Jia Yan Lim^1,2, Siti Madiha Muhammad Amir³, Roslan Yahya³, Marta Peña Fernández², Tze Chuen Yap^1,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-19, 2026, DOI:10.32604/cmc.2025.070707 - 09 December 2025

Abstract Additive Manufacturing, also known as 3D printing, has transformed conventional manufacturing by building objects layer by layer, with material extrusion or fused deposition modeling standing out as particularly popular. However, due to its manufacturing process and thermal nature, internal voids and pores are formed within the thermoplastic materials being fabricated, potentially leading to a decrease in mechanical properties. This paper discussed the effect of printing parameters on the porosity and the mechanical properties of the 3D printed polylactic acid (PLA) through micro-computed tomography (microCT), computational image analysis, and Charpy impact testing. The results for both… More >

Lincong Zhang¹, Yuqing Liu¹, Kefeng Wei², Weinan Zhao¹, Bo Qian^1,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-18, 2026, DOI:10.32604/cmc.2025.069108 - 10 November 2025

Abstract In the field of edge computing, achieving low-latency computational task offloading with limited resources is a critical research challenge, particularly in resource-constrained and latency-sensitive vehicular network environments where rapid response is mandatory for safety-critical applications. In scenarios where edge servers are sparsely deployed, the lack of coordination and information sharing often leads to load imbalance, thereby increasing system latency. Furthermore, in regions without edge server coverage, tasks must be processed locally, which further exacerbates latency issues. To address these challenges, we propose a novel and efficient Deep Reinforcement Learning (DRL)-based approach aimed at minimizing average… More >

Junjun Ren¹, Guoqiang Chen², Zheng-Yi Chai³, Dong Yuan^4,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-26, 2026, DOI:10.32604/cmc.2025.068795 - 10 November 2025

Abstract Vehicle Edge Computing (VEC) and Cloud Computing (CC) significantly enhance the processing efficiency of delay-sensitive and computation-intensive applications by offloading compute-intensive tasks from resource-constrained onboard devices to nearby Roadside Unit (RSU), thereby achieving lower delay and energy consumption. However, due to the limited storage capacity and energy budget of RSUs, it is challenging to meet the demands of the highly dynamic Internet of Vehicles (IoV) environment. Therefore, determining reasonable service caching and computation offloading strategies is crucial. To address this, this paper proposes a joint service caching scheme for cloud-edge collaborative IoV computation offloading. By… More >

Zheng Yao^*, Puqing Chang

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-18, 2026, DOI:10.32604/cmc.2025.068248 - 10 November 2025

Abstract As Internet of Things (IoT) applications expand, Mobile Edge Computing (MEC) has emerged as a promising architecture to overcome the real-time processing limitations of mobile devices. Edge-side computation offloading plays a pivotal role in MEC performance but remains challenging due to complex task topologies, conflicting objectives, and limited resources. This paper addresses high-dimensional multi-objective offloading for serial heterogeneous tasks in MEC. We jointly consider task heterogeneity, high-dimensional objectives, and flexible resource scheduling, modeling the problem as a Many-objective optimization. To solve it, we propose a flexible framework integrating an improved cooperative co-evolutionary algorithm based on More >

Yan Li^1,2,*, Yibin Wu^1,2, Bo Zhang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.12, pp. 2905-2925, 2025, DOI:10.32604/fdmp.2025.072979 - 31 December 2025

Abstract Traditional Computational Fluid Dynamics (CFD) simulations are computationally expensive when applied to complex fluid–structure interaction problems and often struggle to capture the essential flow features governing vortex-induced vibrations (VIV) of floating structures. To overcome these limitations, this study develops a hybrid framework that integrates high-fidelity CFD modeling with deep learning techniques to enhance the accuracy and efficiency of VIV response prediction. First, an unstructured finite-volume fluid–structure coupling model is established to generate high-resolution flow field data and extract multi-component time-series feature tensors. These tensors serve as inputs to a Squeeze-and-Excitation Convolutional Neural Network (SE-CNN), which… More >

Helen Fenske¹, Ingrid R. Niesman^2,*

BIOCELL, Vol.49, No.12, pp. 2433-2455, 2025, DOI:10.32604/biocell.2025.071078 - 24 December 2025

