Young-Vin Kim¹, Hyunkyun Ahn^2,*

International Journal of Mental Health Promotion, Vol.27, No.9, pp. 1301-1334, 2025, DOI:10.32604/ijmhp.2025.068251 - 30 September 2025

Abstract Objectives: Recently, the global esports industry has experienced remarkable growth, leading to an expansion in the scale and influence of professional player communities. However, despite this outward growth, systems to protect players’ mental health remain inadequate. Comprehensive analysis of structural risk factors, including performance pressure, public evaluation, and career instability, remains insufficient. This study, aimed to explore stressors encountered by esports athletes, coping strategies, and the role of social support systems in safeguarding mental health. Using the transactional model of stress and coping, the job demands–resources model, and social support theory, the study adopts an… More >

Jeyapaul Angel Ida Chellam¹, Bright Brailson Mansingh², Daniel Stalin Alex³, Joseph Selvi Binoj^4,*

Journal of Polymer Materials, Vol.42, No.3, pp. 773-794, 2025, DOI:10.32604/jpm.2025.069295 - 30 September 2025

Abstract Machine learning models can predict material properties quickly and accurately at a low computational cost. This study generated novel hybridized nanocomposites with unsaturated polyester resin as the matrix and Areca fruit husk fiber (AFHF), tamarind fruit fiber (TFF), and nano-sized coconut shell powder (NCSP). It is challenging to determine the optimal proportion of raw materials in this composite to achieve maximum mechanical properties. This task was accomplished with the help of ML techniques in this study. The tensile strength of the hybridized nanocomposite was increased by 134.06% compared to the neat unsaturated polyester resin at… More >

Khairul Eahsun Fahim¹, Liyanage C. De Silva², Sk. A. Shezan^3,*, Md Ashraful Islam⁴, Md Shakib Hassan⁵, Hayati Yassin^1,*, Naveed Ahmad⁶

Energy Engineering, Vol.122, No.10, pp. 3985-3997, 2025, DOI:10.32604/ee.2025.066484 - 30 September 2025

Abstract Around the world, there has been a notable shift toward the use of renewable energy technology due to the growing demand for energy and the ongoing depletion of conventional resources, such as fossil fuels. Following this worldwide trend, Brunei’s government has initiated several strategic programs aimed at encouraging the establishment of energy from renewable sources in the nation’s energy mix. These initiatives are designed not only to support environmental sustainability but also to make energy from renewable sources increasingly competitive in comparison to more conventional energy sources like gas and oil, which have historically dominated… More >

Junyu Deng^1,2, Rui Zhang^1,*, Xudong Zhao³, Hongzhi Xu^1,2, Peng Ji¹, Zizhen Zhang¹, Yifan Yang¹

Energy Engineering, Vol.122, No.10, pp. 4153-4168, 2025, DOI:10.32604/ee.2025.065906 - 30 September 2025

Abstract Field tests have demonstrated that depressurization with controlled sand production is an effective technique for natural gas hydrate extraction. Variations in depositional environments and processes result in significant heterogeneity within subsea natural gas hydrate-bearing sediments. However, the influence of permeability heterogeneity on production performance during depressurization with controlled sand production remains inadequately understood. In this study, a multiphase, multi-component mathematical model is developed to simulate depressurization with controlled sand production in methane hydrate-bearing sediments, incorporating geological conditions representative of unconsolidated argillaceous siltstone hydrate deposits in the Shenhu area of the South China Sea. The effects… More >

Zhe Liu^1,2,*, Jiahao Shi³, Dania Santina⁴, Yulong Huang¹, Nabil Mlaiki⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3531-3555, 2025, DOI:10.32604/cmes.2025.071145 - 30 September 2025

Abstract The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations. However, traditional fuzzy clustering algorithms show limitations with the inherent uncertainty and imprecision of such data, as they rely on a single-dimensional membership value. To overcome these limitations, we propose an auto-weighted multi-view neutrosophic fuzzy clustering (AW-MVNFC) algorithm. Our method leverages the neutrosophic framework, an extension of fuzzy sets, to explicitly model imprecision and ambiguity through three membership degrees. The core novelty of AW-MVNFC lies in a hierarchical weighting strategy that adaptively learns the contributions More >

