A Physics-Guided Deep Embedding Framework for Underwater Target Recognition Using Similarity-Based Decision - Tianyang Xu; Hongjian Jia; Wensheng Zhu; Rui Xu (Journal of Marine Science and Engineering, 2026)
In underwater target recognition, the scattering characteristics of small targets are weak and highly sensitive to observation angles, posing significant challenges to achieving stable and robust recognition in complex environments. Existing methods are mainly data-driven and rely on closed-set classifiers, which often lack physical interpretability and show limited generalization under different observation conditions. To address these issues, a physics-guided deep embedding framework for underwater target recognition is proposed. Firstly, an encoder–decoder network is designed to learn representative and physically consistent scattering features from measured echo frequency spectra. The encoder is then extracted to construct a Triplet-based embedding model, which maps high-dimensional scattering spectra into a discriminative low-dimensional feature space. In the embedding space, a similarity-based decision strategy is further adopted to replace the traditional classifier, and recognition is achieved by evaluating the relationships among embedded features. Experimental results show that the proposed method achieves robust recognition performance under varying observation angles and establishes an interpretable connection between scattering characteristics and recognition results. The proposed framework provides an effective way to combine physics-guided feature learning with deep embedding methods for underwater target recognition.

A Strategic–Tactical Collaborative Route Decision System for the Arctic Northeast Passage - Rui Zhang; Adan Wu; Qingchao Xu; Pitukhina Maria; Jinlei Chen; Liuhao Wang; Kaihui Zhang (Journal of Marine Science and Engineering, 2026)
The complex and variable sea ice environment constrains the safety and efficiency of Arctic shipping. To address the limitations of existing methods in balancing long-term planning with dynamic route adjustment ahead of the vessel, this paper develops an Arctic route decision-making system based on strategic–tactical coordination. The system establishes a “Global Guidance–Local Correction” collaborative mechanism: the strategic module utilizes medium-range climate forecast data to generate a set of daily baseline routes over a 30-day forecast window, providing macro-scale route guidance and feasibility assessment for the voyage; meanwhile, the tactical module integrates high-spatiotemporal-resolution sea ice concentration (SIC) data to screen local high-SIC areas that constrain navigation and execute tactical route correction ahead of the vessel. Experimental results demonstrate the feasibility of integrating long-term global planning with dynamic route adjustment. This provides a feasible route planning framework for integrating long-term strategic guidance with tactical-level dynamic adjustment under complex Arctic ice conditions, offering technical support for future intelligent Arctic navigation systems.

Oil Slick Detection in X-Band Marine Radar Imagery: Leveraging a Boundary-Aware SBR Feature and an Improved Whale Optimization Algorithm - Jianxun Rui; Jin Xu; Jianbin Yuan; Zekun Guo; Shuo Zhang; Yiteng Zhang; Qiuyu Fu; Boxi Yao; Yulong Yang; Wenhui Li (Journal of Marine Science and Engineering, 2026)
Marine oil spills pose a persistent threat to marine ecosystems and coastal economies, and their rapid and unpredictable spread requires timely and reliable monitoring. In X-band marine radar images, oil slicks usually appear as low-contrast dark targets embedded in heterogeneous sea clutter, making accurate segmentation particularly challenging. To address this problem, this study proposes a training-free two-stage oil slick detection framework that combines an improved Slick Boundary Ratio (SBR) feature with an improved Whale Optimization Algorithm (WOA). First, the improved SBR feature is used to extract the oil slick region of interest (ROI). Then, the improved WOA is employed to determine the global threshold for oil slick segmentation. Experimental results show that the proposed method achieves accurate and spatially coherent oil slick segmentation in complex radar backgrounds, with an Accuracy of 99.36%, a Precision of 85.73%, a Recall of 84.42%, an F1-score of 85.07%, and an Intersection over Union (IoU) of 74.01%. These results indicate that the proposed framework can effectively suppress false positives while maintaining strong detection sensitivity, thereby improving segmentation robustness in low-contrast marine radar scenes. Owing to its training-free design, the proposed method shows potential for shipborne and coastal oil spill monitoring applications.

