The influence of station-to-station line orientation on sea current speed observations using Coastal Acoustic Tomography (CAT) was quantitatively investigated. For this purpose, we conducted CAT experiments at five stations in Yeosu Bay, South Korea. Through these experiments, the sea current speeds were estimated along a total of six tomographic observation lines with different orientations, and the results were compared with current speeds measured simultaneously by an Acoustic Doppler Current Profiler (ADCP). The comparison showed that the concordance between tomography-estimated sea current speed and ADCP-measured sea current speed tended to decrease as the acute angle between the predominant tidal current direction in Yeosu Bay and a tomographic observation line increased. This tendency is interpreted as arising because the smaller the difference between the two one-way travel times obtained during tomographic observations, the greater the effect of the travel time measurement error whose magnitude is relatively direction-independent. This interpretation was supported by a simple numerical simulation. Furthermore, quantitative analysis of these simulation results indicated that a smaller acute angle between the predominant sea current direction in the survey area and a tomographic observation line enhances the robustness of sea current speed estimation against travel time measurement errors. The results show that the station-to-station line in CAT should be arranged considering the predominant sea current direction in the survey area, which can provide an important guideline for selecting station locations.
Iury Simoes-Sousa, Cesar Rocha, Amit Tandon
et al.
Abstract. Satellite altimetry has revolutionized our understanding of ocean physics by providing global sea-surface height data. These measurements reveal the intricate dynamics of ocean mesoscale strain and vortices, and their interactions with multiple physical scales in the oceans. Although surface dynamics has been extensively studied, investigating the vertical structure of mesoscale eddies globally remains a computational challenge. In this study, we combine the comprehensive World Ocean Database (WOD) with a database of Eulerian mesoscale eddies (META3.2 DT). We pre-process and filter the WOD data, selecting quality controlled profiles at local depths greater than 100 m. By integrating WOD data with altimetry-derived mesoscale eddies, we aim to facilitate future studies on the role of mesoscale vortices in multiple processes, such as heat, mass and nutrient transport, and water-mass subduction. The analysis is performed using high-performance computing resources, with Python packages for parallel processing of the data and analysis of more than 4.2 million profiles with more than 35 million vortex observations. The dataset is available for download from Zenodo at https://doi.org/10.5281/zenodo.17425853 (Simoes-Sousa et al., 2025) and by direct access through an OPeNDAP/HTTP server and an S3 bucket in icechunk format. Additionally, we provide the code for performing the vortex-profile matching, along with an example of use to facilitate future updates to the code and merged data. This dataset supports further research on eddy vertical structure, biogeochemical processes, and their role in climate systems across different regions and time periods.
The growing incidence and prevalence of invasive fungal infections (IFIs) and the emergence of antimicrobial resistance compound clinical antifungal therapies. Given the significant threat posed by IFIs and the limits of the current antifungal agents, the search for novel, effective therapeutic options remains a compelling area of antifungal drug discovery. The s-triazine (1,3,5-triazine) scaffold, renowned for its structural versatility, ease of functionalization, and diverse biological profiles, has been extensively studied in medical chemistry. Driven by this privileged structure, several s-triazine derivatives have been synthesized through molecular hybridization and screened for their antifungal activities. Some of them demonstrated potent efficacy against pathogenic fungi, including Candida, Cryptococcus, and Aspergillus species. Structure–activity relationship (SAR) studies are also discussed whenever possible, underlying the essential substituents for their antifungal effect. This review provides a summary of recent advancements (2014–2024) in the development of antifungal agents featuring the s-triazine scaffold and highlights the antifungal activity of s-triazine derivatives, aiming to prompt further progress in this field.
