Yu-Xuan Zhou¹, Kai-Qing Zhou^1,*, Wei-Lin Chen¹, Zhou-Hua Liao¹, Di-Wen Kang^1,2

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.075099 - 10 February 2026

Abstract The Pigeon-Inspired Optimization (PIO) algorithm constitutes a metaheuristic method derived from the homing behaviour of pigeons. Initially formulated for three-dimensional path planning in unmanned aerial vehicles (UAVs), the algorithm has attracted considerable academic and industrial interest owing to its effective balance between exploration and exploitation, coupled with advantages in real-time performance and robustness. Nevertheless, as applications have diversified, limitations in convergence precision and a tendency toward premature convergence have become increasingly evident, highlighting a need for improvement. This review systematically outlines the developmental trajectory of the PIO algorithm, with a particular focus on its core… More >

Cosmin Dumitru, Emanuel Pantelimon, Alexandru Guzu, Georgian Nicolae^*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072749 - 10 February 2026

Abstract Unmanned aerial vehicles (UAVs), especially quadcopters, have become indispensable in numerous industrial and scientific applications due to their flexibility, low cost, and capability to operate in dynamic environments. This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking, object detection, precision landing, and real-time telemetry via long-range communication protocols. The system integrates an onboard flight controller running real-time sensor fusion algorithms, a vision-based detection system on a companion single-board computer, and a telemetry unit using Long Range (LoRa) communication. Extensive flight tests were conducted to validate the system’s More >

Wenfeng Zheng¹, Guangyu Xu², Siyu Lu³, Junmin Lyu⁴, Feng Bao^5,*, Lirong Yin^6,*

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 >

Mong-Fong Horng^1,#, Thanh-Lam Nguyen^1,#, Thanh-Tuan Nguyen^2,*, Chin-Shiuh Shieh^1,*, 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 >

Faten S. Alamri¹, Adil Ali Saleem², Muhammad I. Khan³, Hafeez Ur Rehman Siddiqui², Amjad Rehman^3,*

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 >

Hosam O. Elansary¹, Naveed A. Noor², Syed M. Ahmad³, Humza Riaz³, Sohail Mumtaz^4,*

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 (E_f) 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 >

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 >

Yang Wu^1,#,*, Dong Xu^1,#, Run Shi¹, Mingwei Zhan², Shaohui Xu³, Xin Wang⁴, Jianpeng Zhang⁵, Zhaokai Zhou⁶, Weizhuo Wang⁷, Yongjie Wang⁸, Minglun Li⁹, Zihao Xu^10,*, Kaifeng Su^11,*

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 >

Jiayu Zou^1,2,3, Yajie Lu³, Jiaqi Li³, Zhaokai Zhou^4,5, Fu Peng³, Pu Qiu^2,*, Hailin Tang⁶, Cheng Peng^1,*

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 >

Tahir Mahmood^1,*, Muhammad Waseem Ashraf^1,*, 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 >