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  • Open Access

    REVIEW

    GNN: Core Branches, Integration Strategies and Applications

    Wenfeng Zheng1, Guangyu Xu2, Siyu Lu3, Junmin Lyu4, Feng Bao5,*, Lirong Yin6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.075741 - 29 January 2026

    Abstract Graph Neural Networks (GNNs), as a deep learning framework specifically designed for graph-structured data, have achieved deep representation learning of graph data through message passing mechanisms and have become a core technology in the field of graph analysis. However, current reviews on GNN models are mainly focused on smaller domains, and there is a lack of systematic reviews on the classification and applications of GNN models. This review systematically synthesizes the three canonical branches of GNN, Graph Convolutional Network (GCN), Graph Attention Network (GAT), and Graph Sampling Aggregation Network (GraphSAGE), and analyzes their integration pathways More >

  • Open Access

    ARTICLE

    Real-Time Mouth State Detection Based on a BiGRU-CLPSO Hybrid Model with Facial Landmark Detection for Healthcare Monitoring Applications

    Mong-Fong Horng1,#, Thanh-Lam Nguyen1,#, Thanh-Tuan Nguyen2,*, Chin-Shiuh Shieh1,*, Lan-Yuen Guo3, Chen-Fu Hung4, Chun-Chih Lo1

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.075064 - 29 January 2026

    Abstract The global population is rapidly expanding, driving an increasing demand for intelligent healthcare systems. Artificial intelligence (AI) applications in remote patient monitoring and diagnosis have achieved remarkable progress and are emerging as a major development trend. Among these applications, mouth motion tracking and mouth-state detection represent an important direction, providing valuable support for diagnosing neuromuscular disorders such as dysphagia, Bell’s palsy, and Parkinson’s disease. In this study, we focus on developing a real-time system capable of monitoring and detecting mouth state that can be efficiently deployed on edge devices. The proposed system integrates the Facial… More >

  • Open Access

    ARTICLE

    Noninvasive Radar Sensing Augmented with Machine Learning for Reliable Detection of Motor Imbalance

    Faten S. Alamri1, Adil Ali Saleem2, Muhammad I. Khan3, Hafeez Ur Rehman Siddiqui2, Amjad Rehman3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074679 - 29 January 2026

    Abstract Motor imbalance is a critical failure mode in rotating machinery, potentially causing severe equipment damage if undetected. Traditional vibration-based diagnostic methods rely on direct sensor contact, leading to installation challenges and measurement artifacts that can compromise accuracy. This study presents a novel radar-based framework for non-contact motor imbalance detection using 24 GHz continuous-wave radar. A dataset of 1802 experimental trials was sourced, covering four imbalance levels (0, 10, 20, 30 g) across varying motor speeds (500–1500 rpm) and load torques (0–3 Nm). Dual-channel in-phase and quadrature radar signals were captured at 10,000 samples per second… More >

  • Open Access

    ARTICLE

    Mechanically Stable, Thermodynamic, Photo-Catalytic and Ferromagnetic Characteristic of Ferrites Al2Mn(S/Se)4 for Energy Storage Applications: DFT-Calculations

    Hosam O. Elansary1, Naveed A. Noor2, Syed M. Ahmad3, Humza Riaz3, Sohail Mumtaz4,*

    Chalcogenide Letters, Vol.23, No.1, 2026, DOI:10.32604/cl.2026.076592 - 26 January 2026

    Abstract Ferrites are remarkable compounds for energy harvesting and spintronic applications. For this purpose, mechanically stable, thermodynamic, photo-catalytic, and ferromagnetic characteristics of ferrites Al2Mn(S/Se)4 have been investigated significantly using PBEsol-GGA and modified Becke Johnson potential (TB-mBJ). In order to determine structural stability, we calculate formation energy (Ef) and Born stability criteria that confirm the structural stability of the Al2Mn(S/Se)4. 2D and 3D plots of Poisson’s ratio (υ) and linear compressibility are also used to indicate the stability of these materials. Additionally, thermodynamic characteristics reveal that both ferrites are stable. Spin-polarized electronic properties indicate that both ferrites are ferromagnetic More >

  • Open Access

    REVIEW

    Recent Advances in Hydrothermal Carbonization of Biomass: The Role of Process Parameters and the Applications of Hydrochar

    Cheng Zhang, Rui Zhang, Yu Shao, Jiabin Wang, Qianyue Yang, Fang Xie, Rongling Yang, Hongzhen Luo*

    Journal of Renewable Materials, Vol.14, No.1, 2026, DOI:10.32604/jrm.2025.02025-0157 - 23 January 2026

    Abstract Biomass is a resource whose organic carbon is formed from atmospheric carbon dioxide. It has numerous characteristics such as low carbon emissions, renewability, and environmental friendliness. The efficient utilization of biomass plays a significant role in promoting the development of clean energy, alleviating environmental pressures, and achieving carbon neutrality goals. Among the numerous processing technologies of biomass, hydrothermal carbonization (HTC) is a promising thermochemical process that can decompose and convert biomass into hydrochar under relatively mild conditions of approximately 180°C–300°C, thereby enabling its efficient resource utilization. In addition, HTC can directly process feedstocks with high… More >