Marine Hydrogen Pressure Reducing Valves: A Review on Multi-Physics Coupling, Flow Dynamics, and Structural Optimization for Ship-Borne Storage Systems - Heng Xu; Hui-Na Yang; Rui Wang; Yi-Ming Dai; Zi-Lin Su; Ji-Chao Li; Ji-Qiang Li (Journal of Marine Science and Engineering, 2025)
As a zero-carbon energy carrier, hydrogen is playing an increasingly vital role in the decarbonization of maritime transportation. The hydrogen pressure reducing valve (PRV) is a core component of ship-borne hydrogen storage systems, directly influencing the safety, efficiency, and reliability of hydrogen-powered vessels. However, the marine environment—characterized by persistent vibrations, salt spray corrosion, and temperature fluctuations—poses significant challenges to PRV performance, including material degradation, flow instability, and reduced operational lifespan. This review comprehensively summarizes and analyzes recent advances in the study of high-pressure hydrogen PRVs for marine applications, with a focus on transient flow dynamics, turbulence and compressible flow characteristics, multi-stage throttling strategies, and valve core geometric optimization. Through a systematic review of theoretical modeling, numerical simulations, and experimental studies, we identify key bottlenecks such as multi-physics coupling effects under extreme conditions and the lack of marine-adapted validation frameworks. Finally, we conducted a preliminary discussion on future research directions, covering aspects such as the construction of coupled multi-physics field models, the development of marine environment simulation experimental platforms, the research on new materials resistant to vibration and corrosion, and the establishment of a standardized testing system. This review aims to provide fundamental references and technical development ideas for the research and development of high-performance marine hydrogen pressure reducing valves, with the expectation of facilitating the safe and efficient application and promotion of hydrogen-powered shipping technology worldwide.

A Simplified Prediction Method for the Hydrodynamic Performance of Ship Propellers Under Heave and Pitch Motions - Wei Zhang; Guoliang Xu; Siyu Wang; Rui Wu (Journal of Marine Science and Engineering, 2025)
This paper presents a simplified computational method for evaluating the hydrodynamic performance of a ship propeller, taking into account the effects of wave-induced heave and pitch motions. The method combines Computational Fluid Dynamics (CFD) for propeller hydrodynamic force calculations with forced heave and pitch motions computed via the potential flow theory-based method. Numerical simulations at three representative wavelengths demonstrate that heave and pitch motions reduce propeller thrust, increase torque, and decrease the propeller’s efficiency significantly. In addition, the results reveal a nonlinear coupling between heave and pitch effects, where their hydrodynamic contributions are not simply additive. Compared to high-fidelity ship–propeller coupling CFD simulations, the proposed method reduces computational costs by approximately four times while maintaining practical accuracy for wave–propeller interaction analysis.

Regional Wave Spectra Prediction Method Based on Deep Learning - Yuning Liu; Rui Li; Wei Hu; Peng Ren; Chao Xu (Journal of Marine Science and Engineering, 2025)
The wave spectrum, as a key statistical feature describing wave energy distribution, is crucial for understanding wave propagation mechanisms and supporting ocean engineering applications. This study, based on ERA5 reanalysis spectrum data, proposes a model combining CNN and xLSTM for rapid gridded wave spectrum prediction over the Bohai and Yellow Seas domain. It uses 2D gridded spectrum data rather than a spectrum at specific points as input and analyzes the impact of various input factors at different time lags on wave development. The results show that incorporating water depth and mean sea level pressure significantly reduces errors. The model performs well across seasons with the seasonal spatial average root mean square error (SARMSE) of spectral energy remaining below 0.040 m2·s and RMSEs for significant wave height (SWH) and mean wave period (MWP) of 0.138 m and 1.331 s, respectively. At individual points, the spectral density bias is near zero, correlation coefficients range from 0.95 to 0.98, and the peak frequency RMSE is between 0.03 and 0.04 Hz. During a typical cold wave event, the model accurately reproduces the energy evolution and peak frequency shift. Buoy observations confirm that the model effectively tracks significant wave height trends under varying conditions. Moreover, applying a frequency-weighted loss function enhances the model’s ability to capture high-frequency spectral components, further improving prediction accuracy. Overall, the proposed method shows strong performance in spectrum prediction and provides a valuable approach for regional wave spectrum modeling.

