This study assesses the concepts of marine resource conservation and sustainability among Taiwanese high school students by developing a Chinese version of the Marine Resources Conservation and Sustainability Scale. Grounded in the cognitive, socio-emotional, and behavioral learning objectives outlined in UNESCO's Education for Sustainable Development Goals (ESDGs), the scale targets students aged 16 to 18 to examine gender differences in marine knowledge and conservation concepts. The scale comprises 31 items across four dimensions: the first section evaluates marine knowledge, while the remaining dimensions utilize a four-point Likert scale to assess cognitive, socioemotional, and behavioral learning objectives, respectively. The results indicate that the scale demonstrates strong reliability and validity, with female students outperforming male students in socio-emotional and behavioral learning objectives. This newly developed scale provides a reliable tool for evaluating students' understanding of marine knowledge and conservation concepts, essential for addressing real-world marine environmental challenges.
Owing to increasingly stringent emission regulations imposed by the International Maritime Organization and rising fuel prices, the demand for enhanced energy efficiency and emission control in marine power systems is increasing. This study presents a case study in which the performance of an aging auxiliary generator is restored by modifying the turbocharger nozzle ring. The vessel, a 12-year-old crude-oil tanker, experienced repeated operational issues with its No. 3 generator. This included elevated exhaust gas temperatures, reduced intake air pressure, and frequent turbocharger surges. To address these challenges, the nozzle-ring blade angle was reduced by approximately 2(degrees) using spare components, while maintaining the original flow area. Key performance indicators, including exhaust gas temperature, turbocharger rotational speed, intake air pressure, and output stability, were measured under consistent load conditions before and after the modification. The results showed that the exhaust gas temperature dropped to approximately 70 C-degrees, while the turbocharger rotational speed increased by approximately 2100 rpm, and intake pressure improved from 1.8 to 2.2 bar. No surging or abnormal vibrations were observed after modification. These findings demonstrate that minor geometric adjustments to the nozzle ring can effectively alleviate performance degradation without the need for full component replacement. Redesigning the nozzle geometry to match combustion flow changes provides a costeffective and technically feasible maintenance strategy that can prevent power failures and improve energy efficiency. Moreover, this ensures compliance with environmental regulations. This approach has potential applicability to different ship types and engine configurations.
Early detection of shrimp diseases is vital for reducing losses and ensuring sustainable aquaculture. In this study, a novel ontology-driven framework for shrimp disease diagnosis that integrates environmental knowledge with machine learning-based image analysis is proposed. An ontology was constructed from a structured dataset of environmental parameters and farm conditions related to shrimp diseases, which formally represents concepts such as farm characteristics, environmental factors, symptoms, and disease types. Two public shrimp image datasets were subsequently used to train convolutional neural networks (ResNet50 and MobileNetV2) for automated disease classification. The predicted disease labels and confidence scores were mapped onto the ontology. Semantic reasoning rules (SWRL) and SPARQL queries were then combined with image-based predictions and environmental risk factors to generate explainable diagnostic results and tailored management recommendations. The experimental results show that this ontology-ML hybrid approach achieves higher diagnostic accuracy than traditional methods without ontology integration do, thus demonstrating its potential for providing more precise, context-aware, and actionable support for shrimp health management.
This study investigates the corrosion protection assessment of offshore wind turbine substructures established in the waters off Keelung, Taiwan. First, a cathodic protection system for the monopile foundation is designed and established. The Boundary Element Method (BEM) is applied using the BEASY simulation software to develop a 3D geometric model for cathodic protection. In the steel monopile simulation analysis, the exposed marine environment is set based on the sea conditions of the Keelung small boat marina, including parameters such as salinity, resistance, and polarization curves, to establish an effective cathodic protection system for underwater structures. By simulating these parameters, a better understanding of the corrosion protection performance of the monopile under different environmental conditions can be achieved. Additionally, the polarization curve of the monopile is set to evaluate the variation in corrosion protection potential. The analysis examines the effects of different corrosion polarization potentials of bare steel monopiles, the distance between anodes and cathodes, and the influence of varying numbers of anode. The BEASY simulation results indicate that under different parameter settings, the corrosion protection potential of the bare steel monopile exhibits varying trends. The simulation analysis of the potential distribution for the bare steel monopile ranges from-998 mV to-1056 mV, meeting DNV-RP-B401 criteria for effective protection, confirming the optimal corrosion protection effectiveness.
