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Satellite remote sensing of sea surface chlorophyll products sometimes yields a significant amount of sporadic missing data due to various variables, such as weather conditions and operational failures of satellite sensors. The limited nature of satellite observation data impedes the utilization of satellite data in the domain of marine research. Hence, it is highly important to investigate techniques for reconstructing satellite remote sensing data to obtain spatially and temporally uninterrupted and comprehensive data within the desired area. This approach will expand the potential applications of remote sensing data and enhance the efficiency of data usage. To address this series of problems, based on the demand for research on the ecological effects of multiscale dynamic processes in the South China Sea, this paper combines the advantages of the optimal interpolation (OI) method and SwinUnet and successfully develops a deep-learning model based on the expected variance in data anomalies, called OI-SwinUnet. The OI-SwinUnet method was used to reconstruct the MODIS chlorophyll- a concentration products of the South China Sea from 2013 to 2017. When comparing the performances of the data-interpolating empirical orthogonal function (DINEOF), OI, and Unet approaches, it is evident that the OI-SwinUnet algorithm outperforms the other algorithms in terms of reconstruction. We conduct a reconstruction experiment using different artificial missing patterns to assess the resilience of OI-SwinUnet. Ultimately, the reconstructed dataset was utilized to examine the seasonal variations and geographical distribution of chlorophyll- a concentrations in various regions of the South China Sea. Additionally, the impact of the plume front on the dispersion of phytoplankton in upwelling areas was assessed. The potential use of reconstructed products to investigate the process by which individual mesoscale eddies affect sea surface chlorophyll is also examined. The reconstructed daily chlorophyll- a dataset is freely accessible at 10.5281/zenodo.10478524 (Ye et al., 2024). [ABSTRACT FROM AUTHOR]

Transcription factors, as the convergence points of multiple signaling pathways in eukaryotic cells, are closely involved in disease development. Pax‐8, an important transcription factor belonging to the Pax family, exerts a crucial influence on the regulation of gene expression required for both physiological conditions and pathological processes. Pax‐8 contributes to the pathogenesis of many human diseases, ranging from cardiovascular disease to many cancers, and therefore, it can be imagined that Pax‐8 holds great therapeutic potential. In this review, we summarize the structure, distribution, function, and regulatory mechanisms of Pax‐8 to provide a new research direction for Pax‐8. [ABSTRACT FROM AUTHOR]

Purpose: The research objective of this study is to use finite element analysis to investigate the impact of anterior cruciate ligament (ACL) injury on medial unicompartmental knee arthroplasty (UKA) and explore whether patients with ACL injuries can undergo UKA. Methods: Based on the morphology of the ACL, models of ACL with diameters ranging from 1 to 10mm are created. Finite element models of UKA include ACL absence and ACLs with different diameters. After creating a complete finite element model and validating it, four different types of loads are applied to the knee joint. Statistical analysis is conducted to assess the stress variations in the knee joint structure. Results: A total of 11 finite element models of UKA were established. Regarding the stress on the ACL, as the diameter of the ACL increased, when a vertical load of 750N was applied to the femur, combined with an anterior tibial load of 105N, the stress on the ACL increased from 2.61 MPa to 4.62 MPa, representing a 77.05% increase. Regarding the equivalent stress on the polyethylene gasket, a notable high stress change was observed. The stress on the gasket remained between 12.68 MPa and 14.33 MPa in all models. the stress on the gasket demonstrated a decreasing trend. The equivalent stress in the lateral meniscus and lateral femoral cartilage decreases, reducing from the maximum stress of 4.71 MPa to 2.61 MPa, with a mean value of 3.73 MPa. This represents a reduction of 44.72%, and the statistical significance is (P < 0.05). However, under the other three loads, there was no significant statistical significance (P > 0.05). Conclusion: This study suggests that the integrity of the ACL plays a protective role in performing medial UKA. However, this protective effect is limited when performing medial UKA. When the knee joint only has varying degrees of ACL injury, even ACL rupture, and the remaining structures of the knee joint are intact with anterior-posterior stability in the knee joint, it should not be considered a contraindication for medial UKA. [ABSTRACT FROM AUTHOR]

Background: Coronary heart disease (CHD) has become a worldwide public health problem. Genetic factors are considered important risk factors for CHD. The aim of this study was to explore the correlation between CYP4A22 gene polymorphism and CHD susceptibility in the Chinese Han population. Methods: We used SNPStats online software to complete the association analysis among 962 volunteers. False-positive report probability analysis was used to confirm whether a positive result is noteworthy. Haploview software and SNPStats were used for haplotype analysis and linkage disequilibrium. Multi-factor dimensionality reduction was applied to evaluate the interaction between candidate SNPs. Results: In overall and some stratified analyses (male, age ≤ 60 years or CHD patients complicated with hypertension), CYP4A22-rs12564525 (overall, OR = 0.83, p-value is 0.042) and CYP4A22-rs2056900 (overall, OR = 1.22, p-value is 0.032) were associated with the risk of CHD. CYP4A22-4926581 was associated with increased CHD risk only in some stratified analyses. FPRP indicated that all positive results in our study are noteworthy findings. In addition, MDR showed that the single-locus model composed of rs2056900 is the best model for predicting susceptibility to CHD. Conclusion: There are significant associations between susceptibility to CHD and CYP4A22 rs12564525, and rs2056900. [ABSTRACT FROM AUTHOR]

