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Tungsten 2025年第1期7卷 80-87页

作者： Fang-Qian Wang Yin Zhang Wei-Wei Wang Mei-Qian Fu Hong-Bing Mo Wei-Dong Yu Chao Liu Jun Yan college of Chemistry and Chemical engineering Central South University Junior Education Department Changsha Normal University School of science Hunan University of Technology and Business

Arsenic-vanadium polyoxometalates（POMs） represent a family of tremendous potential catalysts owing to their peculiar physical and chemical *** in CO2conversion,using POMs to catalyze the conversion of CO2and epoxide into chemical intermediates is the research ***,A new family number of arsenic-vanadium POMs,[N（CH3）4]4[As8V12O38（H2O）]·2H2O({As8V12O38}),was reported and characterized by single-crystal X-ray diffraction,fourier transform infrared spectroscopy,X-ray photoelectron spectroscopy,*** from other allotropicity,{As8V12O38}shows a different structure pattern with an I-43d *** obtained {As8V12O38} was employed as a catalyst for the *** initial catalytic reaction confirmed that {As8V12O38} can catalyze the formation of epoxy carbonate by using 1.01 kPa CO2and epoxide at 70℃.Furtherly,when added amine in the catalytic system,oxazolidinone could be obtained by high yields,which provides an efficient way to convert CO2into profitable ***,a possible catalytic reaction mechanism was proposed by using different characterization analyses.{As8V12O38} first catalyzes the epoxide and CO2to form an epoxy carbonate and then catalyzes epoxy carbonate and benzylamine into oxazolidinone.

关键词： Arsenic CO2 conversion Oxazolidinone Polyoxometalates Vanadium

An Efficient Boron Source Activation Strategy for the Low‑Temperature Synthesis of Boron Nitride Nanotubes

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Nano-Micro Letters 2025年第1期17卷 548-558页

作者： Ying Wang Kai Zhang Liping Ding Liyun Wu Songfeng E Qian He Nanyang Wang Hui Zuo Zhengyang Zhou Feng Ding Yue Hu Jin Zhang Yagang Yao National Laboratory of Solid State Microstructures College of Engineering and Applied SciencesJiangsu Key Laboratory of Artificial Functional Materialsand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093People’s Republic of China School of Electronic Information and Artificial Intelligence Shaanxi University of Science&TechnologyXian 710000People’s Republic of China college of Bioresources Chemical and Materials engineering Shaanxi University of Science&TechnologyXian 710000People’s Republic of China Key Laboratory of Carbon Materials of Zhejiang Province College of Chemistry and Materials EngineeringWenzhou UniversityWenzhou 325000People’s Republic of China Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518000People’s Republic of China college of Chemical and Molecular engineering Peking UniversityBeijing 100871People’s Republic of China

Lowering the synthesis temperature of boron nitride nanotubes(BNNTs)is crucial for their *** primary reason for adopting a high temperature is to enable the effective activation of highmelting-point solid *** this study,we developed a novel approach for efficiently activating boron by introducing alkali metal compounds into the conventional MgO–B *** approach can be adopted to form various low-melting-point AM–Mg–B–O growth *** growth systems have improved catalytic capability and reactivity even under low-temperature conditions,facilitating the synthesis of BNNTs at temperatures as low as 850℃.In addition,molecular dynamics simulations based on density functional theory theoretically demonstrate that the systems maintain a liquid state at low temperatures and interact with N atoms to form BN *** findings offer novel insights into the design of boron activation and are expected to facilitate research on the low-temperature synthesis of BNNTs.

关键词： Boron nitride nanotubes Low-temperature Boron activation Density functional theory

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Magneto‑Dielectric Synergy and Multiscale Hierarchical Structure Design Enable Flexible Multipurpose Microwave Absorption and Infrared Stealth Compatibility

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Nano-Micro Letters 2025年第2期17卷 401-416页

作者： Chen Li Leilei Liang Baoshan Zhang Yi Yang Guangbin Ji School of Electronic science and engineering Nanjing UniversityNanjing 210093People’s Republic of China college of Materials science and Technology Nanjing University of Aeronautics and AstronauticsNanjing 210016People’s Republic of China

