A method for evaluating safety reliability of descend/ascend drop-weight system and mission abort decision for deep-ocean scientific human submersibles.

Descend and ascend of deep-water human-occupied submersibles based on buoyancy changes are enabled using a denomination of dispensable drop-weights, and loss of buoyancy are managed using emergency drop-weights and jettisoning identified systems. Failing to release the drop weights or jettison results in submersible stranding on the sea floor, leads to emergency recovery, and hence the drop-weight configuration has to be highly reliable. The paper, for the first time, based on hydrostatic stability, descend/ascend velocity needs, ocean salinity profile and loss-of-buoyancy situations, proposes a novel on-demand reliability based methodology for determining the safe drop-weight configuration and degradation-based mission abort strategy for deep-ocean human submersibles. Probabilistic on-demand reliability analysis based on IEC61508 standards for safety-critical systems using component field-failure data is carried out and the drop-weight configuration essential to meet the human-rated safety integrity level 3 during all stages of the subsea mission is identified for the deep-ocean human scientific submersible Matsya6000, based on which a mission abort protocol is evolved.

A latent profile analysis of shift work tolerance among Chinese male sailors during a prolonged non-24-h rotating shift schedule at sea.

Shift work tolerance (SWT) refers to the ability to adapt to shift work without significant adverse consequences. The present study aimed to examine the individual differences in SWT and their predictors and outcomes. Latent profile analyses were conducted using cross-sectional data collected form 448 Chinese male sailors who experienced a prolonged (>30 d) non-24-h rotating shift schedule at sea. Depression, anxiety, sleep disturbance, fatigue, domestic disruption, job satisfaction, work engagement, digestive and cardiovascular symptoms were included as indicators of SWT. The results showed that there existed 2 latent profiles of SWT named as High SWT group and Low SWT group. High SWT group was characterized by low levels on all negative bio-psycho-social outcomes but high levels of work engagement and job satisfaction, while Low SWT group exhibited completely opposite characteristics compared to High SWT group. The level of hardiness could predict profile membership that those with higher level of hardiness were more likely to belong to High SWT group. However, there were no significant differences observed in job performance between two groups. In conclusion, hardiness can serve as a predictor of personnel selection for shift work and hardiness-based intervention programs should be encouraged among the shift workers.

A quantitative assessment of continuous versus structured methods for the detection of marine mammals and seabirds via opportunistic shipboard surveys.

Marine monitoring efforts are increasingly supported by opportunistic shipboard surveys. However, opportunistic survey methods often require adaptation to suit the vessel and the operations being conducted onboard. Whilst best-practice techniques for surveying marine wildlife on vessels of opportunity are yet to be established, testing and development of alternative methods can provide means for capturing ecological information in otherwise under-surveyed areas. Explicitly, survey methods can be improved while baseline ecological data for new regions are gathered simultaneously. Herein, we tested different survey approaches on a vessel of opportunity in a remote offshore area where little is known about the community composition of top-order marine vertebrate predators: western and south-western Tasmania, Australia. We found that continuous surveys provide greater species counts than structured "snapshot" surveys over the course of a voyage, but that structured surveys can be more practical when managing factors such as observer fatigue. Moreover, we provide a baseline dataset on the marine vertebrate community encountered in western and south-western Tasmania. This information will be critically important for industry and conservation management objectives, and is key to our understanding of the offshore ecosystem around Tasmania.

Exploration of port environmental efficiency measurement and influential factors in the Yangtze River Delta Pilot Free Trade Zone.

This study focuses on the environmental efficiency of ports in China's Yangtze River Delta Pilot Free Trade Zone (YRD PFTZ), a critical factor in advancing the high-quality development of ports and facilitating Chinese-style modernization. Current research on port efficiency primarily focuses on the geographical level, with relatively few studies examining the economic regional framework. We selected the YRD PFTZ port for our study to address this gap. Covering 2013 to 2021, we employed the Super-SBM with undesirable outputs and utilized the GML index method. We conducted a spatiotemporal analysis to assess dynamic and static aspects and used the Tobit model to thoroughly investigate the factors influencing the GML Index of these ports. The study showed that: (1) the overall environmental efficiency of these ports was relatively high with a fluctuating trend of initial increase, followed by a decrease, and then an upturn. (2) From a dynamic perspective, the average Green Total Factor Productivity (GTFP) Index is 1.549, denoting an exceptional level primarily driven by technological efficiency. The technical efficiency change index is the main factor improving GTFP in Shanghai, Jiangsu, and Anhui provinces. (3) The port cargo volume and total import and export volume significantly impact the environmental efficiency.

