optic tuning has attracted more and more interest due to the small footprint, enhanced light-matter interactions and high energy efficiency. Compared with microring and microdisk resonators, photonic crystal nanobeam cavities （PCNBCs） realize higher quality factors, stronger light-matter interactions, ultrasmall mode volume and a much larger free spectral range （FSR）[3].

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Review of precipitation strengthening in ultrahigh-strength martensitic steel

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 256-269页

作者： Zhihao Tian Chunlei Shang Chaolei Zhang Xiaoye Zhou Honghui Wu Shuize Wang Guilin Wu Junheng Gao Jiaming Zhu Xinping Mao institute for Carbon Neutrality University of Science and Technology BeijingBeijing 100083China institute of Steel Sustainable Technology Liaoning Academy of MaterialsShenyang 110004China Department of Materials Science and Engineering Shenzhen MSU-BIT UniversityShenzhen 518172China institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China School of Civil Engineering Shandong UniversityJinan 250061China

Martensite is an important microstructure in ultrahigh-strength steels,and enhancing the strength of martensitic steels often involves the introduction of precipitated phases within the martensitic *** considerable research efforts devoted to this area,a systematic summary of these advancements is *** review focuses on the precipitates prevalent in ultrahigh-strength martensitic steel,primarily carbides(e.g.,MC,M_(2)C,and M_(3)C)and intermetallic compounds(e.g.,Ni Al,Ni_(3)X,and Fe_(2)Mo).The precipitation-strengthening effect of these precipitates on ultrahigh-strength martensitic steel is discussed from the aspects of heat treatment processes,microstructure of precipitate-strengthened martensite matrix,and mechanical ***,a perspective on the development of precipitation-strengthened martensitic steel is presented to contribute to the advancement of ultrahigh-strength martensitic *** review highlights significant findings,ongoing challenges,and opportunities in the development of ultrahigh-strength martensitic steel.

关键词： ultrahigh-strength martensitic steel precipitation strengthening mechanical property carbide intermetallic compound

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A Novel Model for Describing Rail Weld Irregularities and Predicting Wheel-Rail Forces Using a Machine Learning Approach

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 555-577页

作者： Linlin Sun Zihui Wang Shukun Cui Ziquan Yan Weiping Hu Qingchun Meng State Key Laboratory of High-Speed Railway Track System China Academy of Railway Sciences Corporation LimitedBeijing100081China Railway Engineering Research institute China Academy of Railway Sciences Corporation LimitedBeijing100081China School of Aeronautic Science and Engineering Beihang UniversityBeijing100191China

Rail weld irregularities are one of the primary excitation sources for vehicle-track interaction dynamics in modern high-speed *** can cause significant wheel-rail dynamic interactions,leading to wheel-rail noise,component damage,and *** researchers have employed the vehicle-track interaction dynamic model to study the dynamic interactions between wheel and rail induced by rail weld geometry ***,the cosine wave model used to simulate rail weld irregularities mainly focuses on the maximum value and neglects the geometric *** this study,novel theoretical models were developed for three categories of rail weld irregularities,based on measurements of the high-speed railway from beijing to *** vertical dynamic forces in the time and frequency domains were compared under different running *** forces generated by the rail weld irregularities that were measured and modeled,respectively,were compared to validate the accuracy of the proposed ***,based on the numerical study,the impact force due to rail weld irrregularity is modeled using an Artificial Neural Network(ANN),and the optimum combination of parameters for this model is *** results showed that the proposed model provided a more accurate wheel/rail dynamic evaluation caused by rail weld irregularities than that established in the *** ANN model used in this paper can effectively predict the impact force due to rail weld irrregularity while reducing the computation time.

