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In recent years, noticeable subsidence depressions have occurred along the coastal zone of the Yellow River Delta. In some coastal areas, the average annual subsidence varies from tens of millimeters to hundreds of millimeters. Although some studies have discovered a significant land subsidence funnel in the coastal zone of the Yellow River Delta, it has rarely been reported in recent years. Using Sentinel-1A/1B images from the last five years and permanent scatterers interferometric synthetic aperture radar technology, we found a typical subsidence bowl in the northeastern part of the delta, with a cumulative settlement of nearly 1 m over five years. In addition, we used the approach of soil mechanics to simulate the settlement of confined brine layers with different thicknesses under drainage conditions. We found that the 15 m thick confined aquifer can produce 1 m of settlement for every 15% decrease in water content. The simulation results explain the large settlement of the brine industrial area. This study can provide guidance for brine mining in the future. If we continue to overexploit underground brine, there will be more severe land subsidence in the delta in the future. [ABSTRACT FROM AUTHOR]

Barley is one of the world's oldest cereal crops forming an important component of many traditional diets. Barley is rich in a variety of bioactive phytochemicals with potentially health-promoting effects. However, its beneficial nutritional attributes are not being fully realized because of the limited number of foods it is currently utilized in. It is therefore crucial for the food industry to produce novel barley-based foods that are healthy and cater to customers' tastes. This article reviews the nutritional and functional characteristics of barley, with an emphasis on its ability to improve glucose/lipid metabolism. Then, recent trends in barley product development are discussed. Finally, current limitations and future research directions in glucolipid modulation mechanisms and barley bioprocessing are discussed. [ABSTRACT FROM AUTHOR]

A rapid colloidal gold immunochromatography assay (GICA) for the detection of pefloxacin (PEF) was established and optimized. The anti-PEF monoclonal antibody (mAb) was used to target PEF as a colloidal gold-mAb conjugate. The mAb belonged to the IgG2b subtype, lambda light chain, the affinity constant (Ka) was 5.21 × 109 L·mol−1, and its half maximal inhibitory concentration (IC50) was 0.23 ng·mL−1. No obvious cross-reactivity (CR) was observed with other common fluoroquinolone antibiotics, including ciprofloxacin (CIP), norfloxacin (NOR), lomefloxacin (LOM) and ofloxacin (OFL). The visual limit of detection (vLOD) of the optimized GICA was 2 ng·g−1 under the conventional pretreatment method, and the assay was completed in 15 min. Liquid chromatography tandem-mass spectrometry (LC–MS/MS) was employed to confirm the performance of the strip. In addition, a novel pretreatment was established and compared with conventional pretreatment. Without the removal of organic solvents, the novel pretreatment method reduced the sample pretreatment time (more than 10 min). The vLOD of the optimized GICA was also 2 ng·g−1 when applying the novel pretreatment method. In conclusion, the proposed PEF-GICA could detect samples containing PEF rapidly and accurately, and the novel pretreatment method saved the time of sample pretreatment and improved the efficiency of detection. [ABSTRACT FROM AUTHOR]

Sea ice type is one of the most sensitive variables in Arctic sea ice monitoring, and it is important for the retrieval of ice thickness. In this study, we analyzed various waveform features that characterize the echo waveform shape and Sigma0 (i.e., backscatter coefficient) of CryoSat-2 synthetic aperture radar altimeter data over different sea ice types. Arctic and Antarctic Research Institute operational ice charts were input as reference. An object-based random forest (ORF) classification method is proposed with overall classification accuracy of 90.1%. Accuracy of 92.7% was achieved for first-year ice (FYI), which is the domain ice type in the Arctic. Accuracy of 76.7% was achieved at the border of FYI and multiyear ice (MYI), which is better than current state-of-the-art methods. Accuracy of 83.8% was achieved for MYI. Results showed the overall accuracy of the ORF method was increased by ∼8% in comparison with other methods, and the classification accuracy at the border of FYI and MYI was increased by ∼10.5%. Nevertheless, ORF classification performance might be influenced by the selected waveform features, snow loading, and the ability to distinguish sea ice from leads. [ABSTRACT FROM AUTHOR]

