Adolfo Amador Mendoza^1,*, Rosalba Guadalupe Gomez Raymundo², Ana Rosa Ramírez Seañez¹, Hipolito Hernández Hernández¹, Rogelio Enrrique Palacios Torres¹, Nelda Xanath Martínez Galero³, Miguel Ángel García Muñoz³, Saribel Zilli Gutiérrez^4,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2025.073856 - 30 January 2026

Abstract The cultivation of Soledad pepper (Capsicum annuum L.) is essential in Oaxaca and Veracruz, but it faces issues with pests and diseases, which affect yield and cause economic losses. To mitigate these impacts, farmers have started using biostimulants such as chitosan and plant growth promoting bacteria instead of agrochemicals due to their environmental and health benefits. This study evaluated the effect of Bacillus subtilis and chitosan, both individually and combined, on the growth, yield, and fruit quality of Soledad pepper under greenhouse conditions. Four treatments were applied at different stages of the crop cycle: Q (Chitosan), BS (Bacillus More >

Shengkang Zhang¹, Yong Jin^2,*, Soon Poh Yap^1,*, Haoyun Fan¹, Shiyuan Li³, Ahmed El-Shafie⁴, Zainah Ibrahim¹, Amr El-Dieb⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.075351 - 29 January 2026

Abstract Concrete-filled steel tubes (CFST) are widely utilized in civil engineering due to their superior load-bearing capacity, ductility, and seismic resistance. However, existing design codes, such as AISC and Eurocode 4, tend to be excessively conservative as they fail to account for the composite action between the steel tube and the concrete core. To address this limitation, this study proposes a hybrid model that integrates XGBoost with the Pied Kingfisher Optimizer (PKO), a nature-inspired algorithm, to enhance the accuracy of shear strength prediction for CFST columns. Additionally, quantile regression is employed to construct prediction intervals for… More >

Haoxiang Wen¹, Zhaoyang Wang¹, Zhonglin Ye^1,*, Haixing Zhao¹, Maosong Sun²

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074410 - 29 January 2026

Abstract Multivariate anomaly detection plays a critical role in maintaining the stable operation of information systems. However, in existing research, multivariate data are often influenced by various factors during the data collection process, resulting in temporal misalignment or displacement. Due to these factors, the node representations carry substantial noise, which reduces the adaptability of the multivariate coupled network structure and subsequently degrades anomaly detection performance. Accordingly, this study proposes a novel multivariate anomaly detection model grounded in graph structure learning. Firstly, a recommendation strategy is employed to identify strongly coupled variable pairs, which are then used More >

Abdulrazzak Akroot¹, Kayser Aziz Ameen², Haitham M. Ibrahim³, Hasanain A. Abdul Wahhab^3,*, Miqdam T. Chaichan⁴

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.073702 - 27 January 2026

Abstract Improving energy efficiency and lowering negative environmental impact through waste heat recovery (WHR) is a critical step toward sustainable cement manufacturing. This study analyzes advanced cogeneration systems for recovering waste heat from the Fallujah White Cement Plant in Iraq. The novelty of this work lies in its direct application and comparative thermodynamic analysis of three distinct cogeneration cycles—the Organic Rankine Cycle, the Single-Flash Steam Cycle, and the Dual-Pressure Steam Cycle—within the Iraqi cement industry, a context that has not been widely studied. The main objective is to evaluate and compare these models to determine the… More > Graphic Abstract

Xiaohan Zhang¹, Han Song^2,*, Maoyuan Yin³, Xiaoli Rong²

Chalcogenide Letters, Vol.23, No.1, 2026, DOI:10.32604/cl.2026.076594 - 26 January 2026

Abstract We report the rational design and synthesis of a novel trifunctional catalyst comprising atomically dispersed copper single-atom (Cu-SAC) sites and Cu₉S₅ nanoparticles co-loaded onto a highly crystalline carbon nitride (CCN) support for the photothermal conversion of methane to ethanol. The distinct active sites operate in synergy: the Cu-SAC sites, coordinated to the nitrogen-rich CCN framework, serve as highly efficient centers for the initial activation of methane’s C-H bond to form methyl radicals, while the plasmonic Cu₉S₅ nanoparticles act as dedicated sites for the subsequent C-C coupling and partial oxidation steps, driven by a combination of photochemical More >

