Abdullah A. Alharbi¹, Ahmad Y. Alqassim^1,*, Mohammad A. Jareebi¹, Ahmad A. Alharbi², Nada M. Makein¹, Fatimah H. Al Ghazwi³, Seba Y. Muzaiiadi³, Joud N. Refaei³, Revan A. Arishi³, Bashaer A. Al Rajhi³, Fatima A. Aqili³, Saleha M. Ayoub³, Mohammed A. Muaddi¹

International Journal of Mental Health Promotion, Vol.27, No.5, pp. 701-716, 2025, DOI:10.32604/ijmhp.2025.062924 - 05 June 2025

Abstract Background: Polycystic ovarian syndrome (PCOS), a common endocrine disorder in reproductive-aged women, has substantial physical and psychological impacts. While the physical manifestations of PCOS are well established, the psychological burden, especially anxiety, is understudied in Saudi Arabia. This study aimed to assess the prevalence of generalized anxiety disorder among females with PCOS compared to those without PCOS, and to identify the clinical and sociodemographic factors associated with anxiety in the Jazan region of Saudi Arabia. Methods: A cross-sectional study was conducted between January and March 2023 using an Arabic self-administered online questionnaire distributed via social… More >

Wencheng Wang^1,2,*, Baoxin Yin^1,2, Lei Li^2,*, Lun Li¹, Hongtao Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1595-1616, 2025, DOI:10.32604/cmes.2025.063595 - 30 May 2025

Abstract In low-light environments, captured images often exhibit issues such as insufficient clarity and detail loss, which significantly degrade the accuracy of subsequent target recognition tasks. To tackle these challenges, this study presents a novel low-light image enhancement algorithm that leverages virtual hazy image generation through dehazing models based on statistical analysis. The proposed algorithm initiates the enhancement process by transforming the low-light image into a virtual hazy image, followed by image segmentation using a quadtree method. To improve the accuracy and robustness of atmospheric light estimation, the algorithm incorporates a genetic algorithm to optimize the… More >

Rodolfo V. C. Ramalho¹, Vitoria B. Portilho¹, Davi E. S. Souza¹, Gilton C. A. Furtado¹, Natália M. Graças², Manoel J. S. Sena², Cláudio J. C. Blanco², André L. Amarante Mesquita^1,*

Energy Engineering, Vol.122, No.6, pp. 2197-2213, 2025, DOI:10.32604/ee.2025.064196 - 29 May 2025

Abstract Despite significant Brazilian social programs to expand energy access, approximately one million people in rural Amazonia still lack electricity. Moreover, the existing rural electricity grid in the region is inadequate for supporting efficient small-scale production systems due to both the poor quality and high cost of supplied energy. In parallel, traditional wooden bridges in the Amazon have been progressively replaced by more durable concrete structures in recent years. In this context, this study explores the application of very low-head hydropower installations in the Amazon, focusing on integrating axial-flow turbines beneath small concrete bridges. The methodology… More > Graphic Abstract

He Su, Jianwei Gao, Kang Kong^*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4193-4213, 2025, DOI:10.32604/cmc.2025.063355 - 19 May 2025

Abstract Accurate and robust navigation in complex surgical environments is crucial for bronchoscopic surgeries. This study purposes a bronchoscopic lumen feature matching network (BLFM-Net) based on deep learning to address the challenges of image noise, anatomical complexity, and the stringent real-time requirements. The BLFM-Net enhances bronchoscopic image processing by integrating several functional modules. The FFA-Net preprocessing module mitigates image fogging and improves visual clarity for subsequent processing. The feature extraction module derives multi-dimensional features, such as centroids, area, and shape descriptors, from dehazed images. The Faster R-CNN Object detection module detects bronchial regions of interest and… More >

Vidivelli Soundararajan^*, Manikandan Ramachandran^*, Srivatsan Vinodh Kumar

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5259-5277, 2025, DOI:10.32604/cmc.2025.063059 - 19 May 2025

Abstract Many applications, including security systems, medical diagnostics, and human-computer interfaces, depend on eye gaze recognition. However, due to factors including individual variations, occlusions, and shifting illumination conditions, real-world scenarios continue to provide difficulties for accurate and consistent eye gaze recognition. This work is aimed at investigating the potential benefits of employing transfer learning to improve eye gaze detection ability and efficiency. Transfer learning is the process of fine-tuning pre-trained models on smaller, domain-specific datasets after they have been trained on larger datasets. We study several transfer learning algorithms and evaluate their effectiveness on eye gaze… More >

