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  • Open Access

    ARTICLE

    Nonlinear Study on the Mechanical Performance of Built-Up Cold-Formed Steel Concrete-Filled Columns under Compression

    Oulfa Harrat1,*, Yazid Hadidane1, S. M. Anas2,*, Nadhim Hamah Sor3,4, Ahmed Farouk Deifalla5, Paul O. Awoyera6, Nadia Gouider1

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3435-3465, 2024, DOI:10.32604/cmes.2023.044950

    Abstract Given their numerous functional and architectural benefits, such as improved bearing capacity and increased resistance to elastic instability modes, cold-formed steel (CFS) built-up sections have become increasingly developed and used in recent years, particularly in the construction industry. This paper presents an analytical and numerical study of assembled CFS two single channel-shaped columns with different slenderness and configurations (back-to-back, face-to-face, and box). These columns were joined by double-row rivets for the back-to-back and box configurations, whereas they were welded together for the face-to-face design. The built-up columns were filled with ordinary concrete of good strength. Finite element models were applied,… More > Graphic Abstract

    Nonlinear Study on the Mechanical Performance of Built-Up Cold-Formed Steel Concrete-Filled Columns under Compression

  • Open Access

    ARTICLE

    A Fair and Trusted Trading Scheme for Medical Data Based on Smart Contracts

    Xiaohui Yang, Kun Zhang*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1843-1859, 2024, DOI:10.32604/cmc.2023.047660

    Abstract Data is regarded as a valuable asset, and sharing data is a prerequisite for fully exploiting the value of data. However, the current medical data sharing scheme lacks a fair incentive mechanism, and the authenticity of data cannot be guaranteed, resulting in low enthusiasm of participants. A fair and trusted medical data trading scheme based on smart contracts is proposed, which aims to encourage participants to be honest and improve their enthusiasm for participation. The scheme uses zero-knowledge range proof for trusted verification, verifies the authenticity of the patient’s data and the specific attributes of the data before the transaction,… More >

  • Open Access

    ARTICLE

    Robust and Trustworthy Data Sharing Framework Leveraging On-Chain and Off-Chain Collaboration

    Jinyang Yu1,2, Xiao Zhang1,2,3,*, Jinjiang Wang1,2, Yuchen Zhang1,2, Yulong Shi1,2, Linxuan Su1,2, Leijie Zeng1,2,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2159-2179, 2024, DOI:10.32604/cmc.2024.047340

    Abstract The proliferation of Internet of Things (IoT) systems has resulted in the generation of substantial data, presenting new challenges in reliable storage and trustworthy sharing. Conventional distributed storage systems are hindered by centralized management and lack traceability, while blockchain systems are limited by low capacity and high latency. To address these challenges, the present study investigates the reliable storage and trustworthy sharing of IoT data, and presents a novel system architecture that integrates on-chain and off-chain data manage systems. This architecture, integrating blockchain and distributed storage technologies, provides high-capacity, high-performance, traceable, and verifiable data storage and access. The on-chain system,… More >

  • Open Access

    ARTICLE

    Response Mechanisms to Flooding Stress in Mulberry Revealed by Multi-Omics Analysis

    Jingtao Hu1, Wenjing Chen1, Yanyan Duan1, Yingjing Ru1, Wenqing Cao1, Pingwei Xiang2, Chengzhi Huang2, Li Zhang2, Jingsheng Chen1, Liping Gan1,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 227-245, 2024, DOI:10.32604/phyton.2024.046521

    Abstract Abiotic stress, including flooding, seriously affects the normal growth and development of plants. Mulberry (Morus alba), a species known for its flood resistance, is cultivated worldwide for economic purposes. The transcriptomic analysis has identified numerous differentially expressed genes (DEGs) involved in submergence tolerance in mulberry plants. However, a comprehensive analyses of metabolite types and changes under flooding stress in mulberry remain unreported. A non-targeted metabolomic analysis utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS) was conducted to further investigate the effects of flooding stress on mulberry. A total of 1,169 metabolites were identified, with 331 differentially accumulated metabolites (DAMs) exhibiting up-regulation in… More >

  • Open Access

    ARTICLE

    Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System

    Laith Abualigah1,2,3,4,5,6,*, Serdar Ekinci7, Davut Izci7,8, Raed Abu Zitar9

    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 169-183, 2023, DOI:10.32604/iasc.2023.040291

    Abstract Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability. This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. Our approach outperforms existing optimization techniques on benchmark functions, and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision. Our study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and… More >

