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The “The Use of Lactobacillus in Forage Storage and Processing” Special Issue (SI) in Fermentation has brought together groundbreaking research and innovative methodologies in the realm of forage preservation [...]

The phytoplankton size structure exerts a significant influence on ecological processes and biogeochemical cycles. In this study, the interannual variations in remotely sensed phytoplankton size structure in the southern Tropical Indian Ocean (TIO) and the underlying physical mechanisms were investigated. Significant interannual fluctuations in phytoplankton size structure occur in the southeastern TIO and central southern TIO and are very sensitive to Indian Ocean Dipole (IOD) events. During positive IOD events, the southeast wind anomalies reinforce coastal upwelling off of Java and Sumatra, leading to a shift toward a larger phytoplankton structure in the southeastern TIO. The anomalous anticyclonic circulation deepened the thermocline and triggered the oceanic downwelling Rossby waves, resulting in a smaller phytoplankton structure in the southwestern TIO. During the decay phase of the strong positive IOD events, the sustained warming in the southwestern TIO induced basin-wide warming, thereby maintaining such an anomalous phytoplankton size structure into the following spring. The response of phytoplankton size structure and ocean dynamics displayed inverse patterns during the negative IOD events, with an anomalous larger phytoplankton structure in the central southern TIO. These findings enhance our understanding of phytoplankton responses to climate events, with serious implications for ecosystem changes in a warming climate.

To estimate the changes in the annual mean sea level (MSL) and extreme sea levels (ESLs), the largest collection of tide gauge records from 10 tidal stations along the northern coast of the South China Sea (SCS) were analyzed in this study. Here, all the tide gauge records had been homogenized by a two-step process involving the detection of inhomogeneities, that is, breakpoints caused by non-climatic changes and the application of the adjustment. The study’s conclusions, based on the homogenized tide gauge records, can be summarized as follows: The instrument change and station relocation are the main causes for the identified inhomogeneities. From 1989 to 2018, the sea level along the SCS was at an average rate of 4.0 mm per year, as measured by the homogenized tide gauges. The ESLs from the nine tidal stations rose notably with interannual fluctuations, except for the XSA station. Additionally, the ESLs exhibited substantial decadal variations. The ESLs rose along the northern coast of the SCS and were accelerated at most stations throughout the whole study period, especially after the 1980s. There were significant positive correlations between the ESL and the annual MSL at most tide gauges. The MSL’s changes, especially long-term changes, play an important role in the change in ESLs.

Annually, hundreds of individuals tragically lose their lives at sea due to shipwrecks or aircraft accidents. For search and rescue personnel, the task of locating the debris of a downed aircraft in the vastness of the ocean presents a formidable challenge. A primary task these teams face is determining the search area, which is a critical step in the rescue operation. The movement of aircraft wreckage on the ocean surface is extremely complex, influenced by the combined effects of surface winds, waves, and currents. Establishing an appropriate drift motion prediction model is instrumental in accurately determining the search area for the wreckage. This article initially conducts maritime drift observation experiments on wreckage, and based on the results of these experiments, analyzes the drift characteristics and patterns of the debris. Subsequently, employing a wealth of observational experimental data, three types of drift prediction models for the wreckage are established using the least squares method. These models include the AP98 model, the dynamics model, and an improved model. In conclusion, the effectiveness and accuracy of the three models is evaluated and analyzed using Monte Carlo techniques. The results indicate that the probability of positive crosswind leeway (CWL) is 47.4%, while the probability of negative crosswind leeway (CWL) is 52.6%. The jibing frequency is 7.7% per hour, and the maximum leeway divergence angle observed is 40.4 degrees. Among the three drift prediction models, the refined AP98 drift model demonstrates the highest forecasting precision. The findings of this study offer a more accurate drift prediction model for the search of an aircraft lost at sea. These results hold significant guiding importance for maritime search and rescue operations in the South China Sea.