The Great Whirl (GW) and the Socotra Gyre (SoG), two prominent anticyclonic eddies in the western Arabian Sea, exhibit strong dynamic interactions. This study reports a case of the merging of the GW and the SoG recorded by Argo floats in September 2019. Combined with satellite observations and a state‐of‐the‐art ocean reanalysis, we show that the merging process was first detected at the subsurface layer (∼150 m depth) rather than the surface. As the original water inside the GW is cooler than the SoG, the merging created a baroclinic structure between the eddies. The density gradients associated with the baroclinic structure drive strong subsurface geostrophic currents following the thermal wind relationship, leading to the fast merging at 100–200 m depth. Energy analysis shows that the predominant energy source for the merged eddy was the barotropic and baroclinic instability. The dissipative processes caused the rapid decay of the merged eddy. The merging process induced submesoscale activities and promoted ocean vertical exchanges south of Socotra Island. Plain Language Summary: The Great Whirl (GW) and the Socotra Gyre (SoG) are two large clockwise eddies in the western Arabian Sea. Ocean observations caught the merging process of these two eddies in September 2019. The Argo floats detected the process first at the subsurface layer. Ocean reanalysis reveals that the water inside the GW was cooler than the SoG, which led to the density difference that enhanced the subsurface flow. The subsurface flow transported the warm and salty water from the SoG faster than the surface in the interior of the eddy. During the merging process, the smaller‐scale motions led to increased surface chlorophyll concentrations in the region, with replenished nutrients and dissolved oxygen. Key Points: The merging process of the Great Whirl (GW) and the Socotra Gyre (SoG) was faster at the subsurface, resulting from density gradientsThe barotropic and baroclinic instability provided the predominant energy for the mergingThe merging process stimulated submesoscale activities and promoted ocean vertical exchanges [ABSTRACT FROM AUTHOR]

The wave spectrometer operated by the China–France Oceanography Satellite (CFOSAT) can provide global ocean wave observation data. Although a lot of work on calibration and verification has been carried out in the open oceans dominated by swells, the quality of the data in the relatively enclosed sea area with complex terrain still lacks sufficient examination. The objective of this study is to assess the performance of the significant wave height data of the CFOSAT in the South China Sea (SCS), a unique sea area characterized by semi-enclosed basin and multi-reef terrain, and to recognize the environmental factors affecting the data quality. Compared against the long-term observations from five mooring or buoy sites, we find that the data is well performed in the relatively open and deep areas of the SCS, with an average correlation coefficient as high as 0.87, and a low average root-mean-square error of 0.47 m. However, the combined effects of complex topography, monsoons, and swell proportion variation will affect the performance of data. In the southern deep areas, the waves may be affected by a large number of dotted reefs, leading to wave deformations and energy dissipation in different seasons. In the northern nearshore areas, waves tend to be sheltered by the land or distorted by the shallow topography effects. These processes make it difficult for the swell to fully develop as in the open oceans. The low proportion of swell is a disadvantage for the CFOSAT to correctly observe the wave data and may lead to possible errors. Our results emphasize the importance of more verification when applying the CFOSAT data in certain local seas, and the necessity to adjust the algorithm of inverting wave spectra according to specific environmental factors. [ABSTRACT FROM AUTHOR]

An attention U-Net was proposed to reconstruct the missing chlorophyll-a concentration (Cchla) data. The U-Net is a lightweight full convolution neural network architecture consisting of an enccoder-decoder (i.e., down-sampling and up-sampling). The attention gates (AGs) were integrated into the U-Net. Training the U-Net with AGs could implicitly teach it to suppress irrelevant areas and highlight the salient features in the missing data areas, which would increase the network sensitivity and reconstruction accuracy. The neural network uses the satellite-derived Cchla anomalies and its variance as the input, and the reconstructed fields along with their variances as outputs. The trained network was applied to long-term daily MODIS/Aqua Cchla products in the Pearl River estuary (PRE) and adjacent continental shelf area. The model performance was evaluated by using an independent test dataset from both satellite-derived and in-situ measurements. The results showed that the proposed neural network not only had good performance in the reconstruction of valid pixels, but also provided a more reasonable reconstruction compared to the standard U-Net without AGs. This study provided a feasible method for the reconstruction task in the field of ocean color, which should be helpful in producing a creditable dataset to study the ecological effects of extreme weather conditions such as typhoons on the upper ocean in the PRE waters. Based on the reconstructed Cchla products, the footprints of the typhoons were studied. An increase in surface Cchla near the typhoons' track and a decrease in estuary were found. The composite results illustrated that the Cchla increases occurred for almost the entire area within a radius of 100 km. The time series analysis showed that the Cchla peak appeared on the fifth day after the typhoon's passage. [ABSTRACT FROM AUTHOR]