Urbanisation and boating are the main contributors to underwater soundscapes in three temperate estuaries.

Anthropogenic noise has been identified as one of the most harmful forms of global pollutants impacting both terrestrial and aquatic ecosystems. As global populations continue to increase, coastlines are seeing substantial increases in the level of urbanisation. Although measures are in place to minimise stress on fauna, they rarely consider the impact of anthropogenic noise. In Australia, New South Wales (NSW) estuaries have seen extensive increases in urbanisation in recent years. Yet, there remains minimal baseline data on their soundscapes to determine if noise pollution is a threat. This research provides a first assessment of baseline sounds across a temporal and seasonal scale. Recreational boating was the primary soundscape contributor in estuaries, and estuaries with higher urbanisation levels contained higher sound levels. This research provides useful information for managers of NSW estuaries and is of global relevance in an era of increasing generation of anthropogenic noise in estuarine and coastal systems.

Improved Z-number and fault tree analysis to predict the risk of air pollution due to ship boiler operation.

Ships present a significant source of air pollution, contributing to environmental degradation and posing health risks. Boilers are a significant part of the vessels in which the water is heated to evaporate and generate steam. The boilers emit pollutants such as hazardous air pollutants (HAPs), particle pollution, and volatile organic compounds (VOC). This paper conducts an extended risk analysis for air pollution due to boiler operation on ships. An improved Z-numbers theory and Fault Tree Analysis (FTA) are adopted to predict risk. Whilst improved Z-number theory is capable of handling uncertainties inherent in risk assessment, the FTA presents systematically the causal relationships among various factors contributing to the risk of air pollution on ships. The findings show that the failure probability of air pollution during ship boiler operation is 2.08E-05 and BE-12 is the most significant event. Results provide valuable data to maritime stakeholders in fostering environmentally sustainable practices.

[The actual issues of detection of risk factors and prevention of myocardium infarction in sailors].

In Russia, increases morbidity of myocardial infarction. The statistics of recent years demonstrate failure in meeting target indicators of national programs on reducing number of deaths from this disease. At that, able-bodied population is in high risk zone and their professional activity is under influence of large combination of risk factors of myocardial infarction. This risk area covers profession of seafarer that is characterized by irregular work schedule, high levels of stress and mental tension, low physical activity or, contrariwise, increased working loads, unbalanced diet, isotherm stress and interaction with harmful substances. Besides that, situation is aggravated by limited set of first medical aid measures at exacerbation of disease in view of remoteness from hospitalization centers. Thus, considering high mortality rate from myocardial infarction, it is extremely important for ship crews to have full and timely information about diagnostic, symptomatic and prevention of this disease. The article examines statistics data of morbidity and mortality of myocardial infarction in population of the Russian Federation on the basis of Rosstat data and target indicators of the National project "Health Care". The risk factors of myocardial infarction established by INTERHEART studies are analyzed. The specifics of work conditions of crew members of marine vessels are established. The collection of professional modifying risk factors was selected. The recommendations for their correction were developed to enhance efficiency of primary preventive measures and to decrease morbidity and mortality among seafarers.

[Cross sectional study of odontological incidences on board the spanish Navy flagship Juan Carlos I during its first international peacekeeping mission]. / Estudio observacional descriptivo de la incidencia odontológica a bordo del buque insignia de la Armada española Juan Carlos I en su primera misión internacional de mantenimiento de la paz.

