Aadarsha Lamichhane¹, Arun Kuttoor Vasudevan¹, Ethan Dean¹, Mostafa Mohammadabadi^1,*, Kevin Ragon¹, Ardeshir Adeli²

Journal of Renewable Materials, Vol.14, No.1, 2026, DOI:10.32604/jrm.2025.02025-0146 - 23 January 2026

Abstract This study explores a novel method for processing cotton stalks—an abundant agricultural byproduct—into long strips that serve as sustainable raw material for engineered bio-based panels. To evaluate the effect of raw material morphology on panel’s performance, two types of cotton stalk-based panels were developed: one using long strips, maintaining fiber continuity, and the other using ground particles, representing conventional processing. A wood strand-based panel made from commercial southern yellow pine strands served as the control. All panels were bonded using phenol-formaldehyde resin and hot-pressed to a target thickness of 12.7 mm and density of 640 kg/m³.… More >

Anis Zarrad¹, Thomas Armstrong², Jaber Jemai^3,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072768 - 12 January 2026

Abstract Test case prioritization and ranking play a crucial role in software testing by improving fault detection efficiency and ensuring software reliability. While prioritization selects the most relevant test cases for optimal coverage, ranking further refines their execution order to detect critical faults earlier. This study investigates machine learning techniques to enhance both prioritization and ranking, contributing to more effective and efficient testing processes. We first employ advanced feature engineering alongside ensemble models, including Gradient Boosted, Support Vector Machines, Random Forests, and Naive Bayes classifiers to optimize test case prioritization, achieving an accuracy score of 0.98847… More >

Zonglin Li^1,#, Xu Zhao^2,#, Yan Cao^2,*, Yazhe Li³, Yihong Zhang¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071511 - 12 January 2026

Abstract With the rapid development of Internet technology, REST APIs (Representational State Transfer Application Programming Interfaces) have become the primary communication standard in modern microservice architectures, raising increasing concerns about their security. Existing fuzz testing methods include random or dictionary-based input generation, which often fail to ensure both syntactic and semantic correctness, and OpenAPI-based approaches, which offer better accuracy but typically lack detailed descriptions of endpoints, parameters, or data formats. To address these issues, this paper proposes the APIDocX fuzz testing framework. It introduces a crawler tailored for dynamic web pages that automatically simulates user interactions More >

Longqi Liao¹, Jing Li², Yuhua Li³, Yuemin Wang³, Jinhua Li^1,*, Liyuan Cao^4,*, Chunxiang Li^4,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.072237 - 08 January 2026

Abstract Quantitative detection of sleeve grouting compactness is a technical challenge in civil engineering testing. This study explores a novel quantitative detection method based on ultrasonic time-frequency dual-domain analysis. It establishes a mapping relationship between sleeve grouting compactness and characteristic parameters. First, this study made samples with gradient defects for two types of grouting sleeves, G18 and G20. These included four cases: 2D, 4D, 6D defects (where D is the diameter of the grouting sleeve), and no-defect. Then, an ultrasonic input/output data acquisition system was established. Three-dimensional sound field distribution data were obtained through an orthogonal… 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 >

Jianhua Du¹, Shaofeng Wang¹, Ting Gao², Huiwen Sun², Wenjing Liu^1,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.071189 - 08 January 2026

Abstract In ultrasonic non-destructive testing of high-temperature industrial equipment, sound velocity drift induced by non-uniform temperature fields can severely compromise defect localization accuracy. Conventional approaches that rely on room-temperature sound velocities introduce systematic errors, potentially leading to misjudgment of safety-critical components. Two primary challenges hinder current methods: first, it is difficult to monitor real-time changes in sound velocity distribution within a thermal gradient; second, traditional uniform-temperature correction models fail to capture the nonlinear dependence of material properties on temperature and their effect on ultrasonic velocity fields. Here, we propose a defect localization correction method based on… More >

Yaxin Zhao¹, Qi Han², Hui Shu², Yan Guang^2,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-24, 2026, DOI:10.32604/cmc.2025.070511 - 09 December 2025

Abstract Large Language Models (LLMs) are increasingly applied in the field of code translation. However, existing evaluation methodologies suffer from two major limitations: (1) the high overlap between test data and pretraining corpora, which introduces significant bias in performance evaluation; and (2) mainstream metrics focus primarily on surface-level accuracy, failing to uncover the underlying factors that constrain model capabilities. To address these issues, this paper presents TCode (Translation-Oriented Code Evaluation benchmark)—a complexity-controllable, contamination-free benchmark dataset for code translation—alongside a dedicated static feature sensitivity evaluation framework. The dataset is carefully designed to control complexity along multiple dimensions—including syntactic… More >

Sewwandi Tennakoon¹, Eric Danso¹, Zhenjie Zhao^2,*

Journal on Artificial Intelligence, Vol.7, pp. 517-547, 2025, DOI:10.32604/jai.2025.072628 - 01 December 2025

Abstract Generative Artificial Intelligence (GenAI) systems have achieved remarkable capabilities across text, code, and image generation; however, their outputs remain prone to errors, hallucinations, and biases. Users often overtrust these outputs due to limited transparency, which can lead to misuse and decision errors. This study addresses the challenge of calibrating trust in GenAI through a human centered testing framework enhanced with adaptive explainability. We introduce a methodology that adjusts explanations dynamically according to user expertise, model output confidence, and contextual risk factors, providing guidance that is informative but not overwhelming. The framework was evaluated using outputs… More >

Yang Lei^1,*, Bo Jiang¹, Yucai Zhao², Gaofeng Fu³, Falin Qi¹, Tian Tian¹, Qiankuan Feng¹, Qiming Qu¹

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1657-1679, 2025, DOI:10.32604/sdhm.2025.069415 - 17 November 2025

Abstract Detecting internal defects, particularly voids behind linings, is critical for ensuring the structural integrity of aging high-speed rail (HSR) tunnel networks. While ground-penetrating radar (GPR) is widely employed, systematic quantification of performance boundaries for air-coupled (A-CGPR) and ground-coupled (G-CGPR) systems within the complex electromagnetic environment of multilayer reinforced HSR tunnels remains limited. This study establishes physics-based quantitative performance limits for A-CGPR and G-CGPR through rigorously validated GPRMax finite-difference time-domain (FDTD) simulations and comprehensive field validation over a 300 m operational HSR tunnel section. Key performance metrics were quantified as functions of: (a) detection distance (A-CGPR:… More >

Si-Yu Gao¹, Siu-Man Ng^2,*

International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1471-1482, 2025, DOI:10.32604/ijmhp.2025.068702 - 31 October 2025

Abstract Background: Existing Chinese stigma scales focus on the perceptions of people with mental illness (PMI) without assessing the general public’s attitudes toward integrating PMI into the community. Developing a valid and reliable Chinese instrument measuring the attitude domain will be helpful to future research in this area. The current study aimed to validate a shortened Chinese version of the Community Attitudes towards the Mentally Ill Scale (C-CAMI-SF). Methods: Four hundred participants who are (1) Chinese; (2) aged 18 years and above; and (3) able to complete the Chinese questionnaire in a self-reported manner participated in… More >