The processes of ocean dynamics are complex near the Pearl River Estuary and are not clear due to a lack of abundant observations. The spatial characteristics of the spring sea surface currents in the adjacent waters of the Pearl River Estuary were analyzed using the current data observed by a three-station high-frequency surface wave radar system (HFSWRS). Compared with the two-station HFSWRS, the deviation of current velocity and direction observed by the three-station HFSWRS from the underway measurements decreased by 42.86% and 38.30%, respectively. The analyzed results show that the M2 tidal current is the dominant current among all the tidal constituents, followed by K1, with angles of inclination ranging from 130° to 150°. The tidal flow is dominated by northwest–southeast back-and-forth flow. In the southern part of the observed area, which is far from the coastline, the tidal current ellipses exhibit a circular pattern. The prevalent tidal current type in this region is irregularly semi-diurnal, and the shallow water constituents also have a significant effect. The tidal energy in the adjacent waters of the Pearl River Estuary is affected by potential energy flux and kinetic energy flux. As the water depth and currents velocity increase in the southeast direction, the tidal energy flux increases. In the nearshore zone, the direction of tidal energy flux varies along the coastline. The changes in the residual current within the observed area are correlated with the sea surface wind field. Based on the high-precision sea surface current observed by the three-station HFSWRS, the characteristics of the ocean dynamic processes near the Pearl River Estuary are analyzed comprehensively, which provides important reference and confidence for the application of the developing new radar observing network with about 10 radar stations near the Pearl River Estuary.

Tropical cyclones (TCs) pose a significant threat in terms of wind-induced damage and storm risk to the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. In this research, annual power dissipation index (PDI) and storm surge and wave destructive potential (SDP) index from June to November were used to estimate the damage caused by the TC events in the buffer zone of the GBA. The regime shifts in 1993 and 2013 were identified through the Bayesian changepoint detection in six TC datasets. The TC-induced damage during 1994–2012 (the low-damage period) was weaker than that in 1977–1993 and 2013–2020 (the high-damage periods). The intensity and size of stronger TCs are the dominant factors responsible for the interdecadal changes in the TC damage. This may be explained by the influences of sea surface temperature (SST), surface latent heat flux and mid-level relative humidity. During high-damage periods, TCs can extract more energy from the ocean, leading to increased TC intensity and larger size. Conversely, during low-damage periods, TCs undergo a decrease in energy intake, resulting in reduced TC power and smaller size. The variations in the SST are relative to the Luzon Strait transport. In addition, the reduction in TC translation speed is unfavorable for the development of TCs in low-damage periods. Further research suggested that mid-level steering flow affects the TC movement velocity. The results offer valuable insights into the variations in the TC-induced damage in the GBA.

Nearshore bathymetry plays an essential role in various applications, and satellite-derived bathymetry (SDB) presents a promising approach due to its extensive coverage and comprehensive bathymetric map production capabilities. Nevertheless, existing retrieval techniques, encompassing physics-based and pixel-based statistical methodologies such as support vector regression (SVR), band ratio, and Kriging regression, exhibit limitations stemming from the intricate water reflectance process and the under-exploitation of the spatial component inherent in SDB. To surmount these obstacles, we introduce employment of deep convolutional networks (DCNs) for SDB in this study. We assembled multiple scenes utilizing networks with varying scale emphasis and an assortment of satellite datasets characterized by distinct spatial and spectral resolutions. Our findings reveal that these deep learning models yield high-caliber bathymetry outcomes, with nonlinear normalization further mitigating residuals in shallow water regions and substantially enhancing retrieval performance. A comparative analysis with the prevalent SVR technique substantiates the efficacy of the proposed methodology.

Marine Science and technology are the basis for human beings to understand, develop and protect the ocean [...]

In recent decades, freak waves, characterized by their unusual high amplitude, sharp crest, and concentrated energy, have attracted researchers’ attention due to their potential threat to marine structures. Green-water loads caused by freak waves can be significant and may lead to local damage to the ship structures. Therefore, this paper focuses on the study of green-water loads and examines the structural responses of ship bow structures under the influence of the green-water loads caused by freak waves. Firstly, a three-dimensional numerical wave tank is established in which the superposition model is used to generate freak waves. Validations on the freak-wave generation, ship motion response and the wave loading are carried out to verify the present solvers. The simulation on the interaction between the freak wave and the ship are conducted to obtain the interaction process and green-water loads. Secondly, a finite element (FEM) model of the ship bow is built, on which the green-water loads are applied to calculate the structural responses. Finally, the displacement and stress of the deck and breakwater structures are analyzed. It is found that green water events caused by freak waves can generate enormous impact forces on the bow deck and breakwater, resulting in severe structural responses and even possible damage to the structures. The local strength of structures under freak waves needs to be considered in practical engineering applications.

