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Based on the advantages of large yield and rich nutrients content of typical processing waste in the brewing industry, the characteristics of nutrient content, current status of research on resource utilization and major problems faced by three typical processing waste in brewing industry, soy sauce residue, distillers grains and vinegar residue, were reviewed as follows. The soy sauce residue, which are rich in soybean crude protein, crude fiber and other nutrients, are generally used to generate high-protein feed, organic fertilizer, soybean isoflavones and other products, but it is necessary to overcome the technical problems caused by the high salt content. The distillers grains, rich in crude fiber, crude protein, amino acids and other nutrients, and its resource utilization mainly focuses on the fields of biological biogas, liquid fertilizers and health food, etc., while its high content of ethanol can easily result in secondary fermentation, causing acidification and corruption. Compared with soy sauce residue and distillers grains, vinegar residue has fewer types and lower content of nutrients, which are mainly used for the development of animal feed, fertilizer and other organic products. However, its high acidity tends to inhibit microbial fermentation activity. In the future, in-depth research could be carried out in the breeding of excellent strains with high tolerant capacity, efficient separation and purification technology, microbial high-density fermentation technology coupled with advanced membrane filtration technology, etc., so as to further improve the resource conversion efficiency and high-value utilization of the typical processing waste of Chinas brewing industry. [ABSTRACT FROM AUTHOR]

Cross-view data correlation analysis is a typical learning paradigm in machine learning and pattern recognition. To associate data from different views, many approaches to correlation learning have been proposed, among which canonical correlation analysis (CCA) is a representative. When data is associated with label information, CCA can be extended to a supervised version by embedding the supervision information. Although most variants of CCA have achieved good performance, nearly all of their objective functions are nonconvex, implying that their optimal solutions are difficult to obtain. More seriously, the discriminative scatters and manifold structures are not exploited simultaneously. To overcome these shortcomings, in this paper we construct a Discriminative Correlation Learning with Manifold Preservation, DCLMP for short, in which, in addition to the within-view supervision information, discriminative knowledge as well as spatial structural information are exploited to benefit subsequent decision making. To pursue a closed-form solution, we remodel the objective of DCLMP from the Euclidean space to a geodesic space and obtain a convex formulation of DCLMP (C-DCLMP). Finally, we have comprehensively evaluated the proposed methods and demonstrated their superiority on both toy and real datasets. [ABSTRACT FROM AUTHOR]

Plants can be infected by multiple pathogens concurrently in natural systems. However, pathogen–pathogen interactions have rarely been studied. In addition to the oomycete Phytophthora sojae, fungi such as Fusarium spp. also cause soybean root rot. In a 3‐year field investigation, we discovered that P. sojae and Fusarium spp. frequently coexisted in diseased soybean roots. Out of 336 P. sojae–soybean–Fusarium combinations, more than 80% aggravated disease. Different Fusarium species all enhanced P. sojae infection when co‐inoculated on soybean. Treatment with Fusarium secreted non‐proteinaceous metabolites had an effect equal to the direct pathogen co‐inoculation. By screening a Fusarium graminearum mutant library, we identified Fusariumpromoting factor of Phytophthora sojae infection 1 (Fpp1), encoding a zinc alcohol dehydrogenase. Fpp1 is functionally conserved in Fusarium and contributes to metabolite‐mediated infection promotion, in which vitamin B6 (VB6) produced by Fusarium is key. Transcriptional and functional analyses revealed that Fpp1 regulates two VB6 metabolism genes, and VB6 suppresses expression of soybean disease resistance‐related genes. These results reveal that co‐infection with Fusarium promotes loss of P. sojae resistance in soybean, information that will inform the sustainable use of disease‐resistant crop varieties and provide new strategies to control soybean root rot. [ABSTRACT FROM AUTHOR]

Most studies in the literature analyzed the importance of single jump either in crude oil prices or convenience yield for pricing commodity derivatives, but avoided combining the effect of co-jump diffusions from these two resources into one model. This is probably due to the difficulty of solving the problem particularly with joint jumps. The contribution of this paper is to first introduce co-jump diffusions in spot price of crude oil and convenience yield as well as the stochastic interest rate environment in the pricing of European crude oil options. More importantly, a closed-form solution for such a complicated problem is also provided. Both theoretical analysis and strong empirical evidence are presented to support our findings, including the verification of our newly pricing formula and the effects of co-jump diffusions and interest rate on the option price. [ABSTRACT FROM AUTHOR]

