Yanzhao Yang¹, Xiaowen Song², Zhiying Deng^2,*, Jianyang Yu³

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.074345 - 06 February 2026

Abstract In this study, a Gaussian Process Regression (GPR) surrogate model coupled with a Bayesian optimization algorithm was employed for the single-objective design optimization of fan-shaped film cooling holes on a concave wall. Fan-shaped holes, commonly used in gas turbines and aerospace applications, flare toward the exit to form a protective cooling film over hot surfaces, enhancing thermal protection compared to cylindrical holes. An initial hole configuration was used to improve adiabatic cooling efficiency. Design variables included the hole injection angle, forward expansion angle, lateral expansion angle, and aperture ratio, while the objective function was the More >

Abdulaziz Almalaq¹, Ambe Harrison^2,*, Ibrahim Alsaleh¹, Abdullah Alassaf¹, Mashari Alangari¹

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074815 - 29 January 2026

Abstract We present a computer-modeling framework for photovoltaic (PV) source emulation that preserves the exact single-diode physics while enabling iteration-free, real-time evaluation. We derive two closed-form explicit solvers based on the Lambert W function: a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator. Unlike Taylor-linearized explicit models, our proposed formulation retains the exponential nonlinearity of the PV equations. It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding, all while maintaining limited computational costs and a small… More >

Yewon Choi^1,2, Song Hyeon Ju², Jungsoo Nam^2,*, Min Ku Kim^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.071817 - 29 January 2026

Abstract The composite material layering process has attracted considerable attention due to its production advantages, including high scalability and compatibility with a wide range of raw materials. However, changes in process conditions can lead to degradation in layer quality and non-uniformity, highlighting the need for real-time monitoring to improve overall quality and efficiency. In this study, an AI-based monitoring system was developed to evaluate layer width and assess quality in real time. Three deep learning models Faster Region-based Convolutional Neural Network (R-CNN), You Only Look Once version 8 (YOLOv8), and Single Shot MultiBox Detector (SSD) were… More >

Yunpeng Wen^1,*, Bingyang Ke², Junrong Ding³

Chalcogenide Letters, Vol.23, No.1, 2026, DOI:10.32604/cl.2026.076587 - 26 January 2026

Abstract This study reports an active learning (AL)-guided strategy to optimize the sulfurization–selenization processing conditions of Sb₂(S,Se)₃ thin-film photovoltaic absorbers for enhanced power conversion efficiency (PCE). By coupling Gaussian process modeling with iterative experimental feedback, we explored 20 targeted annealing conditions across the full compositional spectrum (x = 0–1) and identified an optimal S/(S + Se) ratio of 0.40 (x = 0.60), which yielded a band gap (Eg) of ~1.34 eV, close to the theoretical Shockley–Queisser optimum. The optimized process employed a controlled two-step 420°C anneal with sequential H₂Se→H₂S exposure, which produced large plate-like grains (300–500 nm)… 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 >

Aadarsha Lamichhane¹, Arun Kuttoor Vasudevan¹, Ethan Dean¹, Mostafa Mohammadabadi^1,*, Kevin Ragon¹, Ardeshir Adeli²

Journal of Renewable Materials, Vol.14, No.1, 2026, DOI:10.32604/jrm.2025.02025-0146 - 23 January 2026

Abstract This study explores a novel method for processing cotton stalks—an abundant agricultural byproduct—into long strips that serve as sustainable raw material for engineered bio-based panels. To evaluate the effect of raw material morphology on panel’s performance, two types of cotton stalk-based panels were developed: one using long strips, maintaining fiber continuity, and the other using ground particles, representing conventional processing. A wood strand-based panel made from commercial southern yellow pine strands served as the control. All panels were bonded using phenol-formaldehyde resin and hot-pressed to a target thickness of 12.7 mm and density of 640 kg/m³.… More >

JOSé A. BOGA^1,2, ANA COTO-MONTES^2,3,*, RUSSEL J. REITER⁴

BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.068245 - 23 January 2026

Abstract Aerobic glycolysis, also known as the Warburg effect, and the accumulation of lactate that it causes, are increasingly recognized outside the field of oncology as triggers of chronic non-neoplastic disorders. This review integrates preclinical and clinical evidence to evaluate the ability of melatonin to reverse Warburg-effect-like metabolic reprogramming. Literature on neurodegeneration, age-related sarcopenia, type 2 diabetes, chronic kidney disease, heart failure and pulmonary arterial hypertension (PAH) has been reviewed and synthesised. In all of these conditions, hypoxia-inducible factor 1α (HIF-1α) and pyruvate dehydrogenase kinase 4 (PDK4) inhibit the pyruvate dehydrogenase complex. This diverts pyruvate away… More >

Williams Kyei^*, Chunyong Yin, Kelvin Amos Nicodemas, Khagendra Darlami

Journal on Artificial Intelligence, Vol.8, pp. 19-38, 2026, DOI:10.32604/jai.2026.074988 - 20 January 2026

Abstract The COVID-19 pandemic has underscored the need for rapid and accurate diagnostic tools to differentiate respiratory infections from normal cases using chest X-rays (CXRs). Manual interpretation of CXRs is time-consuming and prone to errors, particularly in distinguishing COVID-19 from viral pneumonia. This research addresses these challenges by proposing a customized EfficientNet-B0 model for ternary classification (COVID-19, Viral Pneumonia, Normal) on the COVID-19 Radiography Database. Employing transfer learning with architectural modifications, including a tailored classification head and regularization techniques, the model achieves superior performance. Evaluated via accuracy, F1-score (macro-averaged), AUROC (macro-averaged), precision (macro-averaged), recall (macro-averaged), inference… More >

Tai Liu^1,2, Mao Ye^2,*, Feng Wu³, Chao Zhu², Bo Chen², Guoyan Zhang^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072692 - 12 January 2026

Abstract With the continuous advancement of unmanned technology in various application domains, the development and deployment of blind-spot-free panoramic video systems have gained increasing importance. Such systems are particularly critical in battlefield environments, where advanced panoramic video processing and wireless communication technologies are essential to enable remote control and autonomous operation of unmanned ground vehicles (UGVs). However, conventional video surveillance systems suffer from several limitations, including limited field of view, high processing latency, low reliability, excessive resource consumption, and significant transmission delays. These shortcomings impede the widespread adoption of UGVs in battlefield settings. To overcome these… More >

Shuangqing Song¹, Yuan Chen², Xuguang Hu¹, Juwei Zhang^1,3,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072392 - 12 January 2026

Abstract In multi-domain neural machine translation tasks, the disparity in data distribution between domains poses significant challenges in distinguishing domain features and sharing parameters across domains. This paper proposes a Transformer-based multi-domain-aware mixture of experts model. To address the problem of domain feature differentiation, a mixture of experts (MoE) is introduced into attention to enhance the domain perception ability of the model, thereby improving the domain feature differentiation. To address the trade-off between domain feature distinction and cross-domain parameter sharing, we propose a domain-aware mixture of experts (DMoE). A domain-aware gating mechanism is introduced within the… More >