Si-Woo Kim, Yong Soo Kim^*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073492 - 12 January 2026

Abstract Predictive maintenance (PdM) is vital for ensuring the reliability, safety, and cost efficiency of heavy-duty vehicle fleets. However, real-world sensor data are often highly imbalanced, noisy, and temporally irregular, posing significant challenges to model robustness and deployment. Using multivariate time-series data from Scania trucks, this study proposes a novel PdM framework that integrates efficient feature summarization with cost-sensitive hierarchical classification. First, the proposed last_k_summary method transforms recent operational records into compact statistical and trend-based descriptors while preserving missingness, allowing LightGBM to leverage its inherent split rules without ad-hoc imputation. Then, a two-stage LightGBM framework is developed… More >

Tianyu Zhao¹, Xiaoli Zhao², Kenny S. L. Cheah^3,*, Ye Zhang³

International Journal of Mental Health Promotion, Vol.27, No.12, pp. 2023-2038, 2025, DOI:10.32604/ijmhp.2025.071322 - 31 December 2025

Abstract Background: Despite access to university counseling services, many students underutilize them due to cultural stigma, language barriers, and perceived irrelevance. As a result, ChatGPT has emerged as an informal, always-available support system. This study investigates how international PhD students in Malaysia navigate loneliness, mental well-being, and social disconnection through interactions with Generative AI (mainly ChatGPT. Methods: Using a mixed-methods design, the study surveyed 155 international doctoral students and analyzed quantitative responses across four dimensions: loneliness, well-being (WHO-5), perceived social support, and AI-facilitated emotional support. Additionally, open-ended responses were examined using Latent Dirichlet Allocation (LDA) to identify… More >

Huiping Qiu¹, Shaofang Huang^2,*, Xin Xiong¹, Li Zhang¹

BIOCELL, Vol.49, No.12, pp. 2415-2432, 2025, DOI:10.32604/biocell.2025.070402 - 24 December 2025

Abstract Background: Pulmonary fibrosis is an irreversible lung disorder that currently has a limited number of effective therapeutic strategies. Taraxasterol (TAR), a bioactive triterpenoid isolated from plants used in traditional Chinese medicine (TCM), possesses anti-inflammatory and antioxidant activities. However, its precise role in pulmonary fibrosis remains incompletely defined. This study aimed to elucidate whether TAR alleviates pulmonary fibrosis by modulating Protein Phosphatase 2 Scaffold Subunit Abeta (PPP2R1B) expression. Methods: A bleomycin-induced murine model of pulmonary fibrosis and a transforming growth factor-β1 (TGF-β1) stimulated mouse lung fibroblast cell line (MLg) were established. To evaluate the effects of… More >

Muhammad Saad Farooqui¹, Aizaz Ahmad Khattak², Bakri Hossain Awaji³, Nazik Alturki⁴, Noha Alnazzawi⁵, Muhammad Hanif^6,*, Muhammad Shahbaz Khan²

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4395-4439, 2025, DOI:10.32604/cmes.2025.072023 - 23 December 2025

Abstract Quality of Service (QoS) assurance in programmable IoT and 5G networks is increasingly threatened by cyberattacks such as Distributed Denial of Service (DDoS), spoofing, and botnet intrusions. This paper presents AutoSHARC, a feedback-driven, explainable intrusion detection framework that integrates Boruta and LightGBM–SHAP feature selection with a lightweight CNN–Attention–GRU classifier. AutoSHARC employs a two-stage feature selection pipeline to identify the most informative features from high-dimensional IoT traffic and reduces 46 features to 30 highly informative ones, followed by post-hoc SHAP-guided retraining to refine feature importance, forming a feedback loop where only the most impactful attributes are More >

S. N. Yasinova^a,b,*, A. B. Rzayeva^a,b, M. H. Huseynaliyev^b, B. T. Hagieva^a, G. M. Huseynov^a,b

Chalcogenide Letters, Vol.22, No.10, pp. 883-888, 2025, DOI:10.15251/CL.2025.2210.883

Abstract The thin films and powders of PbS, PbSe, and PbSe and PbS_0.5Se_0.5 have been obtained by chemical precipitation method. The X-ray spectra of the obtained thin layers were obtained through the"Miniflex 600" diffractometer, and elemental analyses were performed. Thermogravimetric analyses of the powders of all three compounds were conducted in the temperature range of 20-800°C using the "NETZSCH STA 449 F3" apparatus. It has been determined from the X-ray spectra that the angular positions of all the peaks of PbS, PbSe, and PbSe and PbS_0.5Se_0.5 thin layers coincide with the positions of the corresponding diffraction peaks More >