In this study, bibliometric analysis and visualization tools were used to investigate the academic network and knowledge structure surrounding global giant clam research. A total of 551 relevant publications from the Web of Science database, published from 1900 to 2024, were analyzed. The findings indicate that research on giant clams has experienced considerable growth since 2012, peaking in publication output in 2021. Sixty-six countries were represented in the study sample, with the United States, Australia, China, Singapore, and Japan being the most represented ones. Notably, the rate of international collaboration was only 29%, highlighting a need for additional integrated cross-border research efforts. Keyword co-occurrence analysis indicated seven major research clusters, covering core themes such as the giant clam growth and symbiotic mechanisms, classification and diversity, conservation management, and climate change. Furthermore, findings on the authors' collaboration network revealed a high concentration of research power, with only a few scholars dominating advances in the field. The present study delineates the knowledge structure and cooperation patterns within giant clam research while identifying current shortcomings in regional collaboration, data sharing, and policy connections. Efforts should be made to strengthen cross-sector integration and long-term monitoring systems as well as to deepen local community participation to enhance the scientific conservation and sustainable management of giant clams. This study contributes to the development of marine conservation policies and research strategies.
Locks are critical nodes in inland waterway transportation systems that concentrate vessel traffic between upstream and downstream reaches, making their operations highly sensitive to hydrological conditions. Therefore, disruptions caused by droughts, floods, or routine maintenance can easily trigger congestion. To address this issue, this study systematically examines the interrelationships among the number of ships awaiting passage, scheduling strategies, the trade-off between lock chamber utilization and ship waiting time, the influence of ship entry sequences on user satisfaction, and the combined effects of these factors on overall lock scheduling performance. Based on these analyses, an integrated decision-making model for two-stage ship lock scheduling under interruption scenarios is developed, with the number of lockage plans and average ship waiting time as the objective functions. The resulting optimization problem is solved using a MATLAB-implemented genetic algorithm. The results of the case study demonstrate that, compared with manual scheduling, the proposed approach reduces the average ship waiting time by approximately 0.55 h, while user satisfaction improves by about 11% relative to the release mode.
Transboundary fisheries governance is increasingly challenged by jurisdictional conflicts, regulatory asymmetries, and climate-induced stock shifts in fish stocks, especially in contested regions like the East China Sea (ECS). This study capitalizes on China's high-frequency BeiDou Navigation Satellite System (BDS) data (June 2021-May 2022) to pioneer a CNN-BiLSTM deep learning model to dynamically identify fishing hotspots and evaluate policy effectiveness. By integrating vessel trajectories, environmental variables, and regulatory events, we examine spatiotemporal patterns of fishing effort relative to seasonal bans, extreme weather, and quota systems. Key findings reveal: (1) post-moratorium (September-December) concentration of fishing intensity, peaking in November; (2) significant weather-driven suppression of spring fishing activity; (3) persistent trawler hotspots in designated closed zones, highlighting areas in need of heightened regulatory scrutiny; (4) measurable impacts of output-controlled quotas on effort distribution; (5) Behavioral indicators derived from BeiDou data support the evaluation of governance effectiveness, including quota-based management; and (6) Chinese fishing vessels from Zhejiang Province exhibit a generally high level of compliance within the Sino-Japanese and Sino-Korean Provisional Measures Zones (PMZs). This research underscores the value of BeiDou data in enabling real-time, adaptive governance. We propose dynamic zoning and climate-responsive quotas to strengthen ecosystem-based management in transboundary fisheries, calling for integrated satellite monitoring and cross-jurisdictional coordination to enhance climate resilience and sustainable exploitation.
