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Journal of Ocean University of China (English Edition)
Journal Prestige (SJR): 0.265  Citation Impact (citeScore): 1 Number of Followers: 1  Hybrid journal (It can contain Open Access articles)ISSN (Print) 1993-5021 - ISSN (Online) 1672-5182 Published by Springer-Verlag  [2468 journals]
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- The Acoustic Attenuation Prediction for Seafloor Sediment Based on in-situ
Data and Machine Learning Methods-
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Abstract: Abstract Accurate acquisition and prediction of acoustic parameters of seabed sediments are crucial in marine sound propagation research. While the relationship between sound velocity and physical properties of sediment has been extensively studied, there is still no consensus on the correlation between acoustic attenuation coefficient and sediment physical properties. Predicting the acoustic attenuation coefficient remains a challenging issue in sedimentary acoustic research. In this study, we propose a prediction method for the acoustic attenuation coefficient using machine learning algorithms, specifically the random forest (RF), support vector machine (SVR), and convolutional neural network (CNN) algorithms. We utilized the acoustic attenuation coefficient and sediment particle size data from 52 stations as training parameters, with the particle size parameters as the input feature matrix, and measured acoustic attenuation as the training label to validate the attenuation prediction model. Our results indicate that the error of the attenuation prediction model is small. Among the three models, the RF model exhibited the lowest prediction error, with a mean squared error of 0.8232, mean absolute error of 0.6613, and root mean squared error of 0.9073. Additionally, when we applied the models to predict the data collected at different times in the same region, we found that the models developed in this study also demonstrated a certain level of reliability in real prediction scenarios. Our approach demonstrates that constructing a sediment acoustic characteristics model based on machine learning is feasible to a certain extent and offers a novel perspective for studying sediment acoustic properties.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5783-5
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- Adsorption Characteristics of Congo Red Dye onto Calcinated Mytilus edulis
Shell Powders-
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Abstract: Abstract Dye wastewater poses a significant threat to aquatic organisms due to its high toxicity. Reducing or eliminating the dye waste from the water is necessary for a healthy and sustainable aquaculture. This study investigated the adsorption properties of Congo red dye on Mytilus edulis shell powders prepared by calcination at 500°C, 700°C, and 900°C The modified shell powder products were analyzed by SEM (scanning eletron microscopy) and FTIR (fourier transform infrared spectroscopy) for the morphology and structural characterization. The effects of different calcination temperatures, reaction times, reaction temperatures, and initial concentration of Congo red on the adsorption properties were investigated. The adsorption kinetics and isothermal adsorption models were also established. The results revealed that the shell powder calcinated at 900° showed the best adsorption capacity on Congo red from aqueous solution. The adsorption reaction reached equilibrium after 150 min and followed by the pseudo-second-order kinetic model. At 25°C, 96.2% of the Congo red in the solution could be removed, and the adsorption capacity could reach at least 1015 mg g−1. The adsorption isotherm is fit with the Freundlich model, indicating a multiphase adsorption process. These results are helpful for cleaning and treating printing and dyeing effluents as well as high-value utilization of shell waste resources.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5930-z
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- Numerical Study of the Shallow-Water Effect on the Hydrodynamic Loads and
Wake of a Ship in Oblique Flow-
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Abstract: Abstract When a ship moves in an oblique flow, its hydrodynamic loads and wake characteristics vary substantially from those in straight-ahead motion. This dissimilarity can be even more complex when the ship operates in a seaway of shallow water. In this paper, a numerical analysis of the shallow-water effect on the hydrodynamic forces and wake characteristics of an international ship model, KVLCC2, in oblique flows is conducted. Numerical simulations are performed based on the Reynolds Averaged Navier-Stokes equation in conjunction with the shear stress transport (SST) k-ω turbulence model. Four relative water depths (h = 1.2T, 1.5T, 3.0T, and 24T; T is the ship draft) and five different drift angles (β = 0°, 5°, 10°, 15°, and 20°) are considered. Results reveal the following: i) The shallow-water effect is strong and leads to nonlinear increases in the longitudinal force regardless of drift angles and on the transverse force and yaw moment whenever the drift angle increases. ii) In shallow water, the mean wake fraction is sensitive to the drift angle, and the strength of the aft-body vortex on the leeward side increases.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5854-7
