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  • Open Access

    REVIEW

    Hypersonic Flow over V-Shaped Leading Edges: A Review of Shock Interactions and Aerodynamic Loads

    Xinyue Dong1, Wei Zhao1, Jingying Wang1,2,*, Shiyue Zhang1, Yue Zhou3, Xinglian Yang1, Chunhian Lee1,3

    FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.076238 - 06 February 2026

    Abstract For hypersonic air-breathing vehicles, the V-shaped leading edges (VSLEs) of supersonic combustion ramjet (scramjet) inlets experience complex shock interactions and intense aerodynamic loads. This paper provides a comprehensive review of flow characteristics at the crotch of VSLEs, with particular focus on the transition of shock interaction types and the variation of wall heat flux under different freestream Mach numbers and geometric configurations. The mechanisms governing shock transition, unsteady oscillations, hysteresis, and three-dimensional effects in VSLE flows are first examined. Subsequently, thermal protection strategies aimed at mitigating extreme heating loads are reviewed, emphasizing their relevance to More >

  • Open Access

    ARTICLE

    Salicylic Acid-Elicited Alkaloid Accumulation in Pinellia ternata Microtubers: Cytotoxicity and Transcriptomic Analysis

    Xiaoqing Jiang1,2,#, Pengchong Li1,2,#, Hongchuang Liu1,2, Wenjie Dong1,2, Wenjing Liu1,2, Di Wu1,2, Jianping Xue1,2, Fenglan Zhao1,2,*, Yongbo Duan1,2,*

    Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.074434 - 30 January 2026

    Abstract As its tuberous alkaloids induce valuable pharmacological effects, Pinellia ternata has considerable clinical value. However, its production currently fails to meet its demand. In vitro microtuber culture, combined with salicylic acid (SA) elicitation, may provide an effective alternative to traditional field production. In this study, an in vitro P. ternata microtuber induction system was developed and used to evaluate SA-induced elicitation of alkaloid accumulation. The quality of in vitro microtubers was assessed by total alkaloid measurement, a cytotoxicity assay, and transcriptomic analysis. With or without SA treatment, P. ternata microtuber induction was achieved within 60 d using petiole-derived explants, with… More >

  • Open Access

    ARTICLE

    Tissue-Specific Transcriptomic Responses and Viral Accumulation in Lily Cultivars Infected with Cucumber Mosaic Virus

    Yun-Im Kang1, Youn Jung Choi1, Su Young Lee1, Young-Ran Lee1, Ki-Byung Lim2,3, Yun-Jae Ahn2,3,*

    Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.073138 - 30 January 2026

    Abstract Cucumber mosaic virus (CMV) threatens lily production by reducing floral quality and enabling carry-over via infected planting stock. To explore tissue-specific host responses, we analyzed a legacy, single-replicate RNA-seq dataset from two cultivars, ‘Cancun’ and ‘Connecticut King’ (CK), profiling leaf (source) and bulb (sink) tissues at 0 and 28 days post-inoculation (dpi), alongside leaf DAS-ELISA. Principal component analysis indicated that tissue identity dominated the transcriptome (PC1 = 47.7%), with CMV treatment driving within-tissue shifts over time. Exploratory Gene Ontology/KEGG summaries and a focused marker panel revealed a consistent split: in leaves, genes linked to jasmonate/WRKY-associated… More >

  • Open Access

    ARTICLE

    A Comparative Benchmark of Deep Learning Architectures for AI-Assisted Breast Cancer Detection in Mammography Using the MammosighTR Dataset: A Nationwide Turkish Screening Study (2016–2022)

    Nuh Azginoglu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.075834 - 29 January 2026

    Abstract Breast cancer screening programs rely heavily on mammography for early detection; however, diagnostic performance is strongly affected by inter-reader variability, breast density, and the limitations of conventional computer-aided detection systems. Recent advances in deep learning have enabled more robust and scalable solutions for large-scale screening, yet a systematic comparison of modern object detection architectures on nationally representative datasets remains limited. This study presents a comprehensive quantitative comparison of prominent deep learning–based object detection architectures for Artificial Intelligence-assisted mammography analysis using the MammosighTR dataset, developed within the Turkish National Breast Cancer Screening Program. The dataset comprises… More >

  • 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

    Geometrically Nonlinear Analyses of Isotropic and Laminated Shells by a Hierarchical Quadrature Element Method

    Yingying Lan, Bo Liu*

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.075706 - 29 January 2026

    Abstract In this work, the Hierarchical Quadrature Element Method (HQEM) formulation of geometrically exact shells is proposed and applied for geometrically nonlinear analyses of both isotropic and laminated shells. The stress resultant formulation is developed within the HQEM framework, consequently significantly simplifying the computations of residual force and stiffness matrix. The present formulation inherently avoids shear and membrane locking, benefiting from its high-order approximation property. Furthermore, HQEM’s independent nodal distribution capability conveniently supports local p-refinement and flexibly facilitates mesh generation in various structural configurations through the combination of quadrilateral and triangular elements. Remarkably, in lateral buckling… 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

    Gradient Descent-Based Prediction of Heat-Transmission Rate of Engine Oil-Based Hybrid Nanofluid over Trapezoidal and Rectangular Fins for Sustainable Energy Systems

    Maddina Dinesh Kumar1,#, S. U. Mamatha2, Khalid Masood3, Nehad Ali Shah4,#, Se-Jin Yook1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074680 - 29 January 2026

    Abstract Fluid dynamic research on rectangular and trapezoidal fins is aimed at increasing heat transfer by means of large surfaces. The trapezoidal cavity form is compared with its thermal and flow performance, and it is revealed that trapezoidal fins tend to be more efficient, particularly when material optimization is critical. Motivated by the increasing need for sustainable energy management, this work analyses the thermal performance of inclined trapezoidal and rectangular porous fins utilising a unique hybrid nanofluid. The effectiveness of nanoparticles in a working fluid is primarily determined by their thermophysical properties; hence, optimising these properties… 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

    Bias Calibration under Constrained Communication Using Modified Kalman Filter: Algorithm Design and Application to Gyroscope Parameter Error Calibration

    Qi Li, Yifan Wang*, Yuxi Liu, Xingjing She, Yixuan Wu

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074066 - 29 January 2026

    Abstract In data communication, limited communication resources often lead to measurement bias, which adversely affects subsequent system estimation if not effectively handled. This paper proposes a novel bias calibration algorithm under communication constraints to achieve accurate system states of the interested system. An output-based event-triggered scheme is first employed to alleviate transmission burden. Accounting for the limited-communication-induced measurement bias, a novel bias calibration algorithm following the Kalman filtering line is developed to restrain the effect of the measurement bias on system estimation, thereby achieving accurate system state estimates. Subsequently, the Field Programmable Gate Array (FPGA) implementation More >

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