N’Landu Dikumbwa^1,*, Scott Tshibang Nawej², Gabriel Mutundo Teteka², Benjamin Mayaka Kibwila³, Jules Aloni Komanda³

Revue Internationale de Géomatique, Vol.35, pp. 13-30, 2026, DOI:10.32604/rig.2026.068019 - 05 February 2026

Abstract Rainfall data from four weather stations, quite far from each other, but located in the Zambezian phytogeographic region, were analysed for the research for indices of climate change. Two variables, rainfall and the annual number of rainy days, were considered. The rainfall data examined are 114 years for Luanda (1901–2014), 106 years for Lubumbashi (1916–2021), respectively, 54 and 41 years for Huambo (1961–2014) and Boma (1981–2021); 100 years (1921–2021) for the annual number of rainy days for only the Lubumbashi weather station. The results were a widespread decline in rainfall at all weather stations. Despite… More >

Jimin Chae¹, Youngbin Lym^2,*, Geiguen Shin^2,3,*

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.071482 - 28 January 2026

Abstract Background: Social connection is widely recognized as a protective determinant of health, yet its direct and indirect effects on mental health remain underexplored. This study examines the relationship between social connection and mental health, focusing on the mediating role of quality of life (QoL) and the moderating effect of regional differences. Methods: We analyzed data from the 2019 Korean Community Health Survey, comprising 229,099 adults. Mental health was assessed through validated measures of depressive symptoms and psychological well-being. Social connection was measured using indicators of interpersonal ties and community participation, and QoL was assessed via self-reported… More >

Thi Kim Chi Duong¹, Bich-Ngoc. Mach², Hoa-Cuc. Nguyen², Thi Nhu Quynh Trinh², Thanh Q. Nguyen^3,4,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.070185 - 08 January 2026

Abstract This study explores theoretical insights and experimental results on monitoring load-carrying capacity degradation in bridge spans through frequency analysis. Experiments were conducted on real bridge structures, including the Binh Thuan Bridge, focusing on analyzing the power spectral density (PSD) of vibration signals under random traffic loads. Detailed digital models of various bridge spans with different structural designs and construction periods were developed to ensure diversity. The study utilized PSD to analyze the vibration signals from the bridge spans under various loading conditions, identifying the vibration frequencies and the corresponding response regions. The research correlated the… More >

Xiaorui Zhang^1,2,*, Chunlin Yuan³, Wei Sun⁴, Ting Wang⁵

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.071043 - 09 December 2025

Abstract Video emotion recognition is widely used due to its alignment with the temporal characteristics of human emotional expression, but existing models have significant shortcomings. On the one hand, Transformer multi-head self-attention modeling of global temporal dependency has problems of high computational overhead and feature similarity. On the other hand, fixed-size convolution kernels are often used, which have weak perception ability for emotional regions of different scales. Therefore, this paper proposes a video emotion recognition model that combines multi-scale region-aware convolution with temporal interactive sampling. In terms of space, multi-branch large-kernel stripe convolution is used to More >

Jiajun Sun, Shunshun Ji, Chao Zhang^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-23, 2026, DOI:10.32604/cmc.2025.068668 - 09 December 2025

Abstract Asparagus stem blight is a devastating crop disease, and the early detection of its pathogenic spores is essential for effective disease control and prevention. However, spore detection is still hindered by complex backgrounds, small target sizes, and high annotation costs, which limit its practical application and widespread adoption. To address these issues, a semi-supervised spore detection framework is proposed for use under complex background conditions. Firstly, a difficulty perception scoring function is designed to quantify the detection difficulty of each image region. For regions with higher difficulty scores, a masking strategy is applied, while the… More >

Lincong Zhang¹, Yuqing Liu¹, Kefeng Wei², Weinan Zhao¹, Bo Qian^1,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-18, 2026, DOI:10.32604/cmc.2025.069108 - 10 November 2025

Abstract In the field of edge computing, achieving low-latency computational task offloading with limited resources is a critical research challenge, particularly in resource-constrained and latency-sensitive vehicular network environments where rapid response is mandatory for safety-critical applications. In scenarios where edge servers are sparsely deployed, the lack of coordination and information sharing often leads to load imbalance, thereby increasing system latency. Furthermore, in regions without edge server coverage, tasks must be processed locally, which further exacerbates latency issues. To address these challenges, we propose a novel and efficient Deep Reinforcement Learning (DRL)-based approach aimed at minimizing average… More >

Qinghua Wang^*, Yi Zhu

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-2, 2025, DOI:10.32604/icces.2025.012693

Abstract This study presents a robust and automated image registration framework designed to enhance the precision and efficiency of full-field deformation measurement in experimental mechanics applications. Traditional optical techniques, such as the sampling moiré method, rely on manual alignment processes that introduce significant errors and inefficiencies, particularly when analyzing large datasets or operating under dynamic experimental conditions. Addressing these limitations, the proposed method integrates the Maximally Stable Extremal Regions (MSER) algorithm to automate the alignment of grating images with sub-pixel accuracy. The technique is specifically tailored to handle challenges arising from high-noise environments and complex deformation… More >

Xingkang Jiang^*, Jing Tian, Yong Xu

Canadian Journal of Urology, Vol.32, No.6, pp. 539-540, 2025, DOI:10.32604/cju.2025.073363 - 30 December 2025

Abstract This article has no abstract. More >

Xiulong Yao¹, Mengge Yu^1,*, Jiali Liu², Qian Zhang¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2795-2814, 2025, DOI:10.32604/fdmp.2025.072708 - 01 December 2025

Abstract High-speed trains operating in freezing rain are highly susceptible to severe ice accretion in the pantograph region, which compromises both power transmission efficiency and dynamic performance. To elucidate the underlying mechanisms of this phenomenon, an Euler–Euler multiphase flow model was employed to simulate droplet impingement and collection on the pantograph surface, while a glaze-ice formation model incorporating wall film dynamics was used to capture the subsequent growth of ice. The effects of key parameters—including liquid water content, ambient temperature, train velocity, and droplet diameter—on the amount and morphology of ice were systematically investigated. The results More >

Hao Yue¹, Di Gao², Jin Gao¹, Chengmei Wei¹, Jiali Duan³, Shaocheng Mei^3,*

Energy Engineering, Vol.122, No.12, pp. 5091-5109, 2025, DOI:10.32604/ee.2025.069140 - 27 November 2025

Abstract Against the backdrop of regional coordinated development and China’s “dual carbon” strategic objectives, the Beijing-Tianjin-Hebei (BTH) region faces an urgent need to transition from its traditional economic growth model, which is heavily reliant on resource consumption. This study investigates the decoupling dynamics among economic growth, energy consumption, and carbon emissions in the BTH region, along with the underlying driving forces, aiming to provide valuable insights for achieving the “dual carbon” targets and fostering high-quality regional development. First, the Tapio decoupling model is employed to analyze the decoupling relationships between economic growth, energy consumption, and carbon… More >