Offshore wind turbines are prone to structural damage over time due to environmental factors, which increases operational costs and the risk of accidents. Early detection of structural damage through monitoring systems can help reduce maintenance costs. However, under complex external conditions and varying structural parameters, existing methods struggle to accurately and quickly detect damage. Understanding the factors that influence structural health is critical for effective long-term monitoring, as these factors directly affect the accuracy and timeliness of damage identification. This study comprehensively analyzed 5 MW offshore wind turbine measurement data, including constructing a digital twin model, establishing a surrogate model, and performing a sensitivity analysis. For monopile-based turbines, sensors in x and y directions were installed at four heights on the pile foundation and tower. Via Bayesian optimization, the finite element model’s structural parameters were updated to align its modal parameters with sensor data analysis results. The update efficiencies of different objective functions and the impacts of neural network hyperparameters on the surrogate model were examined. The sensitivity of the turbine’s structural parameters to modal parameters was studied. The results showed that the modal flexibility matrix is more effective in iteration. A 128-neuron, double-hidden-layer neural network balanced computational efficiency and accuracy well in the surrogate model for modal analysis. Flange damage and soil degradation near the pile mainly impacted the turbine’s health.
Chelsey A. Del Grosso, Chuan Leng, Kexin Zhang
et al.
Antifouling properties of materials play crucial roles in many important applications such as biomedical implants, marine antifouling coatings, biosensing, and membranes for separation.
The naval sector holds paramount importance for the global economy, yet it entails significant environmental impacts throughout the entire life cycle of ships. This review explores the application of life-cycle assessment (LCA) in the naval sector, a methodology for evaluating the environmental impacts associated with all the life stages of a product or service. LCA analysis in the naval context is essential for identifying and mitigating environmental impacts, thus promoting more sustainable development of the sector. This work provides a comprehensive overview of current LCA applications in the naval sector, highlighting major environmental impacts, in particular focusing on greenhouse-gas emissions and climate change. Additionally, this study integrates an analysis of greenhouse-gas emissions using a normalization approach, which has enabled the comparison of various types of fuels and ships, thereby enhancing our understanding of their environmental impacts. Moreover, the limits and challenges to applying LCA in the naval sector are discussed, offering insights for future research and developments in the field. This review aims to raise awareness among policymakers, designers, and operators in the naval sector about the importance of adopting LCA for more sustainable and responsible management of naval activities, thereby contributing to the protection of the marine and global environment.
Biofuel cells have been in the spotlight for the past century because of their potential and promise as a unique platform for sustainable energy harvesting from the human body and the environment. Because biofuel cells are typically developed in a small platform serving as a primary battery with limited fuel or as a rechargeable battery with repeated refueling, they have been interchangeably named biobatteries. Despite continuous advancements and creative proof-of-concept, however, the technique has been mired in its infancy for the past 100 years, which has provoked increasing doubts about its commercial viability. Low performance, instability, difficulties in operation, and unreliable and inconsistent power generation question the sustainable development of biofuel cells. However, the advancement in bioelectrocatalysis revolutionizes the electricity-producing capability of biofuel cells, promising an attractive, practical technique for specific applications. This perspective article will identify the misconceptions about biofuel cells that have led us in the wrong development direction and revisit their potential applications that can be realizable soon. Then, it will discuss the critical challenges that need to be immediately addressed for the commercialization of the selected applications. Finally, potential solutions will be provided. The article is intended to inspire the community so that fruitful commercial products can be developed soon.
Abstract Military effectiveness created a growth in political science literature. However, this work focused overwhelmingly on continental warfare. China’s rise highlights naval warfare. Do the central findings of the literature hold for war at sea? We explore this question by comparing naval and land combat patterns via a new dataset on interstate surface naval battles fought between 1649 and 1988. We find essential differences deriving from the contrasting nature of the sea and land as military environments, which have made naval outcomes more sensitive to materiel, quicker, and more one-sided. There are, however, also important similarities involving material–nonmaterial interactions. These features pose important implications for policy on future anti-access/area denial (A2/AD) warfare in East Asia, the balance of investment in skill and materiel in naval resource allocation, and research on military effectiveness.
Terak Hornik, Maxwell Terry, Michael Krause
et al.
