Rhizoctonia solani Kühn is the causal pathogen of tobacco target spot, a serious fungal disease of tobacco that severely impairs yield and quality in northeast China. The objective of this study was to characterize isolates ofR. solanifrom tobacco in China. Among 58Rhizoctoniaisolates examined, all of them were multinucleate. Phylogenetic analyses and hyphal anastomosis criteria suggest that the isolates belonged toR. solanianastomosis group (AG) 3. Target spot isolates from Liaoning province formed a single phylogenetic group together with tomato isolates ofR. solaniAG-3 from Japan and are more closely related toR. solaniAG-3 isolates in tomato and potato than that in tobacco from USA. Pathogenicity test for each isolates was fulfilled using a method of inoculating tobacco leaves from plants grown for 8 weeks (cv. NC89).
The problem of elderly service supply is a important issue that must be solved for the development of an aging society. This study uses microdata from the China Health and Retirement Longitudinal Study that were published in 2017 and from a regression analysis using a dichotomous logistic model. Finally, the article examines the factors that affect the supply of elderly services and land use in rural China. The results show that 1) the health level is the most direct influencing factor on whether rural elderly people in rural land can obtain elderly services; 2) the family characteristics that affects the supply of elderly services in rural land is the relationship of living with children rather than the number of children; 3) socio-economic status has an impact on the supply of elderly services, but this impact is limited; and 4) the factors affecting the supply of family elderly services and social elderly services for the rural elderly are basically the same, with the fundamental difference between the two being that the service targets are different, which reflects typological characteristics.
Background Alfalfa (Medicago sativa L.) as an important legume plant can quickly produce adventitious roots (ARs) to form new plants by cutting. But the regulatory mechanism of AR formation in alfalfa remains unclear. Results To better understand the rooting process of alfalfa cuttings, plant materials from four stages, including initial separation stage (C stage), induction stage (Y stage), AR primordium formation stage (P stage) and AR maturation stage (S stage) were collected and used for RNA-Seq. Meanwhile, three candidate genes (SAUR, VAN3 and EGLC) were selected to explore their roles in AR formation. The numbers of differentially expressed genes (DEGs) of Y-vs-C (9,724) and P-vs-Y groups (6,836) were larger than that of S-vs-P group (150), indicating highly active in the early AR formation during the complicated development process. Pathways related to cell wall and sugar metabolism, root development, cell cycle, stem cell, and protease were identified, indicating that these genes were involved in AR production. A large number of hormone-related genes associated with the formation of alfalfa ARs have also been identified, in which auxin, ABA and brassinosteroids are thought to play key regulatory roles. Comparing with TF database, it was found that AP2/ERF-ERF, bHLH, WRKY, NAC, MYB, C2H2, bZIP, GRAS played a major regulatory role in the production of ARs of alfalfa. Furthermore, three identified genes showed significant promotion effect on AR formation. Conclusions Stimulation of stem basal cells in alfalfa by cutting induced AR production through the regulation of various hormones, transcription factors and kinases. This study provides new insights of AR formation in alfalfa and enriches gene resources in crop planting and cultivation.
After the reform and opening up, my country’s economic level and total national strength have achieved unprecedented growth. The building of a well-off society in an all-round way is moving towards a harmonious society. The development of social security is also an important part of the development and improvement of a socialist harmonious society. This article is aimed at designing a rural social security system based on deep learning algorithms, using sample collection and statistical analysis methods, collecting samples, simplifying the algorithm, and establishing a new rural social security system. The data collected by the system shows that the proportion of farmers who choose very satisfied, satisfied, average, dissatisfied, and very dissatisfied with the satisfaction of the new rural insurance is 8.94%, 45.53%, 34.96%, 8.13%, and 2.44%. It can be seen that the proportion of farmers who choose to be satisfied is the largest, and more than 10.0% of farmers choose to be dissatisfied or very dissatisfied. Investigate the factors that farmers worry about participating in the new rural insurance, and the questionnaire options can also be set to multiple choices. The survey results show that 29.27% of the farmers think that the individual payment for participating in the new rural insurance is higher; 26.02% of the farmers believe that they do not understand the new rural insurance system; 9.76% of the farmers believe that it is unnecessary to pay for the new rural insurance; 22.76% of farmers choose to rely on themselves or their children in the future; 27.64% of farmers think that the system is unstable. It has basically realized the design of a brand new rural social security system starting from the deep learning of semantic computing.
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