Diurnal variability of the CO2 partial pressure (pCO2) at the sea surface (pCO2sea) and its impact on air‐sea CO2 flux estimations are currently poorly understood. In this work, diurnal variations in pCO2sea were examined in the Bay of Bengal (BoB) based on 3‐hourly observations collected at the BoB Ocean Acidification moored buoy between November 2013 and November 2018 by a moored autonomous pCO2 system. Significant mean diurnal pCO2sea cycles and a mean diurnal amplitude of 11 ± 9 μatm were observed based on 1215 complete diurnal cycles. One‐dimensional mass budget model calculations suggest that temperature was responsible for these mean diurnal variations in pCO2sea and that these variations were intensified by biological activity. The effects of air‐sea gas fluxes and mixing on the mean diurnal pCO2sea variability were very low. A weak annual net source of 12.1 mmol m−2 year−1 was estimated at this site. The sampling frequency greatly impacted the annual air‐sea CO2 flux estimations. Compared to the 3‐hr sampling frequency, random daily sampling resulted in a bias of ±7.7 mmol m−2 year−1 or 64%, and regular daily sampling resulted in a maximum bias of 400%. Factorial experiments showed that wind speed had the largest impact on the air‐sea CO2 flux estimations, followed by pCO2sea and atmospheric pCO2 (pCO2air). These findings indicate the importance of obtaining continuous pCO2 measurements to accurately estimate air‐sea CO2 flux; additionally, pCO2 and wind speed measurements should be obtained at frequencies higher than 6 hr. Plain Language Summary: Approximately 25% of anthropogenic CO2 emissions have been absorbed in the oceans through air‐sea CO2 fluxes (FCO2) over the last decade. The direction and magnitude of FCO2 are determined by the difference between the CO2 partial pressure (pCO2) at the sea surface (pCO2sea) and that in the atmosphere (pCO2air). However, our understanding of diurnal pCO2sea variations and their drivers is limited, and how these drivers impact FCO2 estimations is unclear. In the present study, significant mean diurnal pCO2sea variations were observed using multiyear 3‐hourly observations obtained in the Bay of Bengal. A one‐dimensional mass budget model suggests that temperature was the largest contributor to the mean diurnal pCO2sea variability, leading to a maximum pCO2sea value recorded at 15:17 (local time, hereinafter) and a minimum at 06:17. Biological activity was the second most important contributor to mean diurnal pCO2sea changes. The air‐sea fluxes and mixing had negligible effects on pCO2sea variations. Diurnal variability greatly impacted the FCO2 estimations when the sampling frequency was reduced to fewer than four times per day. The relative deviations induced by the sampling frequency were larger in the open ocean than in coastal waters. Key Points: A mean diurnal amplitude of 11 ± 9 μatm for sea surface pCO2 was observed using 4 years of 3‐h Bay of Bengal observationsThe mean diurnal cycle of sea surface pCO2 was primarily controlled by temperature, and its variation was intensified by biologyThe sampling frequency greatly impacts annual air‐sea CO2 flux estimations in the open ocean areas more than in the coastal waters [ABSTRACT FROM AUTHOR]

The oceanic Kármán vortex street is an important hydrokinetic phenomenon caused by the unsteady separation of sea currents in the wake of an obstacle. This study quantitatively analyzed the characteristics of the small-scale vortex street of Didicas Island in the Luzon Strait based on multimission satellite data. Five groups of vortex streets were captured, and each group was observed by two satellite images within one hour. Based on the displacement and change in the vortex street within one hour, we found that the formation time of a single vortex is longer than 40 min. The vortex propagation speed behind the island is approximately 0.98 m s−1 (ranging from 0.66–1.22 m s−1). The incoming velocity was calculated using the vortex propagation speed and the aspect ratio based on a vortex propagation model, which ranges from 0.72 to 1.47 m s−1 The incoming speed is 1.6–2.3 times the geostrophic speed extracted from AVISO data, implying that the contribution of non-geostrophic flow to the total flow field is comparable to that of geostrophic flow in this region. [ABSTRACT FROM AUTHOR]