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- A Simulation Study to Assess Impacts of Habitat-Dependent Parameters of
Surplus Production Model on Stock Assessment of Chilean Jack Mackerel in
the Southeast Pacific Ocean-
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Abstract: Abstract Pelagic fish are the most abundant species in upwelling regions, contributing 25% of total global fisheries production. Climate-driven changes in the marine environment play a crucial role in their population dynamics. Using Chilean jack mackerel (Trachurus murphyi) as an example, this study conducted simulations to quantify the impacts of environmental variations on the stock assessment. A habitat-based surplus production model was developed by integrating suitable habitat area into the model parameters carrying capacity (K) and intrinsic growth rate (r), with a suitable habitat area serving as the proxy for the environmental conditions for Chilean jack mackerel in the Southeast Pacific Ocean. The dynamics of Chilean jack mackerel stock and fisheries data were simulated, and four assessment models with different configurations were built to fit simulated data, with or without considering environmental effects. The results indicated that Joint K-r model, which integrated both parameters with the suitable habitat area index, outperformed the others by coming closest to the ‘true’ population dynamics. Ignoring habitat variations in the estimation model tended to overestimate biomass and underestimate harvest rate and reference points. Without observation and process error, the results were estimated with bias, while FMSY is relatively sensitive. This research illustrates the importance to consider random errors and environmental influences on populations, and provides foundation guidelines for future stock assessment.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5873-4
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- Reduced Salinity Interacts with Enriched Nitrogen to Enhance the
Photosynthetic Efficiency of Chlorophyta Ulva fasciata-
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Abstract: Abstract Macroalgae dominate nutrient dynamics and function as high-value foods for microbial, meio- and macrofaunal communities in coastal ecosystems. Because of this vital role, it is important to clarify the physiological information associated with environmental changes as it reflects their growth potential. To evaluate the effects of the changes in salinity and nutrients, the photosynthetic efficiency of a green macroalga Ulva fasciata from the Daya Bay was tested at a range of salinity (i.e., 31 to 10 psu) and nitrogen content (i.e., 5 to 60 µmol L−1). The results showed that cellular chlorophyll a (Chl a), carbohydrate and protein contents of U. fasciata were increased due to reduced salinity, and were decreased by interactive nitrogen enrichment. Within a short culture period (i.e., 18 h), the reduced salinity decreased the maximum photosynthetic efficiency (rETRmax and Pmax) derived from the rapid light response curve and photosynthetic oxygen evolution rate versus irradiance curve, respectively, as well as the saturation irradiance (EK). This reducing effect diminished with enlonged cultivation time and reversed to a stimulating effect after 24 h of cultivation. The nitrogen enrichment stimulated the rETRmax and Pmax, as well as the EK, regardless of salinity, especially within short-term cultivation period (i.e., < 24 h). In addition, our results indicate that seawater freshening lowers the photosynthetic efficiency of U. fasciata in the short term, which is mitigated by nitrogen enrichment, but stimulates it in the long term, providing insight into how macroalgae thrive in coastal or estuarine waters where salinity and nutrients normally covary strongly.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5774-6
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- Transcriptome Analysis of Soiny Mullet Larvae Challenge with Polystyrene
Microplastics-
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Abstract: Abstract Microplastics (MPs) pollution has become a worldwide environmental problem. The study about the effects of microplastics on fish, especially on the fish immune system is limited. In the present study, the transcriptome of soiny mullet (Liza haematocheila) larvae at 7 d and 14 d post 0.5 µm MPs exposure were analyzed by DNBSEQ platform. A total number of 96585 unigenes were obtained with average length of 1925 bp. Approximately 72.48% (70004), 76.80% (74176), and 62.94% (60787) unigenes were matched with the annotated sequences for non-redundant (NR), NCBI nucleotide (NT) and Swissprot database, respectively. Compared with control group, 1336 differently expressed genes (DEGs) were identified at 7 d post MPs exposure. As the MPs exposure time extended to 14 d, the number of DEGs in the MPs exposure group reached to 3561. Further, KEGG enrichment analysis revealed that several immune-related pathways, such as interleukin (IL)-17 signaling pathway, tumor necrosis factor (TNF) signaling pathway, were affected by MPs exposure. In addition, apoptosis signaling pathway was also enriched under MPs exposure. These results demonstrated that MPs can alter the expressions of immune-related genes, providing basis for understanding the immune toxicity of MPs on fish and other vertebrates.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5793-3
