Traian-Radu Ploscă^1,*, Alexandru-Mihai Pescaru², Bianca-Valeria Rus¹, Daniel-Ioan Curiac^1,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-23, 2026, DOI:10.32604/cmc.2025.069707 - 10 November 2025

Abstract Objective expertise evaluation of individuals, as a prerequisite stage for team formation, has been a long-term desideratum in large software development companies. With the rapid advancements in machine learning methods, based on reliable existing data stored in project management tools’ datasets, automating this evaluation process becomes a natural step forward. In this context, our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems. For this, we mathematically formalize two categories of expertise: technology-specific expertise, which denotes the skills required for a particular technology, and general expertise, which encapsulates overall knowledge More >

Bo Wang¹, Fuyang Wu², Zifeng Chen², Libin Dai¹, Yifan Dong¹, Xiaotao Gao³, Zongfa Li^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2701-2719, 2025, DOI:10.32604/fdmp.2025.067298 - 01 December 2025

Abstract Tight gas reservoirs are often characterized by pronounced heterogeneity and poor continuity, resulting in wide variability in production enhancement and net present value (NPV) for different geological parameter combinations (see e.g., the Ordos Basin). The conditions governing geological adaptability remain insufficiently defined. To address these challenges, this study integrates large-volume hydraulic fracturing, numerical production simulation, and economic evaluation to elucidate the mechanisms by which large-scale fracturing enhances fracture parameters in tight gas formations. The analysis reveals that, for identical proppant and fluid volumes, increasing the fracturing injection rate leads to longer and taller fractures. Over… More >

Chih-Yin Chien^1,2, Tsae-Jyy Wang¹, Pei-Hung Liao¹, Ying-Hsiang Lee^3,4,5,*, Wei-Sho Ho^6,7,*

Congenital Heart Disease, Vol.20, No.5, pp. 601-612, 2025, DOI:10.32604/chd.2025.072431 - 30 November 2025

Abstract Background: Cardiac implantable electronic devices (CIEDs) are essential for preventing sudden cardiac death in patients with cardiovascular diseases, but implantation procedures carry risks of complications such as infection, hematoma, and bleeding, with incidence rates of 3–4%. Previous studies have examined individual risk factors separately, but integrated predictive models are lacking. We compared the predictive performance and interpretability of artificial neural network (ANN) and logistic regression models to evaluate their respective strengths in clinical risk assessment. Methods: This retrospective study analyzed data from 180 patients who underwent cardiac implantable electronic device (CIED) implantation in Taiwan between 2017… More >

Ratan Kumar Das^1,*, Abhijit Date¹, Harun Chowdhury¹, Hamed Hassan²

Energy Engineering, Vol.122, No.12, pp. 4815-4835, 2025, DOI:10.32604/ee.2025.071727 - 27 November 2025

Abstract Bangladesh has achieved notable progress in expanding electricity access nationwide. Nonetheless, remote and topographically challenging regions such as the Chittagong Hill Tracts (CHT) continue to face coverage gaps due to grid extension difficulties. This research investigates the technical feasibility of micro-hydro power (MHP) systems as viable off-grid solutions for rural electrification in CHT. Field surveys conducted across various sites assessed available head and flow rates using GPS-based elevation measurements and portable flow meters. Seasonal fluctuations were factored into the analysis to ensure year-round operational viability. The study involved estimating power output, selecting appropriate turbine types… More > Graphic Abstract

Tae-hyeon Yun¹, Moohong Min^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2707-2731, 2025, DOI:10.32604/cmes.2025.072357 - 26 November 2025

Abstract The dynamic, heterogeneous nature of Edge computing in the Internet of Things (Edge-IoT) and Industrial IoT (IIoT) networks brings unique and evolving cybersecurity challenges. This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) framework by MITRE and introduces a lightweight, data-driven scoring model that enables rapid identification and prioritization of attacks. Inspired by the Factor Analysis of Information Risk model, our proposed scoring model integrates four key metrics: Common Vulnerability Scoring System (CVSS)-based severity scoring, Cyber Kill Chain–based difficulty estimation, Deep Neural Networks-driven detection scoring, and frequency… More >