The China‐France ocean satellite (CFOSAT) has obtained synchronized observations of sea winds and sea waves for the first time in the world, providing accurate data support for the study of swells. In this paper, the accuracy of key parameters and the wave spectrum of CFOSAT surface waves investigation and monitoring (SWIM) L2 data are analyzed and evaluated using a spatial‐temporal matching criterion. The accuracies of the significant wave height (SWH), spectrum peak period (Tp) and dominant azimuth (Azi) are 0.76 m, 2.89 s and −24.02°, respectively, in the coastal area of the South China Sea (SCS) and 0.30 m, 0.97 s and 13.02° in the offshore area of the SCS. Calculated based on CFOSAT SWIM data, the annual average SWH of mixed waves in the SCS is 1.47 m, and 80% of them are between 0.5 and 3 m. There are high value areas in the central, northeastern and southwestern parts of the SCS. The average annual SWH of swells is 0.93 m, and 99% of swells are less than 2 m. A high swell SWH also exists in the central part of the SCS. Plain Language Summary: Swells are an important marine resource. Due to their long propagation distance and fast propagation speed, they can effectively forecast storm surge. They also have large energy and good stability, which are conducive to acquisition and conversion, and they have become a new method for offshore power generation. China‐France ocean satellite provides a convenient means to observe waves and to verify the accuracy of wave parameters, which is an important step for wave detection. The South China Sea, with its vast sea area and abundant swell energy reserves, is an ideal area for offshore power generation. Understanding the distribution of swell energy in the South China Sea (SCS) provides an opportunity to explore a sustainable and reliable renewable energy source. The SCS is also important and significant to the development and utilization of swell energy and for the site selection of offshore power stations. Key Points: Precision valuation of surface waves investigation and monitoring L2 data such as significant wave height (SWH), spectrum peak period (Tp), dominant azimuth (Azi) were carried out and it was determined that the data were stableThe annual average SWH in the South China Sea is 1.47 m and 80% of them are between 0.5 and 3 mWind‐swell separation was carried out, and the distribution of swell SWH shows a high value in the central part of the South China Sea [ABSTRACT FROM AUTHOR]

Coronary artery disease (CAD) is a common comorbidity of gastroesophageal reflux disease. Since the distal esophagus and heart share a common afferent vagal supply, the delivery of radiofrequency in the distal esophagus can stimulate the coronary artery and induce acute myocardial infarction in a patient with CAD. Acute myocardial infarction may occur after esophageal radiofrequency (RF) therapy on patients with gastroesophageal reflux disease (GERD). Coronary artery disease and related risk factors should be reasonably excluded before treating GERD with esophageal RF therapy (Stretta procedure). [ABSTRACT FROM AUTHOR]

The southwest monsoon between June and October induces upwelling and offshore cold‐water transport in the western South China Sea (SCS). A seasonal collocated chlorophyll bloom also occurs, resulting in a productivity increase in the oligotrophic SCS basin. To accurately quantify productivity transported toward the open ocean, it is necessary to determine whether the transport is continuous or intermittent (intraseasonal oscillation). However, intraseasonal chlorophyll oscillations during summer have not been investigated. The influences of upwelling and an eddy dipole on intraseasonal chlorophyll oscillation also remain unclear. Merged daily chlorophyll data obtained from a multisatellite ocean color product are used to investigate intraseasonal chlorophyll oscillations. Our results indicate that summer chlorophyll development is characterized by an intraseasonal double‐bloom pattern in July‐August and September‐October in 11 out of 20 years (1998–2017). The time interval between the two blooms varies between 23 and 45 days. The timing of the first bloom is correlated with upwelling (R2 = 0.70), but the secondary bloom is not (R2 = 0.26). During the second chlorophyll bloom period, high chlorophyll is observed in the interaction region of an eddy dipole, which is locally generated rather than transported from nearshore areas. A new index is proposed based on finite‐size Lyapunov exponents and the orientations of the associated eigenvectors to represent frontogenetic processes. The index coincides not only spatially with the chlorophyll bloom but also temporally with the chlorophyll variation during the second bloom period (R2 = 0.73). Plain Language Summary: Wind‐driven coastal upwelling occurs in the western South China Sea in summer during the southwest monsoon. Cold water near the coast extends offshore and develops into a cold eastward jet. The upwelling can transport deep nutrient‐rich water to the surface and support phytoplankton growth, generating chlorophyll blooms on a seasonal time scale. We find that due to the synergistic influences of upwelling and an eddy dipole, this seasonal chlorophyll bloom fluctuates on intraseasonal time scales. There are two chlorophyll blooms during summer in 11 out of 20 years (1998–2017). Upwelling contributes to the first chlorophyll bloom, and submesoscale frontogenetic processes associated with an eddy dipole are responsible for the second chlorophyll bloom. Key Points: An intraseasonal double peak of chlorophyll occurs in the western South China Sea in summer in 11 out of 20 years (1998–2017)Upwelling and offshore transport contribute to the first chlorophyll bloomSubmesoscale frontogenetic processes associated with an eddy dipole are responsible for the second chlorophyll bloom [ABSTRACT FROM AUTHOR]

