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Freshwater inputs originating from terrestrial streams and gullies that discharge into quiescent, semi-enclosed coastal regions (such as estuaries, tidal inlets or lagoons), typically provide point sources of nutrients (e.g. nitrates, phosphates) and/or contaminants (e.g. pesticides, pathogens) that may have a deleterious impact on water quality. Many of these sheltered coastal regions also increasingly support aquaculture operations (e.g. finfish, shellfish, or seaweed farms), which can therefore be directly impacted by nutrient and contaminant inputs. Dynamically, these terrestrial freshwater inflows behave as surface buoyant jets or plumes within the coastal saline or brackish receiving waters, due to the salinity-induced density gradients. As such, the presence of infrastructure associated with aquaculture operations in sheltered coastal waters can provide obstruction to the propagation characteristics and residence times for these surface freshwater flows. Consequently, an improved physical understanding of the flow-structure interaction is clearly crucial to assessing the potential contamination risk of aquaculture products. The aim of the current study is therefore to explore, through scaled laboratory experiments within a channel-basin facility, the impact of physical obstruction induced by a vertical grid structure on the flow evolution of a 2D – 3D expanding, surface buoyant jet. Two grid obstructions with different solidity ratios are tested, along with surface gravity currents of different density excesses and freshwater inflows to infer the influence of different parametric conditions on the propagation, blockage and mixing characteristics of the surface current in the vicinity of the grid obstruction. Measurements of the velocity structure and thickness of the expanding surface plume are obtained by ultrasonic velocity profilers, while the density excess in the evolving plume is measured by micro-conductivity probes. Dye visualization results also show that, in the presence of the grid obstruction, the generation of shear-induced billows at the lower interface of the expanding surface current is largely blocked and a local deepening of the fresh-salt water interface in the immediate vicinity of the grid obstruction is observed. In this sense, the obstruction imposed by aquaculture infrastructure in coastal domains can have a considerable influence of the local turbulent mixing and vertical transfer of substances (e.g. nutrients and contaminants), but is likely to have relatively minimal impact in the final dispersion of the surface plume. [ABSTRACT FROM AUTHOR]

This research addresses the critical issue of major fishing vessel accidents, which traditionally suffer from a lack of focused analysis due to their rarity and the subjective nature of their classification. We propose an innovative methodology of Peaks Over Threshold to overcome subjectivity in accident classification. This approach ensures a more representative and accurate analysis of major accidents, distinguishing them from more common, less severe incidents. Employing a Bayesian network model, we further explore the most influential factors contributing to these major accidents. The key innovation lies in our novel approach to data handling and analysis, enabling us to uncover hidden patterns and causal relationships that traditional methods often overlook. The results show that the approach proposed in this study can effectively capture the key factors of major fishing vessel accidents. This study identifies accident type, vessel-related factors, and accident location as the key influential factors leading to major accidents. The findings from our research are intended to inform sustainable fisheries management practices, promoting interventions that aim to decrease the occurrence and impact of severe maritime accidents while balancing economic, safety, and sustainable development considerations. [ABSTRACT FROM AUTHOR]

Since the Ice Silk Road (ISR) was put forward, its development prospect has become the focus of academic circles. To study the influence mechanism of 'fairness preference' on the trade cooperation of countries along the ISR, this paper constructs the trade cooperation network based on the bilateral trade data of countries along the ISR, establishes the theoretical model of network game based on Rabin model, and uses the simulation method to test the model. The results show that: (1) the sense of national cognitive fairness does have an impact on the trade cooperation of the ISR; (2) the 'eye for an eye, tooth for a tooth' strategy is not an advantage strategy in the trade cooperation of the ISR; (3) the most significant factor affecting the trade cooperation of countries along the ISR is the neighbor node in the trade network and the social public opinion pressure of cooperation in the network. [ABSTRACT FROM AUTHOR]

