Sun Park^*, JongWon Kim

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072865 - 12 January 2026

Abstract In real-world autonomous driving tests, unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur. Conducting actual test drives under various weather conditions may also lead to dangerous situations. Furthermore, autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS. Driving simulators, which replicate driving conditions nearly identical to those in the real world, can drastically reduce the time and cost required for market entry validation; consequently, they have become widely used. In this paper, we design a virtual driving test environment capable of More >

Mallikarjun P. Y.¹, Rame Gowda D. N.¹, Trisha J. K.¹, Varshini M.¹, Poornesha S. Shetty¹, Mandar Jatkar^1,*, Arpan Shah²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072507 - 12 January 2026

Abstract As circuit feature sizes approach the nanoscale, traditional Copper (Cu) interconnects face significant hurdles posed by rising resistance-capacitance (RC) delay, electromigration, and high power dissipation. These limitations impose constraints on the scalability and reliability of future semiconductor technologies. Our paper describes the new Vertical multilayer Aluminium Boron Nitride Nanoribbon (AlBN) interconnect structure, integrated with Density functional theory (DFT) using first-principles calculations. This study explores AlBN-based nanostructures with doping of 1Cu, 2Cu, 1Fe (Iron), and 2Fe for the application of Very Large Scale Integration (VLSI) interconnects. The AlBN structure utilized the advantages of vertical multilayer interconnects… More >

Hanaa Nafea¹, Awais Qasim², Sana Abdul Sattar², Adeel Munawar³, Muhammad Nadeem Ali⁴, Byung-Seo Kim^4,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072281 - 12 January 2026

Abstract The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats, making intrusion detection a critical aspect of ensuring their secure operation. Traditional intrusion detection systems have limitations in terms of centralized architecture, lack of transparency, and vulnerability to single points of failure. This is where the integration of blockchain technology with signature-based intrusion detection can provide a robust and decentralized solution for securing smart transportation systems. This study tackles the issue of database manipulation attacks in smart transportation networks by proposing a signature-based intrusion detection system. The introduced More >

Jie Li¹, Nan An^2,3, Youliang Ding^2,3,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.072361 - 08 January 2026

Abstract Vehicle-induced response separation is a crucial issue in structural health monitoring (SHM). This paper proposes a block-wise sliding recursive wavelet transform algorithm to meet the real-time processing requirements of monitoring data. To extend the separation target from a fixed dataset to a continuously updating data stream, a block-wise sliding framework is first developed. This framework is further optimized considering the characteristics of real-time data streams, and its advantage in computational efficiency is theoretically demonstrated. During the decomposition and reconstruction processes, information from neighboring data blocks is fully utilized to reduce algorithmic complexity. In addition, a… More >

Weichen Wang¹, Shaofeng Wang¹, Wenjing Liu^1,*, Luncai Zhou², Erqing Zhang¹, Ting Gao³, Grigory Petrishin⁴

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.071278 - 08 January 2026

Abstract In dry-coupled ultrasonic thickness measurement, thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy. Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise. This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference. By decomposing A-scan signals into Intrinsic Mode Functions (IMFs), the framework employs energy contribution thresholds (>85%) and kurtosis indices (>3) to autonomously select IMFs containing valid specimen echoes. Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing. More >

Thi Kim Chi Duong¹, Bich-Ngoc. Mach², Hoa-Cuc. Nguyen², Thi Nhu Quynh Trinh², Thanh Q. Nguyen^3,4,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.070185 - 08 January 2026

Abstract This study explores theoretical insights and experimental results on monitoring load-carrying capacity degradation in bridge spans through frequency analysis. Experiments were conducted on real bridge structures, including the Binh Thuan Bridge, focusing on analyzing the power spectral density (PSD) of vibration signals under random traffic loads. Detailed digital models of various bridge spans with different structural designs and construction periods were developed to ensure diversity. The study utilized PSD to analyze the vibration signals from the bridge spans under various loading conditions, identifying the vibration frequencies and the corresponding response regions. The research correlated the… More >

Benyu Wang^*, Ke Chen, Bingjian Wang^#,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.070137 - 08 January 2026

Abstract To examine stress redistribution phenomena in bridges subjected to varying operational conditions, this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail steel arch bridge. An initial statistical comparison of sensor data distributions reveals clear temporal variations in stress redistribution patterns. XGBoost (eXtreme Gradient Boosting), a gradient-boosting machine learning (ML) algorithm, was employed not only for predictive modeling but also to uncover the underlying mechanisms of stress evolution. Unlike traditional numerical models that rely on extensive assumptions and idealizations, XGBoost effectively captures nonlinear and time-varying relationships between stress… More >

Se Ha Jang^1,2,#, Hyung Seok Kim^3,#, Jung Woo Eun^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.072240 - 30 December 2025

Abstract Hepatocellular carcinoma (HCC) remains one of the most prevalent and lethal malignancies worldwide. Long non-coding RNAs (lncRNAs) have emerged as crucial regulators of gene expression and cancer progression, yet the functional diversity of RP11-derived lncRNAs—originally mapped to bacterial artificial chromosome (BAC) clones from the Roswell Park Cancer Institute—has only recently begun to be appreciated. This mini-review aims to systematically synthesize current findings on RP11-derived lncRNAs in HCC, outlining their genomic origins, molecular mechanisms, and biological significance. We highlight their roles in metabolic reprogramming, microRNA network modulation, and tumor progression, as well as their diagnostic and More >

Wen-Shou Tan^1,#, Hsuan Kuo^2,#, Chang-Ge Jiang¹, Mei-Han Lu¹, Yi-He Lu¹, Yung-Li Wang¹, Ching-Shuen Wang¹, Thi Thuy Tien Vo³, I-Ta Lee^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070871 - 30 December 2025

Abstract This narrative review examines recent advances in salivary biomarkers for oral squamous cell carcinoma (OSCC), a major subtype of oral cancer with persistently low five-year survival rates due to delayed diagnosis. Saliva has emerged as a noninvasive diagnostic medium capable of reflecting both local tumor activity and systemic physiological changes. Various salivary biomarkers, including microRNAs, cytokines, proteins, metabolites, and exosomes, have been linked to oncogenic signaling pathways involved in tumor progression, immune modulation, and therapeutic resistance. Advances in quantitative polymerase chain reaction, mass spectrometry, and next-generation sequencing have enabled comprehensive biomarker profiling, while point-of-care detection More >

Sarra B. Shakartalla^1,2,3, Iman M. Talaat^1,2,4,*, Nival Ali¹, Shahenaz S. Salih^1,5, Zainab M. Al Shareef^1,2, Noura Alkhayyal⁶, Riyad Bendardaf^2,7,*, Sameh S. M. Soliman^1,8,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070808 - 30 December 2025

Abstract Objectives: Breast cancer (BC) is the leading cause of cancer-related mortality in women, largely due to metastasis. This study aims to explore the role of purine nucleoside phosphorylase (PNP), a key enzyme in purine metabolism, in the aggressiveness and metastatic behavior of BC. Methods: A comprehensive analysis was performed using in silico transcriptomic data (n = 2509 patients), immunohistochemical profiling of BC tissues (n = 103), and validation through western blotting in multiple BC cell lines. Gene expression and survival analyses were conducted using Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and… More >