Ergodicity for the GI/G/1GI/G/1-type Markov Chain

Ergodicity is a fundamental issue for a stochastic process. In this paper, we refine results on ergodicity for a general type of Markov chain to a specific type or the $GI/G/1$-type Markov chain, which has many interesting and important applications in various areas. It is of interest to obtain conditions in terms of system parameters or the given information about the process, under which the chain has various ergodic properties. Specifically, we provide necessary and sufficient conditions for geometric, strong and polynomial ergodicity, respectively.Comment: 16 page

Polysaccharides Derived From the Brown Algae Lessonia nigrescens Enhance Salt Stress Tolerance to Wheat Seedlings by Enhancing the Antioxidant System and Modulating Intracellular Ion Concentration

Soil salinity reduces plant growth and is a major factor that causes decreased agricultural productivity worldwide. Seaweed polysaccharides promote crop growth and improve plant resistance to abiotic stress. In this study, polysaccharides from brown seaweed Lessonia nigrescens polysaccharides (LNP) were extracted and further separated and fractionated. Two acidic polysaccharides (LNP-1 and LNP-2) from crude LNP were obtained and characterized. The latter had a lower molecular weight (MW) (40.2 kDa) than the former (63.9 kDa), but had higher uronic acid and sulfate content. Crude LNP and LNP-2 were composed of mannose, glucuronic acid, fucose, and xylose, whereas LNP-1 has little mannose. Moreover, the effects of the three polysaccharides on plant salt tolerance were investigated. The results showed that crude LNP, LNP-1, and LNP-2 promoted the growth of plants, decreased membrane lipid peroxidation, increased the chlorophyll content, improved antioxidant activities, and coordinated the efflux and compartmentation of intracellular ion. All three polysaccharides could induce plant resistance to salt stress, but LNP-2 was more effective than the other two. The present study allowed to conclude that both MW and sulfate degree contribute to salt resistance capability of polysaccharides derived from L. nigrescens

Development of Deep Learning Methodology for Maize Seed Variety Recognition Based on Improved Swin Transformer

In order to solve the problems of high subjectivity, frequent error occurrence and easy damage of traditional corn seed identification methods, this paper combines deep learning with machine vision and the utilization of the basis of the Swin Transformer to improve maize seed recognition. The study was focused on feature attention and multi-scale feature fusion learning. Firstly, input the seed image into the network to obtain shallow features and deep features; secondly, a feature attention layer was introduced to give weights to different stages of features to strengthen and suppress; and finally, the shallow features and deep features were fused to construct multi-scale fusion features of corn seed images, and the seed images are divided into 19 varieties through a classifier. The experimental results showed that the average precision, recall and F1 values of the MFSwin Transformer model on the test set were 96.53%, 96.46%, and 96.47%, respectively, and the parameter memory is 12.83 M. Compared to other models, the MFSwin Transformer model achieved the highest classification accuracy results. Therefore, the neural network proposed in this paper can classify corn seeds accurately and efficiently, could meet the high-precision classification requirements of corn seed images, and provide a reference tool for seed identification

Microwave-assisted hydrothermal extraction of non-structural carbohydrates and hemicelluloses from tobacco biomass

Microwave-assisted hydrothermal extraction of non-structural carbohydrates and hemicelluloses from tobacco biomass was investigated. Non-structural carbohydrates extraction was optimized by an Optimal design. The maximum yields for the leaf and stem were 118.57 mg/g and 120.33 mg/g biomass, respectively. The extracted stem residue was further treated for hemicelluloses extraction. A temperature of 200 °C without holding was proved to be the most efficient condition to produce a hemicelluloses yield of 105.15 mg/g. GPC results showed that the Mw values of precipitated hemicelluloses decreased from 143.5 kDa to 13.25 kDa with increasing temperature and holding time, while the un-precipitated fraction were ranging from 11.83 to 4.88 kDa. Monosaccharide analysis revealed that hemicelluloses extracted at lower temperature are heterogeneous compositional type, including xylan, glucuronoxylan and xylanglucan, while the ratio of xylose increased significantly (up to 72.64%) with increasing temperature. The developed microwave-assisted hydrothermal extraction process opens new avenues for a sustainable tobacco-based biorefinery

Low-Molecular-Weightt Polysaccharides From Pyropia yezoensis Enhance Tolerance of Wheat Seedlings (Triticum aestivum L.) to Salt Stress

