Giada Faraco^*, Andrea Vincenzo De Nunzio, Nicola Ivan Giannoccaro^*, Arcangelo Messina

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.075327 - 31 March 2026

Abstract Damage detection and localization analysis have gained increasing importance over the years, due to the growing number of catastrophic events and the associated risks that small, undetected cracks in structures may evolve into severe failures if not identified in time. In this context, vibration-based methods have been extensively investigated for structural damage detection. Among them, one of the most widely used approaches since its introduction is the curvature method. It has been successfully employed in numerous studies, consistently providing reliable results. However, the use of second-order or higher-order derivatives can be challenging when dealing with… More >

Wael A. Altabey^*

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.073949 - 31 March 2026

Abstract The study of long-term pavement performance is a fundamental topic in the field of highway engineering. Through comprehensive and in-depth research on the pavement system, the previous scattered, one-sided, superficial, and perceptual knowledge and experience are summarized and sublimated into a systematic and complete engineering theory, thereby providing powerful guidance and assistance for the practice of pavement design, construction, maintenance, operation, and management. In this research, the mentoring system deployment technology for automatic monitoring is carried out for long-term pavement performance. By burying a variety of sensors in different parts of the road surface, base,… More >

Tao Yuan¹, Qin Tang², Zhiwen Zhu^2,*, Jin Jiang², Lin Zhang¹, Gangqiao Wang¹

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.072805 - 31 March 2026

Abstract Using field monitoring data, this study directly compares the stress responses of fatigue-prone orthotropic steel deck (OSD) details with an epoxy asphalt concrete (EAC) overlay during in-service winter and summer seasons. This study was conducted on the E’dong Yangtze River Bridge in China, a cable-stayed bridge featuring a main span of 936 m and an EAC-paved deck pavement. The findings reveal that across all OSD details, stress levels and loading cycles are generally higher in summer than in winter. The most pronounced increase occurs at the rib-to-deck (RD) detail, particularly on the deck plate side.… More >

Mohammadreza Vafaei^1,*, Sophia C. Alih², Abdirahman Abdulkadir¹

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.078250 - 30 March 2026

Abstract Rapid quantification of seismic-induced damage immediately following an earthquake is critical for determining whether a structure is safe for continued occupation or requires evacuation. This study proposes a novel damage identification method that utilizes limited strain data points, significantly reducing installation, maintenance, and data analysis costs compared to traditional distributed sensor networks. The approach integrates finite element (FE) modeling to generate capacity curves through pushover analysis, incorporates noise-augmented datasets for Artificial Neural Network (ANN) training, and classifies structural conditions into four damage levels: Operational (OP), Immediate Occupancy (IO), Life Safety (LS), and Collapse Prevention (CP).… More > Graphic Abstract

Roberta Giorgione^1,#, Daniela Grasso^2,#, Elisabetta Gambale¹, Federico Scolari³, Virginia Rossi¹, Fabrizio Di Maida⁴, Marinella Micol Mela¹, Barbara Marzocchi², Laura Doni¹, Adriano Pasqui¹, Andrea Minervini⁴, Enrico Caliman¹, Sergio Serni^4,5,6, Andrea Bernini², Serena Pillozzi³, Lorenzo Antonuzzo^1,5,*

Oncology Research, Vol.34, No.4, 2026, DOI:10.32604/or.2026.068896 - 23 March 2026

Abstract Objectives: To date, predictive and prognostic biomarkers for Bladder Cancer (BC) remain lacking. Existing literature underscores the potential of metabolomics as a valuable tool for biomarker identification. The primary objective of this study is to characterize the serum metabolic profile of BC patients undergoing platinum-based chemotherapy (Pt-CT) to identify potential biomarkers. Methods: In this pilot study, we investigated the metabolomic profiles of 14 BC patients undergoing Pt-CT in different settings. We compared their baseline profiles with those of healthy controls and tracked key metabolites throughout chemotherapy cycles. Metabolomics profiling was conducted using nuclear magnetic resonance… More >

Xinyue Zhang¹, Yuxuan Zhao², Jeremy S. Smith³, Yuechun Wang⁴, Gabriela Mogos⁵, Ka Lok Man¹, Yutao Yue^6,7,8,9, Young-Ae Jung^10,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075415 - 12 March 2026