Accurate estimation of the near-surface chlorophyll-a (Chl-a) concentration in turbid estuaries via remote sensing is an ongoing challenge. Recently, with the successful launch of the third satellite of the China Ocean Colour Satellite Series, HY-1 C, equipped with the Coastal Zone Imager (CZI) with a 3-day revisit period and 50-m resolution in four bands, this study constructed a Chl-a inversion model via symbolic regression (SR) in the Pearl River Estuary (PRE) considering 60 in situ samples to explore the current ocean colour monitoring potential of the CZI. Compared to five state-of-the-art algorithms, the SR model attained a lower mean absolute percentage error (MAPE, 35.51%), mean absolute error (MAE, 1.56) and root-mean-square error (RMSE, 0.24). Additionally, the Chl-a spatial distributions determined with the SR model also better coincided with those determined with synchronous satellite products. The above results indicate that the SR model performed better than the five state-of-the-art models and could be effectively applied to turbid PRE waters. This research may provide a reference regarding the practicality and feasibility of the CZI in water environment monitoring in coastal and estuarial waters at a high temporal-spatial resolution. [ABSTRACT FROM AUTHOR]

The duration of a single satellite deployment is insufficient to detect long-term trends in phytoplankton biomass. By integrating data from different platforms, we quantified the phytoplankton trends in the South China Sea (SCS) from the early-to-mid 1980s to the present. We focused on winter data because the sea surface temperature (SST) in winter has been increasing over the past three decades. We included data from three different eras: (1) the Coastal Zone Colour Scanner (CZCS) period (1979–1983), (2) the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) period (1998–2002), and (3) the Moderate Resolution Imaging Spectroradiometer (MODIS) period (2010–2014). There was a decline in phytoplankton (approximately 0.15 mg m−3) over the entire SCS from the CZCS period to the SeaWiFS period. The largest reduction (over 0.3 mg m−3) occurred in the northern and western SCS. After the SeaWiFS period, the phytoplankton increased by approximately 0.05 mg m−3. The largest increase was observed to the west of Luzon Strait, extending towards the east coast of Hainan Island. The fluctuations in phytoplankton from the early-to-mid 1980s to the present were consistent with the variation in the wind field rather than with the continued increase in SST. The wind speed decreased from the CZCS period to the SeaWiFS period and increased from the SeaWiFS period to the MODIS period. Moreover, the nutrient variations induced by the mixed-layer depth also contributed to the fluctuations in phytoplankton. [ABSTRACT FROM AUTHOR]

The Bermuda Testbed Mooring (BTM) and Bay of Bengal Ocean Acidification (BOBOA) mooring measurements were used to identify changes in the partial pressure of CO2 at the sea surface (pCO2sea) and air-sea CO2 fluxes (FCO2) associated with passage of two tropical cyclones (TCs), Florence and Hudhud. TC Florence passed about 165 km off the BTM mooring site with strong wind speeds of 24.8 m s–1 and translation speed of 7.23 m s–1. TC Hudhud passed about 178 km off the BOBOA mooring site with wind speeds of 14.0 m s–1 and translation speed of 2.58 m s–1. The present study examined the effect of temperature, salinity, dissolved inorganic carbon (DIC), total alkalinity (TA), air-sea CO2 flux, and phytoplankton chlorophyll a change on pCO2sea as a response to TCs. Enhanced mixed layer depths were observed due to TCs-induced vertical mixing at both mooring sites. Decreased pCO2sea (–15.16±5.60 μatm) at the BTM mooring site and enhanced pCO2sea (14.81±7.03 μatm) at the BOBOA mooring site were observed after the passage of Florence and Hudhud, respectively. Both DIC and TA are strongly correlated with salinity in the upper layer of the isothermal layer depth (ILD). Strong (weak) vertical gradient in salinity is accompanied by strong (weak) vertical gradients in DIC and TA. Strong vertical salinity gradient in the upper layer of the ILD (0.031 psu m–1), that supply much salinity, dissolved inorganic carbon and total alkalinity from the thermocline was the cause of the increased pCO2sea in the BOBOA mooring water. Weak vertical salinity gradient in the upper layer of the ILD (0.003 psu m–1) was responsible for decreasing pCO2sea in the BTM mooring water. The results of this study showed that the vertical salinity gradient in the upper layer of the ILD is a good indicator of the pCO2sea variation after the passages of TCs. [ABSTRACT FROM AUTHOR]

