Search Results (1,452)

Maritime transportation, fishing, scientific research, and other activities rely on various types of ships and platforms, making precise monitoring of ships at sea essential. Synthetic Aperture Radar (SAR) is minimally affected by weather conditions and darkness and is used for ship detection in maritime environments. This study analyzes the differences in backscatter characteristics among various ship types in SAR images and proposes SISS-YOLO, an enhanced model based on YOLOv8. The proposed method addresses the challenge of ship instance segmentation in SAR images involving multiple polarizations, scenarios, and classes. First, the backbone structure was optimized by incorporating additional pooling layers and refining the activation functions. Second, the Coordinate Attention (CA) module was integrated into the C2F template, embedding spatial position information into the channel attention mechanism. Third, a slide loss function was adopted to address the class imbalance across ship categories. The experiments were conducted on the OpenSARShip2.0 dataset, which includes cargo, tanker, passenger and engineering ships. The results show that the SISS-YOLO achieves a mask precision of 88.3%, a mask recall of 86.4% and a mask mAP50 of 93.4% for engineering ships. Compared with YOLOv8m, SISS-YOLO achieved improvements of 15.7% in mask precision and 8.8% in mask recall. The model trained on the OpenSARShip2.0 dataset was directly applied to the FUSAR-Ship1.0 dataset, demonstrating a degree of robustness. When applied to SAR data, the SISS-YOLO model achieves high detection accuracy, demonstrating generalization. Full article

Objective: The Mediterranean diet (MedDiet) is characterized by its emphasis on plant-based foods, olive oil, and fish products, and has been associated with providing relevant fatty acids (FAs) for adolescent physiology. This study aims to investigate the relationship between adherence to the MedDiet and the FA composition of red blood cell (RBC) membranes in an adolescent population. Methods: The current research examines the relationship between MedDiet adherence, assessed using the KIDMED questionnaire, and the composition of RBC membranes, specifically measuring 22 FAs in a cross-sectional analysis of adolescents from two cohorts (mean age = 14.55). Baseline data from 552 participants with complete dietary adherence and FA information were analyzed using multivariable regression models and principal component analysis (PCA) as confirmatory analysis. All regression models were adjusted by age, sex, body mass index, physical activity, maternal education and cohort enrollment. Results: Main results shown that “Good adherence” to the MedDiet was positively associated with omega-3 FAs, including eicosapentaenoic acid (β = 0.34; 95% CI: 0.17, 0.52; p-value < 0.001) and docosahexaenoic acid (β = 0.29; 95% CI: 0.11, 0.46; p-value = 0.001), and inversely associated with specific omega-6 FAs, such as arachidonic acid (β = −0.28; 95% CI: −0.46, −0.11; p-value = 0.002) and adrenic acid (β = −0.19; 95% CI: −0.30, −0.08; p-value < 0.001). PCA identified distinct FA patterns, with “Good adherence” to the MedDiet being associated with an increase in the omega-3 FAs pattern (β = 0.32; 95% CI: 0.14, 0.49; p-value < 0.001). These findings remained robust after multiple test comparisons. Conclusions: This study underscores the potential of the MedDiet to promote optimal RBC FA composition in healthy adolescents, characterized by high levels of omega-3 FAs and reduced levels of arachidonic acid and adrenic acid in RBC membranes. Full article

This paper is based on the fish lateral line sensing mechanism and aims to determine the coupling relationship between the flow field sensing signal and target source position information. Firstly, according to the flow field distribution characteristics of the target source, the equivalent multipole model of the flow field disturbance during the underwater motion of the SUBOFF model is constructed, and then the target localization function based on the least squares method is established according to the theory of potential flow, and the residual function of the target localization is solved optimally using the quasi-Newton method (QN) to obtain the estimated position of the target source. On this basis, a curved bionic lateral line sensing array is constructed on the surface of a robotic fish, and the estimated location of the target source is obtained. The curvilinear bionic lateral line sensing array is constructed on the surface of the robotic fish, and the effectiveness and robustness of the above localization methods are analysed to validate whether the fish lateral line uses the pressure change to sense the underwater target. Full article

