Jin Wang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.011894

Abstract Shape-memory elastomers (SMEs) have emerged as promising smart-materials platforms for soft actuators and intelligent structures due to their programmable thermally-induced reversible shape transformations. However, four critical scientific and technological challenges impede their practical engineering implementation. First, the thermodynamic and molecular mechanisms governing their thermomechanical behavior remain incompletely elucidated. Second, achieving large reversible deformations requires retention of molecular orientation during thermal actuation cycles- a persistent challenge given their large strain recovery at the heating temperature. Third, while biological muscles achieve sub-second actuation, current SME systems exhibit response times spanning several seconds, necessitating at least one order More >

Barkilean Jaismitha¹, Jagadeesan Sasikumar^2,*, Samad Noeiaghdam^3,*, Unai Fernandez-Gamiz⁴, Thirugnanasambandam Arunkumar¹

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1529-1554, 2025, DOI:10.32604/fhmt.2025.067869 - 31 October 2025

Abstract The present study investigates the dynamic behavior of a ternary-hybrid nanofluid within a tapered asymmetric channel, focusing on the impact of unsteady oscillatory flow under the influence of a magnetic field. This study addresses temperature-sensitive water transport mechanisms relevant to industrial applications such as thermal management and energy-efficient fluid transport. By suspending nanoparticles of diverse shapes-platelets, blades, and spheres in a hybrid base fluid comprising cobalt ferrite, magnesium oxide, and graphene oxide, the study examines the influence of both small and large volume fraction values. The governing equations are converted into a dimensionless form. With More >

Muhammad Sajid Farooq¹, Muhammad Saleem², M.A. Khan^3,4, Muhammad Farrukh Khan⁵, Shahan Yamin Siddiqui⁶, Muhammad Shoukat Aslam⁷, Khan M. Adnan^8,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5183-5206, 2025, DOI:10.32604/cmc.2025.069641 - 23 October 2025

Abstract The rapid evolution of smart cities through IoT, cloud computing, and connected infrastructures has significantly enhanced sectors such as transportation, healthcare, energy, and public safety, but also increased exposure to sophisticated cyber threats. The diversity of devices, high data volumes, and real-time operational demands complicate security, requiring not just robust intrusion detection but also effective feature selection for relevance and scalability. Traditional Machine Learning (ML) based Intrusion Detection System (IDS) improves detection but often lacks interpretability, limiting stakeholder trust and timely responses. Moreover, centralized feature selection in conventional IDS compromises data privacy and fails to… More >

Tiren Huang, Chong Luo, Xu Li^*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5847-5865, 2025, DOI:10.32604/cmc.2025.067986 - 23 October 2025

Abstract Automatic pancreas segmentation in CT scans is crucial for various medical applications including early disease detection, treatment planning and therapeutic evaluation. However, the pancreas’s small size, irregular morphology, and low contrast with surrounding tissues make accurate pancreas segmentation still a challenging task. To address these challenges, we propose a novel RPMS-DSAUnet for accurate automatic pancreas segmentation in abdominal CT images. First, a Residual Pyramid Squeeze Attention module enabling hierarchical multi-resolution feature extraction with dynamic feature weighting and selective feature reinforcement capabilities is integrated into the backbone network, enhancing pancreatic feature extraction and improving localization accuracy.… More >

Pasi Fränti^1,*, Claude Cariou², Qinpei Zhao³

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4687-4704, 2025, DOI:10.32604/cmc.2025.066534 - 23 October 2025

Abstract K-means uses the sum-of-squared error as the objective function to minimize within-cluster distances. We show that, as a consequence, it also maximizes between-cluster variances. This means that the two measures do not provide complementary information and that using only one is enough. Based on this property, we propose a new objective function called cluster overlap, which is measured intuitively as the proportion of points shared between the clusters. We adopt the new function within k-means and present an algorithm called overlap k-means. It is an alternative way to design a k-means algorithm. A localized variant is also More >