Developing advanced stealth devices to cope with radar-infrared(IR)fusion detection and diverse application scenarios is increasingly demanded,which faces significant challenges due to conflicting microwave and IR cloaking mechanisms and functional integration ***,we propose a multiscale hierarchical structure design,integrating wrinkled MXene IR shielding layer and flexible Fe_(3)O_(4)@C/PDMS microwave absorption *** top wrinkled MXene layer induces the intensive diffuse reflection effect,shielding IR radiation signals while allowing microwave to pass ***,the permeable microwaves are assimilated into the bottom Fe_(3)O_(4)@C/PDMS layer via strong magneto-electric *** theoretical and experimental optimization,the assembled stealth devices realize a near-perfect stealth capability in both X-band(8–12 GHz)and long-wave infrared(8–14μm)wavelength ***,it delivers a radar cross-section reduction of−20 dB m^(2),a large apparent temperature modulation range(ΔT=70℃),and a low average IR emissivity of ***,the optimal device demonstrates exceptional curved surface conformability,self-cleaning capability(contact angle≈129°),and abrasion resistance(recovery time≈5 s).This design strategy promotes the development of multispectral stealth technology and reinforces its applicability and durability in complex and hostile environments.

关键词： Microwave absorption Radar-infrared compatible stealth Wrinkled MXene Magneto-dielectric synergy Multifunction

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Hybrid Deep Learning Approach for Automating App Review Classification:Advancing Usability Metrics Classification with an Aspect-Based Sentiment Analysis Framework

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Computers, Materials & Continua 2025年第1期82卷 949-976页

作者： Nahed Alsaleh Reem Alnanih Nahed Alowidi Department of Computer science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer science College of Computer Science and EngineeringUniversity of HailHail81451Saudi Arabia

App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their *** the analysis of these reviews is vital for efficient review *** traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior *** research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and *** propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification *** analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,*** contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews *** advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.

关键词： Requirements engineering(RE) app review analysis usabilitymetrics hybrid deep learning BERT-BiLSTM-CNN

Advancements in Liver Tumor Detection:A Comprehensive Review of Various Deep Learning Models

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Computer Modeling in engineering & sciences 2025年第1期142卷 91-122页

作者： Shanmugasundaram Hariharan D.Anandan Murugaperumal Krishnamoorthy Vinay Kukreja Nitin Goyal Shih-Yu Chen Deptartment of Artificial Intelligence and Data science Vardhaman College of EngineeringHyderabad501218India Deptartment of CSE V.S.B College of EngineeringKarur639111India Deptartment of Electrical and Electronics engineering Vardhaman College of EngineeringHyderabad501218India Centre for Research Impact&Outcome Chitkara UniversityRajpura140401PunjabIndia Department of Computer science and engineering School of Engineering and TechnologyCentral University of HaryanaMahendergarh123031HaryanaIndia Department of Computer science and Information engineering National Yunlin University of Science and TechnologyYunlin64002Taiwan Intelligence Recognition Industry Service Research Center National Yunlin University of Science and TechnologyYunlin64002Taiwan

Liver cancer remains a leading cause of mortality worldwide,and precise diagnostic tools are essential for effective treatment *** Tumors(LTs)vary significantly in size,shape,and location,and can present with tissues of similar intensities,making automatically segmenting and classifying LTs from abdominal tomography images crucial and *** review examines recent advancements in Liver Segmentation(LS)and Tumor Segmentation(TS)algorithms,highlighting their strengths and limitations regarding precision,automation,and *** metrics are utilized to assess key detection algorithms and analytical methods,emphasizing their effectiveness and relevance in clinical *** review also addresses ongoing challenges in liver tumor segmentation and identification,such as managing high variability in patient data and ensuring robustness across different imaging *** suggests directions for future research,with insights into technological advancements that can enhance surgical planning and diagnostic accuracy by comparing popular *** paper contributes to a comprehensive understanding of current liver tumor detection techniques,provides a roadmap for future innovations,and improves diagnostic and therapeutic outcomes for liver cancer by integrating recent progress with remaining challenges.

关键词： Liver tumor detection liver tumor segmentation image processing liver tumor diagnosis feature extraction tumor classification deep learning machine learning

A Cross Attention Transformer-Mixed Feedback Video Recommendation Algorithm Based on DIEN

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Computers, Materials & Continua 2025年第1期82卷 977-996页

作者： Jianwei Zhang Zhishang Zhao Zengyu Cai Yuan Feng Liang Zhu Yahui Sun college of Software engineering Zhengzhou University of Light IndustryZhengzhou450000China Faculty of Information engineering Xuchang Vocational Technical CollegeXuchang461000China college of Computer science and Technology Zhengzhou University of Light IndustryZhengzhou450000China college of Electronics and Information Zhengzhou University of Light IndustryZhengzhou450000China