Oil Film Detection for Marine Radar Image Using SBR Feature and Adaptive Threshold - Yulong Yang; Jin Yan; Jin Xu; Xinqi Zhong; Yumiao Huang; Jianxun Rui; Min Cheng; Yuanyuan Huang; Yimeng Wang; Tao Liang; Zisen Lin; Peng Liu (Journal of Marine Science and Engineering, 2025)
Marine oil spills pose a serious and persistent threat to marine ecosystems, coastal resources, and global environmental health. These incidents not only disrupt ecological balance by damaging marine flora and fauna but also lead to long-term economic consequences for fisheries, tourism, and maritime industries. Owing to their rapid spread and often unpredictable occurrence, timely and accurate detection is essential for effective containment and mitigation. An efficient detection system can significantly enhance the responsiveness of emergency teams, enabling targeted interventions that minimize ecological damage and economic loss. This paper proposes a marine radar-based oil spill detection method that combines the Significance-to-Boundary Ratio (SBR) feature with an improved Sauvola adaptive thresholding algorithm. The raw radar data was firstly preprocessed through mean and median filtering, grayscale correction, and contrast enhancement. SBR features were then employed to extract coarse oil spill regions, which were further refined using an improved Sauvola thresholding algorithm followed by a denoising step to obtain fine-grained segmentation. Comparative experiments using different threshold values demonstrate that the proposed method achieves superior segmentation performance by better preserving oil spill boundaries and reducing background noise. Overall, the approach provides a robust and efficient solution for marine oil spill detection and monitoring.

Development of a Mitochondrial Marker for Distinguishing Between Ulva linza and Ulva prolifera - Rui Zhai; Chengnuo Tang; Shuying Wang; Jing Ma; Xinshu Li; Guoqiang Chen; Juntian Xu (Journal of Marine Science and Engineering, 2025)
The green tide is the biggest ecological disaster in Yellow Sea in recent decades, and the species composition has varied from year to year. The ITS (internal transcribed spacer) sequence combined with 5S rDNA spacer are the mainstream molecular markers for green macroalgae. The former can perfectly distinguish the majority of Ulva spp. except the LPP (Ulva linza–procera–prolifera) complex, and the latter is used to distinguish U. linza and U. prolifera exactly based on the former. However, in practice, 5S rDNA spacer is difficult to amplify perfectly with universal primers, and this ultimately affects the experimental process. For this reason, we developed a stable mitochondrial marker for the distinction between U. linza and U. prolifera. The phylogenetic tree based on the mitochondrial rps2 (ribosomal protein S2) gene fragment can distinguish the LPP complex into two clades: U. linza and U. prolifera. Therefore, we concluded that the mitochondrial marker can be a great substitute for 5S primers to distinguish U. linza and U. prolifera.

Underwater Target Detection with High Accuracy and Speed Based on YOLOv10 - Zhengliang Hu; Le Cheng; Shui Yu; Pan Xu; Peng Zhang; Rui Tian; Jingqi Han (Journal of Marine Science and Engineering, 2025)
Underwater target detection exhibits extensive applications in marine target exploration and marine environmental monitoring. However, conventional images of underwater targets present challenges including blurred contour information, complex environmental conditions, and pronounced scattering effects. In this work, an underwater target detection method based on YOLOv10 is designed, and the detection performance is compared with the YOLOv5 model. Experimental results demonstrate that the YOLOv10 model has a mAP50 of 85.6% on the URPC 2020 dataset, improving the mAP50 by 1.2% than that of YOLOv5. This model exhibits high detection accuracy and high proceeding speed, which provides a promising support for precise and fast underwater target detection.

On the Nearshore Significant Wave Height Inversion from Video Images Based on Deep Learning - Chao Xu; Rui Li; Wei Hu; Peng Ren; Yanchen Song; Haoqiang Tian; Zhiyong Wang; Weizhen Xu; Yuning Liu (Journal of Marine Science and Engineering, 2024)
Accurate observation of nearshore waves is crucial for coastal safety. In this study, the feasibility of extracting wave information from wave video images captured by shore-based cameras using deep learning methods was explored, focusing on inverting nearshore significant wave height (SWH) from instantaneous wave video images. The accuracy of deep learning models in classifying wind wave and swell wave images was investigated, providing reliable classification results for SWH inversion research. A classification network named ResNet-SW for wave types with improved ResNet was proposed. On this basis, the impact of instantaneous wave images, meteorological factors, and oceanographic factors on SWH inversion was evaluated, and an inversion network named Inversion-Net for SWH that integrates multiple factors was proposed. The inversion performance was significantly enhanced by the specialized models for wind wave and swell. Additionally, the inversion accuracy and stability were further enhanced by improving the loss function of Inversion-Net. Ultimately, time series inversion results were synthesized from the outputs of multiple models; the final inversion results yielded a mean absolute error of 0.04 m and a mean absolute percentage error of 8.52%. Despite certain limitations, this method can still serve as a useful alternative for wave observation.