The Western and Central Pacific Ocean (WCPO), the key global purse seine fishing ground for skipjack tuna (Katsuwonus pelamis), sees frequent ENSO events. These events drastically alter marine ecosystems and fishery resource patterns, complicating fisheries management—given skipjack tuna’s high mobility and sensitivity to marine environmental changes. To address this, the study proposes an improved spatial prediction framework that incorporates the MGWR model to capture environmental changes. The spatial regression results generated by the MGWR model are incorporated as the mean-field input for the BME model. Additionally, the interannual standard deviation of skipjack tuna resources is fed into the BME model as a measure of spatial uncertainty. The results indicate that the mean field and uncertainty field exhibit a strong correlation, with an R² of 0.54, an RMSE of 583.32, an MAE of 377.22, and an ME of 334.77. Compared to the single prediction models BME and MGWR, the MGWR-BME integrated framework has improved R² by 12%, 30%, and 13% in the 2021–2023 predictions, respectively. Additionally, its prediction performance for distinguishing El Niño, La Niña, and normal years has significantly improved, with R² increasing from 0.6 to 0.67 in 2021, from 0.34 to 0.62 in 2022, and from 0.30 to 0.40 in 2023. According to the evaluation results based on Kernel Density Estimation (KDE) curves, the model performs well in fitting low values but shows weaker performance in fitting high values. By applying this approach, we have clarified the multiscale driving mechanisms through which marine environmental heterogeneity affects the distribution of skipjack tuna under ENSO conditions. This insight enables fishery managers to more accurately predict the dynamic changes in skipjack tuna fishing grounds under different climatic scenarios, thereby providing a reliable scientific basis for formulating rational fishing quotas, optimizing fishing operation layouts, and implementing targeted conservation measures—ultimately contributing to the balanced development of fishery resource utilization and ecological protection. Full article

For aquaculture systems, maximizing feed efficiency is a major challenge since it directly affects growth rates and economic sustainability. Feed is one of the largest costs in aquaculture, and feed waste is a significant environmental issue that requires effective management strategies. This paper suggests a novel approach for optimal fish feeding in pond aquaculture systems that integrates vision language models (VLMs), optical flow, and advanced image processing techniques to enhance feed management strategies. The system allows for the precise assessment of fish needs in connection to their feeding habits by integrating real-time data on biomass estimates and water quality conditions. By combining these data sources, the system makes informed decisions about when to activate automated feeders, optimizing feed distribution and cutting waste. A case study was conducted at a profit-driven tilapia farm where the system had been operational for over half a year. The results indicate significant improvements in feed conversion ratios (FCR) and a 28% reduction in feed waste. Our study found that, under controlled conditions, an average of 135 kg of feed was saved daily, resulting in a cost savings of approximately $1800 over the course of the study. The VLM-based fish feeding behavior recognition system proved effective in recognizing a range of feeding behaviors within a complex dataset in a series of tests conducted in a controlled pond aquaculture setting, with an F1-score of 0.95, accuracy of 92%, precision of 0.90, and recall of 0.85. Because it offers a scalable framework for enhancing aquaculture resource use and promoting sustainable practices, this study has significant implications. Our study demonstrates how combining language models and image processing could transform feeding practices, ultimately improving aquaculture’s environmental stewardship and profitability. Full article

Industrial recirculating aquaculture systems (RAS) constitute an energy-saving and environmentally friendly approach to modern aquaculture production. The hydrodynamic characteristics within these systems, coupled with the ecological environment of the fish, are essential for the efficient operation of the system and for promoting optimal fish growth and welfare. These systems provide several advantages, such as high intensification, efficient water resource utilization, enhanced environmental control, and minimal environmental pollution. Consequently, it has emerged as prominent avenue for advancing aquaculture development in China. This paper begins with an examination of the fundamental concepts and primary tank structures underpinning industrial RAS. It then proceeds to elucidate the hydrodynamic characteristics within RAS and their interrelationship with fish growth and welfare. Furthermore, it offers a thorough review of tank hydrodynamic characteristics and fish interactions from various perspectives, including operational parameters, hydrodynamic drive equipment, fish behavior, and the aquaculture environment. Finally, the limitations of current studies are assessed, and potential future research directions are proposed. Full article

