Yeasul Kim¹, Chaeeun Won¹, Hwankuk Kim^2,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-28, 2026, DOI:10.32604/cmc.2025.069608 - 10 November 2025

Abstract With the increasing emphasis on personal information protection, encryption through security protocols has emerged as a critical requirement in data transmission and reception processes. Nevertheless, IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices, spanning a range of devices from non-encrypted ones to fully encrypted ones. Given the limited visibility into payloads in this context, this study investigates AI-based attack detection methods that leverage encrypted traffic metadata, eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices. Using the UNSW-NB15 and CICIoT-2023 dataset, encrypted and… More >

Xiaohu Song¹, Zhiliang Zhu^2,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-19, 2026, DOI:10.32604/cmc.2025.068930 - 10 November 2025

Abstract Vulnerabilities are a known problem in modern Open Source Software (OSS). Most developers often rely on third-party libraries to accelerate feature implementation. However, these libraries may contain vulnerabilities that attackers can exploit to propagate malicious code, posing security risks to dependent projects. Existing research addresses these challenges through Software Composition Analysis (SCA) for vulnerability detection and remediation. Nevertheless, current solutions may introduce additional issues, such as incompatibilities, dependency conflicts, and additional vulnerabilities. To address this, we propose Vulnerability Scan and Protection (), a robust solution for detection and remediation vulnerabilities in Java projects. Specifically, builds… More >

Mingwei Yue¹, Shen Rao^1,*, Xiaomeng Liu¹, Wei Yang², Yuan Yuan¹, Feng Xu², Shuiyuan Cheng^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3319-3348, 2025, DOI:10.32604/phyton.2025.073602 - 01 December 2025

Abstract Cadmium (Cd), a highly toxic heavy metal, represents a major global environmental threat due to its widespread dispersion through anthropogenic activities. Environmental Cd contamination poses significant risks to living organisms, including humans, animals, and plants. Certain plant species have evolved Cd hyperaccumulating capabilities to adapt to high-Cd habitats, playing critical roles in phytoremediation strategies. Here we review the biodiversity and biogeography of Cd hyperaccumulators, the underlying mechanisms of Cd uptake and accumulation, and the ecological impacts of hyperaccumulation. The major points are the following: twenty-four Cd hyperaccumulator species have been documented, with shoot Cd concentrations More >

Riya Tripathi, Varsha K. Singh, Palak Rana, Sapana Jha, Ashish P. Singh, Payel Rana, Rajeshwar P. Sinha^*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3371-3399, 2025, DOI:10.32604/phyton.2025.070712 - 01 December 2025

Abstract Cyanobacteria are photosynthetic prokaryotes. They exhibit remarkable metabolic adaptability, enabling them to withstand oxidative stress, high salinity, temperature extremes, and UV radiation (UVR). Their adaptive strategies involve complex regulatory networks that affect gene expression, enzyme activity, and metabolite fluxes to maintain cellular homeostasis. Key stress response systems include the production of antioxidants such as peroxidases (POD), catalase (CAT), and superoxide dismutase (SOD), which detoxify reactive oxygen species (ROS). To withstand environmental stresses, cyanobacteria maintain osmotic balance by accumulating compatible solutes, such as glycine betaine, sucrose, and trehalose. They also adapt to temperature and light fluctuations… More >

Miah A. Robinson, Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Khalid H. Abed^*

Journal on Artificial Intelligence, Vol.7, pp. 615-632, 2025, DOI:10.32604/jai.2025.073535 - 01 December 2025

Abstract Ensuring the safety of Artificial Intelligence (AI) is essential for providing dependable services, especially in various sectors such as the military, education, healthcare, and automotive industries. A highly effective method to boost the precision and performance of an AI agent involves multi-configuration training, followed by thorough evaluation in a specific setting to gauge performance outcomes. This research thoroughly investigates the design of three AI agents, each configured with a different number of hidden units. The first agent is equipped with 128 hidden units, the second with 256, and the third with 512, all utilizing the… More >

Ke Li¹, Bendong Liu¹, Yulong Han², Yafeng Zhang³, Chunqi Yang¹, Dawei Yin², Yazhou Zhang³, Wantao Ding^4,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2779-2793, 2025, DOI:10.32604/fdmp.2025.072671 - 01 December 2025

Abstract Traditional cement-based slurries are often constrained by excessive cement consumption, prolonged setting times, and limited controllability, which hinder their broader engineering applications. To overcome these challenges, this study focuses on optimizing ordinary cement-based slurry through the incorporation of targeted additives and rational adjustment of mix proportions, with the aim of developing a rapid-setting, early-strength cementitious system. In particular, a series of comparative and orthogonal experiments were conducted to systematically examine the evolution of the slurry’s macroscopic properties. In addition, the response surface methodology (RSM) was introduced to reveal the interaction mechanisms among key parameters, thereby… More >

Yuchao Pan^*

International Journal of Mental Health Promotion, Vol.27, No.11, pp. 1769-1780, 2025, DOI:10.32604/ijmhp.2025.070147 - 28 November 2025

Abstract Objectives: While organizations are increasingly adopting artificial intelligence (AI), its effects on employees’ well-being remain poorly understood. Drawing on social cognitive theory, this study aimed to examine the underlying mechanism through which organizational AI adoption influences employees’ well-being. Methods: A two-wave time-lagged research design was conducted with 262 Chinese employees employing a voluntary and anonymous survey. The survey included measures of organizational AI adoption, AI use anxiety, job insecurity, subjective well-being, and psychological well-being. The data were analyzed using SPSS 26.0 software and macro PROCESS. Results: The moderation analysis revealed that AI use anxiety moderated the association… More >

Ricardo Dominico Da Silva^1,2, Jangkung Raharjo^1,3,*, Sudarmono Sasmono^1,3

Energy Engineering, Vol.122, No.12, pp. 5073-5090, 2025, DOI:10.32604/ee.2025.071545 - 27 November 2025

Abstract The rapid development of technology has led to an ever-increasing demand for electrical energy. In the context of Timor-Leste, which still relies on fossil energy sources with high operational costs and significant environmental impacts, electricity load forecasting is a strategic measure to support the energy transition towards the Net Zero Emission (NZE) target by 2050. This study aims to utilize historical electricity load data for the period 2013–2024, as well as data on external factors affecting electricity consumption, to forecast electricity load in Timor-Leste in the next 10 years (2025–2035). The forecasting results are expected… 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 >

Tamara Zhukabayeva^1,2, Zulfiqar Ahmad^1,3,*, Nurbolat Tasbolatuly⁴, Makpal Zhartybayeva¹, Yerik Mardenov^1,4, Nurdaulet Karabayev^1,*, Dilaram Baumuratova^1,4

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2573-2599, 2025, DOI:10.32604/cmes.2025.070426 - 26 November 2025

Abstract The Industrial Internet of Things (IIoT), combined with the Cyber-Physical Systems (CPS), is transforming industrial automation but also poses great cybersecurity threats because of the complexity and connectivity of the systems. There is a lack of explainability, challenges with imbalanced attack classes, and limited consideration of practical edge–cloud deployment strategies in prior works. In the proposed study, we suggest an Impact-Aware Taxonomy-Driven Machine Learning Framework with Edge Deployment and SHapley Additive exPlanations (SHAP)-based Explainable AI (XAI) to attack detection and classification in IIoT-CPS settings. It includes not only unsupervised clustering (K-Means and DBSCAN) to extract… More >