Experimental Study on the Classification and Evolution of the Tip Cavitation Morphology in Axial Waterjet Pumps with Two Different Blade Numbers - Xi Shen; Haoran Wu; Gang Yang; Rui Tang; Chenxin Chang; Bin Xu; Suben Lin; Desheng Zhang (Journal of Marine Science and Engineering, 2024)
Tip leakage flow and induced unstable cavitation can significantly damage the performance of axial waterjet pumps. This study investigated the impact of blade numbers on cavitating conditions in an axial waterjet pump by conducting tests of performance characteristics and high-speed photography experiments on three-blade and four-blade impellers. The results showed that the critical cavitation number σc of the three-blade impeller was larger, while the four-blade impeller flow pattern deteriorated more rapidly after σc. Various cavitation structures in the tip region were observed under different conditions, including clearance cavitation, shear layer cavitation, tip leakage vortex cavitation, and suction-side-perpendicular cavitating vortices (SSPCVs). Tip cavitation maps of the test impellers were drawn based on the flow rate coefficient and cavitation number variation. The three-blade impeller exhibited a wider range of severe cavitation, particularly with an increased occurrence of SSPCVs. With the cavitation number and flow rate coefficient decreased, the SSPCV generated from triangular cavitation cloud shedding presented an increased trend in scale and quantity. Conversely, in the case of the four-blade impeller, SSPCVs were often disrupted by the adjacent blade during migration and interfered with the tip cavitation in the neighboring flow passage.

Experimental Study on the Hot Surface Ignition Characteristics and a Predictive Model of Marine Diesel in a Ship Engine Room - Kan Wang; Rui Qiu; Yang Ming; Hang Xu (Journal of Marine Science and Engineering, 2024)
To ensure the safe protection of marine engine systems, it is necessary to explore the hot surface ignition (HSI) characteristics of marine diesel in ship environments. However, an accurate model describing these complex characteristics is still not available. In this work, a new experimental method is proposed in order to enhance prediction performance by integrating testing data of the characteristics of HSI of marine diesel. The sensitivity of HSI is determined by various factors such as surface parameters, flow state, and the ship’s environment. According to variations in the HSI status of marine diesel in an engine room, the HSI probability is distributed in three phases. It is essential to determine whether the presence of marine diesel or surrounding items can intensify the risk of an initial fire beginning in the engine room. A vapor plume model was developed to describe the relationship between HSI height and initial specific buoyancy flux in vertical space. Further, field distribution revealed significant variation in the increase in temperature between 200 and 300 mm of vertical height, indicating a region of initial HSI. In addition, increasing surface temperature did not result in a significant change in ignition delay time. After reaching a temperature of 773 K, the ignition delay time remained around 0.48 s, regardless of how much the hot surface temperature increased. This study reveals the HSI evolution of marine diesel in a ship engine room and develops data-based predictive models for evaluating the safety of HSI parameters during initial accident assessments. The results show that the goodness of fit of the predictive models reached above 0.964. On the basis of the predicted results, the HSI characteristics of marine diesel in engine rooms could be gleaned by actively determining the parameters of risk.

The Effect of Artificial Substrate and Carbon Source Addition on Bacterial Diversity and Community Composition in Water in a Pond Polyculture System - Kun Guo; Mumin Shi; Xiaoli Huang; Liang Luo; Shihui Wang; Rui Zhang; Wei Xu; Guoliang Ruan; Zhigang Zhao (Fishes, 2024)
The use of artificial substrates and biofloc technology can favor fish culture and improve water quality. The aim of this study was to evaluate whether artificial substrates and carbon source additions modify the microbial activity of water bodies. The diversity and structure of microflora in the water after adding artificial substrates and carbon sources to the ponds were analyzed using high-throughput sequencing based on the V3-V4 region of 16S rRNA genes. The results showed that there was no difference in the richness and diversity of intestinal microflora between the control and experimental groups. Principal coordinate analysis (PCoA) and nonmetric multidimensional scaling (NMDS) showed that artificial substrate and carbon source addition changed the structure of the microflora. The results of a linear discriminant analysis (LDA) effect size (LefSe) indicated 11 biomarkers in the EGˍst group. Spearman correlation heatmap analysis showed that environmental factors affected the bacterial communities, and the results of a redundancy analysis indicated that chemical oxygen demand was a critical factor in controlling the bacterial communities in the water. These results provide an understanding of the effect of artificial substrate and carbon source addition on bacterial diversity and community composition in water.

