Heng Cheng¹, Yichen Yang¹, Yumin Cheng^2,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.073178

Abstract The element-free Galerkin (EFG) method, which constructs shape functions via moving least squares (MLS) approximation, represents a fundamental and widely studied meshless method in numerical computation. Although it achieves high computational accuracy, the shape functions are more complex than those in the conventional finite element method (FEM), resulting in great computational requirements. Therefore, improving the computational efficiency of the EFG method represents an important research direction. This paper systematically reviews significant contributions from domestic and international scholars in advancing the EFG method. Including the improved element-free Galerkin (IEFG) method, various interpolating EFG methods, four distinct More >

Guo-Zhi Li¹, Hua-Ping Wang^1,2,*, Si-Kai Wang¹, Jing-Cheng Zhou¹, Ping Xiang^3,4,*

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.072750

Abstract Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity. A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential, as it offers intuitive insights into parametric influences and facilitates enhanced structural performance. This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures. By establishing a two-dimensional composite pavement model, it investigates load transfer characteristics and validates the accuracy through finite element simulation. The proposed method offers a straightforward analytical approach… More >

Shuoting Xiao^1,*, Nikita Igorevich Fomin¹, Kirill Anatolyevich Khvostunkov², Chong Liu¹

CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2025.071961

Abstract Precast concrete structures have gained popularity due to their advantages. However, the seismic performance of their connection joints remains an area of ongoing research and improvement. Grouted Sleeve Connection (GSC) offers a solution for connecting reinforcements in precast components, but their vulnerability to internal defects, such as construction errors and material variability, can significantly impact performance. This article presents a finite element analysis (FEA) to evaluate the impact of internal grouting defects in GSC on the structural performance of precast reinforced concrete columns. Four finite element models representing GSC with varying degrees of defects were… More > Graphic Abstract

Chao Li^1,3,#, Jianing Wang^1,3,#, Caichang Ding^2,*, Zhiwei Ye^1,3

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.071242

Abstract Underwater images frequently suffer from chromatic distortion, blurred details, and low contrast, posing significant challenges for enhancement. This paper introduces AquaTree, a novel underwater image enhancement (UIE) method that reformulates the task as a Markov Decision Process (MDP) through the integration of Monte Carlo Tree Search (MCTS) and deep reinforcement learning (DRL). The framework employs an action space of 25 enhancement operators, strategically grouped for basic attribute adjustment, color component balance, correction, and deblurring. Exploration within MCTS is guided by a dual-branch convolutional network, enabling intelligent sequential operator selection. Our core contributions include: (1) a More >

Atheer Aleran¹, Hanan Almukhalfi¹, Ayman Noor¹, Reyadh Alluhaibi², Abdulrahman Hafez³, Talal H. Noor^1,*

CMC-Computers, Materials & Continua, DOI:10.32604/cmc.2025.070741

Abstract Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs. Conventional maintenance methods, such as reactive maintenance (i.e., run to failure) or time-based preventive maintenance (i.e., scheduled servicing), prove ineffective for complex systems with many Internet of Things (IoT) devices and sensors because they fall short in detecting faults at early stages when it is most crucial. This paper presents a predictive maintenance framework based on a hybrid deep learning model that integrates the capabilities of Long Short-Term Memory (LSTM) Networks and Convolutional Neural Networks (CNNs). The framework… More >

Xiansong Xie^1,*, Xiaoqian Qian²

Structural Durability & Health Monitoring, DOI:10.32604/sdhm.2025.074148

Abstract Correlation function of acceleration responses-based damage identification methods has been developed and employed, while they still face the difficulty in identifying local or minor structural damages. To deal with this issue, a robust structural damage identification method is developed, integrating a modified holistic swarm optimization (MHSO) algorithm with a hybrid objective function. The MHSO is developed by combining Hammersley sequence-based population initialization, chaotic search around the worst solution, and Hooke-Jeeves pattern search around the best solution, thereby improving both global exploration and local exploitation capabilities. A hybrid objective function is constructed by merging acceleration correlation… More >

Luksamee Vittaya^1,*, Chakhriya Chalad¹, Sittichoke Janyong², Nararak Leesakul³

Phyton-International Journal of Experimental Botany, DOI:10.32604/phyton.2025.074891

Abstract Calophyllum inophyllum is a tropical plant that could have useful medicinal properties for pharmaceutical and cosmetic applications. The present study extracted the flower, fruit, leaf, twig, and bark of the plant by maceration in different organic solvents. The correlation between bioactive compounds and their biological activities was investigated, with emphasis on their therapeutic relevance through in silico pharmacokinetic predictions using SwissADME. Qualitative and quantitative analyses were conducted to determine the total phenolic, flavonoid, and saponin contents of the extracts. Spectral analysis of the extracts revealed –OH, C=O, C=C, and C–H functional groups. The antioxidant activity of the… More > Graphic Abstract

Sha Hu^1,2,#, Wenjing Wang^1,#, Qianfang Hu^3,#, Rujuan Zheng^1,2, Qinghe Huang^1,2, Hui Shi^1,2, Xinyuan Ding^3,*, Wenjuan Wang^1,2,*, Zengyan Zhu^1,2,*

Oncology Research, DOI:10.32604/or.2025.068967

Abstract Objectives: Acquired resistance to paclitaxel represents a critical barrier to the effective chemotherapy of non-small cell lung cancer (NSCLC). The present study aimed to elucidate the molecular and pharmacological mechanisms promoting paclitaxel resistance in NSCLC and to explore potential strategies for overcoming this resistance. Methods: Here, we report an integrated pharmacological and analytical approach to quantify paclitaxel disposition and overcome resistance in a A549/TAX cell model (paclitaxel-resistant A549 cells). Results: Cell counting kit-8 (CCK-8) assay, colony formation, and apoptosis assays confirmed that A549/TAX cells exhibited marked resistance to paclitaxel relative to parental A549 cells. Based on… More >

Lingyan Zhang^*, Yuying Yang, Zhuoxuan Huang

International Journal of Mental Health Promotion, DOI:10.32604/ijmhp.2025.073988

Abstract Objectives: Psychological resilience is a critical resource for vocational high school students navigating social biases and fostering mental well-being. This six-month longitudinal study investigated the developmental trajectories of discrimination perception, vocational identity, and psychological resilience in this population. It further examined the longitudinal mediating role of vocational identity in the relationship between discrimination perception and psychological resilience. Methods: A total of 526 students from five vocational high schools in Guangdong, China, were assessed via convenience sampling at two time points: baseline (T1, September 2023) and six-month follow-up (T2, March 2024). Measures of discrimination perception, psychological resilience,… More >

Xiaoyan Zhuo¹, Yukun Ji¹, Yatao Ren^1,*, Xuehui Wang², Hong Qi¹

Frontiers in Heat and Mass Transfer, DOI:10.32604/fhmt.2025.074045

Abstract Flow and heat transfer characteristics during droplet impact on hot walls are pivotal for elucidating the mechanisms of spray cooling and exploring pathways for heat transfer enhancement. When the wall temperature exceeds the Leidenfrost point, a vapor film forms between the droplet and the wall, rendering the heat transfer process highly complex. Furthermore, for droplet impact on curved walls, the presence of curvature introduces additional factors that modify the spreading behavior of the droplet and necessitate in-depth analysis. Therefore, this work investigates the flow and heat transfer dynamics of droplet impact on hot planes and… More >