OBJECTIVE: Oral health is an essential component of the general well-being and quality of life of the population. In Spain, access to dental services and emergency dental care for civilians is relatively straightforward. However, this is not the case for military personnel, especially those deployed on Navy ships that lack dental capabilities and in isolated areas where access to specialized healthcare services is complex and risky. The aim of this study was to evaluate the incidence and management of dental pathology among Spanish military personnel aboard the LHD 61 Juan Carlos I during its first International Peacekeeping Operation. METHODS: A descriptive observational study was conducted on the accumulated incidences of dental pathology and treatments performed between May 1 and June 26, 2018. The population sample consisted of 448 Spanish military personnel aboard the ship. The data were obtained from the databases of the dental activity logbook and the military statistical and health data management systems, which serve to assess the actual health status of the force. RESULTS: A total of 70 patients were treated for dental problems, with gingivitis and caries being the most prevalent conditions, accounting for 23.07% and 18.68% of cases, respectively. The most common treatments performed were dental reconstructions/fillings, making up 40% of the total, and tartar removal, accounting for 21%. CONCLUSIONS: Understanding the incidence of dental pathologies on Spanish Navy ships allows us to establish the training needs of the onboard medical personnel, as well as determine the material resources that should be provided to naval units. Prevention plans and pre-deployment dental check-ups should be conducted well in advance to address any dental issues on land before personnel are deployed.

OBJETIVO: La salud bucodental es un componente esencial para el bienestar general y la calidad de vida de la población. En España el acceso a los servicios odontológicos y a la atención de la urgencia bucodental del personal civil es relativamente sencilla, pero no ocurre lo mismo para el personal militar, especialmente para el que se encuentra desplegado en buques de la Armada que no cuentan con capacidad odontológica y en zonas de aislamiento donde el acceso a los servicios sanitarios especializados es complejo y arriesgado. El objetivo de este estudio fue evaluar la incidencia y manejo de la patología odontológica ocurrida en los militares españoles a bordo del buque LHD 61 Juan Carlos I durante su primera Operación Internacional de Mantenimiento de la Paz. METODOS: Se realizó un estudio observacional descriptivo de incidencias acumuladas de la patología y los tratamientos odontológicos realizados entre el 1 de mayo y el 26 de junio de 2018. La muestra poblacional fue de 448 militares españoles a bordo del buque. Los datos se obtuvieron de las bases de datos del libro de registro de actividad odontológica y de los sistemas militares de estadística y gestión de datos sanitarios que sirven para conocer el estado real de salud de la fuerza. RESULTADOS: Se atendieron un total de 70 pacientes por problemas bucodentales, donde la gingivitis y la caries fueron las enfermedades que más incidencia presentaron, con un 23,07% y un 18,68%, respectivamente. Los tratamientos más realizados fueron las reconstrucciones/obturaciones dentales con un 40% y las tartrectomías con un 21% del total. CONCLUSIONES: El conocimiento de la incidencia de las patologías odontológicas en buques de la Armada Española nos permite establecer las necesidades formativas del personal de sanidad embarcado, así como determinar con qué recursos materiales se debe de dotar a las unidades navales. Los planes de prevención y los reconocimientos odontológicos previos al despliegue deben realizarse con antelación suficiente para poder sanar en tierra las patologías del personal que va a ser desplegado.

Vessel trajectory classification via transfer learning with Deep Convolutional Neural Networks.

The classification of vessel trajectories using Automatic Identification System (AIS) data is crucial for ensuring maritime safety and the efficient navigation of ships. The advent of deep learning has brought about more effective classification methods, utilizing Convolutional Neural Networks (CNN). However, existing CNN-based approaches primarily focus on either sailing or loitering movement patterns and struggle to capture valuable features and subtle differences between these patterns from input images. In response to these limitations, we firstly introduce a novel framework, Dense121-VMC, based on Deep Convolutional Neural Networks (DCNN) with transfer learning for simultaneous extraction and classification of both sailing and loitering trajectories. Our approach efficiently performs in extracting significant features from input images and in identifying subtle differences in each vessel's trajectory. Additionally, transfer learning effectively reduces data requirements and addresses the issue of overfitting. Through extended experiments, we demonstrate the novelty of proposed Dense121-VMC framework, achieving notable contributions for vessel trajectory classification.

Polycyclic aromatic hydrocarbons in ship breaking area and associated ecological risk assessment: evidence from the Sitakund ship-breaking area in Bangladesh.