Water Properties and Diffusive Convection in the Canada Basin - Ling Qu; Shuangxi Guo; Shengqi Zhou; Yuanzheng Lu; Mingquan Zhu; Xianrong Cen; Di Li; Wei Zhou; Tao Xu; Miao Sun; Rui Zeng (Journal of Marine Science and Engineering, 2024)
The aim of this study is to better understand diffusive convection (DC) and its role in the upper ocean dynamic environment and sea ice melting in the Canada Basin. Based on a moored dataset with 6737 profiles collected from August 2003 to August 2011 in the upper layer of the Canada Basin, DC between the warm and salty Atlantic Water (AW) and the colder and less salty Lower Halocline Water (LHW) were investigated. The moorings were designated at four stations: A, B, C, and D, located at the southwestern, southeastern, northeastern, and northwestern parts of the basin, respectively. During the observation period, the temperature, salinity, and depth of the AW and LHW exhibited unique temporal variations. The temperature and salinity of the AW varied among stations, with a decreasing trend from northwest to southeast, consistent with the propagation path of the AW in the Canada Basin. The temperature and salinity of the LHW were similar at all stations. The AW and LHW cores were located between depths of 320–500 m and 160–300 m, respectively, and both gradually deepened over time. Distinct DC staircase structures were observed between the AW and LHW, more pronounced at stations C and D than at stations A and B, which is speculated to be related to eddies at stations A and B during the observation period. The vertical heat fluxes through the DC staircase layer at stations C and D (FHc_C and FHc_D) were estimated using an empirical formula. FHc_C ranged from 0.05 to 0.94 W/m2, and FHc_D ranged from 0.05 to 0.6 W/m2, with the maximum probability value for both at approximately 0.2 W/m2. The effective diffusivities at these two stations (KT_C and KT_D) are similar, ranging from 2 × 10−6 to 3 × 10−5 m2/s, with the highest probability occurring at 6 × 10−6 m2/s. Both the probability density function of the heat flux and the effective diffusivity skewed towards larger values and obey a lognormal distribution, indicating turbulence intermittency of the DC staircase in the Canada Basin. These finding offers new insights into the heat transport and turbulence in the DC staircase, and then bring a deeper understanding of sea ice melting in the Canada Basin.

Deformation Intelligent Prediction of Titanium Alloy Plate Forming Based on BP Neural Network and Sparrow Search Algorithm - Shun Wang; Jiayan Wang; Zhikang Xu; Ji Wang; Rui Li; Jinliang Dai (Journal of Marine Science and Engineering, 2024)
The application of titanium alloy in shipbuilding can reduce ship weight and carbon emissions. To solve the problem of titanium alloy forming, the deformation prediction of titanium alloy line heating based on a backpropagation (BP) neural network and sparrow search algorithm (SSA) was researched. Based on the thermal–elastic–plastic finite element method, the numerical calculation model of TA5 titanium alloy overlapping heating forming was established. The feasibility of the model was verified by comparing it with the numerical calculation and experiment of low-carbon steel. Considering the characteristics of the titanium alloy-forming process, 73 groups of titanium alloy-forming schemes were obtained by the Latin hypercube sampling method. The deformation data of the samples were obtained by using the numerical calculation model of titanium alloy forming. The prediction methods of titanium alloy-forming deformation based on BP, genetic algorithm–backpropagation (GA-BP), and SSA-BP were proposed. The accuracy of different neural network prediction models was analyzed. The mean absolute percentage errors (MAPEs) of BP, GA-BP, and SSA-BP in shrinkage prediction were 7.45%, 4.08%, and 2.96%, respectively. The MAPEs of BP, GA-BP, and SSA-BP in deflection prediction were 8.44%, 4.73%, and 2.64%, respectively. The goodness of fit (R2) of SSA-BP is closest to 1 among the three models. The calculation results show that SSA-BP is better than BP and GA-BP in predicting the forming deformation of titanium alloy. The maximum prediction error of SSA-BP is 4.95%, which is within the allowable range of engineering error. The SSA-BP prediction model is suitable for the rapid and accurate prediction of the deformation of titanium alloy line heating forming. The intelligent prediction model provides data support for intelligent decisions for titanium alloy forming.