Abstract Intelligent Transportation Systems (ITS) represent a cornerstone in modern traffic management, leveraging surveillance cameras as primary visual sensors to monitor road conditions. However, the fixed characteristics of public surveillance cameras, coupled with inherent image resolution limitations, pose significant challenges for Small Object Detection (SOD) in traffic surveillance. To address these challenges, this paper proposes Ghost-Attention YOLO (GA-YOLO), a lightweight model derived from YOLOv8 and specifically designed for traffic SOD. To enhance the attention of small targets and critical features, a novel channel-spatial attention mechanism, termed Small-object Extend Attention (SEA), is introduced. In addition, the original… More >

Huiying Liu^1,2, Wenjin Wu^1,2,3,*, Yaqi Geng^1,2,3, Zhiqu Liu⁴, Xiulai Xiao⁴, Huadong Guo^1,2,3

Revue Internationale de Géomatique, Vol.35, pp. 121-130, 2026, DOI:10.32604/rig.2026.075844 - 04 March 2026

Abstract Moon-based Synthetic Aperture Radar (SAR) is particularly suitable for monitoring polar regions because of its consistent and continuous imaging. It has promising applications in the observation of sea ice by capturing rapid freeze-thaw cycles in the Arctic and Antarctic. However, the long synthetic aperture time inherent in Moon-based SAR may lead to image defocusing due to water fluctuations. Additionally, large incidence angles during observations in polar regions can result in weak backscatter from sea ice, thereby affecting the signal-to-noise ratio and ice–water discrimination. In this study, a ground-based experiment was conducted to evaluate the impact More >

Josmell Alva Alcántara¹, Elder Mendoza Orbegoso¹, Nattan Roberto Caetano², Luis Julca Verástegui¹, Juan Bengoa Seminario¹, Jimmy Silvera Otañe¹, Yvan Leiva Calvanapón¹, Giulio Lorenzini^3,*

Frontiers in Heat and Mass Transfer, Vol.24, No.1, 2026, DOI:10.32604/fhmt.2025.074995 - 28 February 2026

Abstract The continuous improvement of solar thermal technologies is essential to meet the growing demand for sustainable heat generation and to support global decarbonization efforts. This study presents the design, implementation, and validation of a real-time monitoring framework based on the Internet of Things (IoT) and cloud computing to enhance the thermal performance of evacuated tube solar water heaters (ETSWHs). A commercial system and a custom-built prototype were instrumented with Industry 4.0 technologies, including platinum resistance temperature detectors (PT100), solar irradiance and wind speed sensors, a programmable logic controller (PLC), a SCADA interface, and a cloud-connected… More >

Mubarak Alanazi^1,*, Junaid Rashid²

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.2, 2026, DOI:10.32604/cmes.2026.077956 - 26 February 2026

Abstract Wind turbine blade defect detection faces persistent challenges in separating small, low-contrast surface faults from complex backgrounds while maintaining reliability under variable illumination and viewpoints. Conventional image-processing pipelines struggle with scalability and robustness, and recent deep learning methods remain sensitive to class imbalance and acquisition variability. This paper introduces TurbineBladeDetNet, a convolutional architecture combining dual-attention mechanisms with multi-path feature extraction for detecting five distinct blade fault types. Our approach employs both channel-wise and spatial attention modules alongside an Albumentations-driven augmentation strategy to handle dataset imbalance and capture condition variability. The model achieves 97.14% accuracy, 98.65% More >

Tao Jin^1,2, Zhekun Shou¹, Hongchao Liu^1,*, Yuchun Shao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.2, 2026, DOI:10.32604/cmes.2026.076415 - 26 February 2026

Abstract This research centers on structural health monitoring of bridges, a critical transportation infrastructure. Owing to the cumulative action of heavy vehicle loads, environmental variations, and material aging, bridge components are prone to cracks and other defects, severely compromising structural safety and service life. Traditional inspection methods relying on manual visual assessment or vehicle-mounted sensors suffer from low efficiency, strong subjectivity, and high costs, while conventional image processing techniques and early deep learning models (e.g., U-Net, Faster R-CNN) still perform inadequately in complex environments (e.g., varying illumination, noise, false cracks) due to poor perception of fine… More >