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MICROSTRUCTURE AND PROPERTIES Of Zl201 AllOY OBTAINED BY NEAR-lIQUIDUS ElECTROMAGNETIC CASTING

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Acta Metallurgica Sinica(English letters) 2005年第5期18卷 653-658页

作者： P. wang l.f. Shi G.M. lu J.Z. Cui The Key laboratory of Electromagnetic Processing of Material Ministry of Education Northeastern University Shenyang 110004 China

The microstructures of Zl201 alloy slurry prepared by near-liquidus electromagnetic casting （NlEMC）, electromagnetic casting（EMC）, and near-liquidus casting（NlC） were investigated by means of electron microscopy and image analysis. Mechanical properties of as-cast alloys were determined. The results show that the NlEMC induces a fine, uniform, and equiaxed grain structure with a mean equal-area-circle grain diameter of 32.8μm. The as-cast aUoy has a hardness of HV122.8 and a tensite strength of 368MPa. Both of them are betterthan those of the alloys prepared by EMC and by NlC. The mechanism of grain refinement in the NlEMC alloy slurry was discussed.

关键词： near-liquidus casting electromagnetic casting rheocasting,microstructure property

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Robot navigation system using intrinsic evolvable hardware

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 261-266页

作者： TAN K C, lEE T H, RUK X, wang l f, lIU X (Dept. of Electrical and Computer Engineering, National University of Singapore, Singapore 119260) Dept. of Elec. and Comp. Eng. Natl. Univ. of Singapore Singapore 119260 Singapore

Recently there has been great interest in the idea that evolvable system based on the principle of artifcial intelligence can be used to continuously and autonomously adapt the behaviour of physically embedded systems such as autonomous mobile robots and intelligent home devices. Meanwhile, we have seen the introduction of evolvable hardware(EHW): new integrated electronic circuits that are able to continuously evolve to adapt the chages in the environment implemented by evolutionary algorithms such as genetic algorithm(GA) and reinforcement learning. This paper concentrates on developing a robotic navigation system whose basic behaviours are obstacle avoidance and light source navigation. The results demonstrate that the intrinsic evolvable hardware system is able to create the stable robotiiuc behaviours as required in the real world instead of the traditional hardware systems.

关键词： genetic algorithm autonomous mobile robot boolean function controller intrinsic evolvable hardware

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Rational modulation of fluorophosphate cathode by anionic groups to reduce the polarization behavior for fast-charging sodium-ion batteries

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Journal of Energy Chemistry 2025年第1期100卷 509-521页

作者： Xinyuan wang fan Zhang Xingyu Zhou Qian wang Changyu liu Yangyang liu Hui wang Xiaojie liu Key laboratory of Synthetic and Natural functional Molecule of the Ministry of Education College of Chemistry & Materials Science Northwest University

Na3V2（PO4）2O2f （VP） is recognized as a promising cathode material for sodium-ion batteries due to its stable structural framework and high specific *** functional theory （DfT） and finite element simulations show that incorporating SO42-into VP decreases its band gap,lowers the migration energy barrier,and ensures a uniform Na+concentration gradient and stress distribution during charge and discharge ***,the average Na+diffusion coefficient of Na3V2（PO4）1.95（SO4）0.05O2f（VPS-1） is roughly double that of VP,leading to enhanced rate capability (80 C,75.5 mAh g-1) and cycling stability (111.0 mAh g-1capacity after 1000 cycles at 10 C current density) for ***-1 exhibits outstanding fast-charging capabilities,achieving an 80%state of charge in just 8.1 *** assembled VPS-1//SbSn/NPC full cell demonstrated stable cycling over 200 cycles at a high 5 C current,maintaining an average coulombic efficiency of 95.35%.

关键词： Anionic group modulation Polarization behavior fast-charging Sodium-ion battery fluorophosphate Cathode

AI-Enhanced Secure Data Aggregation for Smart Grids with Privacy Preservation

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Computers, Materials & Continua 2025年第1期82卷 799-816页

作者： Congcong wang Chen wang Wenying Zheng Wei Gu School of Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information Science and Engineering Zhejiang Sci-Tech UniversityHangzhou310018China State Key laboratory of Public Big Data Guizhou UniversityGuiyang550025China School of Computer Science and Technology(School of Artificial Intelligence) Zhejiang Sci-Tech UniversityHangzhou310018China School of Computer Science(School of Cyber Science and Engineering) Nanjing University of Information Science and TechnologyNanjing210044China

As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy *** research emphasizes data security and user privacy concerns within smart ***,existing methods struggle with efficiency and security when processing large-scale *** efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent *** paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data *** approach optimizes data preprocessing,integrates long Short-Term Memory(lSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user *** also explores the application of Boneh lynn Shacham(BlS)signatures for user *** proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.