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- Comparative Study on Hydrodynamic Performances of Fully Activated and
Semi-Activated Oscillating Hydrofoils for Energy Harvesting-
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Abstract: Abstract The oscillating hydrofoil represents a promising technology for harvesting energy from tidal currents. While previous research has primarily focused on oscillating hydrofoils utilizing a fully activated control strategy, the industry predominantly employs a semi-activated control strategy in existing tidal current energy converters. It is essential to identify the differences in predicted energy-harvesting performance between these two controlling strategies through experimental modeling or numerical studies. Furthermore, the suitability of the fully activated control strategy in predicting the energy-harvesting capabilities of oscillating hydrofoils is evaluated. The 2D numerical models of hydrofoil based on fully activated and semi-activated control strategies have been developed and validated. The amplitudes of heaving and pitching movements for the fully activated hydrofoil are determined to match those of the semi-activated hydrofoil. The results show that the main difference between the two control strategies lies in the phase shift occurring between the pitching and heaving motions. This phase shift affects the lift force and its coordination with the heaving velocity, which in turn affects the power output. Notably, the maximum relative efficiency difference obtained between the fully activated and semi-activated control strategies can reach 191%.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5781-7
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- Influence of Rhamnolipids Biosurfactant on the Anodic Electrochemical
Performance in Marine Sediment Microbial Fuel Cell and the Acceleration
Degradation of Crude Petroleum-
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Abstract: Abstract Crude petroleum pollution causes some serious ecological disasters in the ocean. Marine sediment microbial fuel cells (MSMFCs) have been utilized as a novel method for in-situ degradation and a long-term power source. Herein, the effect of different concentrations of rhamnolipids biosurfactant on the electrochemical performance of MSMFCs anode and the higher efficiency of oil degradation are creatively investigated. The results indicate that the anode in sediment containing rhamnolipids effectively enriches the indigenous electrogenic Pseudophaeobacter and Pseudomonas, which significantly enhances the electrochemical performance of the MSMFCs. Under rhamnolipids at the concentration of 200 mg kg−1 in sediment, the anode specific capacitance (401.45 F m−2), exchange current density (4.87 × 10−2 mA m−2), and cell maximum power density (140.24 mW m−2) increase by 2.50, 38.65, and 2.11 times, respectively, in comparison with its natural sediment. And the oil degradation rate (40.06%) was higher than the blank (17.55%). It demonstrates that the synergistic effect between electrochemical catalytic degradation and emulsifying solubilization of rhamnolipids surfactant directly accelerates the degradation of petroleum in marine sediment, which will provide a novel method and theoretical guidance for in-situ degradation and efficient removal of crude petroleum on ocean floor.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5820-4
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- General and Specific Combining Abilities of Pacific Oyster (Crassostrea
gigas) and Fujian Oyster (C. angulata) for Growth, Survival and Thermal
Tolerance of Their Reciprocal Hybrids-
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Abstract: Abstract A crossbreeding program was established in 2019 to address the declining Crassostrea gigas harvests caused by Pacific Oyster Mortality Syndrome (POMS). As a part of the program, this study was performed to estimate the genetic structure underlying phenotypic variation. Fifteen complete diallel crossings of C. gigas and C. angulata, comprising 60 full-sib families, were used to evaluate the general combining ability (GCA) and specific combining ability (SCA), as well as genotype and environment interactions for shell height (SH), summer survival (SS), and thermal tolerance (TT) of reciprocal hybrids GA (C. gigas ♀ × C. angulata ♂) and AG (C. angulata ♀ × C. gigas ♂) grown in Rongcheng and Rushan, Shandong Province, China. The results suggested that heterosis of the reciprocal hybrids was evident for SH, SS, and TT. The hybrid GA had larger heterosis than AG in both testing environments, and can be a potential donor in the breeding program. The male C. gigas had better GCA for SH in Rongcheng, whereas male C. angulata was a good general combiner for SS and TT in both Rongcheng and Rushan. The estimate of SCA was much higher than GCA for SH and lower than GCA for TT. To harness both additive and non-additive genetic effects, combination breeding could be taken to develop hybrid varieties possessing both thermal tolerance and fast-growing traits. The positive correlations between SH and TT suggested that these traits could be improved simultaneously. The significant G × E interactions demonstrated the importance to undertake site-specific breeding programs in different environments. Overall, this study can provide essential information for developing crossbreeding strategies for the oyster farming industry.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5857-4