Numerical Investigation of the Impacts of Large Particles on the Turbulent Flow and Surface Wear in Series-Connected Bends - Yuan-Hang Zhang; Xiao-Jie Wang; Xu-Zhen Zhang; Maoukouf Saad; Rui-Jie Zhao (Journal of Marine Science and Engineering, 2024)
The deep sea harbors abundant mineral, oil, and gas resources, making it highly valuable for commercial development, including the extraction of minerals. Due to the relatively large particle size of these minerals, how they interact with fluids is significantly different from that of small particles. However, there has been limited simulation research on the impacts of large particles (the diameter of particles is at the level of centimeters) on the flow and wear characteristics in bends, because the simulation of the particles at such a size is difficult. Additionally, in the field of deep-sea mining, multiple bends are simultaneously connected in series, and the wear in such bends has garnered increasing attention. Based on an improved CFD-DEM model, this article solved the issue that traditional unresolved CFD-DEM methods cannot accurately simulate large particles in a hydraulic conveying pipe and bend. After validating the accuracy of this model against classical experiments, the paper comprehensively analyzes the modulation effect of large particles on turbulence, and the effects of different particle diameters, particle transport concentrations, and transport velocities on the wear of bends connected serially. Finally, the bends connected serially in various configurations are simulated to study the wear on the bent interior surfaces. Results indicate a pronounced modulation effect of large particles on turbulence at higher transport concentrations; the wear rate in the combined bends does not exhibit a linear correlation with the collision frequency of particles on the wall surface. Furthermore, different configurations of serially connected bends exhibit significant differences in the wear morphology of the second bend.

Three Types of Enteromorpha prolifera Bio-Products Based on Different Processing Procedures as Feed Additives in the Diets of Pacific White Shrimp (Litopenaeus vannamei) - Zhibin Zhou; Lubo Wang; Mingqin Dai; Qingyan Gao; Peng Wang; Lili Zhao; Yanlu Li; Rui Xi; Mingchao Pan; Qiang Ma; Houguo Xu; Mengqing Liang; et al. (Fishes, 2023)
A feeding trial was conducted to evaluate the biological activities of Enteromorpha prolifera bio-products in the diets of Pacific white shrimp (Litopenaeus vannamei). Bio-products of E. prolifera included E. prolifera meal, E. prolifera hydrolysate and E. prolifera polysaccharide, which was supplied using different processing procedures. The control diet was supplemented without any E. prolifera bio-products or dietary attractants. Experimental diets were formulated to contain 0.2% and 0.4% of E. prolifera hydrolysate (EPH0.2% and EPH0.4%), 0.03% of E. prolifera polysaccharide (EPP0.03%), 3% of E. prolifera meal (EPM3%), 0.1% of dimethyl-β-propiothetn (DMPT0.1%) and 1% of squid paste (SP1%). Shrimp (~8 g) were randomly distributed in 21 tanks and fed for 44 days. Feed intake showed that 3% of E. prolifera meal and 0.4% of E. prolifera hydrolysate in diets exhibited similar attractant effects as 0.1% of DMPT. Gross qualitative observation showed that the abundance of lipid droplets decreased in hepatopancreas of the EPH0.4% and EPM3% groups, which were supported by hepatopancreas triacylglycerol (TG), where significantly lower concentrations were observed in the EPH0.4% and EPM3% groups compared with the control group. Similarly, TG and low-density lipoprotein cholesterol in serum significantly decreased in the EPH0.4%, EPP0.03% and EPM3% groups compared to the control group. Supplemental E. prolifera bio-products resulted in significantly higher serum glutathione level of EPP0.03% or superoxide dismutase activities of EPH0.4% and EPM3%, but significantly lower serum malondialdehyde level of EPM3%. In addition, tnf-α expression in hepatopancreas was significantly down-regulated in shrimp fed the EPH0.2%, EPH0.4% and EPM3% diets. Based on survival analysis, E. prolifera bio-products improved the resistance of shrimp to hypoxic stresses. Thus, this study confirmed that bio-products of E. prolifera supplied using different processing procedures could be used to reduce the amount of E. prolifera in feed of shrimp without compromising their biological functions.