Microbial fuel cells (MFCs) represent a promising avenue for sustainable energy production by harnessing the metabolic activity of microorganisms. In this study, a novel design of MFC—a Microfluidic Benthic Microbial Fuel Cell (MBMFC)—was developed, fabricated, and tested to evaluate its electrical energy generation. The design focused on balancing microfluidic architecture and wiring procedures with microbial community dynamics to maximize power output and allow for upscaling and thus practical implementation. The testing phase involved experimentation to evaluate the performance of the MBMFC. Microbial feedstock was varied to assess its impact on power generation. The designed MBMFC represents a promising advancement in the field of bioenergy generation. By integrating innovative design principles with advanced fabrication techniques, this study demonstrates a systematic approach to optimizing MFC performance for sustainable and clean energy production.
Ian A. Stokes, Samuel M. Kelly, Andrew J. Lucas
et al.
Abstract We construct a generalized slab model to calculate the ocean’s linear response to an arbitrary, depth-variable forcing stress profile. To introduce a first-order improvement to the linear stress profile of the traditional slab model, a nonlinear stress profile, which allows momentum to penetrate into the transition layer (TL), is used [denoted mixed layer/transition layer (MLTL) stress profile]. The MLTL stress profile induces a twofold reduction in power input to inertial motions relative to the traditional slab approximation. The primary reduction arises as the TL allows momentum to be deposited over a greater depth range, reducing surface currents. The secondary reduction results from the production of turbulent kinetic energy (TKE) beneath the mixed layer (ML) related to interactions between shear stress and velocity shear. Direct comparison between observations in the Iceland Basin, the traditional slab model, the generalized slab model with the MLTL stress profile, and the Price–Weller–Pinkel (PWP) model suggest that the generalized slab model offers improved performance over a traditional slab model. In the Iceland Basin, modeled TKE production in the TL is consistent with observations of turbulent dissipation. Extension to global results via analysis of Argo profiling float data suggests that on the global, annual mean, ∼30% of the total power input to near-inertial motions is allocated to TKE production. We apply this result to the latest global, annual-mean estimates for near-inertial power input (0.27 TW) to estimate that 0.08 ± 0.01 TW of the total near-inertial power input are diverted to TKE production.
The maritime sector is increasingly integrating Information and Communication Technology (ICT) and Artificial Intelligence (AI) technologies to enhance safety, environmental protection, and operational efficiency. With the introduction of the MASS Code by the International Maritime Organization (IMO), which regulates Maritime Autonomous Surface Ships (MASS), ensuring the safety of AI-integrated systems on these vessels has become critical. To achieve safe navigation, it is essential to identify potential risks during the system planning stage and design systems that can effectively address these risks. This paper proposes RA4MAIS (Risk Assessment for Maritime Artificial Intelligence Safety), a risk identification method specifically useful for developing AI-integrated maritime systems. RA4MAIS employs a systematic approach to uncover potential risks by considering internal system failures, human interactions, environmental conditions, AI-specific characteristics, and data quality issues. The method provides structured guidance to identify unknown risk situations and supports the development of safety requirements that guide system design and implementation. A case study on an Electronic Chart Display and Information System (ECDIS) with an AI-integrated collision avoidance function demonstrates the applicability of RA4MAIS, highlighting its effectiveness in identifying specific risks related to AI performance and reliability. The proposed method offers a foundational step towards enhancing the safety of software systems, contributing to the safe operation of autonomous ships.
To study the rapid estimation method and characteristics of low-frequency ambient sea noise generated by far-field ships, firstly, based on the reciprocity principle of sound fields and the fact that the number of noise sources significantly exceeds the number of receiving array elements, the positions of noise sources and receiving array elements were swapped to effectively reduce the sound field estimates and the running time. Secondly, a vertical directionality analysis method for ambient noise generated by ship noise was derived. And lastly, the ambient sea noise generated by ship noise in the Philippine Sea was estimated and analyzed, and the validity of the estimation method was verified based on measured data in the region. The estimation method presented in this paper can be used to predict the level and directionality of ambient noise generated by ship noise in a large area of sea, and acts as technical support for the meaningful use of sonar arrays in the actual marine environment.
