Yoshihiro Kanno^1,*, Izuru Takewaki²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 115-152, 2025, DOI:10.32604/cmes.2025.061551 - 11 April 2025

Abstract Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization. This paper provides a review on optimization-based methods for uncertainty analysis, with focusing attention on specific properties of adopted numerical optimization approaches. We collect and discuss the methods based on nonlinear programming, semidefinite programming, mixed-integer programming, mathematical programming with complementarity constraints, difference-of-convex programming, optimization methods using surrogate models and machine learning techniques, and metaheuristics. As a closely related topic, we also overview the methods for assessing structural robustness using non-probabilistic uncertainty modeling. We conclude the paper by drawing several remarks through More >

Hamada Imtara^1,2,*, Feras Abujaber¹, Faady Siouri¹, Aziz Tumeh¹, Bashar Saad²

Phyton-International Journal of Experimental Botany, Vol.94, No.3, pp. 723-737, 2025, DOI:10.32604/phyton.2025.063403 - 31 March 2025

Abstract Traditional Palestinian medicine uses Thymus capitatus (T. capitatus), a plant recognized for its therapeutic properties due to its high concentration of essential oils such as thymol and carvacrol, to treat skin diseases, gastrointestinal disorders, and respiratory infections. The present study was conducted to evaluate the antioxidant and anticancer activities of T. capitatus essential oil (EO). Moreover, this study employed computational methods including ADMET analysis and molecular docking. Using Gas chromatography-mass spectrometry (GC-MS) analysis, the phytochemical composition of T. capitatus essential oil was identified. The DPPH scavenging method was used to assess antioxidant activity. The Michigan Cancer Foundation-7 (MCF-7) and… More >

Aziz Alotaibi^*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3741-3771, 2025, DOI:10.32604/cmc.2025.061998 - 06 March 2025

Abstract Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of data. Recently, both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/decisions. With the growth in popularity of deep learning and ensemble learning algorithms, they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big data. Ensemble deep learning has exhibited significant performance in enhancing learning generalization through… More >

Yaming Ren^1,*, Xing Deng²

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4503-4533, 2025, DOI:10.32604/cmc.2024.059864 - 06 March 2025

Abstract The exponential growth in the scale of power systems has led to a significant increase in the complexity of dispatch problem resolution, particularly within multi-area interconnected power grids. This complexity necessitates the employment of distributed solution methodologies, which are not only essential but also highly desirable. In the realm of computational modelling, the multi-area economic dispatch problem (MAED) can be formulated as a linearly constrained separable convex optimization problem. The proximal point algorithm (PPA) is particularly adept at addressing such mathematical constructs effectively. This study introduces parallel (PPPA) and serial (SPPA) variants of the PPA… More >

Mohamed A.G. Hazber^1,*, Ebrahim Mohammed Senan^2,3, Hezam Saud Alrashidi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3229-3254, 2025, DOI:10.32604/cmes.2025.062302 - 03 March 2025

Abstract Hepatitis is an infection that affects the liver through contaminated foods or blood transfusions, and it has many types, from normal to serious. Hepatitis is diagnosed through many blood tests and factors; Artificial Intelligence (AI) techniques have played an important role in early diagnosis and help physicians make decisions. This study evaluated the performance of Machine Learning (ML) algorithms on the hepatitis data set. The dataset contains missing values that have been processed and outliers removed. The dataset was counterbalanced by the Synthetic Minority Over-sampling Technique (SMOTE). The features of the data set were processed… More >

HYE IN KA^#, SE HWAN MUN^#, SORA HAN^#, YOUNG YANG^*

Oncology Research, Vol.33, No.3, pp. 519-531, 2025, DOI:10.32604/or.2024.056860 - 28 February 2025

Abstract Osteosarcoma is a bone malignancy characterized by strong invasiveness and rapid disease progression. The tumor microenvironment of osteosarcoma contains various types of immune cells, including myeloid-derived suppressor cells, macrophages, T cells, and B cells. Imbalances of these immune cells can promote the proliferation and metastasis of osteosarcoma. Recent studies have indicated a substantial increase in the levels of myeloid-derived suppressor cells, an immune cell associated with immunosuppressive and pro-cancer effects, in the peripheral blood of patients with osteosarcoma. Moreover, the levels of the pro-inflammatory cytokine interleukin 18 are positively correlated with those of myeloid-derived suppressor More >