Ship-breaking yards are recognized for releasing hazardous polycyclic aromatic hydrocarbons (PAHs), leading to severe environmental pollution in the sediment of ship-breaking areas. This study assessed the concentrations of 16 priority PAHs in surface sediments collected from the intertidal zone adjacent to the Sitakund ship-breaking yards. The samples underwent Soxhlet extraction and detection using PerkinElmer GC-Clarus 690 and MS-Clarus SQ8C with an Elite-5MS capillary column (30 m × 0.25 mm ID × 0.25 µm). The study utilized PAH concentrations to reveal spatial distribution patterns, identify point sources, and assess potential toxicity. The total PAH concentration ranged from 1899.2 to 156,800.08 ng g-1 dw, while the concentration of 7 carcinogenic PAHs ranged from 822.03 to 1899.15 ng g-1 dw. High molecular weight PAHs dominated among the 16 PAHs, whereas low molecular weight PAHs, such as 2-ring PAHs, were negligible. Source characterization based on different molecular ratios suggested that PAHs in the area originated from pyrolytic processes related to ship dismantling, fishing activities, and water transportation for people. The observed PAH concentrations exceeded both national and international standards for sedimentary PAH levels, indicating significant ecological risks. The total TEQcarc values of sediment samples varied from 564.41 to 10,695.12 ng g-1, with a mean value of 3091.25 ng g-1. The study's findings underscore the immediate biological damage that PAH contamination in the Sitakund ship-breaking area could cause, emphasizing the need for effective control measures to ensure ecological and human safety.

Sensor-Based Fuzzy Inference of COVID-19 Transmission Risk in Cruise Ships.

Cruise ships are densely populated ecosystems where infectious diseases can spread rapidly. Hence, early detection of infected individuals and risk assessment (RA) of the disease transmissibility are critical. Recent studies have investigated the long-term assessment of transmission risk on cruise ships; however, short-term approaches are limited by data unavailability. To this end, this work proposes a novel short-term knowledge-based method for RA of disease transmission based on fuzzy rules. These rules are constructed using knowledge elicited from domain experts. In contrast to previous approaches, the proposed method considers data captured by several sensors and the ship information system, according to a recently proposed smart ship design. Evaluation with agent-based simulations confirms the effectiveness of the proposed method across various cases.

[The problematic issues of regulation and organization of labor safety of sailors as factor impacting life quality and health].

In modern conditions of maritime navigation, protection of lives of crew members plays key role for their health and quality of life. The practice testifies that shipowners underestimate real statistics of occupational injuries, since procedure for its management and investigation of accidents on ships are not sufficiently regulated in international and national legislation. Besides, approaches of shipowners to implementation of existing standards also have different levels of responsibility that leaves measures preventing such incidents unreasonably underestimated. This situation results in increasing of occupational injuries on ships and allows shipowners or insurance companies to avoid proper payments to injured sailor or his family members in case of one's death. The complexity of implementation of "belated" medical expertise to determine cause of death or injury of crew member also makes it difficult to obtain positive result of recognition of disability or death of sailor as result of occupational traumatism. All the described above testifies importance and actuality of stated research topic. The article examines in detail normative acts regulating protection of labor and life and medical care of sailors. Also are considered causes, factors and types of occupational traumatism on ships. The accident statistics and procedure of their investigation are analyzed in relation to maritime practice. The issues of medical expertise are studied and main problematic issues are identified. The recommendations for their solution are formulated.

[Measures to preserve the mental health of sailors when working on autonomous surface vessels].

Currently, all sectors of the national economy are subject to rapid processes of digital transformation, which requires the restructuring of both production processes and the improvement of the personnel selection system. The field of maritime transport is no exception, which has recently been focused on the active development of autonomous maritime shipping. The introduction of autonomous ships into operation radically changes the working conditions of ship crew members, including due to a significant reduction in their number. As a result, in the near future, seafarers will be forced not only to work in difficult conditions caused by maritime specifics, but also to experience the additional impact of a limited ship crew. The lack of necessary skills and training among current ship crew members to work in the new realities, as well as the high risk of impairment of their mental health, shows the objective need to find new approaches to the training and selection of seafarers. In order to develop recommendations for improving the rules for training, recruiting and selecting seafarers to work in conditions of a limited ship crew, the article studied regulations and levels of autonomy of sea surface vessels. A survey was conducted among active sailors, which made it possible to identify key problems on the stated issues, and also studied the types of temperament, personality and accentuation.

[Inadequate first medical aid on board a sea vessel as a risk factor for crew members' health].