关键词： Smart grid data security privacy protection artificial intelligence data aggregation

Continuous edge chromatic numbers of abelian group actions

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Science China Mathematics 2025年

作者： Su Gao Ruijun wang Tianhao wang School of Mathematical Sciences and laboratory of Pure Mathematics and Combinatorics Nankai University

We prove that for any generating set S of Z~n, the continuous edge chromatic number χ′c（G） of the Schreier graph of the Bernoulli shift action G = f(S, 2Z~n) is χ′（G） + 1 = |S| + 1. In particular, for the stan...

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Hsa-miR-214-3p inhibits breast cancer cell growth and improves the tumor immune microenvironment by downregulating B7H3

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Oncology research 2025年第1期33卷 103-121页

作者： Yan lu Kang wang Yuanhong Peng Meng Chen lin Zhong luji Huang f U Cheng Xindan Sheng Xin Yang Manzhao Ouyang George A Calin Zhiwei He China-America Cancer Research Institute Guangdong Medical University Dongguan 523808 China. GCP Center Shunde Hospital Southern Medical University (The First People's Hospital of Shunde Foshan) Shunde 528300 China. Department of Gastrointestinal Surgery Shunde Hospital Southern Medical University (The First People's Hospital of Shunde Foshan) Shunde 528300 China. The Second School of Clinical Medicine Southern Medical University Guangzhou 510080 China. Department of Translational Molecular Pathology The University of Texas MD Anderson Cancer Center Houston TX 77030 USA. Department of Oncology Shunde Hospital Southern Medical University (The First People's Hospital of Shunde Foshan) Shunde 528300 China.

Background:Immune checkpoint inhibitors play an important role in the treatment of solid tumors, but the currently used immune checkpoint inhibitors targeting programmed cell death-1 (PD-1), programmed cell death ligand-1 (PD-l1), and cytotoxic T-lymphocyte antigen-4 (CTlA-4) show limited clinical efficacy in many breast cancers. B7H3 has been widely reported as an immunosuppressive molecule, but its immunological function in breast cancer patients remains unclear.Methods:We analyzed the expression of B7H3 in breast cancer samples using data from the Cancer Genome Atlas Program (TCGA) and the Gene Expression Omnibus (GEO) databases. MicroRNAs were selected using the TarBase, miRTarBase, and miRBase databases. The regulatory role of the microRNA hsa-miR-214-3p on B7H3 was investigated through dual-luciferase reporter assays, which identified the specific action sites of interaction. The expression levels of B7H3 and hsa-miR-214-3p in human breast cancer tissues and adjacent normal tissues were quantified using Western blotting and quantitative PCR (qPCR). experiments were performed to observe the effects of modulating the expression of B7H3 or hsa-miR-214-3p on breast cancer cell proliferation and apoptosis. Additionally, the regulatory impact of hsa-miR-214-3p on B7H3 was examined. Enzyme-linked immunosorbent assays (ElISA) and flow cytometry were employed to assess the effects of co-cultured breast cancer cells and normal human peripheral blood mononuclear cells (PBMCs) on immune cells and associated cytokines.Results:In breast cancer tissues, the expression level of B7H3 is inversely correlated with that of hsa-miR-214-3p, as well as with the regulatory effects on breast cancercell behavior. Hsa-miR-214-3p was found to inhibit breast cancer cell growth by downregulating B7H3. Importantly, our research identified, for the first time, two binding sites for hsa-miR-214-3p on the 3' UTR of B7H3, both of which exert similar effects independently. Co-culture experime

关键词： B7H3 Breast cancer Hsa-miR-214-3p Immunotherapy

Anomaly Detection of Controllable Electric Vehicles through Node Equation against Aggregation Attack

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Computers, Materials & Continua 2025年第1期82卷 427-442页

作者： Jing Guo Ziying wang Yajuan Guo Haitao Jiang State Grid Jiangsu Electric Power Co. Ltd.Research InstituteState Grid Corporation of ChinaNanjing211100China