Triplophysa yarkandensis, a unique saline-alkali tolerant fish in the Tarim River Basin, exhibits unclear adaptive mechanisms of its digestive system to saline-alkali stressors. This study compared the histological characteristics of the digestive system in fish reared in saline-alkali water (salinity 5.89, alkalinity 125.60) and freshwater. Histological characteristics were analyzed using hematoxylin-eosin staining, and parameters were quantified via Image-Pro Plus software, with statistical comparisons performed using independent sample t-tests. Key findings included a 2.7-fold increase in oropharyngeal club cell density (48.50 ± 2.68 vs. 17.80 ± 2.04, p < 0.01) with denser stratified squamous epithelium in the saline-alkali group; a 74% increase in esophageal goblet cells (104.42 ± 6.67 vs. 59.94 ± 4.68, p < 0.01) alongside a 39% reduction in mucosal fold height; 87%, 24%, and 51% increases in villi number across the foregut, midgut, and hindgut, respectively, with an 84% elevation in midgut goblet cells (p < 0.01); and mild vacuolization in the hepatopancreas. Results indicate that T. yarkandensis adapts via synergistic strategies of enhanced digestive mucus secretion, epithelial structural optimization, and hepatopancreatic metabolic reprogramming. The coordinated villi proliferation and mucus secretion enhance nutrient absorption and osmotic barrier function, providing a theoretical basis for saline-alkali aquaculture. Full article

This study evaluated the effectiveness of essential oil from Aloysia citrodora (EOAC) (48% citral and 19% limonene) for use in anesthesia and simulated transport of tambaqui (Colossoma macropomum) juveniles at two cargo densities (CDs). Concentrations of 0 (control), 10, 25, 50, 100, 150, 200, and 250 µL EOAC L⁻¹ were tested for use in anesthesia induction and recovery, while 0 (control) and 20 µL EOAC L⁻¹ were tested for their effects on the ventilatory rate (VR) and during 6 h simulated transport at a low CD (LCD, 65 g L⁻¹) and standard CD (SCD, 130 g L⁻¹). Fish were anesthetized at EOAC concentrations above 50 µL L⁻¹, with the optimal anesthesia (141.83 s) and recovery times (160.00 s) at 250 µL L⁻¹. The water unionized ammonia was lowest in the EOAC-LCD group. Using 20 µL EOAC L⁻¹ during transport minimized changes in the hematological parameters (erythrocytes, hemoglobin, hematocrit, total leukocytes, and heterophils) and reduced the liver aspartate aminotransferase activity at both CDs. Transport at an SCD, regardless of EOAC use, increased the plasma glucose, hepatic glycogen, and alanine transaminase activity. The VR was higher with 20 µL EOAC L⁻¹ than in the control group. In conclusion, our findings confirm that 20 µL EOAC L⁻¹ can effectively be used to transport tambaqui for up to 6 h without impairing fish health. Full article

Fish condition detection, including the identification of feeding desire, biological attachments, fence breaches, and dead fishes, has become an important research frontier in fishery aquaculture. However, perception in underwater conditions is less satisfactory and remains a tricky problem. Firstly, we have developed a multimodal dataset based on Neuromorphic vision (NeuroVI) and RGB images, encompassing challenging fishery aquaculture scenarios. Within the fishery aquaculture dataset, a spike neural network (SNN) method is designed to filter NeuroVI images, and the sift feature points are leveraged to select the optimal image. Next, we propose a dual-image cross-attention learning network that achieves scene segmentation in a fishery aquaculture cage. This network comprises double-channels feature extraction and guided attention learning modules. In detail, the feature matrix of NeuroVI images serves as the query matrix for RGB images, generating attention for calculating key and value matrices. Then, to alleviate the computational burden of the dual-channel network, we replace dot-product multiplication with element-wise multiplication, thereby reducing the computational load among different matrices. Finally, our experimental results from the fishery cage demonstrate that the proposed method achieves the state-of-the-art segmentation performance in the management process of fishery aquaculture. Full article

