Search

The pressure dependence of the Sb level is achieved by using the double-band anticrossing model to fit the experimental pressure dependence of the band gap energy of dilute nitride and antimony GaNxSbyAs1−x−y alloy. It is found that the pressure coefficient for the Sb level is much larger than that for the N level. The difference of the pressure dependence between the Sb level and the N level is due to two factors. One is the different locations of the Sb level and the N level. The other is that the atomic size mismatch and electronegativity difference between As and Sb atoms are much smaller than those between N and As atoms. In addition, it is found that the N-Γ conduction band's minimum coupling interaction is the major factor to affect the pressure dependence of the band gap energy of GaNxSbyAs1−x−y. [ABSTRACT FROM AUTHOR]

The impurity-host interaction and the impurity-impurity interaction exist in the Sb-rich GaBixSb1−x alloy. It is found that the effect of impurity-impurity on the band gap energy can be neglected. The impurity-host interaction not only depends on the Bi content, but also on the content of the host material. In order to describe the band gap energy of the Sb-rich GaBixSb1−x, the virtual crystal approximation for conduction band minimum (CBM) and the modified valence band anticrossing model for valence band maximum (VBM) are applied. It is also found that when the Bi content is about 0.259, the band gap energy of GaBixSb1−x becomes 0 eV. In addition, it is found that the Г CBM depending on Bi content is much stronger than that of the Г VBM. It is relative to two factors. One is that the conduction band offset between GaSb and GaBi is much larger than the valence band offset. The other is that the energy difference between the Bi level and the Г VBM of GaSb is very large. The large energy difference usually leads to a weak coupling interaction between the Bi level and the Г VBM of GaSb, thus resulting in weak composition dependence of the Г VBM in the Sb-rich range. [ABSTRACT FROM AUTHOR]

In this study, a novel non-targeted strategy based on high-performance liquid chromatography with ultraviolet detection (HPLC-UV) and fluorescence detection (HPLC-FLD) was first proposed for the classification of Rosa roxburghii Tratt (RRT) from eight geographical origins in Guizhou, China. HPLC-UV and HPLC-FLD fingerprints were simultaneously recorded by an HPLC-UV-FLD instrument. Then, fingerprint data were processed with low-level data fusion and variable reduction strategies before chemometric analysis. Based on different signal types and data orders of the resulting fingerprints, four strategies for RRT classification were proposed and compared. In the first three strategies, three supervised classification methods including partial least squares-discriminant analysis (PLS-DA), principal component analysis-linear discriminant analysis (PCA-LDA) and random forest (RF) were used to build discriminant models, using different kinds of first-order fingerprints (HPLC-UV, HPLC-FLD and HPLC-UV-FLD), respectively. Moreover, N -way partial least squares-discriminant analysis (NPLS-DA) discriminant model was established based on the second-order fingerprints acquired by HPLC-FLD. By comparison, the best result was obtained by PLS-DA based on first-order HPLC-UV-FLD fused fingerprints, the correct classification rates (CCRs) of cross-validation, training set and test set were 98.8%, 100% and 96.9%, respectively. Non-targeted chromatographic fingerprints were used to solve the problem of RRT classification for the first time. • Non-targeted HPLC-UV-FLD for the classification of Rosa roxburghii Tratt fruits (RRTs). • Multiple fingerprints and chemometric strategies to improve analytical performance. • Similar classification capabilities of HPLC-UV in comparison to HPLC-FLD. • Excellent results through first-order HPLC-UV-FLD fingerprints and PLS-DA. • Non-targeted chromatographic fingerprints for RRT classification for the first time. [ABSTRACT FROM AUTHOR]