Currently, one of the most important health and social problems in the world is the constant increase in injuries and deaths at work. Statistics show that timely provision of first aid to victims has a positive effect on further medical support and a reduction in the number of deaths. First aid for crew members of sea vessels is a set of simple medical actions performed by seafarers directly on board the ship, as soon as possible after an injury or illness. As a rule, it is associated with emergency resuscitation of the victim. The lack of necessary skills and training among current ship crew members to carry out first aid operations shows an objective need to develop recommendatory measures to revise the current training system.

Statistical machine learning models for prediction of China's maritime emergency patients in dynamic: ARIMA model, SARIMA model, and dynamic Bayesian network model.

Introduction: Rescuing individuals at sea is a pressing global public health issue, garnering substantial attention from emergency medicine researchers with a focus on improving prevention and control strategies. This study aims to develop a Dynamic Bayesian Networks (DBN) model utilizing maritime emergency incident data and compare its forecasting accuracy to Auto-regressive Integrated Moving Average (ARIMA) and Seasonal Auto-regressive Integrated Moving Average (SARIMA) models. Methods: In this research, we analyzed the count of cases managed by five hospitals in Hainan Province from January 2016 to December 2020 in the context of maritime emergency care. We employed diverse approaches to construct and calibrate ARIMA, SARIMA, and DBN models. These models were subsequently utilized to forecast the number of emergency responders from January 2021 to December 2021. The study indicated that the ARIMA, SARIMA, and DBN models effectively modeled and forecasted Maritime Emergency Medical Service (EMS) patient data, accounting for seasonal variations. The predictive accuracy was evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R 2) as performance metrics. Results: In this study, the ARIMA, SARIMA, and DBN models reported RMSE of 5.75, 4.43, and 5.45; MAE of 4.13, 2.81, and 3.85; and R 2 values of 0.21, 0.54, and 0.44, respectively. MAE and RMSE assess the level of difference between the actual and predicted values. A smaller value indicates a more accurate model prediction. R 2 can compare the performance of models across different aspects, with a range of values from 0 to 1. A value closer to 1 signifies better model quality. As errors increase, R 2 moves further from the maximum value. The SARIMA model outperformed the others, demonstrating the lowest RMSE and MAE, alongside the highest R 2, during both modeling and forecasting. Analysis of predicted values and fitting plots reveals that, in most instances, SARIMA's predictions closely align with the actual number of rescues. Thus, SARIMA is superior in both fitting and forecasting, followed by the DBN model, with ARIMA showing the least accurate predictions. Discussion: While the DBN model adeptly captures variable correlations, the SARIMA model excels in forecasting maritime emergency cases. By comparing these models, we glean valuable insights into maritime emergency trends, facilitating the development of effective prevention and control strategies.

Evolutionary game analysis between regional governments and shipping companies: Considering the impact of government subsidy on shipping companies.

Maritime agencies are imposing stricter limits on fuel sulfur content, and regional governments are encouraging the reduction of various emissions through subsidies. In this study, an evolutionary game model is constructed to analyze the interaction between regional governments and shipping companies under the fixed and dynamic subsidies. The sensitivity analysis reveals the effect of parameters on stabilization strategies. The results show that the bilateral stakeholders can adopt stabilization strategies under dynamic subsidies. The fines, maximum subsidies and extra cost paid by regional governments have a significant impact on these strategies. To reduce the dependence of shipping companies on subsidy policies, it is recommended to improve the LSFO refining technology in the future. Expanding the implementation scope of LSFO subsidy policies will increase the utilization of LSFO by shipping companies. This study offers insights for governments to optimize the LSFO subsidy policy and shipping companies to choose sulfur oxides reduction approaches.

Use of wastewater from passenger ships to assess the movement of COVID-19 and other pathogenic viruses across maritime international boundaries.