The rapid development of short video platforms poses new challenges for traditional recommendation *** systems typically depend on two types of user behavior feedback to construct user interest profiles:explicit feedback(interactive behavior),which significantly influences users’short-term interests,and implicit feedback(viewing time),which substantially affects their long-term ***,the previous model fails to distinguish between these two feedback methods,leading it to predict only the overall preferences of users based on extensive historical behavior ***,it cannot differentiate between users’long-term and shortterm interests,resulting in low accuracy in describing users’interest states and predicting the evolution of their *** paper introduces a video recommendationmodel calledCAT-MFRec(CrossAttention Transformer-Mixed Feedback Recommendation)designed to differentiate between explicit and implicit user feedback within the DIEN(Deep Interest Evolution Network)*** study emphasizes the separate learning of the two types of behavioral feedback,effectively integrating them through the cross-attention ***,it leverages the long sequence dependence capabilities of Transformer technology to accurately construct user interest profiles and predict the evolution of user *** results indicate that CAT-MF Rec significantly outperforms existing recommendation methods across various performance *** advancement offers new theoretical and practical insights for the development of video recommendations,particularly in addressing complex and dynamic user behavior patterns.

关键词： Video recommendation user interest cross-attention transformer

Targets capture by distributed active swarms via bio-inspired reinforcement learning

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science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology college of Automation engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

An NIR-Ⅱ-emissive Ru(Ⅱ) metallacycle for efficient and safe immunotherapy

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science China Chemistry 2025年第1期68卷 5-7页

作者： Chonglu Li Jianbo Zhan Biao Dong Institute of Health Inspection and Testing Hubei Provincial Center for Disease Control and Prevention State Key Laboratory on Integrated Optoelectronics College of Electronic Science and Engineering Jilin University

Immunotherapy, as a groundbreaking cancer treatment, has gained considerable attention for its utilization of the body’s immune system to combat tumors [1]. This therapy induces tumor cell apoptosis, triggering a sustained anti-tumor immune response and effectively preventing tumor recurrence and metastasis [2]. The fundamental principle lies in inducing tumor cell death through specific treatment modalities, leading to the release of a cascade of signaling molecules and antigens, thereby mobilizing the immune system to actively identify and attack tumor cells [3].

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Manufacture the conducting polymer with light

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science China Chemistry 2025年第1期68卷 8-9页

作者： Yang Li Tianyu Li Yan Ji Baoguang Liu college of Electronic and Optical engineering & college of Flexible Electronics (Future Technology) Nanjing University of Posts & Telecommunications

Poly(3,4-ethylenedioxythiophene) (PEDOT), heralded as the “king” of conducting polymers, is esteemed in bioelectronics for its mixed electronic and ionic conductivity, mechanical properties compatible with biological tissues, tunable healing ability and stability in diverse environments [1]. Based on additive manufacturing of three-dimensional structures,PEDOT realizes the implementation in the efficient production of flexible bioelectronics, the construction of intricate electrode-neural implantations, and the development of smart brain-computer-interfaces [2].

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Defect engineering with Rational Dopants Modulation for High‑Temperature Energy Harvesting in Lead‑Free Piezoceramics

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Nano-Micro Letters 2025年第3期17卷 87-101页

作者： Kaibiao Xi Jianzhe Guo Mupeng Zheng Mankang Zhu Yudong Hou Key Laboratory of Advanced Functional Materials Ministry of EducationCollege of Materials Science and EngineeringBeijing University of TechnologyBeijing 100124People’s Republic of China

High temperature piezoelectric energy harvester(HTPEH)is an important solution to replace chemical battery to achieve independent power supply of HT wireless ***,simultaneously excellent performances,including high figure of merit(FOM),insulation resistivity(ρ)and depolarization temperature(Td)are indispensable but hard to achieve in lead-free piezoceramics,especially operating at 250°C has not been reported ***,well-balanced performances are achieved in BiFeO3–BaTiO3 ceramics via innovative defect engineering with respect to delicate manganese *** to the synergistic effect of enhancing electrostrictive coefficient by polarization configuration optimization,regulating iron ion oxidation state by high valence manganese ion and stabilizing domain orientation by defect dipole,comprehensive excellent electrical performances(Td=340°C,ρ250°C>10^(7)Ωcm and FOM_(250°C)=4905×10^(–15)m^(2)N^(−1))are realized at the solid solubility limit of manganese *** HT-PEHs assembled using the rationally designed piezoceramic can allow for fast charging of commercial electrolytic capacitor at 250°C with high energy conversion efficiency(η=11.43%).These characteristics demonstrate that defect engineering tailored BF-BT can satisfy high-end HT-PEHs requirements,paving a new way in developing selfpowered wireless sensors working in HT environments.

关键词： Lead-free piezoceramic Defect engineering Dopants modulation High-temperature Piezoelectric energy harvester

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