Search

After a major debt crisis occurs in a listed company, the stock prices of related enterprises may also fluctuate sharply, resulting in the spread of debt risk to more enterprises. Taking the stocks of listed companies as network nodes, we constructed a complex stock market network over three periods of time through the logarithmic return rate of stocks for the three periods of prophase, metaphase, and anaphase of the debt crisis. We studied the topological characteristics of the network and destructiveness over the three periods. Finally, the minimum spanning tree was used to construct a network and the community structure of the network. The empirical analysis took the debt crisis of the China Evergrande Company as an example to analyze the impact of its major debt crisis on the Chinese stock market. The research findings were as follows: First, the debt crisis increased the inter-industry connections within the network, that is, the correlations between enterprises in different industries was enhanced. Second, the closeness of the cross-industry connections increased the connectivity efficiency of the network, but compared with the other two periods, the debt crisis in the metaphase was less stable. Third, community research showed that in the metaphase of the debt crisis, the enterprises became the core nodes of the network. [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyze the topological structure dynamics of the complex network of stocks before and after the outbreak of the COVID-19, so as to provide a basis for preventing financial risks. We calculate Pearson correlation coefficient between enterprises according to logarithmic rate of return and trading volume ratio of enterprises' stocks, and then constructed a complex network of stock market price and volume before and after the outbreak of the COVID-19. First, through thresholding and heat map imaging of the correlation matrix, the change characteristics of the correlation between various industries in 2019 and 2020 are studied. Second, the node degree, average weighted degree, graph density, clustering coefficient, and average clustering coefficient are used to study the topological structure change of the complex network of stock correlation. Third, the principle of node betweenness centrality is used to analyze the characteristics of a complex network after removing the core nodes. The research shows that, first, under the influence of the COVID-19 pandemic, the correlation among industries has the characteristics of industrial clusters, that is, the correlation in a industry is strengthened. In addition to banking, the correlation between industries has weakened, and the correlation between the banking industry and other industries has strengthened. Second, the node difference in betweenness centrality of core nodes in 2020 is higher than that in 2019, indicating that the network stability in 2019 is higher than that in 2020. These two points indicate that under the influence of the COVID-19 epidemic, the complex network topology of China's entire stock market has changed, and companies need to undertake countermeasures in the face of the crisis to effectively prevent and control systemic risks. [ABSTRACT FROM AUTHOR]

Because most chickens are reared in intensive farms, where a range of feed additives are used routinely, concerns have been raised on the potential public health risk of chicken product consumption. This study was conducted to characterize the contents of trace metals in fresh chicken tissues (354 samples) on the food markets in Guangdong province of southern China, a major region of chicken production with heavy per capita chicken consumption, and to assess the public health risk from chronic dietary exposure to the trace metals through chicken consumption. With the exception of Cr, Ni, and Pb, the contents of trace metals were generally higher in the chicken giblets (livers, gizzards, hearts, and kidneys) compared to muscles (breasts and drumsticks). Chicken tissues from the urban markets generally contained higher levels of As, Cu, Mn, and Zn than those from the rural markets, while the contents of Pb were typically higher in the chicken muscles from the rural markets. Results of statistical analyses indicate that Cu, Zn, and As in the chicken tissues derived mainly from the feeds, which is consistent with the widespread use of Cu, Zn, and phenylarsenic compounds as feed supplements/additives in intensive poultry farming. No non-carcinogenic risk is found with the consumption of fresh chicken meat products on the food markets, while approximately 70% of the adult population in Guangzhou and 30% of those in Lianzhou have bladder and lung cancer risk above the serious or priority level (10 −4 ), which arises from the inorganic arsenic contained in the chicken tissues. These findings indicate that the occurrence of inorganic arsenic at elevated levels in chicken tissues on the food markets in Guangdong province poses a significant public health risk, thus the use of phenylarsenic feed additives in China's poultry farming should be significantly reduced and eventually phased out. [ABSTRACT FROM AUTHOR]