The atmospheric water vapour is an important indicator of the climate state and evolution, and also the key parameter affecting the hydrological cycle, atmospheric convection, and the weather. This study validated the accuracy of surface pressure and temperature data interpolated from European Centre for Medium-Range Weather Forecasts (ECMWF) Interim ReAnalysis (ERA-Interim) and ECMWF 5th ReAnalysis (ERA5) datasets, and evaluated the performance of the interpolation meteorological data for precipitable water vapour (PWV) retrieval using the measured meteorological data and Global Positioning System (GPS) data of the year 2014 obtained from 25 stations of the Chinese Coastal GPS Observation Network. We then analysed the temporal and spatial distribution of water vapour in the coastal regions of China using a 3-year GPS PWV time series calculated with the interpolated reanalysis meteorological data at 25 stations from 2014 to 2016. Evaluation of the reanalysis meteorological data results showed that the accuracies of the interpolated pressure and temperature data from ERA5 were slightly superior than those from ERA-Interim. The root-mean-square errors (RMSEs) of the surface temperature and pressure interpolated from two reanalysis datasets were less than 2.4 K and 1.6 hPa, respectively. Data based on GPS PWV products that used interpolated parameters were very close to those of meteorological observations, with biases within ±0.4 mm and RMSEs below 0.5 mm in most areas; these data also strongly agreed with radiosonde observations. However, the interpolated meteorological data from reanalysis datasets could not reflect the true change during typhoon events, which could not be used in GPS PWV retrieval. The analysis of the temporal and spatial distribution showed that the distribution of water vapour was mainly affected by latitude, land-sea distribution, and water vapour advection. The variations in water vapour were mainly seasonal with the highest PWV occurring in the summer and the lowest always occurring in the winter. Significant diurnal variations of water vapour varied with season and latitude, with an amplitude of about 0.9–3.5 mm; the peak value occurred in the afternoon or early morning, and was affected by surface evaporation, large-scale land–sea breeze circulation, and valley-wind circulation. [ABSTRACT FROM AUTHOR]

In this study, to meet the need for the accurate prediction of sea level anomaly (SLA), a hybrid model is proposed. In this model, empirical mode decomposition is combined with singular spectrum analysis and least-squares extrapolation to predict satellite-derived SLA. Each intrinsic mode function series of an empirical mode decomposition is decomposed and reconstructed using singular spectrum analysis. The reconstructed components and the residual series are predicted using least-squares extrapolation. This hybrid model was used for satellite-derived SLAs that were obtained using multi-mission along-track satellite altimetry data from September 1992 to January 2018, and the prediction errors for 3 years lead times were analysed. The observations and predictions of the principal components for annual or interannual periods correlated well, and the proposed hybrid model effectively predicted the SLAs. For the 3 years lead time predictions, the mean absolute error and root-mean-square error were 1.03 and 1.32 cm, respectively, which were less than those reported for existing methods. [ABSTRACT FROM AUTHOR]

We have previously reported an aqueous extract of fermented barley with Lactobacillus plantarum dy-1 (LFBE) has more efficient anti-obesity effect compared with that of Saccharomyces cerevisiae. To further explore associated effects of LFBE on body weight and body fat distribution, and lipid profiles related metabolic outcomes, serum metabolites were analysed using LC-MS-MS and partial least-squares-discriminant analysis (PLS-DA). Obese and lean groups were clearly discriminated from each other on PLS-DA score plot and major metabolites contributing to the discrimination were assigned as lipid metabolites (fatty acids), lipid metabolism intermediates (choline, betaine, carnitine and butyryl-carnitine), amino acids and citric acid. A high-fat diet increased lipid metabolites and decreased lipid metabolism intermediates, indicating that abnormal lipid metabolism induced by a high-fat diet resulted in fat accumulation via decreased β-oxidation. But LFBE can inhibit fat accumulation by reducing lipid metabolites and increasing lipid metabolism intermediates. Furthermore, the level changes of these metabolites can be used to assess the risk of obesity and the therapeutic effect of obesity management. [ABSTRACT FROM AUTHOR]

Island shoreline mapping based on field measurements by collecting visually discernible features is costly and even unrealistic to be implemented in practice because of the nonuniqueness, fuzziness, and ambiguity of shoreline features. The MHHW (the mean higher high water) shoreline, i.e., the intersection of the coastal profile with the MHHW, is recommended to be chosen as a significant shoreline indicator of an island. An approach for mapping the MHHW shoreline using the aerial/satellite stereo images is proposed. In the proposed procedure, first, the height difference between the instantaneous shoreline and the MHHW shoreline is calculated by the ocean tide model; then the orthometric/normal height of the instantaneous shoreline is determined from the stereo images; last, the instantaneous shoreline is used as an intermediate for determination of the height of the MHHW shoreline. The proposed procedure is applied to the MiaoZiHu Island located in the East China Sea. Preliminary experimental result shows that in ideal cases, the horizontal positional accuracy of the extracted shoreline can reach 0.2 m from aerial images of 0.1 m resolution. [ABSTRACT FROM AUTHOR]

