Binchang Ma¹, Xinhai Yu², Gang Huang^3,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.071320 - 10 November 2025

Abstract Vacancy defects, as fundamental disruptions in metallic lattices, play an important role in shaping the mechanical and electronic properties of aluminum crystals. However, the influence of vacancy position under coupled thermomechanical fields remains insufficiently understood. In this study, transmission and scanning electron microscopy were employed to observe dislocation structures and grain boundary heterogeneities in processed aluminum alloys, suggesting stress concentrations and microstructural inhomogeneities associated with vacancy accumulation. To complement these observations, first-principles calculations and molecular dynamics simulations were conducted for seven single-vacancy configurations in face-centered cubic aluminum. The stress response, total energy, density of states More >

Abdullah Alourani¹, Mehtab Alam^2,*, Ashraf Ali³, Ihtiram Raza Khan⁴, Chandra Kanta Samal²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-32, 2026, DOI:10.32604/cmc.2025.070161 - 10 November 2025

Abstract The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management. Earlier approaches have often advanced one dimension—such as Internet of Things (IoT)-based data acquisition, Artificial Intelligence (AI)-driven analytics, or digital twin visualization—without fully integrating these strands into a single operational loop. As a result, many existing solutions encounter bottlenecks in responsiveness, interoperability, and scalability, while also leaving concerns about data privacy unresolved. This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing, distributed intelligence, and simulation-based decision support. The… More >

Yafei Liu^1,2, Yuling Chen^1,2,*, Xuewei Wang³, Yuxiang Yang², Chaoyue Tan²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.069152 - 10 November 2025

Abstract As blockchain technology rapidly evolves, smart contracts have seen widespread adoption in financial transactions and beyond. However, the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems. Although numerous detection techniques have been proposed, existing methods suffer from significant limitations, such as class imbalance and insufficient modeling of transaction-related semantic features. To address these challenges, this paper proposes an oversampling-based detection framework for Ponzi smart contracts. We enhance the Adaptive Synthetic Sampling (ADASYN) algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions. This enhancement facilitates the… More >

Manzhu Liao¹, Lan Yang¹, Liehua Tie¹, Qiqiang Guo^1,*, Weilie Zheng^2,*, Jiangrong Li², Yongxia Li²

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3633-3652, 2025, DOI:10.32604/phyton.2025.072725 - 01 December 2025

Abstract Cupressus gigantea is an endemic endangered tree species in the Tibet Plateau, and studying the survival status of the different C. gigantea populations and revealing the main environmental factors that affect the population survival are particularly significant for the conservation and sustainable development of endangered species. Based on the 28 sample plots, the Hierarchical Cluster Method was used to classify the C. gigantea populations into four community types. Age structure diagrams were drawn based on the structure of each community, static life tables and survival curves were compiled, and the future development trends of each age group in… More >

Chirag Devendrakumar Parikh^*

Journal on Artificial Intelligence, Vol.7, pp. 571-584, 2025, DOI:10.32604/jai.2025.073765 - 01 December 2025

Abstract With the increasing complexity and scale of hyperscale data centers, the requirement for intelligent, real-time power delivery has never been more critical to ensure uptime, energy efficiency, and sustainability. Those techniques are typically static, reactive (since CPU and workload scaling is applied to performance events that occur after a request has been submitted, and is thus can be classified as a reactive response.), and require manual operation, and cannot cope with the dynamic nature of the workloads, the distributed architectures as well as the non-uniform energy sources in today’s data centers. In this paper, we… More >

Zhenzhen Shen^1,2, Kang Yang², Dengfeng Wei², Quansheng Liang², Zhenpeng Ma², Hong Wang², Keyu Wang², Chunwei Zhang², Xiaohu Yang^3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2741-2760, 2025, DOI:10.32604/fdmp.2025.070395 - 01 December 2025

Abstract The rapid prediction of seepage mass flow in soil is essential for understanding fluid transport in porous media. This study proposes a new method for fast prediction of soil seepage mass flow by combining mesoscopic modeling with deep learning. Porous media structures were generated using the Quartet Structure Generation Set (QSGS) method, and a mesoscopic-scale seepage calculation model was applied to compute flow rates. These results were then used to train a deep learning model for rapid prediction. The analysis shows that larger average pore diameters lead to higher internal flow velocities and mass flow More >

Yan Wang^1,2,*, Fuqiang Zhang¹, Long An¹, Bo Wang¹, Xueya Yang¹, Jie Jin^3,4

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2651-2671, 2025, DOI:10.32604/fdmp.2025.070122 - 01 December 2025

Abstract A downburst is a strong downdraft generated by intense thunderstorm clouds, producing radially divergent and highly destructive winds near the ground. Its characteristic scales are expressed through random variations in jet height, velocity, and diameter during an event. In this study, a reduced-scale parked wind turbine is exposed to downburst wind fields to investigate the resulting extreme wind loads. The analysis emphasizes both the flow structure of downbursts and the variations of surface wind pressure on turbine blades under different jet parameters. Results show that increasing jet velocity markedly enhances the maximum horizontal wind speed,… More > Graphic Abstract

Yang Dou¹, Hao Qin¹, Yuzhi Zhang^1,2, Ning Wang¹, Haiqing Liu^3,4, Wanli Yang^1,2,4,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2673-2700, 2025, DOI:10.32604/fdmp.2025.069719 - 01 December 2025

Abstract In recent years, tuned liquid dampers (TLDs) have attracted significant research interest; however, overall progress has been limited due to insufficient understanding of the mechanisms governing sloshing-induced loads. In particular, it remains unclear whether the water in aqueducts—common water-diversion structures in many countries—can serve as an effective TLD. This study investigates the generation mechanisms of sloshing loads during the first-order transverse resonance of water in a U-shaped aqueduct using a two-dimensional (2D) numerical model. The results reveal that, at the equilibrium position, the free surface difference between the left and right walls, the horizontal force… More >

Maysaa Al-Qurashi¹, Ayesha Siddiqa², Shazia Karim³, Yu-Ming Chu^4,5,*, Saima Rashid^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2057-2129, 2025, DOI:10.32604/cmes.2025.071629 - 26 November 2025

Abstract Chikungunya is a mosquito-borne viral infection caused by the chikungunya virus (CHIKV). It is characterized by acute onset of high fever, severe polyarthralgia, myalgia, headache, and maculopapular rash. The virus is rapidly spreading and may establish in new regions where competent mosquito vectors are present. This research analyzes the regulatory dynamics of a stochastic differential equation (SDE) model describing the transmission of the CHIKV, incorporating seasonal variations, immunization efforts, and environmental fluctuations modeled through Poisson random measure noise under demographic heterogeneity. The model guarantees the existence of a global positive solution and demonstrates periodic dynamics… More >

Seong-Su Yoon, Dong-Hyuk Shin, Ieck-Chae Euom^*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2683-2706, 2025, DOI:10.32604/cmes.2025.071577 - 26 November 2025

Abstract With the continuous expansion of digital infrastructures, malicious behaviors in host systems have become increasingly sophisticated, often spanning multiple processes and employing obfuscation techniques to evade detection. Audit logs, such as Sysmon, offer valuable insights; however, existing approaches typically flatten event sequences or rely on generic graph models, thereby discarding the natural parent-child process hierarchy that is critical for analyzing multiprocess attacks. This paper proposes a structure-aware threat detection framework that transforms audit logs into a unified two-dimensional (2D) spatio-temporal representation, where process hierarchy is modeled as the spatial axis and event chronology as the More >