This study explores the weather resistance, mechanical properties and corrosion resistance of polyurea coatings in marine environments. The relevant analysis results can be used as a reliability assessment of offshore wind turbine structural coatings during their service life under the influence of marine environments. The long-term experiment uses seawater and 70 degrees C thermal aging conditions as coating reliability assessment items. The microstructure of the samples that have been immersed in seawater for a long time and thermally aged is observed using a scanning electron microscope (SEM). The results show that the surface of the 100 and 125 series polyurea coatings is flat at the beginning of the seawater corrosion test (96 h). At this time point, the polyurea coating will be accompanied by the phenomenon of mechanical property recovery (i.e., the mechanical properties are improved). When the test time is increased to 168 h to 3 months, precipitates will appear on the coating surface and holes will form; when the test time is increased to 5-12 months, wrinkles and holes will appear on the test piece. After the functional group detection by Fourier transform infrared spectroscopy (FTIR), the spectrum shows that the peak at a frequency of 3300 cm(-1) belongs to the stretching vibration reaction of the N-H bond, and the peak intensity of the N-H bond will weaken as the test time increases. The peak at a frequency of 1660-1620 cm(-1) belongs to the carbonyl bond. The test results show that the carbonyl bond peak will shift as the test time increases. This shift belongs to the reaction of hydrogen bond aging and dissociation. Finally, the mechanical property test results show that the mechanical property retention rate of the coating can be maintained at more than 80% after long-term testing. The results of the QUV test and the marine exposure test show that the corrosion rate of the steel pile coating in the marine environment is only 0.00141 mm/year, the weight loss is 0.076%, and there is no significant peeling on the coating surface, only seaweed and shells are attached. The actual results of marine corrosion show that the polyurea coating has excellent corrosion resistance and has long-term stability in harsh marine environments, and can be used as an outer protective layer for marine structures.
Seagrass meadows provide essential coastal ecosystem functions by stabilizing sediments, enhancing water quality, and shaping nutrient and microbial dynamics. With global seagrass losses accelerating due to climate change and anthropogenic pressures, artificial seagrass (ASG) has been proposed as a nature-based alternative to mimic these functions. However, its ability to replicate biological interactions, particularly microbial regulation and pathogen suppression, remains unclear. In this study, we conducted a six-week mesocosm experiment comparing natural Thalassia hemprichii and ASG within coral reef-associated habitats in southern Taiwan. Physicochemical parameters, sedimentation rates, nutrient concentrations, and planktonic and benthic bacterial communities were analyzed. Sedimentation rates and nutrient levels did not show statistically detectable differences between natural and artificial seagrass treatments, suggesting comparable physical conditions under the experimental scale and replication. Community-level analyses showed that within the planktonic communities, ASG and natural seagrass systems differed significantly, whereas benthic communities did not exhibit statistically detectable treatment effects. Nonetheless, taxon-specific patterns revealed important functional divergences. Natural seagrass mesocosms were associated with higher relative abundance of bacterial taxa commonly link to nutrient cycling and nitrogen transformation, including members of the Alphaproteobacteria. In contrast, ASG mesocosms showed higher relative abundances of potentially pathogenic or opportunistic taxa such as Vibrio spp. and filamentous cyanobacteria (Phormidium). Overall, while ASG reproduced key aspects of the physical habitat structure, the microbial community patterns observed here suggest that artificial substrates may not fully capture the biologically mediated interactions characteristic of living seagrass systems. Within the limits of experimental duration and replication, our results indicate that ASG can approximate structural habitat functions but do not provide evidence of full functional equivalence to natural seagrass meadows. ASG may therefore contribute short-term structural habitat complexity, whereas the broader ecological functions associated with intact seagrass ecosystems likely depend on plant-driven biological interactions that were only partially represented under the present experimental conditions.