Lan Luo¹, Yun Shen¹, Zuntao Gu², Linbing Wang¹, Shijian Sun^3,*

Journal of Psychology in Africa, Vol.35, No.5, pp. 713-721, 2025, DOI:10.32604/jpa.2025.066529 - 24 October 2025

Abstract This cross-sectional study examined how parenting styles influence college students’ romantic attitudes through para-social relationships. A total of 571 college students (females = 71.2%) completed the Short-form Parenting Style Scale, the Para-social Relationship Scale, and the Questionnaire on College Students’ View of Marriage and Love. Mediation was examined with bootstrap-corrected structural equation modelling (5000 resamples). Results indicated that maternal rejection (indirect effect β = −0.019, 95% CI = −0.055–−0.001, p < 0.05) and overprotection (indirect effect β = −0.02, 95% CI = −0.055–−0.001, p < 0.05) indirectly undermined college students’ marriage views by intensifying para-social relationships, whereas More >

Jiaqi Lu¹, Fang Wang^2,*

Journal of Psychology in Africa, Vol.35, No.5, pp. 651-659, 2025, DOI:10.32604/jpa.2025.066088 - 24 October 2025

Abstract This study explores parenting and family adjustment profile effects on toddler socioemotional competence by the underlying mechanisms of effortful control. Participants were Chinese parent caregivers (N = 448) of 448 toddlers aged 15–36 months. They completed measures of parenting and family adjustment, toddler socioemotional competence, and effortful control. Latent profile analysis (LPA) identified three family profiles—Strict-Detached, Constrained-Collaborative, and Harmonious-Aligned. These three profiles of parenting and family adjustment directly affect toddler socioemotional competence through variations in emotional support, discipline strategies, and parent–child interactions. Effortful control mediates this relationship of parenting and family adjustment and toddler socioemotional More >

Sheng Bi^1,2,*, Jiayan Wang¹, Dong Su¹, Hui Lu¹, Yu Zhang¹

Energy Engineering, Vol.122, No.10, pp. 4135-4151, 2025, DOI:10.32604/ee.2025.066735 - 30 September 2025

Abstract By comparing price plans offered by several retail energy firms, end users with smart meters and controllers may optimize their energy use cost portfolios, due to the growth of deregulated retail power markets. To help smart grid end-users decrease power payment and usage unhappiness, this article suggests a decision system based on reinforcement learning to aid with electricity price plan selection. An enhanced state-based Markov decision process (MDP) without transition probabilities simulates the decision issue. A Kernel approximate-integrated batch Q-learning approach is used to tackle the given issue. Several adjustments to the sampling and data… More >

Sen Yang¹, Jie Zhong¹, Boyu Gan¹, Yi Sun¹, Changming Bu¹, Mingtao Zhang¹, Jiehong Li^1,*, Yang Yu^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2943-2967, 2025, DOI:10.32604/cmes.2025.067282 - 30 September 2025

Abstract Foam concrete is widely used in engineering due to its lightweight and high porosity. Its compressive strength, a key performance indicator, is influenced by multiple factors, showing nonlinear variation. As compressive strength tests for foam concrete take a long time, a fast and accurate prediction method is needed. In recent years, machine learning has become a powerful tool for predicting the compressive strength of cement-based materials. However, existing studies often use a limited number of input parameters, and the prediction accuracy of machine learning models under the influence of multiple parameters and nonlinearity remains unclear.… More >

José Luis Rodríguez-Lorenzo¹, Bohuslav Janoušek¹, Emilio Cervantes^2,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2649-2667, 2025, DOI:10.32604/phyton.2025.068936 - 30 September 2025

Abstract Grapevine is unique among crops because its domestication resulted not only in new morphological characteristics, but also in altered reproductive mechanisms. Viticulture involves a change from a dioecious to a hermaphroditic mating system, which makes the reproductive system more efficient. In consequence and the fact that it is one of the oldest and most economically important cultivated plants, Vitis vinifera could be defined as an over-domesticated species. Here we review some key aspects in viticulture. The main areas of interest have remained consistent throughout history, including the origin and characterisation of cultivars, resistance to environmental conditions,… More >