Md Minhazul Islam^1,2, Yunfei Yin^1,2,*, Md Tanvir Islam^1,2, Zheng Yuan^1,2, Argho Dey^1,2

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072550 - 12 January 2026

Abstract Automatic segmentation of landslides from remote sensing imagery is challenging because traditional machine learning and early CNN-based models often fail to generalize across heterogeneous landscapes, where segmentation maps contain sparse and fragmented landslide regions under diverse geographical conditions. To address these issues, we propose a lightweight dual-stream siamese deep learning framework that integrates optical and topographical data fusion with an adaptive decoder, guided multimodal fusion, and deep supervision. The framework is built upon the synergistic combination of cross-attention, gated fusion, and sub-pixel upsampling within a unified dual-stream architecture specifically optimized for landslide segmentation, enabling efficient… More >

Tsu-Yang Wu¹, Chengyuan Yu¹, Yanan Zhao², Saru Kumari³, Chien-Ming Chen^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.069139 - 12 January 2026

Abstract With the increasing complexity of logistics operations, traditional static vehicle routing models are no longer sufficient. In practice, customer demands often arise dynamically, and multi-depot systems are commonly used to improve efficiency. This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand. New customers appear in the delivery process at any time and are periodically optimized according to time slices. Then, we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem. The classical ant colony More >

Ashok Kumar Sah^1,*, Ranjay Kumar Choudhary^1,2, Velilyaeva Alie Sabrievna³, Karomatov Inomdzhon Dzhuraevich⁴, Anass M. Abbas⁵, Manar G. Shalabi⁵, Nadeem Ahmad Siddique⁶, Raji Rubayyi Alshammari⁷, Navjyot Trivedi⁸, Rabab H. Elshaikh¹

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.068238 - 30 December 2025

Abstract Male breast cancer (MBC) is rare, representing 0.5%–1% of all breast cancers, but its incidence is increasing due to improved diagnostics and awareness. MBC typically presents in older men, is human epidermal growth factor receptor 2 (HER2)-negative and estrogen receptor (ER)-positive, and lacks routine screening, leading to delayed diagnosis and advanced disease. Major risk factors include hormonal imbalance, radiation exposure, obesity, alcohol use, and Breast Cancer Gene 1 and 2 (BRCA1/2) mutations. Clinically, it may resemble gynecomastia but usually appears as a unilateral, painless mass or nipple discharge. Advances in imaging and liquid biopsy have More >

Jingshuai Pang^1,2, Songcen Wang¹, Hongyin Chen^1,2,*, Xiaoqiang Jia¹, Yi Guo¹, Ling Cheng¹, Xinhe Zhang¹, Jianfeng Li¹

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.070256 - 27 December 2025

Abstract To achieve the goals of sustainable development of the energy system and the construction of a low-carbon society, this study proposes a multi-energy storage collaborative optimization strategy for industrial park that integrates the laddered carbon trading mechanism with demand response. Firstly, a dual dimensional DR model is constructed based on the characteristics of load elasticity. The alternative DR enables flexible substitution of energy loads through complementary conversion of electricity/heat/cold multi-energy sources, while the price DR relies on time-of-use electricity price signals to guide load spatiotemporal migration; Secondly, the LCT mechanism is introduced to achieve optimal… More >

Salahudin Robo^1,2, Triyanna Widiyaningtyas^1,*, Wahyu Sakti Gunawan Irianto¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.073011 - 09 December 2025

Abstract Recommendation systems are an integral and indispensable part of every digital platform, as they can suggest content or items to users based on their respective needs. Collaborative filtering is a technique often used in various studies, which produces recommendations by analyzing similarities between users and items based on their behavior. Although often used, traditional collaborative filtering techniques still face the main challenge of sparsity. Sparsity problems occur when the data in the system is sparse, meaning that only a portion of users provide feedback on some items, resulting in inaccurate recommendations generated by the system.… More >

