Interactive effects of grassland utilization and climatic factors govern the plant diversity-soil C relationship in steppe of North China.

The relationship between plant diversity and the ecosystem carbon pool is important for understanding the role of biodiversity in regulating ecosystem functions. However, it is not clear how the relationship between plant diversity and soil carbon content changes under different grassland use patterns. In a 3-year study from 2013 to 2015, we investigated plant diversity and soil total carbon (TC) content of grasslands in northern China under different grassland utilization methods (grazing, mowing, and enclosure) and climatic conditions. Shannon-Wiener and Species richness index of grassland were significantly decreased by grazing and mowing. Plant diversity was positively correlated with annual precipitation (AP) and negatively correlated with annual mean temperature (AMT). AP was the primary regulator of plant diversity. Grazing and mowing decreased TC levels in grasslands compared with enclosures, especially in topsoil (0-20 cm). The average TC content was decreased by 58 % and 36 % in the 0-10 cm soil layer, while it was decreased by 68 % and 39 % in 10-20 cm soil layer. TC was positively correlated with AP and negatively correlated with AMT. Principal component analysis (PCA) showed that plant diversity was positively correlated with soil TC, and the correlation decreased with an increase in the soil depth. Overall, this study provides a theoretical basis for predicting soil carbon storage in grasslands under human disturbances and climate change impacts.

Variance Analysis in China's Coal Mine Accident Studies Based on Data Mining.

The risk of coal mine accidents rises significantly with mining depth, making it urgent for accident prevention to be supported by both scientific analysis and advanced technologies. Hence, a comprehensive grasp of the research progress and differences in hotspots of coal mine accidents in China serves as a guide to find the shortcomings of studies in the field, promote the effectiveness of coal mine disaster management, and enhance the prevention and control ability of coal mine accidents. This paper analyzes Chinese and foreign literature based on data mining algorithms (LSI + Apriori), and the findings indicate that: (1) 99% of the available achievements are published in Chinese or English-language journals, with the research history conforming to the stage of Chinese coal industry development, which is characterized by "statistical description, risk evaluation, mechanism research, and intelligent reasoning". (2) Chinese authors are the primary contributors that lead and contribute to the continued development of coal mine accident research in China globally. Over 81% of the authors and over 60% of the new authors annually are from China. (3) The emphasis of the Chinese and English studies is different. Specifically, the Chinese studies focus on the analysis of accident patterns and causes at the macroscale, while the English studies concentrate on the occupational injuries of miners at the small-scale and the mechanism of typical coal mine disasters (gas and coal spontaneous combustion). (4) The research process in Chinese is generally later than that in English due to the joint influence of the target audience, industrial policy, and scientific research evaluation system. After 2018, the Chinese studies focus significantly on AI technology in deep mining regarding accident rules, regional variation analysis, risk monitoring and early warning, as well as knowledge intelligence services, while the hotspots of English studies remain unchanged. Furthermore, both Chinese and English studies around 2019 focus on "public opinion", with Chinese ones focusing on serving the government to guide the correct direction of public opinion while English studies focus on critical research of news authenticity and China's safety strategy.

Perceptions of Chinese older adults with type 2 diabetes mellitus about self-management mobile platform: A qualitative study.

OBJECTIVE: To explore the perceptions of Chinese older adults with type 2 diabetes mellitus (T2DM) about the WeChat-based self-management mobile health (mhealth) platforms. METHODS: A semi-structured interview was conducted with a purposive sample of 20 older adults with T2DM. Interview data were summarized and refined with the NVivo 11.0 software. Content analysis was used for qualitative research. RESULTS: Three themes emerged from the interviews: Perception One: Better experience when using a self-management mobile platform; Perception Two: More practical functions of the platform; and Perception Three:Trust and assistance from others. CONCLUSION: Older adults with T2DM have a high willingness to use the WeChat-based self-management mhealth platform. To encourage them to use the platform more frequently, the following factors should be taken into consideration: the perceived experience, fundamental demand for self-management, and need for others' support and assistance. These age-appropriate approaches to self-management health reform may benefit older adults with T2DM.

QTL mapping of adult-plant resistances to stripe rust and leaf rust in Chinese wheat cultivar Bainong 64.

Stripe rust and leaf rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss. and P. triticina, respectively, are devastating fungal diseases of common wheat (Triticum aestivum L.). Chinese wheat cultivar Bainong 64 has maintained acceptable adult-plant resistance (APR) to stripe rust, leaf rust and powdery mildew for more than 10 years. The aim of this study was to identify quantitative trait loci/locus (QTL) for resistance to the two rusts in a population of 179 doubled haploid (DH) lines derived from Bainong 64 × Jingshuang 16. The DH lines were planted in randomized complete blocks with three replicates at four locations. Stripe rust tests were conducted using a mixture of currently prevalent P. striiformis races, and leaf rust tests were performed with P. triticina race THTT. Leaf rust severities were scored two or three times, whereas maximum disease severities (MDS) were recorded for stripe rust. Using bulked segregant analysis (BSA) and simple sequence repeat (SSR) markers, five independent loci for APR to two rusts were detected. The QTL on chromosomes 1BL and 6BS contributed by Bainong 64 conferred resistance to both diseases. The loci identified on chromosomes 7AS and 4DL had minor effects on stripe rust response, whereas another locus, close to the centromere on chromosome 6BS, had a significant effect only on leaf rust response. The loci located on chromosomes 1BL and 4DL also had significant effects on powdery mildew response. These were located at the same positions as the Yr29/Lr46 and Yr46/Lr67 genes, respectively. The multiple disease resistance locus for APR on chromosome 6BS appears to be new. All three genes and their closely linked molecular markers could be used in breeding wheat cultivars with durable resistance to multiple diseases.

QTL mapping of adult-plant resistance to stripe rust in a population derived from common wheat cultivars Naxos and Shanghai 3/Catbird.

Stripe rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss., is a severe foliar disease of common wheat (Triticum aestivum L.) worldwide. Use of adult-plant resistance (APR) is an efficient approach to provide long-term protection of crops from the disease. The German spring wheat cultivar Naxos showed a high level of APR to stripe rust in the field. To identify the APR genes in this cultivar, a mapping population of 166 recombinant inbred lines (RILs) was developed from a cross between Naxos and Shanghai 3/Catbird (SHA3/CBRD), a moderately susceptible line developed by CIMMYT. The RILs were evaluated for maximum disease severity (MDS) in Sichuan and Gansu in the 2009-2010 and 2010-2011 cropping seasons. Composite interval mapping (CIM) identified four QTL, QYr.caas-1BL.1RS, QYr.caas-1DS, QYr.caas-5BL.3 and QYr.caas-7BL.1, conferring stable resistance to stripe rust across all environments, each explaining 1.9-27.6, 2.1-5.8, 2.5-7.8 and 3.7-9.1 % of the phenotypic variance, respectively. QYr.caas-1DS flanked by molecular markers XUgwm353-Xgdm33b was likely a new QTL for APR to stripe rust. Because the interval between flanking markers for each QTL was less than 6.5 cM, these QTL and their closely linked markers are potentially useful for improving resistance to stripe rust in wheat breeding.