Chunming Tang^*, Yu Wang

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5115-5128, 2025, DOI:10.32604/cmc.2025.062328 - 19 May 2025

Abstract Image dehazing aims to generate clear images critical for subsequent visual tasks. CNNs have made significant progress in the field of image dehazing. However, due to the inherent limitations of convolution operations, it is challenging to effectively model global context and long-range spatial dependencies effectively. Although the Transformer can address this issue, it faces the challenge of excessive computational requirements. Therefore, we propose the FS-MSFormer network, an asymmetric encoder-decoder architecture that combines the advantages of CNNs and Transformers to improve dehazing performance. Specifically, the encoding process employs two branches for multi-scale feature extraction. One branch… More >

Jerome Gacu^1,2,3,*, John Angelo Venus¹, Cleo Faith Forio¹, Leo Banay¹, Eljay Soledad¹, Anabeth Famini¹, April Rose Fajiculay¹, Aprille Ann Sim¹, Jason Rufon¹

Revue Internationale de Géomatique, Vol.34, pp. 235-257, 2025, DOI:10.32604/rig.2025.063512 - 25 April 2025

Abstract The rapid urbanization of rural areas often leads to the construction of medium to high-rise buildings without adequate knowledge of ground suitability, posing significant risks to structural safety and long-term development. This study addresses this critical issue by developing a Comprehensive Ground Suitability Index (CGSI) framework tailored for rural municipalities. Using Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP), the CGSI integrates geophysical, geo-environmental, and geohazard parameters to systematically evaluate land suitability for construction. Data were collected from government agencies, previous studies, and field surveys focusing on the Municipality of Odiongan, Romblon. Parameters… More >

Jie Zou^1,2, Ping Wu^2,*, Jianwei Chen³, Weijie Fan², Yidong Xu²

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 441-471, 2025, DOI:10.32604/sdhm.2024.058864 - 03 April 2025

Abstract As an essential part of the urban infrastructure, underground utility tunnels have a long service life, complex structural performance evolution and dynamic changes both inside and outside the tunnel. These combined factors result in a wide variety of disaster risks during the operation and maintenance phase, which make risk management and control particularly challenging. This work first reviews three common representative disaster factors during the operation and maintenance period: settlement, earthquakes, and explosions. It summarizes the causes of disasters, key technologies, and research methods. Then, it delves into the research on the intelligent operation and More >

Yuxin Zheng, Ke Xu, Baicheng Zhang, Shengxin Guan, Lin Xia, Zhaoge Huang^*

Journal of Polymer Materials, Vol.42, No.1, pp. 237-253, 2025, DOI:10.32604/jpm.2025.059622 - 27 March 2025

Abstract In this manuscript, we conveniently prepared a series of polyester-polycarbonate copolymer (PPC-P)/polybutylene adipate terephthalate (PBAT) blends that exhibit both flame-retardant properties and toughness. Piperazine pyrophosphate (PAPP), melamine phosphate (MPP) and ZnO were used as synergistic flame retardants for PPC-P/PBAT blends. The effects of synergistic flame retardants on thermal stability, combustion behavior and flame retardancy of PPC-P/PBAT blends were investigated. The results showed that when the ratio of PAPP/MPP/ZnO was 18.4:9.2:2.4, the LOI of PPC-P/PBAT composite was 42.8%, and UL-94 reached V-0 level. The results of cone calorimetry showed that the mass loss rate (MLR), the… More >

Xiaojian Chen^1,2,#, Zhujiang Dai^1,#, Qiang Wang³, Wei Chen¹, Yun Liu^1,*, Zhongchuan Wang^1,*

BIOCELL, Vol.49, No.3, pp. 503-518, 2025, DOI:10.32604/biocell.2025.059286 - 31 March 2025

Abstract Background: Nudix Hydrolase 21 (NUDT21) is crucial for the regulation of alternative polyadenylation, with its reduced expression frequently resulting in a shortened mRNA 3^′ untranslated region (UTR), thereby enhancing the protein levels of downstream genes. Although NUDT21 is widely recognized for its tumor-suppressive function in various cancers, its involvement in colorectal cancer (CRC) remains poorly understood. Methods: The expression of NUDT21 in CRC and adjacent normal tissues was analyzed through qPCR, Western blot, and immunohistochemistry (IHC). Additionally, we investigated the correlation between NUDT21 expression and patient prognosis. With Cell Counting Kit-8 assay and Transwell assay, we… More >