Remaining useful life (RUL) prediction for offshore wind turbines is important for predictive maintenance. However, its practical use is limited by the lack of reliable RUL labels, the small number of fault events, and the complex degradation links among turbine components. Most existing data-driven methods require labeled failure data and cannot fully capture how the degradation of different components is related. To address...

Accurate sea state estimation is of great significance to marine engineering safety and disaster prevention and mitigation. This paper proposes a new sea state estimation architecture integrating multi-scale 1D-CNN, transformer encoder, and the MC-DropKey mechanism. First, the front-end multi-scale 1D-CNN is used in sequence modeling to extract high-quality local features. Then, the back-end transformer encoder is used to capt...

High-fidelity ship dynamics models are essential for the reliable operation of maritime autonomous systems. However, existing Markov-based maneuvering models and purely data-driven predictors struggle to capture hydrodynamic memory and degrade under non-ideal sensing. To address these challenges, this paper proposes a novel approach for robust ship motion prediction, the Non-Markovian Memory-Augmented Environment-Perceived and...

Marine fish communities in coastal systems are increasingly shaped by environmental gradients associated with anthropogenic pressures and climate variability, yet how these factors influence community assembly and functional traits remain poorly understood. In this study, environmental DNA (eDNA) metabarcoding using the 12S MiFish primer with 33 water samples was integrated with taxonomic and functional diversity analyses, co-...