Sudhakar Tummala^1,2,*, Sajjad Hussain Chauhdary³, Vikash Singh⁴, Roshan Kumar⁵, Seifedine Kadry⁶, Jungeun Kim^7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3585-3605, 2025, DOI:10.32604/cmes.2025.069731 - 30 September 2025

Abstract Lightweight deep learning models are increasingly required in resource-constrained environments such as mobile devices and the Internet of Medical Things (IoMT). Multi-head convolution with channel attention can facilitate learning activations relevant to different kernel sizes within a multi-head convolutional layer. Therefore, this study investigates the capability of novel lightweight models incorporating residual multi-head convolution with channel attention (ResMHCNN) blocks to classify medical images. We introduced three novel lightweight deep learning models (BT-Net, LCC-Net, and BC-Net) utilizing the ResMHCNN block as their backbone. These models were cross-validated and tested on three publicly available medical image datasets:… More >

Lakshmi Alekhya Jandhyam^1,*, Ragupathy Rengaswamy¹, Narayana Satyala²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3679-3714, 2025, DOI:10.32604/cmes.2025.068941 - 30 September 2025

Abstract Human Activity Recognition (HAR) has become increasingly critical in civic surveillance, medical care monitoring, and institutional protection. Current deep learning-based approaches often suffer from excessive computational complexity, limited generalizability under varying conditions, and compromised real-time performance. To counter these, this paper introduces an Active Learning-aided Heuristic Deep Spatio-Textural Ensemble Learning (ALH-DSEL) framework. The model initially identifies keyframes from the surveillance videos with a Multi-Constraint Active Learning (MCAL) approach, with features extracted from DenseNet121. The frames are then segmented employing an optimized Fuzzy C-Means clustering algorithm with Firefly to identify areas of interest. A deep ensemble More >

Florentin Smarandache¹, Saleh I. Alzahrani², Sulaiman Al Amro³, Ijaz Ahmad⁴, Mubashir Ali^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3715-3735, 2025, DOI:10.32604/cmes.2025.068736 - 30 September 2025

Abstract Hemoglobin is a vital protein in red blood cells responsible for transporting oxygen throughout the body. Its accurate measurement is crucial for diagnosing and managing conditions such as anemia and diabetes, where abnormal hemoglobin levels can indicate significant health issues. Traditional methods for hemoglobin measurement are invasive, causing pain, risk of infection, and are less convenient for frequent monitoring. PPG is a transformative technology in wearable healthcare for noninvasive monitoring and widely explored for blood pressure, sleep, blood glucose, and stress analysis. In this work, we propose a hemoglobin estimation method using an adaptive lightweight… More >

Jing Zhang, Liang Meng^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.011468

Abstract Shape memory alloys (SMA), with their unique phase transformation capability, can deform under external force and recover their original shape through a martensite-to-austenite phase transformation triggered by heating [1]. Utilizing this characteristic, SMA wires can be pre-stretched and fixed, generating internal stress during shape recovery, which increases the natural frequency of SMA wire structures [2]. This property is of significant importance in structural dynamics design. Based on this, structures incorporating SMA wires and SMA-reinforced plate structures can be designed to dynamically adjust their natural frequencies and control structural dynamic responses. Furthermore, the vibration modes of More >

Xiaocui Li¹, Fu-Rong Chen^1,*, Yang Lu^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.010503

Abstract Traditionally, it is relatively easy to process metal materials and polymers (plastics), while ceramic and inorganic semiconductor materials are hard to process, due to their intrinsic brittleness caused by directional covalent bonds or strong electrostatic interactions among ionic species. This brittleness can degrade semiconductor performance and lead to catastrophic failures, thereby limiting their application scenarios and service lifetime. Achieving room-temperature deformability in semiconductor materials without compromising their functionality has been a long-standing goal in materials science. Recently, room-temperature ductile semiconductors have emerged, with their deformability enhanced by factors such as size effects, fewer pre-existing micro-cracks,… More >