Božo Damjanović^*, Pejo Konjatić, Marko Katinić

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1735-1753, 2025, DOI:10.32604/cmes.2025.072256 - 26 November 2025

Abstract Ensuring the structural integrity of piping systems is crucial in industrial operations to prevent catastrophic failures and minimize shutdown time. This study investigates a transportation-damaged pipe exposed to high-temperature conditions and cyclic loading, representing a realistic challenge in plant operation. The objective was to evaluate the service life and integrity assessment parameters of the damaged pipe, subjected to 22,000 operational cycles under two daily charge and discharge conditions. The flaw size in the damaged pipe was determined based on a failure assessment procedure, ensuring a conservative and reliable input. The damage was characterized as a… More >

José Velázquez, Dolores Ojados, Adrián Semitiel, Francisco Cavas^*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1821-1837, 2025, DOI:10.32604/cmes.2025.071131 - 26 November 2025

Abstract This research establishes a methodological framework for generating geometrically accurate 3D representations of human crystalline lenses through scanning technologies and digital reconstruction. Multiple scanning systems were evaluated to identify optimal approaches for point cloud processing and subsequent development of parameterized solid models, facilitating comprehensive morpho-geometric characterization. Experimental work was performed at the 3D Scanning Laboratory of SEDIC (Industrial Design and Scientific Calculation Service) at the Technical University of Cartagena, employing five distinct scanner types based on structured light, laser, and infrared technologies. Test specimens—including preliminary calibration using a lentil and biological analysis of a human… More >

Lailan Ni`mah^1,*, Sri Rachmania Juliastuti², Mahfud Mahfud²

Journal of Renewable Materials, Vol.13, No.11, pp. 2169-2190, 2025, DOI:10.32604/jrm.2025.02025-0044 - 24 November 2025

Abstract This study evaluates the effectiveness of microwave technology in producing activated carbon from lemongrass waste, an underutilized agricultural byproduct. Microwave-assisted production offers faster heating, lower energy consumption, and better process control compared to conventional methods. It also enhances pore development, resulting in larger, cleaner, and more uniform pores, making the activated carbon more effective for adsorption. The microwave-assisted process significantly accelerates production, reducing the required time to just 10 min at a power of 400 W. Activated carbon derived from lemongrass waste at 400 W exhibits a water absorption capacity of 7.88%, ash content of… More > Graphic Abstract

Xinrui Ma, Shizhi Chen^*

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1745-1767, 2025, DOI:10.32604/sdhm.2025.071148 - 17 November 2025

Abstract The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intensive, and prone to human error. To address these challenges, this study proposes STPEIC (Swin Transformer-based Framework for Interpretable Post-Earthquake Structural Classification), an automated deep learning framework designed for analyzing post-earthquake images. STPEIC performs two key tasks: structural components classification and damage level classification. By leveraging the hierarchical attention mechanisms of the Swin Transformer (Shifted Window Transformer), the model achieves 85.4% accuracy in structural component classification and 85.1% More >

Andrea Panunzio¹, Rossella Orlando¹, Federico Greco^2,3, Giovanni Mazzucato⁴, Floriana Luigina Rizzo¹, Serena Domenica D’Elia¹, Antonio Benito Porcaro⁵, Alessandro Antonelli⁵, Alessandro Tafuri^1,6,*

Canadian Journal of Urology, Vol.32, No.5, pp. 375-384, 2025, DOI:10.32604/cju.2025.066140 - 30 October 2025

Abstract Background: The Barthel Index (BI) measures the level of patient independence in activities of daily living. This review aims to summarize current evidence on the use of the BI in urology, highlighting its potential as a tool for assessing patients prior to surgery. Materials and methods: A comprehensive search of PubMed, Scopus, and Web of Science databases was conducted for studies evaluating the BI in patients undergoing urologic surgery, following Systematic Review and Meta-analyses (PRISMA) guidelines. The BI was investigated both as a descriptor of baseline or postoperative health status and a prognostic indicator. A qualitative… More >