Effects of Dietary Eucommia ulmoides Leaf Extract on Growth, Muscle Composition, Hepatopancreas Histology, Immune Responses and Microcystin-LR Resistance of Juvenile Red Claw Crayfish (Cherax quadricarinatus) - Yao-Peng Lu; Pei-Hua Zheng; Jia-Rui Xu; Yan-Lei Cao; Jun-Tao Li; Chen-Guang Hao; Ze-Long Zhang; Jian-An Xian; Xiu-Xia Zhang; An-Li Wang (Fishes, 2022)
The objective of the present study was to investigate the effects of different doses of dietary Eucommia ulmoides leaf extract (ELE) on juvenile red claw crayfish (Cherax quadricarinatus). A total number of 720 red claw crayfish (initial body weight of 0.24 ± 0.01 g) were randomly assigned to six groups and fed diets containing 0 (Diet 1), 0.5 (Diet 2), 1 (Diet 3), 2 (Diet 4), 4 (Diet 5) and 10 (Diet 6) g dry weight (dw) ELE kg (dw)−1 diets for eight weeks and challenged with microcystin-LR stress. The results indicated that dietary supplementation with 1–2 g dw ELE kg (dw)−1 diet could significantly improve the weight gain rate (WGR) and specific growth rate (SGR) of crayfish. Muscle crude protein contents of crayfish fed Diet 2, Diet 3, and Diet 4 were significantly higher than those of the control group. Compared with the control group, dietary ELE could increase total antioxidant capacity (T-AOC), superoxide dismutase (SOD), glutathione peroxidase (GPx), acid phosphatase (ACP), alkaline phosphatase (AKP), and phenoloxidase (PO) activities and decrease malondialdehyde (MDA) level of crayfish. Dietary ELE significantly increased the relative expression levels of SOD, thioredoxin 1 (TRX1), GPx, selenium-dependent glutathione peroxidase (Se-GPx), cytochrome P450 (CYP450), anti-lipopolysaccharide factor (ALF) and C-type lysozyme (C-LZM) mRNA of crayfish compared with the control group during the feeding experiment. When subjected to MC-LR stress for 48 h, the mRNA expression levels of SOD, GPx, Se-GPx, glutathione-s-transferase 1 (GST1), ALF, hemocyanin (HEM), and C-LZM in the hepatopancreas could be improved to varying degrees compared with the Diet 1. Supplementation of 1–2 g dw ELE kg (dw)−1 diet could improve the survival rate (SR) of crayfish under MC-LR stress. These results indicated that dietary ELE (1–2 g dw ELE kg (dw)−1 diet) could improve the growth performance, muscle protein, and non-specific immune response and increase the SR of crayfish under MC-LR stress by regulating the mRNA expression levels of the immune- and antioxidant-related genes.

Analysis of Cyclic Shear Stress–Displacement Mechanical Properties of Silt–Steel Interface in the Yellow River Delta - Peng Yu; Jie Dong; Haisong Liu; Rui Xu; Rujie Wang; Meijun Xu; Hongjun Liu (Journal of Marine Science and Engineering, 2022)
Pile foundations of offshore structures are often subjected to cyclic loads under storm loads, thus reducing their vertical bearing capacity. Therefore, studying the cyclic shear behavior of the soil–structure interface is important for maintaining the stability of offshore structures. A series of cyclic shear tests of the silt–steel interface were carried out using a large interface shear apparatus. The effects of various factors (i.e., normal stress, shear displacement amplitude, roughness, and water content) on the shear stress characteristics of the silt–steel interface were investigated. The stress–displacement model of the cyclic shear silt–steel interface was deduced. The results showed that the shear stress at the silt–steel interface was softened, and the type of bulk deformation was shear shrinkage under cyclic shear. With the increase in shear amplitude, the hysteresis curve gradually developed from “parallelogram” to “shuttle” and “hysteresis cake”. With the increase in normal stress and roughness and the decrease in water content, the interfacial shear strength, volume displacements growth rate, and growth rate increased. The stress–displacement mathematical model of the silt–steel interface based on the modified hyperbolic model was in good agreement with the test data.