Soil salinity is one of the major issues worldwide that affects plant growth and reduces agricultural productivity. Seaweed polysaccharides have been shown to promote crop growth and improve the resistance of plant to abiotic stresses. Pyropia yezoensis is a commercially important edible red alga in Southeast Asia. However, there is little research on the application of polysaccharides from P. yezoensis in agriculture. The molecular weight (MW) of polysaccharides influences their properties. Therefore, in this study, four representative polysaccharides from P. yezoensis (PP) with different MWs (MW: 3.2, 10.5, 29.0, and 48.8 kDa) were prepared by microwave-assisted acid hydrolysis. The relationship between the degradation of polysaccharides from P. yezoensis (DPP) and their effects on plant salt tolerance was investigated. The results showed that exogenous PP and DPPs increased wheat seedling shoot and root lengths, and fresh and dry weights, alleviated membrane lipid peroxidation, increased the chlorophyll content and enhanced antioxidant activities. The expression level examination analysis of several Na+/K+ transporter genes suggested that DPPs could protect plants from the damage of salt stress by coordinating the efflux and compartmentation of Na+. The results demonstrated that polysaccharides could regulate antioxidant enzyme activities and modulate intracellular ion concentration, thereby to protect plants from salt stress damage. Furthermore, there was a significant correlation between the tolerance of wheat seedlings to salt stress and MW of polysaccharides. The results suggested that the lower-MW samples (DPP1, 3.2 kDa) most effectively protect wheat seedlings against salt stress

Genomic, Transcriptomic and Enzymatic Insight into Lignocellulolytic System of a Plant Pathogen Dickeya sp. WS52 to Digest Sweet Pepper and Tomato Stalk

Dickeya sp., a plant pathogen, causing soft rot with strong pectin degradation capacity was taken for the comprehensive analysis of its corresponding biomass degradative system, which has not been analyzed yet. Whole genome sequence analysis of the isolated soft-rotten plant pathogen Dickeya sp. WS52, revealed various coding genes which involved in vegetable stalk degradation-related properties. A total of 122 genes were found to be encoded for putative carbohydrate-active enzymes (CAZy) in Dickeya sp. WS52. The number of pectin degradation-related genes, was higher than that of cellulolytic bacteria as well as other Dickeya spp. strains. The CAZy in Dickeya sp.WS52 contains a complete repertoire of enzymes required for hemicellulose degradation, especially pectinases. In addition, WS52 strain possessed plenty of genes encoding potential ligninolytic relevant enzymes, such as multicopper oxidase, catalase/hydroperoxidase, glutathione S-transferase, and quinone oxidoreductase. Transcriptome analysis revealed that parts of genes encoding lignocellulolytic enzymes were significantly upregulated in the presence of minimal salt medium with vegetable stalks. However, most of the genes were related to lignocellulolytic enzymes, especially pectate lyases and were downregulated due to the slow growth and downregulated secretion systems. The assay of lignocellulolytic enzymes including CMCase and pectinase activities were identified to be more active in vegetable stalk relative to MSM + glucose. However, compared with nutrient LB medium, it needed sufficient nutrient to promote growth and to improve the secretion system. Further identification of enzyme activities of Dickeya sp.WS52 by HPLC confirmed that monosaccharides were produced during degradation of tomato stalk. This identified degradative system is valuable for the application in the lignocellulosic bioenergy industry and animal production

Smart decision-support system for pig farming

There are multiple participants, such as farmers, wholesalers, retailers, financial institutions, etc., involved in the modern food production process. All of these participants and stakeholders have a shared goal, which is to gather information on the food production process so that they can make appropriate decisions to increase productivity and reduce risks. However, real-time data collection and analysis continue to be difficult tasks, particularly in developing nations, where agriculture is the primary source of income for the majority of the population. In this paper, we present a smart decision-support system for pig farming. Specifically, we first adopt rail-based unmanned vehicles to capture pigsty images. We then conduct image stitching to avoid double-counting pigs so that we can use image segmentation method to give precise masks for each pig. Based on the segmentation masks, the pig weights can be estimated, and data can be integrated in our developed mobile app. The proposed system enables the above participants and stakeholders to have real-time data and intelligent analysis reports to help their decision-making.AI SingaporeNanyang Technological UniversityNational Research Foundation (NRF)Published versionThis research is supported by the Joint NTU-WeBank Research Centre on Fintech (Award No: NWJ-2020-007), Nanyang Technological University, by the AI Singapore Programme (Award No: AISG-GC-2019-003) and the NRF Investigatorship Programme (Award No. NRF-NRFI05-2019-0002) of the National Research Foundation, Singapore, and by the the China-Singapore International Joint Research Institute (Award No. 206-A021002)