Geonho Na¹, Ryewon Ma^2,*, Heetae Cho^1,*

International Journal of Mental Health Promotion, Vol.27, No.12, pp. 1867-1882, 2025, DOI:10.32604/ijmhp.2025.073087 - 31 December 2025

Abstract Background: Academic achievement is an important indicator of student development, and its pursuit should be considered alongside students’ mental health and overall quality of life. Traditional martial arts, as an educational activity that emphasizes self-discipline, communal values, and positive emotional experiences, may support key psychological factors related to learning, such as optimism, school belonging, and well-being. However, how these factors are connected to academic achievement has not been fully examined. Therefore, this study investigated the associations between these psychological resources and academic achievement among students participating in traditional martial arts training. Methods: Data were collected from… More >

Hongmei Yuan¹, Siting Li^1,2,3,*, Yu Zhang^2,3, Yunheng Zhao¹, Dan Shen¹, E. Scott Huebnerd⁴

Journal of Psychology in Africa, Vol.35, No.6, pp. 723-730, 2025, DOI:10.32604/jpa.2025.073368 - 30 December 2025

Abstract Academic engagement is a key factor in students’ academic success, yet its psychological pathways remain underexplored in the context of physical activity. This study investigated the relationship between sports participation and academic engagement, with a focus on the sequential mediating roles of positive affect and life satisfaction. A total of 1365 Chinese secondary school students (females = 55.09%; mean age = 15.95 years, SD = 1.65) participated in the study. Participants completed the Physical Activity Rating Scale, the Positive Affect and Negative Affect Scale, the Satisfaction with Life Scale, and the Academic Engagement Scale. Correlation More >

B. Yassine, B. Tahar^*, G. Fathi, B. Meriem, B. Ibtissem

Chalcogenide Letters, Vol.22, No.7, pp. 637-648, 2025, DOI:10.15251/CL.2025.227.637 - 17 December 2025

Abstract In this paper, we designed a two-junction (tandem) solar cell model (tandem solar cell), consisting of an top and bottom subcell with absorber layers of Cu₂SnZnS₄ (CZTS) and Cu₂SnZnSe₄ (CZTSe) materials, respectively, for each subcell with a ZnS buffer layer and a ZnO window layer. This model was validated using the SCAPS-1D numerical simulation program. We also optimized the performance of the tandem cell as a whole using the simulation by studying the effect of the thickness of the absorber layer of the top subcell and the thickness of the absorber layer of the bottom subcell More >

S. Younus, N. Amin^*, A. Ali, K. Mahmood

Chalcogenide Letters, Vol.22, No.10, pp. 905-915, 2025, DOI:10.15251/CL.2025.2210.905

Abstract Wastewater generated by the textile industry contains high levels of various pollutants. Advanced conventional methods, such as chemical and electrical treatments, are effective in addressing these contaminants. However, the significant operational and capital costs associated with these conventional systems limit their accessibility for industrial stakeholders. In contrast, more economically viable methods tend to be less efficient. This study aims to identify a suitable approach for integrating photocatalytic degradation (PCD) with a low-cost method to enhance the cost-effectiveness of wastewater treatment processes in the textile sector. The study utilized silver copper sulfide (AgCuS) nanocomposites as a… More >

Edward Danso Ansong^*, Simon Bonsu Osei^*, Raphael Adjetey Adjei

Journal of Cyber Security, Vol.7, pp. 533-564, 2025, DOI:10.32604/jcs.2025.061821 - 11 December 2025

Abstract The surge in identity fraud, driven by the rapid adoption of mobile money, internet banking, and e-services during the COVID-19 pandemic, underscores the need for robust cybersecurity solutions. Zero-Knowledge Proofs (ZKPs) enable secure identity verification by allowing individuals to prove possession of a National ID card without revealing sensitive information. This study implements a ZKP-based identity verification system using Camenisch-Lysyanskaya (CL) signatures, reducing reliance on complex trusted setup ceremonies. While a trusted issuer is still required, as assumed in this work, our approach eliminates the need for broader system-wide trusted parameters. We evaluate the system’s More >