An algorithm of the red-peak envelop area (PEA) near 700 nm was evaluated using in situ data during nine cruises in the Pearl River estuary and compared with other algorithms using the reflectance peak (RP) near 700 nm, including the fluorescence line height (FLH), maximum chlorophyll index (MCI), and MCI2 algorithms. Of all algorithms, the PEA algorithm presented the most accurate performance [ $R^{2}= 0.74$ , root-mean-square error RMSE = 0.12] and provided a more rational spatial distribution of phytoplankton blooms when both Sentinel 3 Ocean and Land Color Instrument (OLCI) and Hyperion data were used because the PEA integrates information from both the moving peak and the asymmetric curve on each side of the peak due to the high correlation relationship ($R^{2}= 0.7$) of chlorophyll and the ratio of the peak area between the left and right halves. Moreover, compared with other algorithms, the PEA algorithm developed using the Hyperion (higher spectral resolution) and OLCI band settings presented similar retrieval accuracies. These results demonstrated that the PEA algorithm is less dependent on the band settings, and the spectral band settings of OLCI from 650 to 750 nm are reasonable and can be used to detect phytoplankton blooms if the PEA algorithm is applied. The OLCI PEA algorithm was applied to determine the variations in phytoplankton blooms under the influences of strong precipitation events. The most obvious increases in chlorophyll concentration (from 20 to 30 mg $\text{m}^{-3}$) were observed in the middle river channel upstream of the Pearl River estuary after strong precipitation events. [ABSTRACT FROM AUTHOR]

To obtain dual active near-infrared (NIR) nanomaterial with strong absorption and emission properties, we report herein a novel precursor reactivity differentiation strategy, i.e., utilizing 1-octadecene (ODE)-Se having the ability to react with Ag salts much stronger and faster than ODE-thiourea, for single-step preparation of Ag2Se@Ag2S nanocrystals (NCs). With this strategy, we were able to synthesize high-quality Ag2Se@Ag2S NCs with both excellent NIR absorption and emission properties. Particularly, these nanocrystals possess a rather strong and sharp excitonic absorption peak with a full width at half maximum less than 70 nm and a maximum fluorescence quantum yield as high as 24.3%. Their appealing optical properties and structural features were founded to be highly dependent on the Se to S precursor ratio in the reaction solutions, owing to such a ratio exerting a direct influence on the core sizes and shell thicknesses of the as-formed NCs. Taking advantage of their remarkable NIR absorption properties, self-powered photoelectrochemical-type photodetectors based on the as-prepared Ag2Se@Ag2S NCs were successfully fabricated, which demonstrate a much better response performance and photostability in comparison with those based on Ag2Se NCs. [ABSTRACT FROM AUTHOR]

Abstract: Phytoplankton blooms induced by the interaction between typhoons and oceanic mesoscale eddies in the South China Sea were investigated using the composite averaging method based on cyclone‐centric coordinates from nine years (2002–2010) of satellite observations. Increases in the chlorophyll (Chl) concentration following the passage of a typhoon differed greatly among the pre‐existing cyclonic eddy (PCE), pre‐existing anticyclonic eddy (PACE) and non‐eddy (NE) ocean conditions (with Chl increases of approximately 35%, 6% and 12%, respectively), but the magnitude of sea surface temperature (SST) cooling was similar under the three conditions (∼1°C). Under the same level of SST decreases, the greater increase in the Chl concentration in the PCE condition was attributed to the longer persistence of both SST cooling and nutrient input caused by the typhoon‐strengthened PCE (associated with upwelling), which stopped the re‐warming of the typhoon‐induced cold water. [ABSTRACT FROM AUTHOR]

Ocean remote sensing is the only technique capable of quantitatively detecting long-term and global variability of marine primary production. However, because the spectral curves of light derived from satellite sensors have a limited capability to identify the physiological state of phytoplankton, the direct estimation of photoadaptive variables, such as daily maximum carbon fixation in a water column (P{opt^{b}}), from the spectra of satellite sensors is difficult. This difficulty results in most of the errors in ocean color-based primary productivity models. In this paper, algorithms were developed to estimate $P_{{{\rm opt}}}^{{\rm b}}$ using statistical models known as support vector machines (SVM). The algorithms were run using three different inputs: sea surface temperature (SST); both SST and sea surface chlorophyll a concentration; and SST, sea surface chlorophyll a concentration and photosynthetically active radiation (PAR) together. The results indicate that the algorithm using the three inputs (SST, sea surface chlorophyll a concentration, and PAR) had the best performance. The algorithms based on the SVM had better results than the general statistical regression method. Using the new $P_{{{\rm opt}}}^{{\rm b}}$ algorithm, the performances of the previous primary production models, including the vertically generalized production model and the statistical model developed in our earlier research, were improved. In contrast to the previous algorithm, the global primary productivity estimated using the new $P_{{{\rm opt}}}^{{\rm b}}$ algorithm showed regional changes, with higher primary productivity in most open ocean areas and lower primary productivity in coastal waters. [ABSTRACT FROM PUBLISHER]

The Finite Time Lyapunov Exponent technique is a highly effective way to visualize and analyze flow fields. Its ridges are referred to as Lagrangian Coherent Structures which reveal the transport barriers of fluid systems, or their hidden skeletons. This allows us to investigate the complex mesoscale and submesoscale ocean processes on a Lagrangian view. In this article, we use the Lagrangian technique to investigate one chlorophyll bloom event in the northeastern South China Sea and discuss the impact of horizontal transport on the distribution of surface chlorophyll. Our results demonstrate that horizontal transport barriers uncovered by Lagrangian Coherent Structures can shape the vortex and filament in a simple and distinct way. [ABSTRACT FROM PUBLISHER]