SHAOFENG XIONG^1,2, WENKAI LV³, GUOSHENG CAO⁴, LONGSHENG FU¹, WEN LIU³, MENGFAN LEI², YANNI LV^1,5,*

BIOCELL, Vol.50, No.1, 2026, DOI:10.32604/biocell.2025.073401 - 23 January 2026

Abstract Objective: Leucine-rich alpha-2 glycoprotein 1 (Lrg1) could regulate diverse cells in cerebral ischemia-reperfusion. Our study seeks to uncover Lrg1’s impact on endothelial cell heterogeneity via differentiation pathways and transcription factors. Method: The CSOmap model measured cell-to-brain-center distances using single-cell RNA sequencing (scRNA-seq) data in middle cerebral artery occlusion reperfusion (MCAO/R). Monocle2 mapped endothelial differentiation paths. Gene set enrichment analysis (GSEA) analyzed endothelial subcluster variations. Database searches revealed a zinc finger MIZ-type containing 1 protein-frizzled 3 (Zmiz1-Fzd3) promoter interaction. Endothelial cells were transfected with a Fzd3 promoter-luciferase plasmid. Polymerase chain reaction (PCR) and western blotting assessed… More >

Xinyang Li^1,2,3,#, Luyuan Ma^1,2,3,#, Chuan Shen^1,2,3, Ruolan Gu^1,2,3, Shilong Dong^1,2,3, Mingjie Liu^1,2,3, Ying Xiao^1,2,3, Wenpeng Liu^1,2,3, Yuexia Liu^1,2,3, Caiyan Zhao^1,2,3,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.073179 - 19 January 2026

Abstract Background: Hepatocellular carcinoma (HCC) is an aggressive and lethal malignancy. Metabolic reprogramming dynamically remodels the tumor microenvironment (TME) and drives HCC progression. This study investigated the mechanism through which metabolic reprogramming remodels the TME in HCC. Methods: HCC patient transcriptome data were subjected to bioinformatics analysis to identify differentially expressed genes and immune infiltration status. Immunohistochemical analysis was performed to determine the correlation between succinate dehydrogenase complex subunit A (SDHA) expression and M2 macrophage infiltration. SDHA-knockdown or SDHA-overexpressing HCC cells were used for in vitro experiments, including co-culturing, flow cytometry, and enzyme-linked immunosorbent assay. Western blotting… More >

Shuai Zhao, Zhiwei Zhang^*, Junkai Wang, Ye Yuan, Guoren Wang

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073315 - 12 January 2026

Abstract With the development of sharded blockchains, high cross-shard rates and load imbalance have emerged as major challenges. Account partitioning based on hashing and real-time load faces the issue of high cross-shard rates. Account partitioning based on historical transaction graphs is effective in reducing cross-shard rates but suffers from load imbalance and limited adaptability to dynamic workloads. Meanwhile, because of the coupling between consensus and execution, a target shard must receive both the partitioned transactions and the partitioned accounts before initiating consensus and execution. However, we observe that transaction partitioning and subsequent consensus do not require… More >

Lifu He¹, Zhongchu Huang¹, Haidong Shao^2,*, Zhangbo Hu¹, Yuting Wang¹, Jie Mei¹, Xiaofei Zhang³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073227 - 12 January 2026

Abstract Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction. However, several challenges remain. First, signal noise collected during blade operation masks fault features, severely impairing the fault diagnosis performance of deep learning models. Second, current blade fault diagnosis often relies on single-sensor data, resulting in limited monitoring dimensions and ability to comprehensively capture complex fault states. To address these issues, a multi-sensor fusion-based wind turbine blade fault diagnosis method is proposed. Specifically, a CNN-Transformer Coupled Feature Learning Architecture is constructed to enhance the ability to More >

Xun Chen¹, Jinbao Lin^1,2,*, Zai Wang¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072495 - 12 January 2026

Abstract This work investigates the effects of deformation mechanisms on the mechanical properties and anisotropy of rolled AZ31B magnesium alloy under uniaxial tension, combining experimental characterization with Visco-Plastic Self Consistent (VPSC) modeling. The research focuses particularly on anisotropic mechanical responses along transverse direction (TD) and rolling direction (RD). Experimental measurements and computational simulations consistently demonstrate that prismatic <a> slip activation significantly reduces the strain hardening rate during the initial stage of tensile deformation. By suppressing the activation of specific deformation mechanisms along RD and TD, the tensile mechanical behavior of the magnesium alloy was further investigated. More >