Disease outbreaks pose a significant challenge in aquaculture, leading to substantial economic losses for producers. Tenacibaculosis, a significant ulcerative bacterial disease caused by Tenacibaculum maritimum, affects a wide range of marine fish species globally. Current disease management relies on antibiotics and chemicals, leading to environmental issues, impaired fish and consumer health, and increased antimicrobial-resistant bacteria. This narrative review critically explores welfare-oriented alternatives, specifically examining the potential of temperature modulation and functional diets. Although thermal strategies show promise for warm-water species through behavioural fever mechanisms, their effectiveness remains limited by species-specific thermal tolerances and lack of commercial validation. Nutritional interventions using marine algae, probiotics, and immunostimulants demonstrate broader applicability but suffer from inconsistent methodologies, limited commercial validation, and significant knowledge gaps. We propose that integration of these approaches could theoretically represent a paradigm shift from pathogen-focused to host-centred disease management, pending empirical validation. However, this integration concept requires rigorous validation, as significant knowledge gaps persists regarding optimal implementation protocols, welfare monitoring frameworks, and economic viability assessments. From our perspective, transitioning to welfare-oriented aquaculture demands rigorous evaluation and validation, commercial-scale trials, economic cost–benefit analysis, and the establishment of regulatory frameworks before these theoretical alternatives can be responsibly implemented. Full article

Caffeic acid (CA), a plant-derived phenolic compound, is emerging as a promising natural feed additive for sustainable aquaculture. Its growth-promoting, immunomodulatory, and antimicrobial activities suggest utility as an alternative that diminishes antibiotic use in fish farming. Evidence across multiple species indicates improvements in innate immune responses, enhanced antioxidant capacity, and increased survival during pathogen challenge. Nevertheless, adoption remains limited by unresolved questions regarding optimal inclusion levels, species-specific physiological responses, interactions with other dietary components, and effects on the gut microbiota. This review synthesizes current research on CA, critically evaluates its functional roles in aquaculture, and assesses its relevance to sustainable production. Priorities for future work include elucidating mechanisms of action, conducting cross-species dose–response studies, standardizing dosing protocols, clarifying microbiome effects, and evaluating economic feasibility for large-scale use. Addressing these gaps will be essential to realize the full potential of CA as a functional feed additive in sustainable aquaculture systems. Full article

Particle Swarm Optimization (PSO) is a metaheuristic optimization technique based on population behavior, inspired by the movement of a flock of birds or a school of fish. In this method, particles move in a search space to find the global minimum of an objective function. In this work, a modified PSO algorithm written in Fortran 90 is proposed. The optimized structures obtained with this algorithm are compared with those obtained using the basin-hopping (BH) method written in Python (3.10), and complemented with density functional theory (DFT) calculations using the Gaussian 09 software. Additionally, the results are compared with the structural parameters reported from single crystal X-ray diffraction data for carbon clusters ${\mathrm{C}}_n$(n = 3–5), and tungsten–oxygen clusters, ${\mathrm{WO}}_n^{m-}$(n = 4–6, $m=2,4,6$). The PSO algorithm performs the search for the minimum energy of a harmonic potential function in a hyperdimensional space $\in {\mathbb{R}}^{3N}$ (where N is the number of atoms in the system), updating the global best position ( $g_{best}$) and local best position ( $p_{best}$), as well as the velocity and position vectors for each swarm cluster. A good approximation of the optimized structures and energies of these clusters was obtained, compared to the geometric optimization and single-point electronic energies calculated with the BH and DFT methods in the Gaussian 09 software. These results suggest that the PSO method, due to its low computational cost, could be useful for approximating a molecular structure associated with the global minimum of potential energy, accelerating the prediction of the most stable configuration or conformation, prior to ab initio electronic structure calculation. Full article