The rapid proliferation of electric vehicle(EV)charging infrastructure introduces critical cybersecurity vulnerabilities to power grids *** study presents an innovative anomaly detection framework for EV charging stations,addressing the unique challenges posed by third-party aggregation *** approach integrates node equations-based on the parameter identification with a novel deep learning model,xDeepCIN,to detect abnormal data reporting indicative of aggregation *** employ a graph-theoretic approach to model EV charging networks and utilize Markov Chain Monte Carlo techniques for accurate parameter *** xDeepCIN model,incorporating a Compressed Interaction Network,has the ability to capture complex feature interactions in sparse,high-dimensional charging *** results on both proprietary and public datasets demonstrate significant improvements in anomaly detection performance,with f1-scores increasing by up to 32.3%for specific anomaly types compared to traditional methods,such as wide&deep and DeepfM(factorization-Machine).Our framework exhibits robust scalability,effectively handling networks ranging from 8 to 85 charging ***,we achieve real-time monitoring capabilities,with parameter identification completing within seconds for networks up to 1000 *** research contributes to enhancing the security and reliability of renewable energy systems against evolving cyber threats,offering a comprehensive solution for safeguarding the rapidly expanding EV charging infrastructure.

关键词： Anomaly detection electric vehicle aggregation attack deep cross-network

Controlled cationic ring-opening polymerization of l-lactide by organic ion pair: novel approach to isotactic-rich and crystalline polylactide

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Science China Chemistry 2025年第1期 394-402页

作者： Zhiqiang Ding Mingqian wang Zijing Zhou Bin wang Yuesheng li Tianjin Key laboratory of Composite & functional Materials School of Materials Science and Engineering Tianjin University

living/controlled cationic ring-opening polymerization （ROP） of l-lactide is a promising approach to isotactic-rich and crystalline poly（l-lactide）.In contrast with the unsubstituted lactones,l-lA can not be polymerized by organic lewis acids or carbenium ions,and the state of the art in this field is the cationic ROP of l-lA catalyzed by Br?nsted acid/alcohol system via activated monomer ***,we reported the first example of controlled cationic ROP of l-lA by using Meerweintype ion pair[Me3O]+[B（C6f5）4]-as the catalyst.[Me3O]+[B（C6f5）4]-promoted rapid l-lA cationic polymerization in the absence of alcohol,producing isotactic-rich and crystalline PllA without transesterification and epimerization side *** activated chain end mechanism,involving twice SN2 substitution and configuration-inversion （S→R→S） with the assistance of released Me2O,was proposed and further verified by density functional theory and control *** work expands the catalytic toolbox of isotactic-rich and crystalline polylactide *** represents a unique example of cationic-controlled polymerization of l-lA catalyzed by an organic ion pair.

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DDoS Attack Autonomous Detection Model Based on Multi-Strategy Integrate Zebra Optimization Algorithm

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Computers, Materials & Continua 2025年第1期82卷 645-674页

作者： Chunhui li Xiaoying wang Qingjie Zhang Jiaye liang Aijing Zhang School of Information Engineering Institute of Disaster PreventionLangfang065201China langfang Key laboratory of Network Emergency Protection and Network Security Langfang065201China

Previous studies have shown that deep learning is very effective in detecting known ***,when facing unknown attacks,models such as Deep Neural Networks(DNN)combined with long Short-Term Memory(lSTM),Convolutional Neural Networks(CNN)combined with lSTM,and so on are built by simple stacking,which has the problems of feature loss,low efficiency,and low ***,this paper proposes an autonomous detectionmodel for Distributed Denial of Service attacks,Multi-Scale Convolutional Neural Network-Bidirectional Gated Recurrent Units-Single Headed Attention(MSCNN-BiGRU-SHA),which is based on a Multistrategy Integrated Zebra Optimization Algorithm(MI-ZOA).The model undergoes training and testing with the CICDDoS2019 dataset,and its performance is evaluated on a new GINKS2023 *** hyperparameters for Conv_filter and GRU_unit are optimized using the Multi-strategy Integrated Zebra Optimization Algorithm(MIZOA).The experimental results show that the test accuracy of the MSCNN-BiGRU-SHA model based on the MIZOA proposed in this paper is as high as 0.9971 in the CICDDoS 2019 *** evaluation accuracy of the new dataset GINKS2023 created in this paper is *** to the MSCNN-BiGRU-SHA model based on the Zebra Optimization Algorithm(ZOA),the detection accuracy on the GINKS2023 dataset has improved by 5.81%,precisionhas increasedby 1.35%,the recallhas improvedby 9%,and thef1scorehas increasedby 5.55%.Compared to the MSCNN-BiGRU-SHA models developed using Grid Search,Random Search,and Bayesian Optimization,the MSCNN-BiGRU-SHA model optimized with the MI-ZOA exhibits better performance in terms of accuracy,precision,recall,and f1 score.

关键词： Distributed denial of service attack intrusion detection deep learning zebra optimization algorithm multi-strategy integrated zebra optimization algorithm