Yuyao Huang, Hui Shu, Fei Kang^*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071552 - 12 January 2026

Abstract Message structure reconstruction is a critical task in protocol reverse engineering, aiming to recover protocol field structures without access to source code. It enables important applications in network security, including malware analysis and protocol fuzzing. However, existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery, resulting in imprecise and incomplete reconstructions. In this paper, we propose ProRE, a novel method for reconstructing protocol field structures based on program execution slice embedding. ProRE extracts code slices from protocol parsing at runtime, converts them into embedding vectors using a data flow-sensitive assembly language model, More >

Yongbo Jiang, Shengnan Huang, Tao Feng, Baofeng Duan^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-22, 2026, DOI:10.32604/cmc.2025.069423 - 10 November 2025

Abstract In the context of modern software development characterized by increasing complexity and compressed development cycles, traditional static vulnerability detection methods face prominent challenges including high false positive rates and missed detections of complex logic due to their over-reliance on rule templates. This paper proposes a Syntax-Aware Hierarchical Attention Network (SAHAN) model, which achieves high-precision vulnerability detection through grammar-rule-driven multi-granularity code slicing and hierarchical semantic fusion mechanisms. The SAHAN model first generates Syntax Independent Units (SIUs), which slices the code based on Abstract Syntax Tree (AST) and predefined grammar rules, retaining vulnerability-sensitive contexts. Following this, through More >

Xiulong Yao¹, Mengge Yu^1,*, Jiali Liu², Qian Zhang¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2795-2814, 2025, DOI:10.32604/fdmp.2025.072708 - 01 December 2025

Abstract High-speed trains operating in freezing rain are highly susceptible to severe ice accretion in the pantograph region, which compromises both power transmission efficiency and dynamic performance. To elucidate the underlying mechanisms of this phenomenon, an Euler–Euler multiphase flow model was employed to simulate droplet impingement and collection on the pantograph surface, while a glaze-ice formation model incorporating wall film dynamics was used to capture the subsequent growth of ice. The effects of key parameters—including liquid water content, ambient temperature, train velocity, and droplet diameter—on the amount and morphology of ice were systematically investigated. The results More >

Jin Zhu^1,2,*, Yanxin Xu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2849-2872, 2025, DOI:10.32604/cmes.2025.070287 - 30 September 2025

Abstract Ice accretion on structures such as aircraft wings and wind turbine blades poses serious risks to aerodynamic performance and operational safety, particularly in cold and humid environments. This study conducts numerical simulations of ice formation on thin flat plates using CFD and FENSAP-ICE, exploring how air temperature, wind velocity, and angle of attack (AOA) affect icing behavior and aerodynamic characteristics. Results indicate that ice thickness increases linearly over time. Rime ice forms at low temperatures due to immediate droplet freezing, whereas glaze ice develops at higher temperatures when a water film forms and subsequently refreezes… More >

Chunling Yan^1,2, Renzhang Yan^1,2,*, Zhenxiu Zhan¹, Xiyang Chen¹, Yu Han³

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 1037-1056, 2025, DOI:10.32604/sdhm.2025.058780 - 30 June 2025

Abstract The steel tube arch rib in a large-span concrete-filled steel tube arch bridge has a large span and diameter, which also leads to a larger weld seam scale. Large-scale welding seams will inevitably cause more obvious welding residual stress (WRS). For the purpose of studying the influence of WRS from large-scale welding seam on the mechanical properties of steel tube arch rib during arch rib splicing, test research and numerical simulation analysis on the WRS in arch rib splicing based on the Guangxi Pingnan Third Bridge, which is the world’s largest span concrete-filled steel… More >

Min-Gyu Kim¹, Hwankuk Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2391-2415, 2025, DOI:10.32604/cmes.2025.063558 - 30 May 2025