A novel fowl adenovirus 4 (FAdV-4) has caused significant economic losses to the poultry industry in China since 2015. We established an easy-to-use reverse genetics system for modification of the whole right and partial left ends of the novel FAdV-4 genome, which worked through cell-free reactions of restriction digestion and Gibson assembly. Three recombinant viruses were constructed to test the assumption that species-specific viral genes of ORF4 and ORF19A might be responsible for the enhanced virulence: viral genes of ORF1, ORF1b and ORF2 were replaced with GFP to generate FAdV4-GFP, ORF4 was replaced with mCherry in FAdV4-GFP to generate FAdV4-GX4C, and ORF19A was deleted in FAdV4-GFP to generate FAdV4-CX19A. Deletion of ORF4 made FAdV4-GX4C form smaller plaques while ORF19A deletion made FAdV4-CX19A form larger ones on chicken LMH cells. Coding sequence (CDS) replacement with reporter mCherry demonstrated that ORF4 had a weak promoter. Survival analysis showed that FAdV4-CX19A-infected chicken embryos survived one more day than FAdV4-GFP- or FAdV4-GX4C-infected ones. The results illustrated that ORF4 and ORF19A were non-essential genes for FAdV-4 replication although deletion of either gene influenced virus growth. This work would help function study of genes on the right end of FAdV-4 genome and facilitate development of attenuated vaccines. [ABSTRACT FROM AUTHOR]

A good understanding of the power system resilience is necessary for optimizing the investment strategies and supporting the emergency rescue, but the existing quantitative estimation results based on real outage events are still lacked due to the data limitations. Therefore, this study first establishes a unified framework to measure the power system resilience under different natural disasters, by integrating the electricity performance curve with the dynamic inoperability input-output model. Then, a database of 285 Chinese historical big power outage events caused by natural disasters is established, and the city-level power system resilience values are estimated. Finally, a benefit analysis is conducted for improving the power system resilience. Our major findings are that: (1) Electricity system recoveries quickest from hail (23.05 h), while restores slowest from snowstorm (117.31 h). (2) China's city electricity system is the most resilient to the thunderstorm, while is the least resilient to the earthquake. (3) Enhancing the power system resilience will significantly reduce the requirements for rescue resources, and the saved emergency rescue cost ranges from 0.57 million yuan to 12.08 million yuan with 1% reduction of initial inoperability. • Power system resilience under natural disasters is estimated • A database of disaster induced power outages is established • The sectoral interdependency is considered in the resilience estimation • The cost-benefit analysis is conducted for the resilience enhancement • Statistical analysis of the historical outage events is conducted [ABSTRACT FROM AUTHOR]

About two-thirds of global CO 2 emissions from the energy and industry sectors are generated in China, accounting for approximately 30% of total global CO 2 emissions. These carbon-intensive processes usually produce a large amount of so-called alkaline solid wastes e.g. blast furnace slag (BFS), which have shown great potential to serve as CO 2 absorbers. In this regard, the climate impacts of these human activities should be re-evaluated by considering the carbon offsetting effects. While recent studies have been focusing on accelerated carbonation of such 'waste' from a technical perspective, the natural carbonation of these solid residues has not been comprehensively investigated. In this research, combining experimental data, we established an analytical carbon sink accounting model to estimate the CO 2 uptake of 7 types of alkaline solid wastes produced in China between 1930 and 2020 using material flow analysis (MFA), life-cycle assessment (LCA), and Monte Carlo methods. The results show that China's alkaline solid wastes from the identified industrial and agroforestry processes in 2020 absorbed 64.27 Mt CO 2 (35.91–111.01, 95% CI), offsetting 2.2% of the CO 2 emissions from Chinese industrial production. Cumulatively, 1099.51 Mt CO 2 had been sequestered by natural carbonation, since 1930. The majority of CO 2 uptake is attributed to coal combustion ash (CCA) and biomass ash (BA), which accounted for 35.9% and 26.3% of the total uptake combined respectively. All types of solid wastes exhibited rapidly increasing sequestration from 1930 to 2020 apart from yellow phosphorous slag (YPS) and oil shale ash (OSA), with substantial interannual variability. Our results indicate that the natural carbonation of such 'waste' can reduce the carbon footprint of the corresponding industrial and agroforestry processes, and make the case for further research of their full potential. [ABSTRACT FROM AUTHOR]