The COVID-19 pandemic created significant challenges for higher education, with universities being shut down and face-to-face teaching and assessment shifting to an online format. This presented an opportunity to focus on the continuity of learning through distance education, especially in the maritime context, due to the on-board training requirements, and even though five years have passed, this shift has reshaped the education landscape, proving that remote learning has come to stay. At the Barcelona School of Nautical Studies, we have developed a weather routing software in the framework of distance education and teaching innovation. We conducted a teaching trial alternatively at sea (distance education) and onshore (face-to-face education), and results have been compared in terms of competence acquisition in the maritime education and training framework. The focus of this paper is twofold, as it is not only to validate a novel teaching tool for assessing maritime competences but also to ascertain whether there are any significant divergences in competence acquisition regardless of the educational environment.
Enhancing resilience through early warning is a critical strategy for mitigating disruption risks in the maritime supply chain (MSC). This study proposes a novel early warning assessment framework to determine the resilience of the MSC. It is referred to as a resilience early warning system. An evaluation index system for shipping enterprises is developed based on four dimensions: withstand capacity, adaptive capacity, learning capability, and the external environment. A resilience assessment model that uses the Bayesian best-worst method (BBWM) and the extension cloud model (ECM) is established to quantify MSC resilience. An early warning evaluation model based on a Bayesian network (BN) is constructed to dynamically link resilience indicators with risk propagation patterns. Empirical validation is conducted using the MSC of China's new energy vehicle (NEV) exports. The proposed BBWM-ECM-BN resilience early warning model uses BNs to capture complex relationships among indicators, overcoming the limitations of traditional methods that rely on linear assumptions. Using probabilistic early warning thresholds instead of deterministic estimates enables risk prediction. The results show the following. (1) The resilience early warning level of China's NEV export MSC is moderate. Among primary indicators, withstand capacity has a minor warning level, trending toward moderate. Adaptive capacity and External environment are at a moderate level, trending toward severe. Learning capacity is at a moderate level, trending toward minor. (2) Sensitivity analysis shows that Technology Improvement and Innovation Ability is the most influential secondary indicator (0.7360), followed by Security Risk (0.4310) and Government Risk (0.2310). This study advances theoretical understanding of MSC resilience assessment and provides data-driven tools to mitigate escalating international maritime disruption risks, supporting the stable development of China's NEV export industry and global MSC networks.
In addition to using second-hand oil tankers to fulfil immediate shipping needs, shipowners can leverage price fluctuations in the tanker market to make vessel sale-and-purchase (S&P) transactions. Given that the profitability of vessel S&P transactions depends primarily on timing decisions, in this study, technical analysis was applied to identify the optimal transaction timing for 5-, 10-, and 15-year-old second-hand Aframax tankers. In a simulation, an S&P strategy based on technical analysis outperformed a benchmark buy-and-hold strategy, particularly for newer tankers, possibly due to the higher price volatility and lower market efficiency in the markets for these vessels. However, the lack of liquidity in the second-hand tanker market limited the performance of technical analysis in vessel trading, particularly for older tankers. These findings suggest that shipowners can select an appropriate technical indicator to profit from the lack of efficiency in the tanker market while avoiding the pitfalls caused by insufficient market liquidity.