The flux and seasonality of planktonic foraminifera were studied through a time-series sediment trap deployed in the Xisha Trough, South China Sea from June 2009 to August 2011. The general flux pattern for planktonic foraminifera showed high values during the winter half-year/season (from late September/October to February) and low flux during the rest of the year. This flux pattern contrasts with the bimodal pattern in the central and southern South China Sea, which shows two high flux peaks corresponding to the prevailing summer and winter monsoon periods, respectively. Apparent interannual flux differences, which may be related to the climate change from an El Niño year to a La Niña year, were observed. Monsoonal driven seasonality is most prominent inPulleniatina obliquiloculata, Neogloboquadrina dutertreiandGlobigerina bulloides, with over 80% of their species-specific fluxes (93% forG. bulloides) occurring from late September/October to February.Globigerinoides sacculiferandGlobigerinoides rubershow similar seasonality, generally following the trend of the total flux of planktonic foraminifer.G. bulloidesmay have the potential to be developed as a winter proxy-species.Globigerinoides conglobatusmostly appears in June to August and can be developed as a summer proxy-species. [ABSTRACT FROM PUBLISHER]

The wave data measured by CFOSAT (China France Oceanography Satellite) have been validated mainly based on numerical model outputs and altimetry products on a global scale. It is still necessary to further calibrate the data for specific regions, e.g., the southern South China Sea. This study analyses the practicability of calibrating the dominant wavelength by using artificial neural networks and mean impact value analysis based on two sets of buoy data with a 2-year observation period and contemporaneous ERA5 reanalysis data. The artificial neural network modeling experiments are repeated 1000 times randomly by Monte Carlo methods to avoid sampling uncertainty. Both experimental results based on the random sampling method and chronological sampling method are performed. Independent buoy observations are used to validate the calibration model. The results show that although there are obvious differences between the CFOSAT wavelength data and the field observations, the parameters observed by the satellite itself can effectively calibrate the data. In addition to the wavelength, nadir significant wave height, nadir wind speed, and the distance between the calibration point and satellite observation point are the most important parameters for the calibration. Accurate data from other sources, such as ERA5, would be helpful to further improve the calibration results. The variable contributing the most to the calibration effect is the mean wave period, which virtually provides relatively accurate wavelength information for the calibration network. These results verify the possibility of synchronous self-calibration for the CFOSAT wavelength data and provide a reference for the further calibration of the satellite products in other regions. [ABSTRACT FROM AUTHOR]

The abundance of phytoplankton is generally estimated by measuring the chlorophyll-a concentration (Cchla), which is an important factor in photosynthesis and can be used to analyze the density and biomass of phytoplankton in the ecosystem. The band-ratio-based empirical or semi-analytical algorithms are operationally applied to retrieve Cchla in global oceans, which generally experience difficulties from the diversity of optical properties and the complexity of the radiative transfer equations in analytical analyses, respectively. With an attempt to develop an accurate Cchla retrieval model for the optically complex coastal and estuarine waters, this study aimed to explore the deep learning (DL) methods in satellite retrieval of Cchla. A two-stage convolutional neural network (CNN), named Cchla-Net, was proposed, which utilized the spectral information of remote sensing reflectances at MODIS/Aqua's visible bands. In the first-stage phase, the Cchla-Net was pretrained by a set of remote sensing patches, in which the Cchla was generated from an existing model (OC3M). The pretrained results were than used as the initial values to refine the network with the synthetic oversampled in-situ dataset in the second-stage training phase. Using in-situ samples for training with the new initial values has a higher probability to reach the global optimum. The quantitative analyses showed that the two-stage training was more likely to achieve a global optimum in the optimization than the one-stage training. Matchups of the in-situ Cchla measurements were used to evaluate the retrieval models. Results showed that the proposed Cchla-Net produced obvious better performance than the empirical and semi-analytical algorithms, implying the DL method was more effective for optically complex waters with extremely high Cchla. This study provided an applicable method for remote sensing retrieval of Cchla, which should be helpful for studying the spatial distribution and temporal variability in the productive Pearl River estuary (PRE) waters. [ABSTRACT FROM AUTHOR]