A marine heatwave (MHW) can significantly harm marine ecosystems and fisheries. Based on a remotely sensed sea surface temperature (SST) product, this study investigated MHWs behaviors in the South China Sea (SCS) throughout the warm season (May to September) from 1982 to 2020. The distributions of the three MHW indices used in this study showed significant latitudinal variations: more frequent, longer, and more intense MHWs appear in the northern SCS, and less frequent, shorter, and weaker MHWs appear in the southern SCS. Using the empirical orthogonal function (EOF) method, we found that the first leading modes of the three MHW indices account for more than half of the total variance. The first leading modes reveal uniform anomalies throughout the SCS, with the maximum in the deep central portion and its surroundings. Their corresponding time series showed significant interdecadal variations, with a turning point around 2009. Since 2010, the SCS has seen an increase in the frequency, length, and severity of MHWs. The incidence of MHWs has been linked to the presence of stable near-surface anticyclonic anomalies, which reduced cloud cover and increased solar radiation. This abnormal pattern was usually accompanied by the intensification and westward shift of the western North Pacific subtropical high (WNPSH). The findings imply that MHWs in the SCS may be predictable on interannual and decadal scales.

East-Asia winter cooling and the associated atmospheric and oceanic influences were investigated based on the wintertime daily temperature and circulation fields during 1950–2020. Both the case study on the 2020/2021 cold surge and the large-sample clustering in the recent 71 winters extracted similar circulation signatures for East-Asia cooling, which are featured by the blocking-related anticyclonic circulation in North Eurasia, large-scale mid-to-high-latitude wave trains, decrease in the sea surface temperature (SST) in tropical Pacific, and the sea-ice cover (SIC) reduction in the Barents and Kara Seas (BKS). From the joint clustering of Eurasian circulation and temperature, two circulation modes that have a cooling effect on East Asia account for 41% of winter days. One of the two modes is characterized by the cyclonic circulation over Northeast Asia coupled with a southward-extending negative-phase Arctic Oscillation (AO−), whose cooling effect is mainly concentrated in central Siberia. The other cooling mode, featuring an anticyclonic circulation over the Urals and AO+ in middle-to-high latitudes, has a relatively stronger cooling effect on lower latitudes, including Mongolia and North China. In general, the occurrences of the mode with warming/cooling effect on East Asia show an overall downward/upward trend. The two cooling modes are significantly influenced by the La Niña-type SST anomaly and reduced SIC in BKS through large-scale wave trains, of which the tropical oceanic forcing mainly acts as a climatic background. Furthermore, the polar forcing is more tightly bound to internal atmospheric variability. Therefore, the tropical SST tends to exert impact over a seasonal scale, but the SIC influence is more significant below the intraseasonal scale; moreover, the synergy between the tropical and polar oceanic forcing can increase the East-Asia cooling days by 3–4% and cold extremes by 5%, mainly through enhancing the AO-related circulation mode.

In computer vision, pollutant detection is a highly concerning issue, and it has been widely used in the fields of pollutant identification, tracking, and precise positioning. In the ocean, oil tends to disperse into the water column as droplets under breaking waves, and it is called sunken and submerged oil. Aiming at the most difficult issue of identifying liquid submerged oil pollution, this paper proposes a method of synthesized data containing specific markers for oil detection. The Canny operator was used to remove the background of the liquid submerged oil. Then, affine transformation was applied to simulate the real situation of oil deformation. Linear mapping was presented by matrix multiplication, and translation was represented by vector addition. At last, bilinear interpolation was used to integrate the oil into the image of the laboratory pictures. In addition, this research randomly added interference information, so that the probability distribution of synthesized data was closer to the probability distribution of the real data. Then, this paper combined various methods to improve the accuracy of liquid oil detection, such as Feature Pyramid Networks, RoIAlign, difficult sample mining. Based on the above methods, 1838 images were synthesized in this paper and combined into a training set. The results show that the average accuracy of the oil detection is increased by 79.72%. The accuracy of the synthesized data method for labeled oil detection was 18.56% higher than that of oil detection without labeling. This research solves the difficulty of obtaining sunken and submerged oil images and the high cost of image annotation.