  • Open Access

    REVIEW

    Cancer-Associated Fibroblasts in Prostate Cancer: Unraveling Mechanisms and Therapeutic Implications

    Yang Wu1,#,*, Dong Xu1,#, Run Shi1, Mingwei Zhan2, Shaohui Xu3, Xin Wang4, Jianpeng Zhang5, Zhaokai Zhou6, Weizhuo Wang7, Yongjie Wang8, Minglun Li9, Zihao Xu10,*, Kaifeng Su11,*

    Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.073265 - 19 January 2026

    Abstract Prostate cancer (PCa) remains a major cause of cancer-related mortality in men, largely due to therapy resistance and metastatic progression. Increasing evidence highlights the tumor microenvironment (TME), particularly cancer-associated fibroblasts (CAFs), as a critical determinant of disease behavior. CAFs constitute a heterogeneous population originating from fibroblasts, mesenchymal stem cells, endothelial cells, epithelial cells undergoing epithelial–mesenchymal transition (EMT), and adipose tissue. Through dynamic crosstalk with tumor, immune, endothelial, and adipocyte compartments, CAFs orchestrate oncogenic processes including tumor proliferation, invasion, immune evasion, extracellular matrix remodeling, angiogenesis, and metabolic reprogramming. This review comprehensively summarizes the cellular origins, phenotypic More >

  • Open Access

    REVIEW

    Progression on Mechanism and Therapeutic Implications of Neddylation in Lung Cancer

    Jiayu Zou1,2,3, Yajie Lu3, Jiaqi Li3, Zhaokai Zhou4,5, Fu Peng3, Pu Qiu2,*, Hailin Tang6, Cheng Peng1,*

    Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.071940 - 19 January 2026

    Abstract Lung cancer is the most common but fatal malignant tumor worldwide. Patients with lung cancer experienced a relatively low 5-year overall survival rate, and issues such as metastasis and drug resistance remain prominent challenges in its clinical management. Neddylation, a novel type of post-translational modification, was overactivated in lung cancer and was closely associated with its occurrence, development, metastasis, and drug resistance. This review systematically summarizes the biological process of neddylation and deeply explores the latest research progress on how neddylation affects lung cancer cell proliferation, metastasis, and drug resistance mechanisms, with a focus on More >

  • Open Access

    ARTICLE

    Machine Learning Based Simulation, Synthesis, and Characterization of Zinc Oxide/Graphene Oxide Nanocomposite for Energy Storage Applications

    Tahir Mahmood1,*, Muhammad Waseem Ashraf1,*, Shahzadi Tayyaba2, Muhammad Munir3, Babiker M. A. Abdel-Banat3, Hassan Ali Dinar3

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072436 - 12 January 2026

    Abstract Artificial intelligence (AI) based models have been used to predict the structural, optical, mechanical, and electrochemical properties of zinc oxide/graphene oxide nanocomposites. Machine learning (ML) models such as Artificial Neural Networks (ANN), Support Vector Regression (SVR), Multilayer Perceptron (MLP), and hybrid, along with fuzzy logic tools, were applied to predict the different properties like wavelength at maximum intensity (444 nm), crystallite size (17.50 nm), and optical bandgap (2.85 eV). While some other properties, such as energy density, power density, and charge transfer resistance, were also predicted with the help of datasets of 1000 (80:20). In… More >

  • Open Access

    ARTICLE

    A REST API Fuzz Testing Framework Based on GUI Interaction and Specification Completion

    Zonglin Li1,#, Xu Zhao2,#, Yan Cao2,*, Yazhe Li3, Yihong Zhang1

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071511 - 12 January 2026

    Abstract With the rapid development of Internet technology, REST APIs (Representational State Transfer Application Programming Interfaces) have become the primary communication standard in modern microservice architectures, raising increasing concerns about their security. Existing fuzz testing methods include random or dictionary-based input generation, which often fail to ensure both syntactic and semantic correctness, and OpenAPI-based approaches, which offer better accuracy but typically lack detailed descriptions of endpoints, parameters, or data formats. To address these issues, this paper proposes the APIDocX fuzz testing framework. It introduces a crawler tailored for dynamic web pages that automatically simulates user interactions More >

  • Open Access

    REVIEW

    Circulating Tumor DNA in Cervical Cancer: Clinical Utility and Medico-Legal Perspectives

    Abdulrahman K. Sinno1, Aisha Mustapha1, Navya Nair1, Simona Zaami2, Lina De Paola2, Valentina Billone3, Eleonora Conti3, Giuseppe Gullo3,*, Pasquale Patrizio4

    Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.072176 - 30 December 2025

    Abstract Cervical cancer related to human papillomavirus (HPV) is a leading cause of cancer-related mortality among women worldwide. Cancer cells release fragments of their DNA, known as circulating tumor DNA (ctDNA), which can be detected in bodily fluids. A PubMed search using the terms “ctHPV” or “circulating tumor DNA” and “cervical cancer”, limited to the past ten years, identified 104 articles, complemented by hand-searching for literature addressing medico-legal implications. Studies were evaluated for relevance and methodological quality. Detection and characterization of circulating tumor HPV DNA (ctHPV DNA) have emerged as promising tools for assessing prognosis and More >

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