Lung adenocarcinoma (LUAD) is usually found at the metastatic stage. Circular RNA dihydrouridine synthase 2‐like (DUS2L) (circDUS2L) has been discovered to be upregulated in LUAD. Nevertheless, the function of circDUS2L in LUAD has not been verified. Levels of circDUS2L, microRNA‐590‐5p (miR‐590‐5p), and phosphoglycerate mutase 1 (PGAM1) mRNA were analyzed using quantitative real‐time polymerase chain reaction (RT‐qPCR). Cell proliferation, apoptosis, metastasis, and invasion were assessed by 3‐(4,5‐Dimethylthiazol‐2‐yl)‐2,5‐Diphenyltetrazolium Bromide (MTT), colony formation, 5‐ethynyl‐2′‐deoxyuridine (Edu), flow cytometry, and transwell assays. Protein levels were detected by western blotting. Cell glycolysis was analyzed by measuring cell glucose consumption, lactate production, and extracellular acidification rate (ECAR). The regulatory mechanism of circDUS2L in LUAD cells was analyzed by bioinformatics analysis, dual‐luciferase reporter, RNA pull‐down, and RNA immunoprecipitation (RIP) assays. Xenograft assay was conducted to confirm the function of circDUS2L in vivo. CircDUS2L was highly expressed in LUAD tissues and cells. CircDUS2L silencing constrained xenograft tumor growth in vivo. CircDUS2L knockdown induced apoptosis, repressed viability, colony formation, proliferation, metastasis, invasion, and glycolysis of LUAD cells in vitro by releasing miR‐590‐5p via functioning as a miR‐590‐5p sponge. MiR‐590‐5p was lowly expressed in LUAD tissues and cells, and miR‐590‐5p mimic curbed malignant behaviors and glycolysis of LUAD cells by targeting PGAM1. PGAM1 was overexpressed in LUAD tissues and cells, and circDUS2L sponged miR‐590‐5p to regulate PGAM1 expression. CircDUS2L elevated PGAM1 expression through functioning as a miR‐590‐5p sponge, thus driving malignant behaviors and glycolysis of LUAD cells. Highlights: CircDUS2L was overexpressed in LUAD tissues and cells.Knockdown of circDUS2L repressed malignant behaviors and glycolysis of LUAD cells.CircDUS2L served as a miR‐590‐5p decoy.PGAM1 was a downstream target of miR‐590‐5p. [ABSTRACT FROM AUTHOR]

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In recent years, semantic segmentation of high-resolution remote sensing images has been gradually applied to many important scenes. However, with the rapid development of remote sensing data acquisition technology, the existing image data processing methods are facing major challenges. Especially in the accuracy of extraction and the integrity of the edges of objects, there are often problems such as small objects being assimilated by large objects. In order to solve the above problems, based on the excellent performance of Transformer, convolution and its variants, and feature pyramids in the field of deep learning image segmentation, we designed two encoders with excellent performance to extract global high-order interactive features and low-order local feature information. These encoders are then used as the backbone to construct a global and local feature fusion network with a dual encoder (GLFFNet) to effectively complete the segmentation of remote sensing images. Furthermore, a new auxiliary training module is proposed that uses the semantic attention layer to process the extracted feature maps separately, adjust the losses, and more specifically optimize each encoder of the backbone, thus optimizing the training process of the entire network. A large number of experiments show that our model achieves 87.96% mIoU on the Potsdam dataset and 80.42% mIoU on the GID dataset, and it has superior performance compared with some state-of-the-art methods on semantic segmentation tasks in the field of remote sensing. [ABSTRACT FROM AUTHOR]

Taking Ganmai-Dazao decoction as the research object, and the extraction amount of 5-21st alkyl resor- cinol (ARs-21) as the main evaluation index, the three extraction conditions of water extraction, alcohol extrac- tion, and water extraction and alcohol precipitation were optimized by a single factor test combined with response surface test, and the main physical and chemical indexes and production cost of the extract were compared and ana- lyzed. The results showed that the optimum extraction conditions were as follows: solid-liquid ratio 1 : 30, ethanol concentration 505 g / L, and extraction time 43 min. Under these conditions, the color and state of the extract were good, and the extraction amounts of ARs-21 and total flavonoids were high, but the industrial cost was high. The optimum extraction conditions of water extraction were as follows: solid-liquid ratio 1 : 31, extraction temperature 90 °C, extraction time 36 min. Under these conditions, the dry extract yield of the extract was higher, the particle size was smaller, and the cost was lower, which was suitable for large-scale production. However, there were some problems, such as darker color, higher viscosity, and lower extraction amount of ARs-21 and total flavonoids than those of alcohol extraction. The water extraction and alcohol precipitation method would produce white yellow floc- culent precipitate after alcohol precipitation, which could not be dissolved back, and the product quality stability was poor, which was not suitable for the extraction of Ganmai Dazao decoction. [ABSTRACT FROM AUTHOR]