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- Muti-Biomarker Approach and IBR Index to Evaluate the Oxidative Stress of
Nanoplastic on the Clams, Meretrix meretrix and Sinonovacula constricta-
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Abstract: Abstract Nanoplastic (NP) contaminants are receiving increasing attention due to the harm they can cause to aquatic organisms and their accumulation in the human body through the food web. The goal of this study was to evaluate the oxidative stress caused by NPs on the clams Meretrix meretrix and Sinonovacula constricta. Specimens were exposed to three concentrations of fluorescently labeled polystyrene NPs (PS-NPs; 0, 0.1, and 1 mg L−1) for 7 d followed by a 3 d recovery period. The activities of antioxidant enzymes, such as catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx) and the content of malonaldehyde (MDA) were measured in the digestive gland, gills, and mantle tissues. Results showed that the SOD activity in the gills of M. meretrix was significantly higher than that of the control at day 1, and PS-NPs exposure inhibited the CAT activity in the gills and SOD and GPx activities in the mantle. Exposure to low or high concentrations of PS-NPs increased the activities of both CAT and GPx in the gills of S. constricta at day 3. The oxidative damage was more severe in the digestive gland of M. meretrix and in the mantle of S. constricta based on MDA level, and it returned to normal after recovery. Integrated biomarker response, index version 2 (IBRv2) values showed that the gills were more sensitive to PS-NPs than mantle and digestive gland. Therefore, the oxidative stress by PS-NPs depended on exposure time, dose, organ, and species.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5784-4
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- Intestinal Flatulence in Pampus argenteus: Changes in Gut Microbiota
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Abstract: Abstract Pampus argenteus is a commercially valuable species in many countries. Its artificial cultivation has been impacted by intestinal flatulence, leading to increased mortality. However, the role of gut microbiota in this process remains unclear. Therefore, this study utilized high-throughput sequencing of 16S rRNA genes to investigate the gut microbiota in both flatulent and healthy P. argenteus. A total of 227571 high-quality and classifiable reads, representing 312 Amplicon Sequence Variants (ASVs), were obtained. Proteobacteria emerged as the predominant phylum in all samples, with the flatulent group displaying the highest relative abundance (85.3%). Microbial diversity was significantly greater in samples from water than those from tissues. Composition analysis using Bray-Curtis distance via CPCoA revealed distinct gut microbiota compositions between the samples with flatulence and the healthy samples. Co-occurrence network analysis demonstrated that the bacterial community in the flatulent group exhibited disorder due to the high abundance of Vibrio. Functional predictive analysis (PICRUSt2) indicated that flatulence in P. argenteus was associated with impaired methane and lipid metabolism, potentially resulting in excessive methane synthesis utilizing hydrogen and acetic acid as substrates produced by Clostridium sensu stricto 1, Cetobacterium, and Peptoclostridium. This study holds significant implications for early diagnosis and prevention of intestinal flatulence through the regulation of gut microbiota.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5888-x
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- Modeling Bivariate Distribution of Wind Speed and Wind Shear for
Height-Dependent Offshore Wind Energy Assessment-
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Abstract: Abstract A joint statistical model of wind speed and wind shear is critical for height-dependent wind resource characteristic analysis. However, given the different atmospheric conditions that may be involved, the statistical distribution of the two variables may show multimodal characteristics. In this work, a finite mixture bivariate statistical model was designed to describe the statistical properties, which is composed of several components, each with a Weibull distribution and a normal distribution for wind speed and wind shear, respectively, with a Gaussian copula to describe the dependency structure between the two variables. To confirm the developed model, reanalysis data from six positions in the coastal sea areas of China were used. Our results disclosed that the developed joint statistical model can accurately capture the different multimodal structures presented in all the bivariate samples under mixed atmospheric conditions, giving acceptable predictions of the joint probability distributions. Proper consideration of wind shear coefficient variation is crucial in estimating height-dependent wind resource characteristics. Importantly, unlike traditional methods that are limited to specific hub heights, the model developed here can estimate wind energy potential across different hub heights, enhancing the economic viability assessment of wind power projects.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5830-2