This paper proposes a rolling bearing fault diagnosis method based on HFMD and a dual-branch parallel network, aiming to address the issue of diagnostic accuracy being compromised by the disparity in data quality across different source domains due to sparse feature separation in rolling bearing acoustic signals. Traditional methods face challenges in feature extraction, sensitivity to noise, and difficulties in handling coupled multi-fault conditions in rolling bearing fault diagnosis. To overcome these challenges, this study first employs the HawkFish Optimization Algorithm to optimize Feature Mode Decomposition (HFMD) parameters, thereby improving modal decomposition accuracy. The optimal modal components are selected based on the minimum Residual Energy Index (REI) criterion, with their time-domain graphs and Continuous Wavelet Transform (CWT) time-frequency diagrams extracted as network inputs. Then, a dual-branch parallel network model is constructed, where the multi-scale residual structure (Res2Net) incorporating the Efficient Channel Attention (ECA) mechanism serves as the temporal branch to extract key features and suppress noise interference, while the Swin Transformer integrating multi-stage cross-scale attention (MSCSA) acts as the time-frequency branch to break through local perception bottlenecks and enhance classification performance under limited resources. Finally, the time-domain graphs and time-frequency graphs are, respectively, input into Res2Net and Swin Transformer, and the features from both branches are fused through a fully connected layer to obtain comprehensive fault diagnosis results. The research results demonstrate that the proposed method achieves 100% accuracy in open-source datasets. In the experimental data, the diagnostic accuracy of this study demonstrates significant advantages over other diagnostic models, achieving an accuracy rate of 98.5%. Under few-shot conditions, this study maintains an accuracy rate no lower than 95%, with only a 2.34% variation in accuracy. HFMD and the dual-branch parallel network exhibit remarkable stability and superiority in the field of rolling bearing fault diagnosis. Full article

A pH-responsive bilayer film was developed for real-time freshness monitoring and preservation of yellowfin seabream. The emulsified layer contained chitosan (CS) and flaxseed oil (FO), while the indicator layer comprised carrageenan (CAR), gelatin (GEL), grape seed anthocyanins (GSA), and curcumin (CUR). Optimization via response surface methodology determined the ideal formulation: CAR/GEL mass ratio 1.11:1, CS concentration 1.70%, and GSA/CUR dosage 53.99 mg/100 mL. The optimized film demonstrated superior mechanical properties (TS = 12.74 MPa, EAB = 68.24%), enhanced hydrophobicity (WVP = 1.21 × 10⁻¹¹ g·m⁻¹·s⁻¹·Pa⁻¹), and potent antioxidant activity (HRC = 92.35%). FTIR and SEM confirmed stable cross-linking and bilayer compatibility. Distinct color transitions (yellow → reddish-brown) occurred at different pH levels, correlating with fish spoilage indicators. During 25°C storage, the film effectively inhibited quality deterioration (TVB-N, TBARS, moisture loss, lipid oxidation) while extending shelf-life. Strong correlations were observed among TVB-N, TBARS, moisture (|r| > 0.97), and PUFAs’ spoilage contribution (r ≈ −0.99). This intelligent film enables dual-functionality: active preservation and visual freshness monitoring. Full article

The red mullet (Mullus barbatus, Linnaeus 1758) is a commercially vital demersal species in the Eastern Aegean Sea, yet it is subjected to high fishing pressure. This study assesses the population dynamics, growth, and exploitation status of M. barbatus based on 64 commercial trawl surveys conducted between 2022 and 2024 in the Lesvos–Ayvalik region. Length-frequency data identified eight age classes, with dominant cohorts at ages 3 (26.4%) and 5 (25%). The von Bertalanffy growth model estimated an asymptotic length (L∞) of 27.9 cm and growth coefficient (k = 0.21 year⁻¹), indicating a slow growth rate. The estimated fishing mortality (F = 0.74) exceeded natural mortality (M = 0.44), producing an exploitation rate (E = 0.63) that indicates overfishing. The length at 50% capture (LC₅₀ = 10.92 cm) was substantially below the optimal biomass length (Le = 16.6 cm), highlighting gear selectivity issues. Net benefit analysis revealed optimal fishing at 50–85 m depth and during December. These findings underscore the urgent need for improved management, including gear modifications, seasonal closures, and reduced effort, to restore sustainability and protect juvenile fish in the Eastern Aegean trawl fishery. Full article