We provide explicit solutions of certain forward-backward stochastic differential equations (FBSDEs) with quadratic growth. These particular FBSDEs are associated with quadratic term structure models of interest rates and characterize the zero-coupon bond price. The results of this paper are naturally related to similar results on affine term structure models of Hyndman (Math. Financ. Econ. 2(2):107–128, 2009) due to the relationship between quadratic functionals of Gaussian processes and linear functionals of affine processes. Similar to the affine case a sufficient condition for the explicit solutions to hold is the solvability in a fixed interval of Riccati-type ordinary differential equations. However, in contrast to the affine case, these Riccati equations are easily associated with those occurring in linear-quadratic control problems. We also consider quadratic models for a risky asset price and characterize the futures price and forward price of the asset in terms of similar FBSDEs. An example is considered, using an approach based on stochastic flows that is related to the FBSDE approach, to further emphasize the parallels between the affine and quadratic models. An appendix discusses solvability and explicit solutions of the Riccati equations. [ABSTRACT FROM PUBLISHER]

The multi-beam echo sounder system can not only obtain high-precision seabed bathymetry data, but also obtain high-resolution seabed backscatter strength data. A number of studies have applied acoustic remote sensing method to classify seabed sediment type with multi-beam backscatter strength data, and obtained better classification results than the traditional sediment sampling method. However, these studies mainly focus on the single type sediment classification or seabed mixed sediment classification using single beam data, not multi-beam echo sounder data. Based on backscatter strength data by a high-frequency (300 kHz) Simrad EM3000 multi-beam echo sounder and seabed sediment sampling data of Jiaozhou Bay in Qingdao, China, we establish the relation model between seabed backscatter strength and sediment type characteristics after data processing and corrections. The purpose of data processing is to diminish or weaken the influence of local bottom slope and near nadir reflection on backscatter strength data. Processed backscatter strength data through corrections and compensations can better characterize the features of the seabed sediments. Applying the back propagation neural network method based on genetic algorithm, we present a fast and accurate seabed classification method in this paper which could identify not just a single type of sediment-like rock, sand but also mixed types of sediment like sand gravel, clayey silt and sand-silt-clay. [ABSTRACT FROM PUBLISHER]

In this study, the self-organizing map (SOM), which is an unsupervised clustering algorithm, and a supervised proportional learning vector quantization (PLVQ), are employed to develop a combined method of seafloor classification using multibeam sonar backscatter data. The PLVQ is a generalized learning vector quantization based on the proportional learning law (PLL). The proposed method was evaluated in an area where there are four types of sediments. The results show that the performance of the proposed method is better than the SOM and a statistical classification method. [ABSTRACT FROM AUTHOR]

AbstractIn the past decade, the synthetic aperture radar interferometry (InSAR) technique has been extensively employed in deltas, making it possible to obtain more subsidence signals. However, the spatiotemporal nonlinearity of land subsidence often results in inaccurate estimations. Based on 72 Sentinel-1A images captured from 2016 to 2021 and the time-series persistent scatterer-interferometric SAR (PS-InSAR) method, we comprehensively analyze the temporal and spatial dynamics of recent land subsidence in the Yellow River Delta (YRD). The findings suggest a notable spatial shift in the subsidence funnel area within this delta region over the past 6 years (2016–2021), with gradual westward movement from the salt fields in the northeast to those in the central north. Additionally, with 2020 as the demarcation point, there was a notable change in magnitude, initially exhibiting acceleration at −333 mm/yr, followed by deceleration at −231 mm/yr and culminating in renewed acceleration at −413 mm/yr. The subsidence characteristics may be attributed to changes in the underground brine reserves, leading to consolidation of the confined aquifer. Furthermore, the ground subsidence trend suddenly slowed at the end of 2019, which we speculate is related to the significant reduction in human activities caused by COVID-19 prevention and control measures. [ABSTRACT FROM AUTHOR]