Revetment elements and protective facilities on a breakwater can effectively weaken the impact of waves. In order to resist storm surges, there is a plan to build a breakwater on the northern shore of Meizhou Bay in Putian City, China. To better design it, considering different environmental conditions, physical and numerical experiments were carried out to accurately study the effects of the breakwater and its auxiliary structures on wave propagation. In the experiments, the influence of the wave type, initial water depth, and the structure of the fence plate are considered. The wave run-up and dissipation, the wave overtopping volume, and the structure stability are analyzed. The results indicate that the breakwater can effectively resist the wave impact, reduce the wave run-up and overtopping, and protect the rear buildings. In addition, under the same still water depth and significant wave height, the amount of overtopped water under regular waves is larger than that under irregular waves. With the increase of the still water depth and significant wave height, the overtopped water increases, which means that when the storm surge occurs, damage on the breakwater under the high tide level is greater than that under the low tide level. Besides, the fence plate can effectively dissipate energy and reduce the overtopping volume by generating eddy current in the cavity. Considering the stability and the energy dissipation capacity of the fence plate, it is suggested that a gap ratio of 50% is reasonable.

Remote sensing building extraction is of great importance to many applications, such as urban planning and economic status assessment. Deep learning with deep network structures and back-propagation optimization can automatically learn features of targets in high-resolution remote sensing images. However, it is also obvious that the generalizability of deep networks is almost entirely dependent on the quality and quantity of the labels. Therefore, building extraction performances will be greatly affected if there is a large intra-class variation among samples of one class target. To solve the problem, a subdivision method for reducing intra-class differences is proposed to enhance semantic segmentation. We proposed that backgrounds and targets be separately generated by two orthogonal generative adversarial networks (O-GAN). The two O-GANs are connected by adding the new loss function to their discriminators. To better extract building features, drawing on the idea of fine-grained image classification, feature vectors for a target are obtained through an intermediate convolution layer of O-GAN with selective convolutional descriptor aggregation (SCDA). Subsequently, feature vectors are clustered into new, different subdivisions to train semantic segmentation networks. In the prediction stages, the subdivisions will be merged into one class. Experiments were conducted with remote sensing images of the Tibet area, where there are both tall buildings and herdsmen’s tents. The results indicate that, compared with direct semantic segmentation, the proposed subdivision method can make an improvement on accuracy of about 4%. Besides, statistics and visualizing building features validated the rationality of features and subdivisions.

Originating in the grapes, monomeric anthocyanins in young red wines contribute the majority of color and the supposed beneficial health effects related to their consumption, and as such they are recognized as one of the most important groups of phenolic metabolites in red wines. In recent years, our increasing knowledge of the chemical complexity of the monomeric anthocyanins, their stability, together with the phenomena such as self-association and copigmentation that can stabilize and enhance their color has helped to explain their color representation in red wine making and aging. A series of new enological practices were developed to improve the anthocyanin extraction, as well as their color expression and maintenance. This paper summarizes the most recent advances in the studies of the monomeric anthocyanins in red wines, emphasizing their origin, occurrence, color enhancing effects, their degradation and the effect of various enological practices on them.

Originating in the grapes, anthocyanins and their derivatives are the crucial pigments responsible for the red wine color. During wine maturation and aging, the concentration of monomeric anthocyanins declines constantly, while numerous more complex and stable anthocyanin derived pigments are formed, mainly including pyranoanthocyanins, polymeric anthocyanins produced from condensation between anthocyanin and/or flavan-3-ols directly or mediated by aldehydes. Correspondingly, their structural modifications result in a characteristic variation of color, from purple-red color in young red wines to brick-red hue of the aged. Because of the extreme complexity of chemical compounds involved, many investigations have been made using model solutions of know composition rather than wine. Thus, there is a large amount of research still required to obtain an overall perspective of the anthocyanin composition and its change with time in red wines. Future findings may well greatly revise our current interpretation of the color in red wines. This paper summarizes the most recent advances in the studies of the anthocyanins derived pigments in red wines, as well as their color evolution.

Anthocyanins, synthesized via the flavonoid pathway, are a class of crucial phenolic compounds which are fundamentally responsible for the red color of grapes and wines. As the most important natural colorants in grapes and their products, anthocyanins are also widely studied for their numerous beneficial effects on human health. In recent years, the biosynthetic pathway of anthocyanins in grapes has been thoroughly investigated. Their intracellular transportation and accumulation have also been further clarified. Additionally, the genetic mechanism regulating their biosynthesis and the phytohormone influences on them are better understood. Furthermore, due to their importance in the quality of wine grapes, the effects of the environmental factors and viticulture practices on anthocyanin accumulation are being investigated increasingly. The present paper summarizes both the basic information and the most recent advances in the study of the anthocyanin biosynthesis in red grapes, emphasizing their gene structure, the transcriptional factors and the diverse exterior regulation factors.

