Wei Chen, Yang Wu^*, Tingting Pei, Jie Lin, Guojing Yuan

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070905 - 27 January 2026

Abstract In view of the insufficient utilization of condition-monitoring information and the improper scheduling often observed in conventional maintenance strategies for photovoltaic (PV) modules, this study proposes a predictive maintenance (PdM) strategy based on Remaining Useful Life (RUL) estimation. First, a RUL prediction model is established using the Transformer architecture, which enables the effective processing of sequential degradation data. By employing the historical degradation data of PV modules, the proposed model provides accurate forecasts of the remaining useful life, thereby supplying essential inputs for maintenance decision-making. Subsequently, the RUL information obtained from the prediction process is… More >

Hongsheng Su, Zhensheng Teng^*, Zihan Zhou

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.069495 - 27 January 2026

Abstract Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy, replacement-based maintenance practices that deviate from actual operational conditions, and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization, this study proposes a Time-Based Incomplete Maintenance (TBIM) strategy incorporating reliability constraints through stochastic differential equations (SDE). By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions, a high-precision SDE degradation model is constructed, achieving 16% residual reduction compared to… More >

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 >

Atheer Aleran¹, Hanan Almukhalfi¹, Ayman Noor¹, Reyadh Alluhaibi², Abdulrahman Hafez³, Talal H. Noor^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.070741 - 12 January 2026

Abstract Modern industrial environments require uninterrupted machinery operation to maintain productivity standards while ensuring safety and minimizing costs. Conventional maintenance methods, such as reactive maintenance (i.e., run to failure) or time-based preventive maintenance (i.e., scheduled servicing), prove ineffective for complex systems with many Internet of Things (IoT) devices and sensors because they fall short in detecting faults at early stages when it is most crucial. This paper presents a predictive maintenance framework based on a hybrid deep learning model that integrates the capabilities of Long Short-Term Memory (LSTM) Networks and Convolutional Neural Networks (CNNs). The framework… More >

Xiaopan Zou^1,2, Meiyang Sun³, Xin Jiang¹, Jingze Yu², Xiaomeng Li^4,*, Bingyu Nie^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.066662 - 30 December 2025

Abstract Objective: Triple-negative breast cancer (TNBC) is highly aggressive and lacks an effective targeted therapy. This study aimed to elucidate the functions and possible mechanisms of action of zinc finger miz-type containing 2 (ZMIZ2) and minichromosome maintenance complex component 3 (MCM3) in TNBC progression. Methods: The relationship between ZMIZ2 expression and clinical characteristics of TNBC was investigated. In vitro and in vivo experiments were performed to investigate the role of ZMIZ2 dysregulation in TNBC cell malignant behaviors. The regulatory relationship between ZMIZ2 and MCM3 was also explored. Transcriptome sequencing was performed to elucidate possible mechanisms underlying the ZMIZ2/MCM3… More >

Tiankui Sun^*, Shuyi Zhuang, Yongling Lu, Wenqiang Xie, Ning Guo, Sudi Xu

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.070213 - 27 December 2025

Abstract To ensure an uninterrupted power supply, mobile power sources (MPS) are widely deployed in power grids during emergencies. Comprising mobile emergency generators (MEGs) and mobile energy storage systems (MESS), MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies, offering advantages such as flexibility and high resilience through electricity delivery via transportation networks. This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator (DWIG) intended for MEG applications, employing an improved particle swarm optimization (PSO) algorithm based on a back-propagation neural network (BPNN). A… More >

Bo Zhu^1,#, Enzhi Dong^1,#, Zhonghua Cheng^1,*, Xianbiao Zhan², Kexin Jiang¹, Rongcai Wang ³

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-26, 2026, DOI:10.32604/cmc.2025.069194 - 10 November 2025

Abstract With the increasing complexity of industrial automation, planetary gearboxes play a vital role in large-scale equipment transmission systems, directly impacting operational efficiency and safety. Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment, leading to excessive maintenance costs or potential failure risks. However, existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes. To address these challenges, this study proposes a novel condition-based maintenance framework for planetary gearboxes. A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals, which were then processed using a… More >

Szymon Piątek¹, Anna Dańska-Bidzińska^2,*, Paweł Derlatka², Bartosz Szymanowski³, Renata Duchnowska³, Aleksandra Zielińska⁴, Natalia Sawicka⁴, Aleksander Gorzeń⁵, Wojciech Michalski⁶, Mariusz Bidziński¹

Oncology Research, Vol.33, No.11, pp. 3405-3416, 2025, DOI:10.32604/or.2025.068609 - 22 October 2025

Abstract Objectives: Monitoring of Cancer Antigen 125 (CA125) during ovarian cancer (OC) maintenance treatment with poly(ADP-ribose) polymerase inhibitors (PARPis) may be insufficient when using Gynecologic Cancer Intergroup (GCIG) biochemical progression criteria. This study aimed to evaluate the usefulness of CA125 monitoring in detecting OC recurrence during PARPis maintenance treatment. Methods: This multicenter retrospective cohort study included patients with primary OC who achieved complete or partial response after first-line platinum-based chemotherapy followed by PARPis maintenance treatment. Progression was defined using Response Evaluation Criteria in Solid Tumors (RECIST) and GCIG biochemical criteria. New biochemical progression definitions, based on… More >

Acácio M. R. Amaral^1,2,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3825-3859, 2025, DOI:10.32604/cmc.2025.067179 - 23 September 2025

Abstract Power converters are essential components in modern life, being widely used in industry, automation, transportation, and household appliances. In many critical applications, their failure can lead not only to financial losses due to operational downtime but also to serious risks to human safety. The capacitors forming the output filter, typically aluminum electrolytic capacitors (AECs), are among the most critical and susceptible components in power converters. The electrolyte in AECs often evaporates over time, causing the internal resistance to rise and the capacitance to drop, ultimately leading to component failure. Detecting this fault requires measuring the… More >

Shuo Zhang, Hanwu He, Yueming Wu^*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 801-826, 2025, DOI:10.32604/cmc.2025.066540 - 29 August 2025

Abstract Virtual maintenance, as an important means of industrial training and education, places strict requirements on the accuracy of participant pose perception and assessment of motion standardization. However, existing research mainly focuses on human pose estimation in general scenarios, lacking specialized solutions for maintenance scenarios. This paper proposes a virtual maintenance human pose estimation method based on multi-scale feature enhancement (VMHPE), which integrates adaptive input feature enhancement, multi-scale feature correction for improved expression of fine movements and complex poses, and multi-scale feature fusion to enhance keypoint localization accuracy. Meanwhile, this study constructs the first virtual maintenance-specific… More >