A. B. Rzayeva^1,2,*, F. E. Abbdullayeva¹, S. C. Imanova¹, S. H. Aliyeva^1,2, S. N. Yasinova^1,2

Chalcogenide Letters, Vol.22, No.11, pp. 965-970, 2025, DOI:10.15251/CL.2025.2211.965

Abstract Lead indium selenide (PbIn2Se₄) is a promising chalcogenide semiconductor for optoelectronic and energy applications. We report a hydrothermal synthesis route using ethylene glycol under moderate conditions (433– 453 K, 7–12 h), yielding up to 85–87%. The product crystallized into a cotton-like morphology composed of nanoand microparticles. Structural and compositional integrity were confirmed by chemical analysis, thermogravimetric analysis, and transmission electron microscopy. These results demonstrate that hydrothermal synthesis provides an efficient and controllable pathway to high-purity PbIn2Se₄, opening opportunities for its use in advanced functional devices. More >

Yingjie Wang^1,#, Wanlin Dong^1,#, Can Wang², Zirui Li¹, Yongqiang Wang¹, Qi Li¹, Cheng-Ya Dong^1,*

Oncology Research, Vol.33, No.12, pp. 4093-4111, 2025, DOI:10.32604/or.2025.068313 - 27 November 2025

Abstract Objectives: Glioblastoma is a prevalent malignant brain tumor, and the actions of the long non-coding RNA HOXA10-AS in its invasion and migration remain unclear. Here, the function of HOXA10-AS in glioblastoma cell invasion and migration and associated mechanisms were investigated. Methods: HOXA10-AS was knocked down in glioblastoma cells, and Transwell and wound healing assays were conducted to elucidate its impacts on cell invasion and migration. Western blotting and quantitative reverse transcription polymerase chain reaction (qRT-PCR) assessed HOXA10-AS’s impact on the epithelial-mesenchymal transition (EMT). Microarray analysis identified differentially expressed genes, complemented by bioinformatics approaches to explore… More >

Hongrong Wang^1,2, Xinjian Li^3,4, Xingjing She¹, Wenjian Ma^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2039-2055, 2025, DOI:10.32604/cmes.2025.072572 - 26 November 2025

Abstract In modern complex systems, real-time regression prediction plays a vital role in performance evaluation and risk warning. Nevertheless, existing methods still face challenges in maintaining stability and predictive accuracy under complex conditions. To address these limitations, this study proposes an online prediction approach that integrates event tracking sensitivity analysis with machine learning. Specifically, a real-time event tracking sensitivity analysis method is employed to capture and quantify the impact of key events on system outputs. On this basis, a mutual-information–based self-extraction mechanism is introduced to construct prior weights, which are then incorporated into a LightGBM prediction More >

Yiqiao Gong^1,2, Chunlai Wu¹, Wenfeng Zheng^1,*, Siyu Lu³, Guangyu Xu⁴, Lijuan Zhang⁵, Lirong Yin^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2223-2252, 2025, DOI:10.32604/cmes.2025.072136 - 26 November 2025

Abstract Recent Super-Resolution (SR) algorithms often suffer from excessive model complexity, high computational costs, and limited flexibility across varying image scales. To address these challenges, we propose DDNet, a dynamic and lightweight SR framework designed for arbitrary scaling factors. DDNet integrates a residual learning structure with an Adaptively fusion Feature Block (AFB) and a scale-aware upsampling module, effectively reducing parameter overhead while preserving reconstruction quality. Additionally, we introduce DDNetGAN, an enhanced variant that leverages a relativistic Generative Adversarial Network (GAN) to further improve texture realism. To validate the proposed models, we conduct extensive training using the More >

Adeel Munawar¹, Muhammad Nadeem Ali², Awais Qasim³, Byung-Seo Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 1189-1211, 2025, DOI:10.32604/cmes.2025.071876 - 30 October 2025

Abstract Cyber-physical systems (CPS) represent a sophisticated integration of computational and physical components that power critical applications such as smart manufacturing, healthcare, and autonomous infrastructure. However, their extensive reliance on internet connectivity makes them increasingly susceptible to cyber threats, potentially leading to operational failures and data breaches. Furthermore, CPS faces significant threats related to unauthorized access, improper management, and tampering of the content it generates. In this paper, we propose an intrusion detection system (IDS) optimized for CPS environments using a hybrid approach by combining a nature-inspired feature selection scheme, such as Grey Wolf Optimization (GWO),… More >