Abstract This study proposes an efficient traffic classification model to address the growing threat of distributed denial-of-service (DDoS) attacks in 5th generation technology standard (5G) slicing networks. The proposed method utilizes an ensemble of encoder components from multiple autoencoders to compress and extract latent representations from high-dimensional traffic data. These representations are then used as input for a support vector machine (SVM)-based metadata classifier, enabling precise detection of attack traffic. This architecture is designed to achieve both high detection accuracy and training efficiency, while adapting flexibly to the diverse service requirements and complexity of 5G network… More >

Ganesh Wakte^1,*, Mukesh Kumar², Mohammad Aljaidi³, Ramesh Kumar⁴, Manish Kumar Singla⁴

Energy Engineering, Vol.122, No.6, pp. 2519-2537, 2025, DOI:10.32604/ee.2025.060658 - 29 May 2025

Abstract Nodal pricing is a critical mechanism in electricity markets, utilized to determine the cost of power transmission to various nodes within a distribution network. As power systems evolve to incorporate higher levels of renewable energy and face increasing demand fluctuations, traditional nodal pricing models often fall short to meet these new challenges. This research introduces a novel enhanced nodal pricing mechanism for distribution networks, integrating advanced optimization techniques and hybrid models to overcome these limitations. The primary objective is to develop a model that not only improves pricing accuracy but also enhances operational efficiency and… More > Graphic Abstract

WENYING ZHENG^1,#, YANYAN SHANG^1,#, KAI DU¹, AILING LUO¹, LIJUN PEI¹, MEIQI LI¹, GUOPING ZHANG^2,*, MIN DENG^1,*

Oncology Research, Vol.33, No.5, pp. 1121-1133, 2025, DOI:10.32604/or.2025.060958 - 18 April 2025

Abstract Background: Alterations in splicing factors contribute to aberrant alternative splicing (AS), which subsequently promotes tumor progression. The splicing factor polypyrimidine tract binding protein 1 (PTBP1) has been shown to facilitate cancer progression by modulating oncogenic variants. However, its specific role and underlying mechanisms in hepatocellular carcinoma (HCC) remain to be elucidated. Methods: PTBP1 expression was evaluated in HCC tissues and cell lines. Subsequently, cells were transfected with vectors designed for PTBP1 overexpression or downregulation. The biological function of PTBP1 was assessed in vitro and in vivo using MTS assays, colony formation assays, transwell assays, xenograft formation, tail… More > Graphic Abstract

MING YANG^1,#, LIANGZHAO CHU^1,#, SHUKAI LIN², HAN PENG¹, NIYA LONG¹, KAYA XU¹, HUA YANG¹, FENG HAN^1,*, JIAN LIU^1,*

Oncology Research, Vol.33, No.5, pp. 1189-1198, 2025, DOI:10.32604/or.2024.055102 - 18 April 2025

Abstract Background: Glioblastoma (GBM) is one of the most malignant types of central nervous system tumors. Oxygen deprivation in the tumor microenvironment is thought to be an important factor in promoting GBM progression. However, the mechanisms of hypoxia-promoted tumor progression remain elusive. Methods: Alternative splicing of diacylglycerol kinase gamma (DGKG)-Δ exon13 was amplified and verified by PCR-Sanger sequencing. The functions of DGKG and DGKG-Δ exon13 were analyzed by Cell counting kit-8 (CCK-8), Transwell, Matrigel-transwell experiments, and in vivo orthotropic GBM animal models. Transcriptome analyses were done to find out the regulated genes. Results: In this study, we found… More > Graphic Abstract

Mariam Ishtiaq^1,2, Jong-Un Won^1,2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5343-5361, 2025, DOI:10.32604/cmc.2025.061466 - 06 March 2025

Abstract Fire detection has held stringent importance in computer vision for over half a century. The development of early fire detection strategies is pivotal to the realization of safe and smart cities, inhabitable in the future. However, the development of optimal fire and smoke detection models is hindered by limitations like publicly available datasets, lack of diversity, and class imbalance. In this work, we explore the possible ways forward to overcome these challenges posed by available datasets. We study the impact of a class-balanced dataset to improve the fire detection capability of state-of-the-art (SOTA) vision-based models and propose… More >