Longyue Li¹, Guoqing Zhang¹, Bo Cao¹, Shuqi Wang², Ye Tian^1,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-26, 2026, DOI:10.32604/cmc.2025.070622 - 09 December 2025

Abstract Modern battlefields exhibit high dynamism, where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values, leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command, where static weights cannot reflect the operational value decay or surge of key indicators. To address this issue, this study proposes a dynamic adaptive weighting method for evaluation indicators based on G1-CRITIC-PIVW. First, the G1 (Sequential Relationship Analysis Method) subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via… More >

Carlos Torres-Aguilar^1,*, Pedro Moreno^2,*, Diego Rossit³, Sergio Nesmachnow⁴, Karla M. Aguilar-Castro¹, Edgar V. Macias-Melo¹, Luis Hernández-Callejo⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3859-3881, 2025, DOI:10.32604/cmes.2025.069996 - 23 December 2025

Abstract Solar chimneys are renewable energy systems designed to enhance natural ventilation, improving thermal comfort in buildings. As passive systems, solar chimneys contribute to energy efficiency in a sustainable and environmentally friendly way. The effectiveness of a solar chimney depends on its design and orientation relative to the cardinal directions, both of which are critical for optimal performance. This article presents a supervised learning approach using artificial neural networks to forecast the performance indicators of solar chimneys. The dataset includes information from 2784 solar chimney configurations, which encompasses various factors such as chimney height, channel thickness, More > Graphic Abstract

Hui Qi¹, Jingyi Lian², Congjun Rao^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 995-1028, 2025, DOI:10.32604/cmes.2025.069722 - 30 October 2025

Abstract For the past few years, the prevalence of cardiovascular disease has been showing a year-on-year increase, with a death rate of 2/5. Coronary heart disease (CHD) rates have increased 41% since 1990, which is the number one disease endangering human health in the world today. The risk indicators of CHD are complicated, so selecting effective methods to screen the risk characteristics can make the risk prediction more efficient. In this paper, we present a comprehensive analysis of CHD risk indicators from both data and algorithmic levels, propose a method for CHD risk indicator identification based… More >

Xiao Li^*, Junxiang Liu, Weinan Fan, Shiying Xu

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-2, 2025, DOI:10.32604/icces.2025.012285

Abstract With global warming, the frequency of extreme precipitation events is continuously increasing. The Pearl River Basin is an important region for agricultural production and population concentration in China. Extreme precipitation events have significant impacts on various aspects such as agriculture, transportation, and water resources in this region. The ERA5 reanalysis dataset is a global atmospheric reanalysis product with high spatial and temporal resolution, as well as diverse meteorological information, offering substantial research value for basin weather forecasting and climate change studies. Based on daily precipitation data from 71 meteorological stations in the Pearl River Basin… More >

Hao Fang^1,2, Hongyun Guo¹, Yinchao Chen³, Hui Shi⁴, Yihan Gan⁵, Lin Li^6,*

International Journal of Mental Health Promotion, Vol.27, No.7, pp. 1051-1069, 2025, DOI:10.32604/ijmhp.2025.066369 - 31 July 2025

Abstract Objectives: Emotional stress is a significant public health challenge. Virtual reality (VR) offers the potential for aiding emotional recovery. This study explores the impact of VR environment design factors on emotional recovery, examining underlying mechanisms through physiological indicators and behavioral responses. Methods: Two experiments were conducted. Experiment 1 employed a 4 [Scene Type: real environment (RE), virtual scenes that restore the RE (VR), virtual scenes that incorporate natural window view design (VR-W), and a no-scene control condition (CTL)] × 3 (Experimental Phase: baseline, emotion arousal, recovery) mixed design (N = 33). Participants viewed a 4-min… More >

Li Ling^*, Danhao Song, Qianlong Hu, Zihao Xiang, Zeyu Zhang

Energy Engineering, Vol.122, No.8, pp. 3309-3328, 2025, DOI:10.32604/ee.2025.065824 - 24 July 2025

