Dandan Wang^*, Jiaxin Chen, Yanwen Zhang

Phyton-International Journal of Experimental Botany, Vol.94, No.4, pp. 1137-1158, 2025, DOI:10.32604/phyton.2025.063894 - 30 April 2025

Abstract Taxus cuspidata, a rare species of the Taxus genus, and its wild resources are under severe threat. The development of cultivated species has become an important strategy to replace wild species. The objective of this work was to elucidate the differences in secondary metabolite accumulation, particularly in the paclitaxel biosynthesis pathway, between wild and cultivated species. This study employed liquid chromatography-tandem mass spectrometry (LC-MS/MS) and RNA sequencing (RNA-Seq) technologies to conduct integrated metabolomic and transcriptomic analyses of wild and cultivated species of T. cuspidata. The results showed that the content of paclitaxel in cultivated species was significantly higher… More >

Pikkili Gopala Krishna^1,*, Jalari Somasekar²

Intelligent Automation & Soft Computing, Vol.40, pp. 235-259, 2025, DOI:10.32604/iasc.2025.063657 - 28 April 2025

Abstract Stress is mental tension caused by difficult situations, often experienced by hospital workers and IT professionals who work long hours. It is essential to detect the stress in shift workers to improve their health. However, existing models measure stress with physiological signals such as PPG, EDA, and blink data, which could not identify the stress level accurately. Additionally, the works face challenges with limited data, inefficient spatial relationships, security issues with health data, and long-range temporal dependencies. In this paper, we have developed a federated learning-based stress detection system for IT and hospital workers, integrating… More >

Yumei Lv¹, Wei Dai², Shupeng Xie¹, Peng Hu^1,*, Fei He^1,*

Frontiers in Heat and Mass Transfer, Vol.23, No.2, pp. 397-420, 2025, DOI:10.32604/fhmt.2025.062781 - 25 April 2025

Abstract Aiming at the global design issue of transpiration cooling thermal protection system, a self-driven circulation loop is proposed as the internal coolant flow passage for the transpiration cooling structure to achieve adaptive cooling. To enhance the universality of this internal cooling pipe design and facilitate its application, numerical studies are conducted on this system with four commonly used cooling mediums as coolant. Firstly, the accuracy of the numerical method is verified through an established experimental platform. Then, transient numerical simulations are performed on the flow states of different cooling mediums in the new self-circulation system. More >

Bushra Tayyaba¹, Muhammad Usman Ghani Khan^1,2,3, Talha Waheed², Shaha Al-Otaibi⁴, Tanzila Saba^3,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2851-2864, 2025, DOI:10.32604/cmc.2025.060365 - 16 April 2025

Abstract Reference Evapotranspiration (ETo) is widely used to assess total water loss between land and atmosphere due to its importance in maintaining the atmospheric water balance, especially in agricultural and environmental management. Accurate estimation of ETo is challenging due to its dependency on multiple climatic variables, including temperature, humidity, and solar radiation, making it a complex multivariate time-series problem. Traditional machine learning and deep learning models have been applied to forecast ETo, achieving moderate success. However, the introduction of transformer-based architectures in time-series forecasting has opened new possibilities for more precise ETo predictions. In this study,… More >

Jahanzaib Latif ¹, Ahsan Wajahat¹, Alishba Tahir², Anas Bilal^3,*, Mohammed Zakariah⁴, Abeer Alnuaim⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 539-567, 2025, DOI:10.32604/cmes.2025.062301 - 11 April 2025

Abstract Glaucoma, a leading cause of blindness, demands early detection for effective management. While AI-based diagnostic systems are gaining traction, their performance is often limited by challenges such as varying image backgrounds, pixel intensity inconsistencies, and object size variations. To address these limitations, we introduce an innovative, nature-inspired machine learning framework combining feature excitation-based dense segmentation networks (FEDS-Net) and an enhanced gray wolf optimization-supported support vector machine (IGWO-SVM). This dual-stage approach begins with FEDS-Net, which utilizes a fuzzy integral (FI) technique to accurately segment the optic cup (OC) and optic disk (OD) from retinal images, even More >