Field determination and ecological risk assessment of dissolved lead (Pb) were performed at two Yellow Sea sites in China using a continuous automated electrochemical system (CAEDS). This CAEDS instrument includes an automatic triple filter sampler and an electrochemical detection water quality analyzer, which might be operated automatically four times daily. The dissolved Pb concentrations varied from 0.29 to 1.57 μg/L in the South Yellow Sea over 16 days and from 0.32 to 2.28 μg/L in the North Yellow Sea over 13 days. During the typhoon and algal bloom periods, the Pb concentration was as high as ten times greater than usual. According to the calculation of contamination factors (C<sub>f</sub>) and subsequent analysis, seawater quality was classified as Grade II. Through species sensitivity distribution (SSD) method experiments and ecological risk analysis, an average risk quotient (RQ) below 1 for both areas was obtained, indicating a low-to-moderate ecological risk. This system will be helpful for Pb monitoring and assessment in seawater and contribute to the biogeochemical cycling study of Pb.
In deep-sea mining hydraulic lifting systems, centrifugal pumps are very important as power units. In the process of transportation, the fluid prewhirl phenomenon in the impeller inlet will lead to changes in the state of motion of the particles and fluid and cause the wear of the inlet pipe, which can lead to centrifugal pump failure in serious cases. In this paper, a numerical simulation of the centrifugal pump is carried out based on the CFD-DEM coupling method to analyze the influence of the prewhirl on the wear of the inlet pipe. The results show that the velocity streamline near the impeller inlet position changes significantly. The flow field velocity increases along the radial direction of the inlet pipe, and it has a maximum value at <i>r/R</i> = 0.98. The prewhirl flow pulls the particles to change their original motion direction, and the area where the particles are subjected to high fluid force is concentrated between 0.5 <i>d/D</i> and 1 <i>d/D</i>, about 0.015 to 0.018 N, resulting in the uneven distribution of particles. The high-wear area appears in the bottom-left area (specifically, L4, L9, and L13), and this is also the location of the largest cumulative force; the high-wear area shows a triangle. The collision energy loss of particles increases due to the influence of the prewhirl, which leads to an increase in wear.
ABSTRACT For European naval powers, whose economic and political well-being depended on the success of naval enterprises, warships played a fundamental role. Based on a multi-scalar and comparative approach, evidence from post-medieval (or historical) shipwrecks, can contribute to a better understanding of modern technology and society. This article deals with the innovations of British, French, and Spanish warships that sailed from about 1750 to 1815. An archaeological, archaeometric, and documentary study of wreck sites, with emphasis on ships’ structure, equipment, and ordnance, provided novel data to address the development of naval technology of the period. Based on this comprehensive approach, the information obtained allowed for a discussion of the impacts of industrialisation, warfare, and science on the innovation dynamic developed within the aforementioned states.
Dariusz Zmysłowski, P. Skokowski, Krzysztof Malon
et al.
: Fifth ‐ generation (5G) technology is currently developing in mobile networks. The civilian 3rd Generation Partnership Project (3GPP) standard is the basis for this implementation. Higher throughput, network capacity, user density, and lower latency are the main advantages offered by 5G over Long Term Evolution (LTE) and older standards. For this reason, these advantages are increasingly recognized in critical mission and military solutions. However, the 5G technology utilization in military equipment requires a deep analysis of the 3GPP standard, especially regarding technological gaps, security, and use cases. This is particularly important in using communication equipment during armed conflicts. Such equipment must be characterized by greater security and reliability than civilian equipment. Currently, work and analyses in this area are realized by the European Defence Agency (EDA), North Atlantic Treaty Organization (NATO) Communications and Information Agency (NCIA), Allied Command Transformation (ACT), and NATO Science and Technology Organization (STO). In the Information Systems Technology (IST) Panel of the NATO STO, the research task group (RTG) ʺ IST ‐ 187 ‐ RTG on 5G Technologies Application to NATO Operations ʺ is working on this topic. This paper presents exemplary 5G use cases in the navy. We indicate potential advantages, problems, and technological gaps that should be solved before implementing 5G technology in naval systems.