  • Open Access

    ARTICLE

    Placenta-derived mesenchymal stem cells attenuate secondary brain injury after controlled cortical impact in rats by inhibiting matrix metalloproteinases

    PING YANG1,2,3, YUANXIANG LAN1,2, ZHONG ZENG1,2, YAN WANG1,2, HECHUN XIA1,2,*

    BIOCELL, Vol.48, No.1, pp. 149-162, 2024, DOI:10.32604/biocell.2023.042367

    Abstract Background: As a form of biological therapy, placenta-derived mesenchymal stem cells (PDMSCs) exhibit considerable promise in addressing the complex pathological processes of traumaticbrain injury (TBI) due to their multi-target and multi-pathway mode of action. Material & Methods: This study investigates the protective mechanisms and benefits of PDMSCs in mitigating the effects of controlled cortical impact (CCI) in rats and glutamate-induced oxidative stress injury in HT22 cells in vitro. Our primary objective is to provide evidence supporting the clinical application of PDMSCs. Results: In the in vivo arm of our investigation, we observed a swift elevation of matrix metalloproteinase-9 (MMP-9) in… More > Graphic Abstract

    Placenta-derived mesenchymal stem cells attenuate secondary brain injury after controlled cortical impact in rats by inhibiting matrix metalloproteinases

  • Open Access

    ARTICLE

    A Blockchain-Based Access Control Scheme for Reputation Value Attributes of the Internet of Things

    Hongliang Tian, Junyuan Tian*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1297-1310, 2024, DOI:10.32604/cmc.2024.047058

    Abstract The Internet of Things (IoT) access control mechanism may encounter security issues such as single point of failure and data tampering. To address these issues, a blockchain-based IoT reputation value attribute access control scheme is proposed. Firstly, writing the reputation value as an attribute into the access control policy, and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control; Secondly, storing a large amount of resources from the Internet of Things in Inter Planetary File System (IPFS) to improve system throughput; Finally, map resource access… More >

  • Open Access

    ARTICLE

    Recommendation Method for Contrastive Enhancement of Neighborhood Information

    Hairong Wang, Beijing Zhou*, Lisi Zhang, He Ma

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 453-472, 2024, DOI:10.32604/cmc.2023.046560

    Abstract Knowledge graph can assist in improving recommendation performance and is widely applied in various personalized recommendation domains. However, existing knowledge-aware recommendation methods face challenges such as weak user-item interaction supervisory signals and noise in the knowledge graph. To tackle these issues, this paper proposes a neighbor information contrast-enhanced recommendation method by adding subtle noise to construct contrast views and employing contrastive learning to strengthen supervisory signals and reduce knowledge noise. Specifically, first, this paper adopts heterogeneous propagation and knowledge-aware attention networks to obtain multi-order neighbor embedding of users and items, mining the high-order neighbor information of users and items. Next,… More >

  • Open Access

    ARTICLE

    Network Configuration Entity Extraction Method Based on Transformer with Multi-Head Attention Mechanism

    Yang Yang1, Zhenying Qu1, Zefan Yan1, Zhipeng Gao1,*, Ti Wang2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 735-757, 2024, DOI:10.32604/cmc.2023.045807

    Abstract Nowadays, ensuring the quality of network services has become increasingly vital. Experts are turning to knowledge graph technology, with a significant emphasis on entity extraction in the identification of device configurations. This research paper presents a novel entity extraction method that leverages a combination of active learning and attention mechanisms. Initially, an improved active learning approach is employed to select the most valuable unlabeled samples, which are subsequently submitted for expert labeling. This approach successfully addresses the problems of isolated points and sample redundancy within the network configuration sample set. Then the labeled samples are utilized to train the model… More >

  • Open Access

    ARTICLE

    IndRT-GCNets: Knowledge Reasoning with Independent Recurrent Temporal Graph Convolutional Representations

    Yajing Ma1,2,3, Gulila Altenbek1,2,3,*, Yingxia Yu1

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 695-712, 2024, DOI:10.32604/cmc.2023.045486

    Abstract Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events, we propose an Independent Recurrent Temporal Graph Convolution Networks (IndRT-GCNets) framework to efficiently and accurately capture event attribute information. The framework models the knowledge graph sequences to learn the evolutionary representations of entities and relations within each period. Firstly, by utilizing the temporal graph convolution module in the evolutionary representation unit, the framework captures the structural dependency relationships within the knowledge graph in each period. Meanwhile, to achieve better event representation and establish effective correlations,… More >

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