The China-France Oceanography SATellite (CFOSAT), launched on 29 October 2018, is a joint mission developed by China and France. To evaluate the CFOSAT wind product, L2B swath data with a spatial resolution of 25 × 25 km were compared with in situ measurements between December 2018 and December 2020. The in situ measurements were collected from 217 buoys. All buoy winds were adjusted to 10 m height using a simple logarithmic correction method. The temporal and spatial separations between the CFOSAT and in situ measurements were restricted to less than 30 min and 0.25°. The results indicate that the CFOSAT wind retrievals agree well with the buoy measurements. The root mean square errors (RMSEs) of wind vectors were 1.39 m s−1 and 34.32° and negligible biases were found. In the near shore under rain-free conditions, the RMSEs were enhanced to 1.42 m s−1 and 33.43°. Similarly, the RMSEs were reduced to 1.16 m s−1 and 30.41° offshore after the rain effect was removed. After winds less than 4 m s−1 were removed, the RMSE of wind directions was reduced to 19.69°. The effects of significant wave height, air-sea temperature difference, sea surface temperature, atmospheric pressure and ocean surface current on the wind residuals were assessed. The performance of wind retrievals under the passage of tropical cyclones was evaluated. The evaluation results show that the CFOSAT wind retrievals satisfy the accuracy requirements of scientific research, although some improvements are needed to enhance the performance. [ABSTRACT FROM AUTHOR]

Hangzhou Bay (HZB) is the largest macro-tidal bay in China, where suspended sediment concentrations are significantly modulated by tidal oscillations. This makes it an ideal area for the study of the impact of tide on temporal–spatial variation in suspended sediment. The GaoFen-4 (GF-4) satellite is the first high-resolution geosynchronous orbiting satellite of China. It exhibits the unique advantages of capturing minute variations and finer details of total suspended matter (TSM) due to the enhancement in spatial resolution (50 m) and observation time interval (20 s). In this study, TSM concentration of the HZB was retrieved based on the GF-4 satellite. The spatial distribution and minute variations of TSM concentration under the ebb tide from 7:30 to 7:40 a.m. on 28 August 2017, were analyzed. The results showed that the average TSM concentration inside HZB was (371.8 ± 1.8) mg/L. There was a linearly increasing trend of TSM concentration at ebb tide, with an increment of (3.96 ± 0.31) (mg/L)/min, and a more significant increase was observed in the high TSM areas. This increase in TSM concentration was associated with both the bottom topography and tide processes. The tidal potential energy generated by the tidal range and the strong shear stress generated by the high current velocity both led to the re-suspension of the sedimentary particles, which affected the variation of TSM concentration. In addition, the influence of bottom topography changed the intensity of re-suspension and also affected the distribution of TSM concentration in HZB. [ABSTRACT FROM AUTHOR]

The Hong Kong-Zhuhai-Macau Bridge crosses the Pearl River Estuary and is the largest bridge and tunnel project in the world. During the construction period of this project, the excessive suspended sediment was found in the construction region. The suspended sediment generated by sand excavation in the upstream was assumed to have a significant impact on the suspended sediment in the tunnel region. In this study, we assessed the impact of upstream sand excavation on the suspended sediment in the Hong Kong-Zhuhai-Macau Bridge construction area using Landsat OLI, ETM+, and TM data. Regional suspended sediment algorithms were developed for Landsat using a symbolic regression method based on data from in situ measurements in the study area from 2003 to 2014. A band shift was conducted on the remote sensing reflectance data from Landsat ETM+ and OLI to produce a time series of the suspended sediment concentrations that was internally consistent with that of the Landsat TM data. The suspended sediment distribution was extracted and used to compare under two different conditions, with and without sand excavation. The correlations of the time series of the suspended sediment concentrations in different regions in the surrounding waters, including the correlations between the construction regions and the sand excavation regions, were calculated. Our results indicated that the sand excavation north of the Pearl River Estuary had a limited impact on the surface suspended sediment concentrations in the Hong Kong-Zhuhai-Macau Bridge tunnel area. [ABSTRACT FROM AUTHOR]

Water transparency, measured with Secchi disk depth (SDD), is an important parameter for describing the optical properties of a water body. This study evaluates variations of SDD and related impact factors in the Bohai and Yellow Seas (BYS). Based on a new mechanistic model proposed by Lee et al. (2015) applied to MODIS remote sensing reflectance data, climatological SDD variation from 2003 to 2019 was estimated. The annual mean images showed an increasing trend from the coastal zone to the deep ocean. Lower values were found in the Bohai Sea (BHS), while higher values observed in the center of the southern Yellow Sea (SYS). Additionally, the entire sea has shown a decreasing temporal tend, with the variation rate lowest in the BHS at 0.003 m y−1, and highest in the SYS at 0.015 m y−1. However, the weak increasing trend that appeared since 2017 suggests that water quality seems to have improved. Further, it displayed seasonal patterns of low in winter and spring and high in summer and autumn. The empirical orthogonal function (EOF) analysis of SDD variations over the BYS, shows that the first SDD EOF mode is the highest, strongly correlated with total suspended matter. With the high correlation coefficients of chromophoric dissolved organic matter, it illustrates that the SDD variation is mainly dominated by the optical components in the seawater, although correlation with chlorophyll-a is the weakest. The second and third EOF modes show that photosynthetically available radiation, sea surface temperature, sea surface salinity, and wind speed are the main covariates that cause SDD changes. Water transparency evaluation on a long-term scale is essential for water quality monitoring and marine ecosystem protection. [ABSTRACT FROM AUTHOR]