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- The First Non-Chordates QRFP-Like Peptide Receptor Gene in the Cephalopod
Sepiella japonica: Identification, Characterization and Possible Role in
Food Intake-
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Abstract: Abstract The novel identified receptor, GPR103, now renamed QRFPR (also referred to as SP9155 or AQ27), is the endogenous receptor for the neuropeptide QRFP (also referred to as 26RFa). The distribution pattern, structure, and biological actions, such as feeding behavior, bone formation, and hormone secretion of QRFPR have been largely described in chordate species, while no research on QRFPR has been reported in non-chordate species. Here, the first non-chordates QRFP-like peptide receptor gene in the cephalopod Sepiella japonica (Sj_QRFPLR) was identified and characterized. Evidence from multiple alignments, phylogenetic analysis, and in vitro subcellular localization analysis indicated that Sj_QRFPLR is a class A GPCR and it belongs to the QRFPR family. Meanwhile, QRFPR is likely to be structurally conserved in cephalopod species. In situ hybridization and RT-PCR data revealed a wide-spread distribution pattern of Sj_QRFPLR in multiple function lobes of the female brain and numerous peripheral tissues in both male and female cuttlefish. Subsequently, a food deprivation and refeeding experiment showed that Sj_QRFPLR is likely to stimulate food intake in cuttlefish. Additionally, a possible link between Sj_QRFPLR and immune response was briefly detected in cuttlefish. The results will contribute to our understanding of QRFPR in the cephalopod as well as the peptidergic regulation of the QRFP/QRFPR system in non-chordates.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5874-3
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- Mining Subsidence Based on Integrated SBAS-InSAR and Unmanned Aerial
Vehicles Technology-
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Abstract: Abstract The Small Baseline Subset InSAR (SBAS-InSAR) and unmanned aerial vehicles (UAVs) as common ocean-land technologies, have been extensively applied in subsidence, glacial movement, surface deformation, and maritime positioning and navigation. A novel method integrating SBAS-InSAR and UAV photogrammetry is used to analyze ground subsidence deformation in the Gesar gold mine located in Maqu, Northwest China. This approach uses SBAS-InSAR to calculate two-dimensional deformation data for capturing ascending and descending measurements. This method can provide precise information on small-sized deformations within mining regions. The deformation data obtained from UAVs and the vertical deformation data derived from InSAR are integrated to generate comprehensive and accurate ground subsidence data from the mining district. Results demonstrate that using a combined InSAR (vertical) and UAV technique to analyze surface subsidence in mining districts resolves inconsistency between the line-of-sight and deformation orientations. Furthermore, the incoherence issue of InSAR in regions with large deformation gradients is addressed, while the inherent errors of UAV monitoring of mining surface subsidence are mitigated. The genetic algorithm (GA)-backpropagation (BP) neural network algorithm is combined with InSAR data to predict subsidence in collapsed areas. As observed, the GA-BP algorithm has the smallest residual under the same training samples. Therefore, the GA-BP neural network model can effectively predict surface subsidence in mining areas and can be used for subsequent subsidence prediction.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-6009-6
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- Large-Scale Environmental DNA Metabarcoding Shows a Comprehensive Fish
Community in the East China Sea: Do Water Layer and Habitat Matter'-
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Abstract: Abstract Biodiversity serves as the foundation for human survival and development. Marine fishes play a crucial role in supporting both global biodiversity and food sources. The conventional methods for fish diversity and fishery resources survey are inadequate to meet the growing demand for large-scale and long-period surveys. The eDNA metabarcoding approach provides an effective and non-invasive monitoring revolution, and has been applied to identify fish diversities. This study conducted a comprehensive comparison of fish diversity in the East China Sea on a large scale both horizontally and vertically. The results showed a total of 81 fish species, which were classified into 20 orders, 44 families and 72 genera. Although no statistically