Combined Effects of Eco-Substrate and Carbon Addition on Water Quality, Fish Performance and Nutrient Budgets in the Pond Polyculture System - Kun Guo; Zhigang Zhao; Jun Xie; Liang Luo; Shihui Wang; Rui Zhang; Wei Xu; Xiaoli Huang (Fishes, 2022)
Traditional aquaculture can cause serious environmental pollution. Biofilm and biofloc technology have the potential to limit aquaculture pollution. An outdoor experiment was conducted to evaluate the combined effects of eco-substrates and carbon addition on water quality, fish performance and nutrient budgets in the pond polyculture system. In the treatment group, the total ammonia nitrogen, nitrate nitrogen, nitrite nitrogen, and total nitrogen of the water were significantly lower compared to the control group (p 92%) and P (>95%) input during the experiment. Comprehensive accumulation was the main N (>58%) and P (>69%) output. The N and P feed input and comprehensive accumulation output declined in the treatment group. The N utilization efficiency in the experimental group increased slightly (p > 0.05), while the P utilization efficiency in the experimental group was significantly higher compared to the control (p

Population Genetic Diversity and Differentiation of Mitten Crab, Genus Eriocheir, Based on Microsatellite Markers - Shihui Wang; Liang Luo; Rui Zhang; Kun Guo; Wei Xu; Zhigang Zhao (Fishes, 2022)
Mitten crab, Eriocheir sensu stricto, is an important indigenous aquatic species and food source in Eastern Asia. Genetic diversity is an important prerequisite for the conservation and utilization of germplasm resources. However, the genetic diversity and differentiation of Eriocheir s. s. remains unclear. This study evaluated population genetic diversity and genetic differentiation of three Eriocheir s. s. populations from Suifenhe (SFH), Liaohe (LH), and Nanliujiang (NLJ), China, based on 19 microsatellite markers. The mean observed number of alleles (Na) was 22.84 alleles, and the mean polymorphism information content (PIC) was 0.86, which demonstrated high genetic diversity. The allele frequency distribution showed an “L” shape, ranging from 0.01 to 0.74. The genetic diversity parameter values of the LH population were higher than those of the other two populations. All pairwise FST values showed significant differences among the three Eriocheir s. s. populations (p

A State-Dependent Constitutive Model for Gas Hydrate-Bearing Sediments Considering Cementing Effect - Qingmeng Yuan; Liang Kong; Rui Xu; Yapeng Zhao (Journal of Marine Science and Engineering, 2020)
This paper presents a state-dependent constitutive model for gas hydrate-bearing sediments (GHBS), considering the cementing effect for simulating the stress–strain behavior of GHBS. In this work, to consider the influence of hydrate on matrix samples in theory, some representative GHBS laboratory tests were analyzed, and it was found that GHBS has obvious state-related characteristics. At the same time, it was found that GHBS has high bonding strength. In order to describe these characteristics of GHBS, the cementation strength related to hydrate saturation is introduced in the framework of a sand state correlation model. In addition, in order to accurately reflect the influence of cementation on the hardening law of GHBS, the degradation rate of cementation strength is introduced, and the mixed hardening theory is adopted to establish the constitutive model. The model presented in this paper reproduces the experimental results of Masui et al. and Miyazaki et al., and the prediction performance of the model is satisfactory, which proves the rationality of this work.

Design and Experiment of a Plateau Data-Gathering AUV - Hao Xu; Guo-Cheng Zhang; Yu-Shan Sun; Shuo Pang; Xiang-Rui Ran; Xiang-Bin Wang (Journal of Marine Science and Engineering, 2019)
The design, control, and implementation of an autonomous underwater vehicle (AUV) for collecting hydrological information from plateau rivers and lakes are presented in this paper. The hardware and software structures of the control system were previously described. A novel sliding mode controller (SMC) with combinational reaching law of vertical hovering motion is proposed to improve the robustness and stability. The S-plane control, a nonlinear controller with little parameters, is used in the horizontal motion. Besides, the navigation strategy based on the dead-reckoning algorithm, a path tracking based on the light-of-sight (LOS) algorithm, and a control allocation strategy considering saturation are present. Finally, experiments were performed in a tank and in a river in the Qinghai–Tibet Plateau to prove the feasibility and reliability of the AUV system.