This paper presents a deep reinforcement learning (RL) framework for optimizing block storage allocation in shipbuilding yards. During the shipbuilding process, vessels are constructed in block units to maximize the operational efficiency. Following assembly, these blocks must be stored in limited yard spaces, creating a complex variant of the binary packing problem. This storage allocation problem is further complicated by operational constraints, including the barge capacity and transportation time restrictions. Moreover, poor storage decisions can lead to redundant block movements, which can adversely affect downstream processes and increase operational costs. To resolve this problem, a policy-gradient-based synchronous RL model was developed and an embedding layer was introduced to improve its inference performance. The proposed model was validated using both synthetic data and real-world stockyard data. The synthetic dataset was used to prove the proposed model's efficacy and evaluate the hyper parameter value. The real-world data with operational constraints derived from actual field conditions is used for systematic comparisons with mathematical optimization. The comparison demonstrated that the proposed RL method effectively generated solutions that satisfied practical operational constraints, offering a viable alternative to traditional mathematical methods.
This study addresses the network design for international cruise services in a duopolistic market, where carriers enter and make decisions sequentially. The leader, who makes the first move, makes decisions as there is no competitor in the market. The follower, who makes decisions later, has to design their network considering the existing leader's network. The leader's model is a mixed integer linear problem while the follower's model is a mixed integer nonlinear problem. Therefore, a heuristic is proposed to solve the problem. The commercially available general algebraic modeling system is used in conjunction with its different solvers to solve the problems. Finally, the performance of the models is tested using an illustrated network. The results highlight the importance of considering competitive influence and show that our methods are able to handle the problem in a competitive environment.
Illegal, unreported, and unregulated (IUU) fishing activity is a global threat and continues to undermine the effectiveness of fisheries regulations and management measures. However, the extent of illegal fishing in Philippine waters remains unclear. This study aims to identify the types of illegal fishing in Philippine waters and analyzed their temporal and spatial patterns. Data were obtained from the records of the Philippine Coast Guards (PCG) and Maritime Law Enforcement Agencies from 2015 to 2020. A total of 602 apprehensions were recorded, resulting in 813 violations, of which 630 cases were fishery violations. Most of the watercrafts involved in the fishery violations were small-scale vessels (43.1 %). The largest and second largest age groups for violation individuals were 21-30 years (23.2 %), and 31-40 years (23 %), respectively. At least seven types of fishery violations were identified; an 'invalid fishing vessel permit or license' was the most common violation (35.7 %), followed by 'use of active gear' (27.9 %), and 'use of fine-mesh net' (12.9 %). The annual composition of violation types varied over the six years investigated, with the highest number of cases occurring in 2020 (169 cases, 38.3 %). Fishery violations occurred most commonly in Q3 (July to September; 29.5 %) and between 06:00 and 12:00 (31.7 %), although the differences were not statistically significant. The central region of the Philippines had the highest number of illegal fishing cases (35.4 %), with an 'invalid fishing vessel permit or license' being the most common type of violation (52.0 %) in this region. The violation types varied across regions, with an 'invalid fishing vessel permit or license', 'use of active gear,' and 'use of a fine-mesh net' being the most common types in each region. The factors influencing illegal fishing & horbar;including fisheries overcapacity, inconsistent fisheries regulations (such as inconsistent fines and penalties), and potential effects of environmental variability & horbar;are discussed. Proposed measures for improvements include fishing vessel registration, amended regulations (enforcement and penalties), and enhanced interagency cooperation. This study integrated available data on illegal fishing in the Philippines, and provides substantial information with which the PCG can plan appropriate strategies and enforcement schedule.
This study conducted validation and simulation analysis of the cathodic corrosion protection system for bare steel foundation piles in marine environments, focusing on its protective performance and long-term stability. The study selected S355J2H high-strength low-alloy structural steel as the pile material and employed the sacrificial anode cathodic protection method, with aluminum alloy used as the anode material. During the research process, field experiments and BEASY CP software simulations were used to track and compare corrosion potential and current density over an extended period, while also evaluating the impact of marine biofouling on the cathodic protection system. Results showed that after 36 months of exposure, the sacrificial anode blocks continued to degrade, confirming the effective operation of the cathodic protection system. The consumption rate of the sacrificial anodes ranged between 67.7 % and 94.8 %, with field-measured corrosion potentials maintained between-969 mV/SSC and-1078 mV/SSC, meeting the DNVGL-RP-B401 standard requirements. Simulation results indicated corrosion potentials ranging from-975 mV/SSC to-1035 mV/SSC, validating the rationality of the cathodic protection system's design. Additionally, the surface of the bare steel foundation piles was covered with algae and bivalve species, predominantly oysters. The growth of marine organisms has stabilized, with the maximum individual size consistently reaching 9 cm.
Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings. This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco marker contour and corner detection in low-resolution images. For wind resistance control, we use the positional error between the world coordinate system and the ArUco marker as input and regulate the drone's motion using a PID-controlled velocity component. To predict deck motion, we employ an online Backpropagation Neural Network to estimate the ship's roll angle and determine the optimal landing timing. Our approach is evaluated through land-based simulation experiments and compared with existing methods. Most importantly, we validate its effectiveness through real-world landing tests in an actual maritime environment. The landing error was consistent with those observed in land-based experiments, with an average X and Y error of 5.731 cm, indicating the robustness of the system even in offshore conditions. In comparison to existing drone landing research, this study presents significant improvements, particularly with the precision landing system, offering an 18.13 % improvement over the best-known method, which has a 7 cm error. This demonstrates that our system can achieve a significantly higher accuracy, with practical implications for offshore drone operations.
Sand lances (Ammodytes spp.) rely on rapid burrowing into sediment for predator avoidance. Although their sediment grain-size preferences are well documented, the biomechanics underlying burrowing success remain unclear because natural substrates are opaque. Using a transparent-sediment system, we directly visualized and quantified burrowing kinematics to: (1) test the effect of body size (total length, TL) on burrowing success; (2) examine entry mechanisms (e.g., swimming speed, entry angle); and (3) describe locomotion within sediment. Logistic regression on the full dataset (N = 28 fish) identified TL as the primary determinant of success, with larger individuals exhibiting significantly higher success rates ( p < 0.01). A secondary analysis of kinematic variables (N = 36 trials) found no significant predictors of success (all p > 0.05), suggesting that size-related physical capacity dominates over variation in entry technique. Within the sediment, fish employed serpentine locomotion described by sinusoidal waveforms. Waveform parameters (amplitude, wavenumber) were unrelated to TL ( p > 0.15), indicating a conserved, size-independent movement pattern. This study provides the first direct quantitative analysis of sand lance subterranean biomechanics and identifies body size as a key constraint on burrowing performance and habitat use.
Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to spontaneously generate transactions between nodes. Considering the legal uncertainties regarding electronic transferable records in international trade, a uniform legal regime based on international conventions or common standards would better grant the feasibility of the blockchain bill of lading. Positive law instruments such as the Rotterdam Rules and the UNCITRAL Model Law on Electronic Transferable Records (MLETR) could provide a significant regulatory framework for the future legal infrastructure of blockchain bills of lading. This article identifies the specific issues as well as the solutions that can be achieved to the existing legal framework to accommodate the integration of blockchain methodology into bills of lading in the shipping industry.
The motion of ship in wave can be discussed in seakeeping and maneuvering. In model tests, the former is found by the motion response of waves while the latter requires captive model test to acquire hydrodynamic derivatives. The hydrodynamic derivatives in waves are discovered to be different from those in calm water. To understand better the behavior of maneuverability in waves, maneuvering tests in a wide range of waves are performed in this study. This study presents an experimental investigation into the maneuvering behavior of a container ship in regular waves, covering a wide range of wavelengths from half to twice the ship's length. Captive model tests including Oblique Towing Tests (OTT) and pure sway tests were conducted in a towing basin. Maneuvering derivatives were found to suggest that third-order polynomial model may lacks sufficient flexibility to describe maneuverability in waves. Regarding high-frequency forces, components at multiples of the encounter frequency were observed with significant magnitude. The distribution of nonlinearity is found to be strongly dependent on wavelength.