significant difference in fish diversity was found amongst the horizontal groups (east-middle-west, south-middle-north, and shallow-middle-deep) and the various sampling layers (surface-middle-bottom), discernible trends were obtained in this study. Fish diversity results revealed the orders of east > middle > west, middle > north > south and deep > shallow > middle in horizontal groups. Additionally, surface water exhibited a higher level of fish diversity than other water layers. Some fish species were only detected at specific vertical depths. The diverse composition of fish species across different water layers can be attributed to their distinct ecological types. The overall findings suggest that an increase of sampling stations and mixed samples should be collected in deeper water bodies for comprehensive understanding of fish diversity. This study can also provide the fundamental data and experimental design reference for future studies and fishery management.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5893-0
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- Spatial Characteristics of the Plasma Spark Source Wavelet
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Abstract: Abstract Plasma spark sources are widely used in high-resolution seismic exploration. However, research on the excitation mechanism and propagation characteristics of plasma spark sources is very limited. In this study, we elaborated on the excitation process of corona discharge plasma spark source based on indoor experimental data. The electrode spacing has a direct impact on the movement of bubbles. As the spacing between bubbles decreases, they collapsed and fused, thereby suppressing the secondary pulse process. Based on the premise of linear arrangement and equal energy synchronous excitation, the motion equation of multiple bubbles under these conditions was derived, and a calculation method for the near-field wavelet model of plasma spark source was established. We simulated the source signals received in different directions and constructed a spatial wavelet face spectrum. Compared with traditional far-field wavelets, the spatial wavelet facial feature representation method provides a more comprehensive display of the variation characteristics and propagation properties of source wavelets in three-dimensional space. The spatial wavelet variation process of the plasma spark source was analyzed, and the source depth and the virtual reflection path are the main factors affecting the wavelet. The high-frequency properties of plasma electric spark source wavelets lead to their sensitivity to factors such as wave fluctuations, position changes, and environmental noise. Minor changes in collection parameters may result in significant changes in the recorded waveform and final data resolution. So, the facial feature method provides more effective technical support for wavelet evaluation.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5839-6
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- Illuminating Growth: How Light Spectra Influence Juvenile Steelhead Trout
(Oncorhynchus mykiss) Growth and Metabolism-
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Abstract: Abstract The diurnal variation in the sun’s altitude alters the red-to-blue light spectrum ratio under identical water layers. This study explores how juvenile steelhead trout (Oncorhynchus mykiss) (initial weight: 34.67 g ± 2.69 g) responds to these fluctuating light conditions, focusing on growth, daily activity levels, and energy budget. During 16 weeks, the experiment was conducted to examine six lighting scenarios: 12 h white light followed by 12 h darkness (12W); 12 h blue light followed by 12 h darkness (12B); 12 h red light followed by 12 h darkness (12R); 1.5 h blue light, 9 h red light, and again 1.5 h blue light followed by 12 h darkness (3B9R); 3 h blue light, 6 h red light, and again 3 h blue light followed by 12 h darkness (6B6R); and 12 h combined blue and red lights followed by 12 h darkness (T12BR). The findings reveal that the 3B9R lighting condition notably enhanced specific growth rate (SGR), feed conversion efficiency (FCE), and growth energy allocation, while diminishing daily activity levels in steelhead trout. Conversely, under the 6B6R condition, there was a significant reduction in SGR and FCE, indicating that growth was inhibited. Under the 12R condition, despite the high activity and respiratory energy loss, the trout exhibited improved SGR and FCE with reduced fecal energy loss. The study suggests that 3B9R and 12R lighting conditions might be beneficial in commercial steelhead trout farming, potentially lowering costs and boosting production. These results offer valuable insights for the application of supplementary lighting technology in salmon aquaculture.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5877-0
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- Experimental Analysis of Resistivity Logging Response of Marine Gas
Hydrate Reservoirs-