Recently, as humans have become increasingly interested in ocean resources, underwater vehicle-manipulator systems (UVMSs) have played an increasingly important role in ocean exploitation. To realize precise operation in underwater narrow spaces, the fly arm underwater vehicle manipulator system (FAUVMS) is proposed with manipulators as its core. However, this system suffers severe dynamic coupling effects due to the combination of small vehicle and big manipulators. To resolve this issue, we propose a robust adaptive controller that contains two parts. In the first part, the extended Kalman filter (EKF) is designed to estimate the system states and predicts external disturbances to achieve adaptive control. In the second part, a chattering-free sliding mode control (SMC) is designed to converge the tracking errors to zero, thus guaranteeing the robustness of the controller. We constructed the simulation platform based on the geometric model of FAUVMS, and various simulations are carried out under different situations. Compared to the traditional methods, the proposed method has a faster convergent speed, a better robustness and adaptiveness to external disturbances, and the tracking errors of positions of the vehicle and each end-effector are much smaller.
Abstract Numerous studies have proven the critical role of macrophages in the renal fibrosis process. Notably, G Protein-coupled Estrogen Receptor 1 (GPER1), a novel estrogen receptor, has been shown to play a ubiquitous role in regulating macrophage activities and proinflammatory pathways. However, the precise role of GPER1 in macrophage-mediated renal fibrosis is unknown. In this study, we aimed to investigate the function of macrophage GPER1 in the UUO-induced renal fibrosis model. Compared to vehicle-treated ovariectomized (OVX) female and male unilateral ureteral obstruction (UUO) models, we observed that G-1 (GPER1 agonist)-treated OVX female and male UUO mice had fewer renal fibrotic lesions and less M1 and M2 macrophage infiltration in the kidney tissues. Conversely, Gper1 deletion in male UUO mice accelerated renal fibrosis and increased inflammation. In vitro studies also revealed that GPER1 activation reduced M0 macrophage polarization towards M1 or M2 phenotypes. The RNA-sequencing analysis and immunoblotting indicated that GPER1 activation was primarily involved in downregulating immune pathways activation and inactivating MAPK pathways. Tubular epithelial cells co-cultured with G-1-pretreated M1 macrophages exhibited fewer injuries and immune activation. In addition, fibroblasts co-cultured with G-1-pretreated M2 macrophages showed downregulated extracellular matrix expression. Overall, this is the first study to demonstrate the effect of GPER1 on macrophage-mediated renal fibrosis via inhibition of M1 and M2 macrophage activation. These findings indicate that GPER1 may be a promising therapeutic target for treating renal fibrosis.
Machine learning (ML)-based techniques have found significant impact in many fields of engineering and sciences, where data-sets are available from experiments and high-fidelity numerical simulations. Those data-sets are generally utilised in a machine learning model to extract information about the underlying physics and derive functional relationships mapping input variables to target quantities of interest. Commonplace machine learning algorithms utilised in scientific machine learning (SciML) include neural networks, support vector machines, regression trees, random forests, etc. The focus of this article is to review the applications of ML in naval architecture, ocean and marine engineering problems; and identify priority directions of research. We discuss the applications of machine learning algorithms for different problems such as wave height prediction, calculation of wind loads on ships, damage detection of offshore platforms, calculation of ship-added resistance and various other applications in coastal and marine environments. The details of the data-sets including the source of data-sets utilised in the ML model development are included. The features used as the inputs to the ML models are presented in detail and finally, the methods employed in optimisation of the ML models were also discussed. Based on this comprehensive analysis, we point out future directions of research that may be fruitful for the application of ML to ocean and marine engineering problems.