Abstract Rack-level loop thermosyphons have been widely adopted as a solution to data centers’ growing energy demands. While numerous studies have highlighted the heat transfer performance and energy-saving benefits of this system, its economic feasibility, water usage effectiveness (WUE), and carbon usage effectiveness (CUE) remain underexplored. This study introduces a comprehensive evaluation index designed to assess the applicability of the rack-level loop thermosyphon system across various computing hub nodes. The air wet bulb temperature T_a,w was identified as the most significant factor influencing the variability in the combination of PUE, CUE, and WUE values. The results indicate… More >

Dongfeng Yang, Ruirui Zhang, Chuang Liu^*, Guoliang Bian

Energy Engineering, Vol.122, No.7, pp. 2673-2694, 2025, DOI:10.32604/ee.2025.062154 - 27 June 2025

Abstract Under the current long-term electricity market mechanism, new energy and thermal power face issues such as deviation assessment and compression of generation space. The profitability of market players is limited. Simultaneously, the cooperation model among various energy sources will have a direct impact on the alliance’s revenue and the equity of income distribution within the alliance. Therefore, integrating new energy with thermal power units into an integrated multi-energy complementary system to participate in the long-term electricity market holds significant potential. To simulate and evaluate the benefits and internal distribution methods of a multi-energy complementary system… More >

S. Y. Labonno, M. S. Raihan, M. Mohi-Ud-Din, A. K. M. Aminul Islam^*

Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1545-1563, 2025, DOI:10.32604/phyton.2025.063916 - 29 May 2025

Abstract Morpho-physiological evaluation of a crop’s genetic resources is necessary to find possible genotypes to include in breeding initiatives. The objective of this study was to identify heat-tolerant wheat genotypes among36 mutant lines using morpho-physiological indices. Seedlings of mutant lines and check varieties were grown under both normal (control) and heat-stress conditions in growth chambers. Data were recorded on root-shoot parameters (length, fresh weight, dry weight, and ratio), relative water content (RWC), stability of cell membrane, pigment content, and chlorophyll fluorescence. Two-way analysis of variance showed significant (p < 0.01, p < 0.001) variation among15 morpho-physiological features… More >

Ahmed El Youssefi¹, Abdelaaziz Hessane^1,2, Imad Zeroual¹, Yousef Farhaoui^1,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3411-3433, 2025, DOI:10.32604/cmc.2025.063218 - 16 April 2025

Abstract This study provides a systematic investigation into the influence of feature selection methods on cryptocurrency price forecasting models employing technical indicators. In this work, over 130 technical indicators—covering momentum, volatility, volume, and trend-related technical indicators—are subjected to three distinct feature selection approaches. Specifically, mutual information (MI), recursive feature elimination (RFE), and random forest importance (RFI). By extracting an optimal set of 20 predictors, the proposed framework aims to mitigate redundancy and overfitting while enhancing interpretability. These feature subsets are integrated into support vector regression (SVR), Huber regressors, and k-nearest neighbors (KNN) models to forecast the… More >

IOANA MARIA MIHAI¹, GANG WANG^1,2,*

Oncology Research, Vol.33, No.3, pp. 533-547, 2025, DOI:10.32604/or.2024.055155 - 28 February 2025

Abstract The advent of precision medicine has underscored the importance of biomarkers in predicting therapy response for bladder cancer, a malignancy marked by considerable heterogeneity. This review critically examines the current landscape of biomarkers to forecast treatment outcomes in bladder cancer patients. We explore a range of biomarkers, including genetic, epigenetic, proteomic, and transcriptomic indicators, from multiple sample sources, including urine, tumor tissue and blood, assessing their efficacy in predicting responses to chemotherapy, immunotherapy, and targeted therapies. Despite promising developments, the translation of these biomarkers into clinical practice faces significant challenges, such as variability in biomarker More >