Huu-Tuong Ho^1,#, Luong Vuong Nguyen^1,#, Minh-Tien Pham¹, Quang-Huy Pham¹, Quang-Duong Tran¹, Duong Nguyen Minh Huy², Tri-Hai Nguyen^3,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1733-1756, 2025, DOI:10.32604/cmc.2025.060363 - 17 February 2025

Abstract In multimodal learning, Vision-Language Models (VLMs) have become a critical research focus, enabling the integration of textual and visual data. These models have shown significant promise across various natural language processing tasks, such as visual question answering and computer vision applications, including image captioning and image-text retrieval, highlighting their adaptability for complex, multimodal datasets. In this work, we review the landscape of Bootstrapping Language-Image Pre-training (BLIP) and other VLM techniques. A comparative analysis is conducted to assess VLMs’ strengths, limitations, and applicability across tasks while examining challenges such as scalability, data quality, and fine-tuning complexities. More >

Jeng-Shyang Pan^1,2, Na Yu¹, Shu-Chuan Chu^1,*, An-Ning Zhang¹, Bin Yan³, Junzo Watada⁴

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2495-2520, 2025, DOI:10.32604/cmc.2024.058450 - 17 February 2025

Abstract The widespread adoption of cloud computing has underscored the critical importance of efficient resource allocation and management, particularly in task scheduling, which involves assigning tasks to computing resources for optimized resource utilization. Several meta-heuristic algorithms have shown effectiveness in task scheduling, among which the relatively recent Willow Catkin Optimization (WCO) algorithm has demonstrated potential, albeit with apparent needs for enhanced global search capability and convergence speed. To address these limitations of WCO in cloud computing task scheduling, this paper introduces an improved version termed the Advanced Willow Catkin Optimization (AWCO) algorithm. AWCO enhances the algorithm’s… More >

JINGWEI JIANG^1,2, BO JIA³, CHUAN WANG³, CHEN FANG¹, YUGUI LI¹, GUOXING LING¹, BAOSHI ZHENG^1,*, CHENG LUO^1,*

BIOCELL, Vol.49, No.1, pp. 61-78, 2025, DOI:10.32604/biocell.2024.056981 - 24 January 2025

Abstract The role and regulatory mechanisms of macrophage polarization in cardiac transplantation have gained significant attention. Macrophages can polarize into either the M1 (pro-inflammatory) or M2 (anti-inflammatory) phenotype in response to environmental cues. M1 macrophages facilitate transplant rejection by releasing inflammatory mediators and activating T cells, whereas M2 macrophages support graft survival by secreting anti-inflammatory factors and promoting tissue repair. Mitochondrial quality control regulation plays a crucial role in macrophage polarization, which may influence graft survival and immune responses. This review provides an overview of the current understanding of mitochondrial quality control-regulated macrophage polarization in cardiac More >

Ghulam E Mustafa Abro^1,*, Ayman M Abdallah^1,2, Faizan Zahid³, Saleem Ahmed⁴

Intelligent Automation & Soft Computing, Vol.40, pp. 99-123, 2025, DOI:10.32604/iasc.2025.060364 - 23 January 2025

Abstract This review synthesises and assesses the most recent developments in Unmanned Aerial Vehicles (UAVs) and swarm robotics, with a specific emphasis on optimisation strategies, path planning, and formation control. The study identifies key methodologies that are driving progress in the field by conducting a comprehensive analysis of seven critical publications. The following are included: sensor-based platforms that facilitate effective obstacle avoidance, cluster-based hierarchical path planning for efficient navigation, and adaptive hybrid controllers for dynamic environments. The review emphasises the substantial contribution of optimisation techniques, including Max-Min Ant Colony Optimisation (MMACO), to the improvement of convergence… More >