Shallow water depth measurements using multispectral images are crucial for marine surveying and mapping. At present, relevant studies either depend on the use of other auxiliary data (such as field water depths or water column data) or contain too many unknown variables, thus making these studies suitable only for images that contain enough visible wavebands. To solve this problem, a Quasi-Analytical Algorithm (QAA) approach is proposed in this paper for estimating the water depths around Weizhou Island by developing a QAA to estimate the diffuse attenuation coefficients and simplifying the parameterization of the bathymetric model. The approach contains an initialization sub-approach and a novel global adjustment sub-approach. It is not only independent of other auxiliary data but also greatly reduces the number of unknowns. Experimental results finally demonstrated that the Root Mean Square Errors (RMSEs) were 1.01 m and 0.77 m for the ZY-3 image and the WorldView-3 (WV-3) image, respectively, so the approach is competitive to other QAA bathymetric methods. Besides, the global adjustment sub-approach was also seen to be superior to common smoothing filters: if the Signal-to-Noise Ratio (SNR) is as low as 42, i.e., ZY-3, it can smooth the water depths and improve the accuracies, otherwise can avoid the over-smoothing of water depths.

The oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), is a notable agricultural pest that undergoes pupation in the soil. Mortality risk from predation and parasitism decreases as the depth of the pupal location increases from the ground surface, with a one-centimetre increase in depth causing a significant change. Soil properties, such as moisture and hardness, influence pupation depth, but the effect of temperature has not been fully tested. This laboratory study examined whether a biologically important variation in pupation depth (e.g., one centimetre) is caused by naturally experienced temperature variations (20 to 35 °C) in B. dorsalis . The temperature-pupation depth relationship revealed a unimodal pattern, with the deepest pupation occurring at intermediate temperature levels and shallower pupation at the two extreme temperature ranges. Strong quantitative effects were observed, with the highest mean pupation depth of 40.8 mm at 27.5 °C and the lowest mean pupation depth of 15 mm at 35 °C. The observed quantitative effect suggests that temperature can strongly affect pupal mortality from predators and parasitoids by influencing pupation depth. Future studies that reveal the ability of biological control agents to forage underground for pupae at different temperatures are awaited, as this is key information for evaluating the effectiveness of these agents.

Background : Pompe disease is a rare metabolic myopathy caused by the lack or deficiency of the lysosomal acid alpha-glucosidase, resulting in skeletal muscle weakness and cardiomyopathy. The disease varies by onset age and genetic mutations and is categorized into infantile-onset and late-onset Pompe disease. Respiratory muscle weakness may persist regardless enzyme replacement therapy. This systemic review and meta-analysis aim to assess the effect of respiratory muscle training (RMT) on respiratory muscle strength, functional endurance, and pulmonary function in patient with Pompe disease. Methods : PubMed, EMBASE, and Cochrane databases were searched up until Aug 2024. Studies examining the therapeutic effects of RMT in patients with Pompe disease were included. Outcome measures included the change in maximal inspiratory pressure (MIP), maximal expiratory pressure (MEP), six-minute walking test (6MWT), pulmonary function before after RMT, quality of life and adverse events. Results : The meta-analysis consisted of 5 single-arm studies, including 31 patients in total. Regarding inspiratory muscle strength, RMT has significantly improving MIP (8.71 cmH 2 O; 95% CI, 6.23-11.19, p < 0.001) and MEP (12.15 cmH 2 O; 95% CI, 10.55-13.74, p < 0.001) in both types of Pompe disease. However, no significant change regarding 6MWT. No serious adverse events were reported. Conclusions : Our meta-analysis revealed that RMT may increase inspiratory muscle and expiratory muscle strength, but may not have an effect on 6MWT in patients with Pompe disease. RMT has potential to be integrated into the cardioplulmonary rehabilitation for patients with Pompe disease. Further large randomized controlled trials are needed to verify the efficacy and safety of RMT in patients with Pompe disease., Competing Interests: The authors declare no conflicts of interest.