In Brief In this study, we employed biochemical, pathological, 16S rRNA amplicon sequencing and non-targeted metabolomic analysis based on UPLC-Q-Exactive Orbitrap/MS analysis to evaluate the effects of natto on biochemical parameters, body weight, gut microflora and fecal metabonomics in high-fat diet (HFD)-induced hyperlipidemia mice. Our study suggests that after 8 weeks of natto treatment, it can effectively prevent HFD-induced hyperlipidemia mainly by regulating the gut microflora community (such as Lactobacillus , Faecalibaculum and Oscillibacter) and their related metabolites (such as O-propanoylcarnitine, butyryl-L-carnitine and L -tryptophan), which provides new information for the further development of natto as a functional food. [Display omitted] • Natto shows good hyperlipidemia prevention activity in high-fat diet (HFD)-fed mice. • Using 16S rRNA amplicon sequencing and non-targeted metabonomics to analyze gut microbiota and its metabolites. • Natto treatment regulates the gut microbial community and their related metabolites in hyperlipidemic mice. Natto has long been considered as a medical-food dual-use product with a hypolipidemic effect. Our study showed that natto was effective in reducing the levels of total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), and increasing the level of high-density lipoprotein cholesterol (HDL-C) in the serum of hyperlipidemic mice. Metabolism analysis showed that natto could improve the levels of amino acid metabolites, reduce the contents of acylcarnitines, and reverse the levels of purine alkaloids, mainly involving the tricarboxylic acid (TCA) cycle and metabolism of amino acids. Moreover, natto increased beneficial gut microbiota (e.g., Lactobacillus , Faecalibaculum and Oscillibacter) and reduced pathogenic gut microbiota (e.g., Alistipes and Prevotellaceae-UCG-003). In conclusion, our findings suggest that natto-mediated changes in the gut microbiota and its related metabolites can support the prevention of high-fat diet (HFD)-induced hyperlipidemia, laying the theoretical foundation for the continued development of natto as a functional food. [ABSTRACT FROM AUTHOR]

A rapid and sensitive analytical strategy combining high-performance liquid chromatography-diode array detection (HPLC-DAD) and chemometrics methods was developed for the determination of multi-class food additives in a variety of beverage samples. Different kinds of beverages, which contain diverse unknown interferences, can be directly injected into a chromatographic system after a simple dilution or pretreatment step, and the data were recorded in a short time under a simple gradient elution mode. Although peaks overlapped and changeable interferences existed in the dimension of the chromatographic and spectral in real beverages, all food additives were accurately resolved by using a second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm, and accurate chromatographic profiles, spectral profiles, and concentration profiles were also obtained. Limits of detection for all additives were between 1.40 and 165.1 ng mL−1, while limits of quantitation ranged from 4.20 to 500.2 ng mL−1. The spiked recoveries were in the range of 87.3-103% (except amaranth) with RSDs less than 10.2%. Compared with the results obtained by classic HPLC method, our proposed method was more accurate. In all, the proposed method is fast, sensitive, and universal and could be used as a reliable tool to determine food additives and quality monitoring in different complex beverages. [ABSTRACT FROM AUTHOR]

Microplastics and nanoplastics in aquatic systems have become a global concern because of their persistence and adverse consequences to ecosystems and potentially human health. Though wastewater treatment plants (WWTPs) are considered a potential source of microplastics in the environment, the role of extracellular polymeric substances (EPS) of activated sludge on the fate of nanoplastics is not clear. In this study, the role of EPS in the influence of polystyrene nanoparticles (PS-NPs) on the endogenous respiration of activated sludge was investigated for the first time. The results showed that the acute inhibition of activated sludge by PS-NPs was enhanced with increasing PS-NPs concentration. X-ray photoelectron spectroscopy (XPS) results indicate that the functional groups involved in the interactions between PS-NPs and EPS were carbonyl and amide groups and the side chains of lipids or amino acids. Furthermore, the Fourier transform infrared (FTIR) spectroscopy results show that the protein secondary structures in EPS were changed by PS-NPs and lead to the bioflocculation of activated sludge, which provides a better understanding on the fate of nanoplastics in WWTPs. [ABSTRACT FROM AUTHOR]

A model was constructed to describe the band gap reduction of the O-rich ZnSexO1−x. The results show that the band gap reduction resulting from the upward movement of the valence band maximum (VBM) is larger than that resulting from the downward movement of the conduction band minimum (CBM), which suggests that the Se content has a larger influence on the VBM than it does on the CBM. It was also discovered that the physical mechanism for the band evolution in the O-rich range is quite different from that in the Se-rich range. The band gap reduction for the O-rich ZnSexO1−x is mainly due to two factors: the impurity-impurity interaction, and the intraband coupling within the valence band and the conduction band. [ABSTRACT FROM AUTHOR]

Least squares reverse-time migration (LSRTM) is an inversion method that removes artificial images and preserves the amplitude of reflectivity sections. LSRTM has been used in reservoir exploration and processing of 4D seismic data. LSRTM is, however, a computationally costly and memory-intensive method. In this study, LSRTM in the pseudodepth domain was combined with the conjugate gradient method to reduce the computational cost while maintaining precision. The velocity field in the depth domain was transformed to the velocity field in the pseudodepth domain; thus, the total number of vertical sampling points was reduced and oversampling was avoided. Synthetic and field data were used to validate the proposed method. LSRTM in the pseudodepth domain in conjunction with the conjugate gradient method shows potential in treating field data. [ABSTRACT FROM AUTHOR]