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Abstract: Abstract Natural gas hydrates are widely distributed in marine and permafrost environments. As a novel energy resource, accurately describing reservoir characteristics and assessing energy potential is crucial for its commercial development. Resistivity logging serves as a valuable approach for achieving these goals. Nevertheless, due to inadequate comprehension of the electrical conductivity mechanism in hydrate-bearing sediments, existing data processing models still encounter certain challenges. This study conducts both core-scale and pore-scale simulation experiments to examine the relationship between resistivity variations and the distribution of gas hydrate porosity. The results indicate that the characteristics of resistivity variation is associated with the gas hydrate formation process, and the gas hydrate saturation index, denoted as ‘n’, varies between 0 and 3 depending on different gas hydrate distribution patterns. As the saturation increases, gas hydrate distribution in pore spaces transitions from floating to contacting and cementing patterns. It is proposed that the aqueous pore tortuosity can be utilized to correct the saturation index ‘n’ in Archie’s equation. Based on the analysis of experimental data, a correction method for Archie’s equation is suggested, and its effectiveness in controlling relative error has been validated.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5746-x
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- Interpretable Machine Learning-Based Spring Algal Bloom Forecast Model for
the Coastal Waters of Zhejiang-
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Abstract: Abstract The 2016–2022 monitoring data from three ecological buoys in the Wenzhou coastal region of Zhejiang Province and the dataset European Centre for Medium-Range Weather Forecasts were examined to clarify the elaborate relationship between variations in ecological parameters during spring algal bloom incidents and the associated changes in temperature and wind fields in this study. A long short-term memory recurrent neural network was employed, and a predictive model for spring algal bloom in this region was developed. This model integrated various inputs, including temperature, wind speed, and other pertinent variables, and chlorophyll concentration served as the primary output indicator. The model training used chlorophyll concentration data, which were supplemented by reanalysis and forecast temperature and wind field data. The model demonstrated proficiency in forecasting next- day chlorophyll concentrations and assessing the likelihood of spring algal bloom occurrences using a defined chlorophyll concentration threshold. The historical validation from 2016 to 2019 corroborated the model’s accuracy with an 81.71% probability of correct prediction, which was further proven by its precise prediction of two spring algal bloom incidents in late April 2023 and early May 2023. An interpretable machine learning-based model for spring algal bloom prediction, displaying effective forecasting with limited data, was established through the detailed analysis of the spring algal bloom mechanism and the careful selection of input variables. The insights gained from this study offer valuable contributions to the development of early warning systems for spring algal bloom in the Wenzhou coastal area of Zhejiang Province.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5833-z
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- Spatial and Temporal Distribution of Metal Elements in the Rivers of
Northern Jiangsu Province-
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Abstract: Abstract The concentrations of V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Mo, Cd, and Pb were determined in Doulonggang River, Xinyanggang River, Huangshagang River, Sheyanghe River, Guangaizongqu River, and Linhonghe River at the North of Jiangsu Province in 2019. The annual average concentrations of V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Mo, Cd and Pb in the six rivers were 2.20, 1.22, 4.53, 21.9, 0.13, 2.79, 1.77, 4.00, 2.97, 3.87, 0.01, 0.19 µg L−1 respectively. The highest concentration of most trace metals were found in Guangaizongqu River and Linhonghe River, and the lowest concentration were found in Xinyanggang River and Huangshagang River. The principal component analysis (PCA) resulted of two factors together explained 91.2% of the variance with >1 initial eigenvalue, indicating that both natural and anthropogenic activities were contributing factors as the source of metal abundance in rivers of northern Jiangsu Province. The first major component represented the influence of anthropogenic activities, including industry and agriculture, with a contribution rate of 54.1%, affected Cr, Fe, Cu, Zn, Mo, Cd and Pb. The second (such as V, Mn, Co, Ni, As) was a mixed source, including the natural processes such as precipitation, erosion and weathering and anthropogenic action like industry and agriculture, with a contribution rate of 37.1%. Seasonal variations in trace metal concentrations were influenced by temperature, salinity, water discharge, and input of external pollutants. The highest concentrations were found in wet season and were strongly influenced by rainfall and seasonal industrial and agricultural activities.
PubDate: 2025-02-01
DOI: 10.1007/s11802-025-5824-0
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