Ship collisions emerge from interactions among human, vessel, environmental, and management factors. Aggregate accident networks can, however, combine relations across events and evidence levels, obscuring whether recurrent topology represents event-level pathways. We coded 364 official Chinese collision investigation reports using Systems-Theoretic Process Analysis and constructed a directed binary network of 46 factors and 2...

Deep-sea exploration increasingly relies on Autonomous Underwater Vehicles (AUVs) to enable persistent, wide-area surveying in harsh and uncertain environments. In practice, however, deployments are constrained by tight energy budgets and bandwidth-limited, intermittent acoustic links, which complicate mission-level coordination. Moreover, many existing systems treat perception and control as loosely coupled modules, often res...

The development of robust autonomous maritime systems is fundamentally constrained by the “data silo” problem, where valuable operational data from disparate fleets remain isolated due to privacy concerns, severely limiting the scalability of general-purpose navigation intelligence. To address this barrier, we propose a novel Federated Meta-Transfer Learning (FMTL) framework that enables collaborative evolution of unmanned sur...

Offshore tubular pile systems in earthquake-active marine regions face risks from vertical seismic excitation, water dynamics, and pile–soil interactions. Thus, an analytical solution for offshore tubular piles considering multi-physical field coupling (the mutual interactions between seawater, tubular pile, and surrounding soil) is developed to investigate their dynamic responses under vertical seismic loading. Firstly, the d...