Objective: The worldwide spread of SARS-CoV-2 and the resulting COVID-19 pandemic has been driven by international travel. This has led to the desire to develop surveillance approaches which can estimate the rate of import of pathogenic organisms across international borders. The aim of this study was to investigate the use of wastewater-based approaches for the surveillance of viral pathogens on commercial short-haul (3.5 h transit time) roll-on/roll-off passenger/freight ferries operating between the UK and the Republic of Ireland. Methods: Samples of toilet-derived wastewater (blackwater) were collected from two commercial ships over a 4-week period and analysed for SARS-CoV-2, influenza, enterovirus, norovirus, the faecal-marker virus crAssphage and a range of physical and chemical indicators of wastewater quality. Results: A small proportion of the wastewater samples were positive for SARS-CoV-2 (8% of the total), consistent with theoretical predictions of detection frequency (4%-15% of the total) based on the national COVID-19 Infection Survey and defecation behaviour. In addition, norovirus was detected in wastewater at low frequency. No influenza A/B viruses, enterovirus or enterovirus D68 were detected throughout the study period. Conclusion: We conclude that testing of wastewater from ships that cross international maritime boundaries may provide a cost-effective and relatively unbiased method to estimate the flow of infected individuals between countries. The approach is also readily applicable for the surveillance of other disease-causing agents.

Effect of cyclic meditation on anxiety and sleep quality in sailors on merchant ships-A quasi-experimental study.

Background: Sailors undergo anxiety and sleep disturbances due to prolonged journeys and the nature of their work on ships. Earlier studies indicate Cyclic Meditation (CM) being beneficial for managing anxiety and improving sleep quality. Thus, the current study was designed to investigate the effect of CM on anxiety and sleep quality among sailors. Materials and methods: Fifty sailors were assigned to experimental (n = 25) and control (n = 25) groups. The experimental group received 45 min of CM, 7 days a week for 3 weeks. Control group continued with their routine activities and were offered CM practice the following 3 weeks. Hamilton Anxiety Scale for anxiety (HAM-A) and the Pittsburg Sleep Quality Index (PSQI) for sleep along with blood pressure and pulse rate were taken at baseline and by the end of 3 weeks. Data were analyzed using Repeated Measures Analysis of Variance (RM ANOVA) for within and between group effects. Results: Significant differences were found between the groups following 3 weeks for all the variables. Experimental group demonstrated reduced anxiety (p < 0.001) and improved sleep (p < 0.001) along with improvements in blood pressure and pulse rate. The control group did not show any significant changes following 3 weeks. Conclusion: CM could be incorporated as a routine for sailors to manage their anxiety and improve sleep quality during the period on board ships.

New clusterization of global seaport countries based on their DEA and FDEA network efficiency scores.

Global seaport network efficiency can be measured using the Liner Shipping Connectivity Index (LSCI) with Gross Domestic Product. This paper utilizes k-means and hierarchical strategies by leveraging the results obtained from Data Envelopment Analysis (DEA) and Fuzzy Data Envelopment Analysis (FDEA) to cluster 133 countries based on their seaport network efficiency scores. Previous studies have explored hkmeans clustering for traffic, maritime transportation management, swarm optimization, vessel trajectory prediction, vessels behaviours, vehicular ad hoc network etc. However, there remains a notable absence of clustering research specifically addressing the efficiency of global seaport networks. This research proposed hkmeans as the best strategy for the seaport network efficiency clustering where our four newly founded clusters; low connectivity (LC), medium connectivity (MC), high connectivity (HC) and very high connectivity (VHC) are new applications in the field. Using the hkmeans algorithm, 24 countries have been clustered under LC, 47 countries under MC, 40 countries under HC and 22 countries under VHC. With and without a fuzzy dataset distribution, this demonstrates that the hkmeans clustering is consistent and practical to form grouping of general data types. The findings of this research can be useful for researchers, authorities, practitioners and investors in guiding their future analysis, decision and policy makings involving data grouping and prediction especially in the maritime economy and transportation industry.

Development of a ship-based camera monitoring system for floating marine debris.

This study developed an automatic monitoring system for Floating Marine Debris (FMD) aimed at reducing the labor-intensiveness of traditional visual surveys. It involved creating a comprehensive FMD database using 55.6 h of video footage and numerous annotated images, which facilitated the training of a deep learning model based on the YOLOv8 architecture. Additionally, the study implemented the BoT-SORT algorithm for FMD tracking, significantly enhancing detection accuracy by effectively filtering out disturbances such as sea waves and seabirds, based on the movement patterns observed in FMD trajectories. Tested across 16 voyages in various marine environments, the system demonstrated high accuracy in recognizing different types of FMD, achieving a mean Average Precision (mAP@0.5) of 0.97. In terms of detecting FMD from video footage, the system reached an F1 score of 83.63 %. It showed potential as a viable substitute for manual methods for FMD larger than 20 cm.