关键词： Rail weld irregularity high-speed railway vehicle-track coupled dynamics wheel/rail dynamic vertical force artificial neural networks

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MXene Hybridized Polymer with Enhanced Electromagnetic Energy Harvest for Sensitized Microwave Actuation and Self‑Powered Motion Sensing

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Nano-Micro Letters 2025年第3期17卷 265-279页

作者： Yu‑Ze Wang Yu‑Chang Wang Ting‑Ting Liu Quan‑Liang Zhao Chen‑Sha Li Mao‑Sheng Cao School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081People’s Republic of China School of Materials Science and Engineering Peking UniversityBeijing 100871People’s Republic of China School of Mechanical and Material Engineering North China University of TechnologyBeijing 100144People’s Republic of China Key Laboratory of Functional Inorganic Material Chemistry Ministry of Education of the People’s Republic of ChinaHeilongjiang UniversityHarbin 150080People’s Republic of China

Polymeric microwave actuators combining tissue-like softness with programmablemicrowave-responsive deformation hold great promise for mobile intelligentdevices and bionic soft robots. However, their application is challenged by restricted electromagneticsensitivity and intricate sensing coupling. In this study, a sensitized polymericmicrowave actuator is fabricated by hybridizing a liquid crystal polymer with Ti3C2Tx(MXene). Compared to the initial counterpart, the hybrid polymer exhibits unique spacechargepolarization and interfacial polarization, resulting in significant improvements of230% in the dielectric loss factor and 830% in the apparent efficiency of electromagneticenergy harvest. The sensitized microwave actuation demonstrates as the shortenedresponse time of nearly 10 s, which is merely 13% of that for the initial shape memory polymer. Moreover, the ultra-low content of MXene (upto 0.15 wt%) benefits for maintaining the actuation potential of the hybrid polymer. An innovative self-powered sensing prototype that combinesdriving and piezoelectric polymers is developed, which generates real-time electric potential feedback (open-circuit potential of ~ 3 mV) duringactuation. The polarization-dominant energy conversion mechanism observed in the MXene-polymer hybrid structure furnishes a new approachfor developing efficient electromagnetic dissipative structures and shows potential for advancing polymeric electromagnetic intelligent devices.

关键词： Microwave absorption Electromagnetic response Energy harvest Self-sensing Soft actuator

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Negative PO3-implanted bionic ion transport channels for promoting Li-S battery

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Science China Chemistry 2025年

作者： Wenhuan Huang Shun Wang Xuehan Hou Yanan Zhang Xingxing Zhang Yaoxiao Zhao Xilang Jin Huabin Zhang Fei Wang Jian Zhang Key Laboratory of Chemical Additives for China National light industry College of Chemistry and Chemical EngineeringShaanxi University of Science and Technology School of Materials and Chemical Engineering Xi'an Technological University Chemistry Program Physical Science and Engineering Division King Abdullah University of Science and Technology State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences

Lithium-sulfur （Li-S） battery,as a promising next-generation high-energy-density battery,suffers from lithium polysulfides（LPSs） shuttle and Li dendrites *** crystalline framework-based membranes as separator can effectively absorb and restrain LPSs but without precise structural design principal exploration and mechanism ***,bio-inspired 1D oriented lithium-ion transport channels with molecular negatively charged PO3（-1） have been developed in hybrid tetrazole frameworks for promoting the transmission of Li+*** theoretical calculations and in situ spectroscopy demonstrated the higher binding energy and inhibited diffusion of LPSs in *** assembled PP@PO3Janus separator in Li-S coin cell delivered a high initial capacity of 1410.9 mAh g-1at 0.1 C and a low attenuation rate of 0.038%per cycle over 500 cycles at 5 ***,the high capacities of 862,542 and 409 mAh g-1based on high-sulfur-loading cathodes of 2.6,3.8 and 5.0 mg cm-2at0.5 C were achieved,***,the punch battery of PO3@PP separator with S-cathode of 1.2 mg cm-2has been developed for demonstrating its potentials commercial application,which displays impressive capacity of 873.4 mAh g-1with the retention of～78.9%over 50 cycles.

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