The Bohai Rim region constitutes the third prominent "growth pole" in China's economic landscape, wherein the Bohai Rim multi-port system, encompassing Tianjin Port, Dalian Port, and Qingdao Port, engages in intense competition to establish itself as the foremost shipping hub in northern China. This study compares the ternary diagram method and employs the comprehensive concentration index (CCI), Lerner index (LI), and spatial shift-share analysis (SSSA) methods to delve into the intricacies of concentration, inequality, and evolving competitive dynamics within the Bohai Rim multi-port system over the four decades spanning from 1981 to 2023. The aim is to analyze the evolutionary trajectory and underlying dynamic mechanisms of this multipartite port system. The analysis delineates the development trajectory of the system into three stages: the dominant stage of Tianjin Port from 1981 to 1990, the efficiency competition stage from 1991 to 1996, and the ascendancy of Qingdao Port from 1997 to 2023. The results indicate that: (i) the Bohai Rim multi-port system exhibits a relatively low level of concentration, ensuring balanced growth within a non-monopolistic competitive environment; (ii) the internal competitiveness of the Bohai Rim multi-port system has gradually shifted from Tianjin Port to Qingdao Port, with Dalian Port experiencing steady development in its container transport capabilities. (iii) Dalian Port has witnessed a decline in container throughput since 2015, indicating a weakening competitive posture. These revelations suggest that Qingdao Port is a viable candidate for development into the northern China shipping center, leveraging its increasing competitiveness and strategic location. The method applied in this study may also prove beneficial for similar multi-port systems elsewhere. [ABSTRACT FROM AUTHOR]

The accurate timing for collision avoidance actions is crucial for preventing maritime collisions. Traditional methods often rely on collision risk assessments, using quantitative indicators like the Distance to the Closest Point of Approach (DCPA) and the Time to the Closest Point of Approach (TCPA). Ship Officers on Watch (OOWs) are required to execute avoidance maneuvers once these indicators reach or exceed preset safety thresholds. However, the effectiveness of these indicators is limited by uncertainties in the maritime environment and the human behaviors of OOWs. To address these limitations, this study introduces a machine learning method to learn collision avoidance behavior from empirical data of ship collision avoidance, particularly in cross-encounter situations. The research utilizes Automatic Identification System (AIS) data from the open waters around Ningbo Zhoushan Port. After data preprocessing and applying spatio-temporal constraints, this study identifies ship trajectory pairs in crossing scenarios and calculates their relative motion parameters. The Douglas–Peucker algorithm is used to identify the timing of ship collision avoidance actions and a collision avoidance decision dataset is constructed. The Random Forest algorithm was then used to analyze the factors affecting the timing of collision avoidance, and six key factors were identified: the distance, relative speed, relative bearing, DCPA, TCPA, and the ratio of the lengths of the giving-way and stand-on ships. These factors serve as inputs for the XGBoost algorithm model, which is enhanced with Particle Swarm Optimization (PSO), and thus constructing a ship collision avoidance decision model. In addition, considering the inherent errors in any model and the dynamic nature of the ship collision avoidance process, an action time window for collision avoidance is introduced, which provides a more flexible time range for ships to make timely collision avoidance responses based on actual conditions and the specific encounter environment. This model provides OOWs with accurate timing for taking collision avoidance decisions. Case studies have validated the practicality and effectiveness of this model, offering new theoretical foundations and practical guidance for maritime collision avoidance. [ABSTRACT FROM AUTHOR]

Featured Application: Port Environmental Management systems; automated spill and waste detection in port waters. Water quality and pollution is the main environmental concern for ports and adjacent coastal waters. Therefore, the development of Port Environmental Management systems often relies on water pollution monitoring. Computer vision is a powerful and versatile tool for an exhaustive and systematic monitoring task. An investigation has been conducted at the Port of Palma de Mallorca (Spain) to assess the feasibility and evaluate the main opportunities and difficulties of the implementation of water pollution monitoring based on computer vision. Experiments on surface slicks and marine litter identification based on random image sets have been conducted. The reliability and development requirements of the method have been evaluated, concluding that computer vision is suitable for these monitoring tasks. Several computer vision techniques based on convolutional neural networks were assessed, finding that Image Classification is the most adequate for marine pollution monitoring tasks due to its high accuracy rates and low training requirements. Image set size for initial training and the possibility to improve accuracy through retraining with increased image sets were considered due to the difficulty in obtaining port spill images. Thus, we have found that progressive implementation can not only offer functional monitoring systems in a shorter time frame but also reduce the total development cost for a system with the same accuracy level. [ABSTRACT FROM AUTHOR]