Saleh Albahli^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1095-1128, 2025, DOI:10.32604/cmes.2025.058821 - 11 April 2025

Abstract Predicting hospital readmission and length of stay (LOS) for diabetic patients is critical for improving healthcare quality, optimizing resource utilization, and reducing costs. This study leverages machine learning algorithms to predict 30-day readmission rates and LOS using a robust dataset comprising over 100,000 patient encounters from 130 hospitals collected over a decade. A comprehensive preprocessing pipeline, including feature selection, data transformation, and class balancing, was implemented to ensure data quality and enhance model performance. Exploratory analysis revealed key patterns, such as the influence of age and the number of diagnoses on readmission rates, guiding the More >

Jeng-Shyang Pan^1,2,3, Mengfei Zhang¹, Shu-Chuan Chu^2,*, Xingsi Xue⁴, Václav Snášel⁵

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 475-496, 2025, DOI:10.32604/cmc.2025.060170 - 26 March 2025

Abstract Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data analysis. Traditional clustering algorithms, such as K-means, are widely used due to their simplicity and efficiency. This paper proposes a novel Spiral Mechanism-Optimized Phasmatodea Population Evolution Algorithm (SPPE) to improve clustering performance. The SPPE algorithm introduces several enhancements to the standard Phasmatodea Population Evolution (PPE) algorithm. Firstly, a Variable Neighborhood Search (VNS) factor is incorporated to strengthen the local search capability and foster population diversity. Secondly, a position update model, incorporating a spiral mechanism, is… More >

Qinglei Zhang, Bai Hu^*, Jiyun Qin, Jianguo Duan, Ying Zhou

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1257-1273, 2025, DOI:10.32604/cmc.2025.059955 - 26 March 2025

Abstract Grasping is one of the most fundamental operations in modern robotics applications. While deep reinforcement learning (DRL) has demonstrated strong potential in robotics, there is too much emphasis on maximizing the cumulative reward in executing tasks, and the potential safety risks are often ignored. In this paper, an optimization method based on safe reinforcement learning (Safe RL) is proposed to address the robotic grasping problem under safety constraints. Specifically, considering the obstacle avoidance constraints of the system, the grasping problem of the manipulator is modeled as a Constrained Markov Decision Process (CMDP). The Lagrange multiplier… More >

Prathap Sarma¹, Palesa Mogane^2,*, Katharina Vanderdonck³, Moses Kebalepile¹, Palesa Motshabi Chakane⁴

Congenital Heart Disease, Vol.20, No.1, pp. 41-53, 2025, DOI:10.32604/chd.2025.060382 - 18 March 2025

Abstract Background: Congenital cardiac diseases (CCD) are common congenital birth defects that require high-risk surgery. Outcomes following congenital cardiac surgery in children living in high-income countries (HIC) have been documented, but little is known from the African continent. This study aimed to determine factors associated with perioperative mortality in patients who underwent congenital cardiac surgery at our institution. Methods: This retrospective, cross-sectional study was conducted at Charlotte Maxeke Johannesburg Academic Hospital over 12 years (2006–2017). A multivariable regression analysis was performed for the factors which had a p-value of 0.1 and less in the univariable regression analysis. A… More >

Mian Xia^1,2, Baoguo Xie^3,4, Lijun He^5,*, Jingru Chen⁶

International Journal of Mental Health Promotion, Vol.27, No.2, pp. 231-240, 2025, DOI:10.32604/ijmhp.2025.058878 - 03 March 2025

Abstract Objectives: Recently, how family-related factors influence employees’ mental health has garnered increasing attention from researchers and practitioners. Drawing on the cognitive appraisal theory of stress, this study aims to examine how and when family financial stress affects the employees’ mental health and investigate the mediating role of performance stress and the moderating role of workplace competition. Methods: A cross-sectional survey was conducted with 23,520 Chinese employees by using a voluntary and anonymous structured questionnaire, which included family financial stress, performance stress, symptom checklist 90 (SCL-90) scale, and workplace competition. The data were analyzed using SPSS… More >