Abstract Objective: Tyrosinase is the rate-limiting enzyme in the generation of melanin. The feline tyrosinase mutation, G302R, confers temperature-sensitive loss of function, resulting in the familiar Siamese cat phenotype. Crystal or cryoEM structures are elusive for any mammalian tyrosinase to date. Protein misfolding is suggested as a basis for phenotypes resulting from mutant tyrosinases, but this hypothesis needs structural confirmation. Our objective for this study is to confirm misfolding of mutant tyrosinase as a basis for temperature-sensitive phenotypes compared to catalytic dysfunction that may be responsible for other tyrosinase mutant breed phenotypes. Methods: We have employed… More >

Asgar Ali^1,*, Nayan Sardar², Poly Karmakar³, Sanatan Das⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3563-3626, 2025, DOI:10.32604/cmes.2025.074082 - 23 December 2025

Abstract Hybrid nanofluids have gained significant attention for their superior thermal and rheological characteristics, offering immense potential in energy conversion, biomedical transport, and electromagnetic flow control systems. Understanding their dynamic behavior under coupled magnetic, rotational, and reactive effects is crucial for the development of efficient thermal management technologies. This study develops a neuro-fuzzy computational framework to examine the dynamics of a reactive Cu–TiO₂–H₂O hybrid nanofluid flowing through a squarely elevated Riga tunnel. The governing model incorporates Hall and ion-slip effects, thermal radiation, and first-order chemical reactions under ramped thermo-solutal boundary conditions and rotational electromagnetic forces. Closed-form analytical… More >

Edward Danso Ansong^*, Simon Bonsu Osei^*, Raphael Adjetey Adjei

Journal of Cyber Security, Vol.7, pp. 533-564, 2025, DOI:10.32604/jcs.2025.061821 - 11 December 2025

Abstract The surge in identity fraud, driven by the rapid adoption of mobile money, internet banking, and e-services during the COVID-19 pandemic, underscores the need for robust cybersecurity solutions. Zero-Knowledge Proofs (ZKPs) enable secure identity verification by allowing individuals to prove possession of a National ID card without revealing sensitive information. This study implements a ZKP-based identity verification system using Camenisch-Lysyanskaya (CL) signatures, reducing reliance on complex trusted setup ceremonies. While a trusted issuer is still required, as assumed in this work, our approach eliminates the need for broader system-wide trusted parameters. We evaluate the system’s More >

Yuxin Wang¹, Youjiang Wang², Jieping Wang², Chao Zhang^1,*, Fanguang Meng³, Linhua Zhang¹, Yongxing Song^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2761-2777, 2025, DOI:10.32604/fdmp.2025.072236 - 01 December 2025

Abstract High-pressure water jet technology has emerged as a highly effective method for removing industrial-scale deposits from pipelines, offering a clean, efficient, and environmentally sustainable alternative to conventional mechanical or chemical cleaning techniques. Among the many parameters influencing its performance, the geometry of the nozzle plays a decisive role in governing jet coherence, impact pressure distribution, and overall cleaning efficiency. In this study, a comprehensive numerical and experimental investigation is conducted to elucidate the influence of nozzle geometry on the behavior of high-pressure water jets. Using Computational Fluid Dynamics (CFD) simulations based on the Volume of… More >

Kashif Ahmed Soomro^1,2,3,*, Rahool Rai^1,3,4, S. R. Qureshi², Sudhakar Kumarasamy^4,5,6, Abdul Hameed Memon¹, Rabiya Jamil¹

Energy Engineering, Vol.122, No.12, pp. 4857-4872, 2025, DOI:10.32604/ee.2025.069847 - 27 November 2025

Abstract Plate heat exchangers suffer from significant energy losses, which adversely affect the overall efficiency of thermal systems. To address this challenge, various heat transfer enhancement techniques have been investigated. Notably, the incorporation of surface corrugations is widely recognized as both effective and practical. Chevron corrugation is the most employed design. However, there remains a need to investigate alternative geometries that may offer superior performance. This study aims to find a novel corrugation design by conducting a comparative CFD analysis of flat, square, chevron, and cylindrical corrugated surfaces, assessing their impact on heat transfer enhancement within… More > Graphic Abstract