The Impact of Digital Currency on the Financial System: Universal Decentralized Digital Currency, Is It Possible?

With the continuous development of computer and blockchain technology, digital currency has gradually replaced some functions of legal tender. This paper investigated the impact and the feasibility of digital currency on the financial market. Combining the money demand theory of Karl Heinrich Marx and Milton Friedman respectively, we discussed the impact of electronic and cryptocurrencies on the amount of money in circulation. Then, through further empirical analysis, we conclude that in China, digital currency has a substitution effect on current deposits in the long term. Furthermore, the welfare effect level of different countries adopting different policies on digital currency is analyzed by using the local equilibrium model of tariff effect in small countries, and the policy choice of maximizing the total welfare level is discussed based on game theory. Finally, we put forward some suggestions on establishing the global financial supervision system

The influence of local officials' promotion incentives on carbon emission in Yangtze River Delta, China

China's carbon emissions is heavily influenced by economic growth, which can be largely related to the local officials' promotion incentives. The current study was conducted to test the hypothesis that the influence of local officials' individual characteristics on carbon emissions was driven by the promotion incentives. Yangtze River Delta where carbon emissions accounted for around 13.95% of China's total emissions was selected as the research area. The multiple linear regression model was applied to determine the relationship between local officials' characteristics and total carbon emissions and carbon emissions from different sectors. The results indicated that local officials' promotion source, tenure and age significantly influenced the total carbon emission. Despite insignificance influence of officials' academic level on carbon emissions, the professional background in economics and management had a significant influence on carbon reduction. Our results indicated the importance of local officials' promotion incentives for carbon emission in China. Therefore, low carbon development should be included as an important part of official promotion system

Low-Temperature Gas Plasma Combined with Antibiotics for the Reduction of Methicillin-Resistant \u3ci\u3eStaphylococcus aureus\u3c/i\u3e Biofilm Both in Vitro and in Vivo

Biofilm infections in wounds seriously delay the healing process, and methicillin-resistant Staphylococcus aureus is a major cause of wound infections. In addition to inactivating micro-organisms, low-temperature gas plasma can restore the sensitivity of pathogenic microbes to antibiotics. However, the combined treatment has not been applied to infectious diseases. In this study, low-temperature gas plasma treatment promoted the effects of different antibiotics on the reduction of S. aureus biofilms in vitro. Low-temperature gas plasma combined with rifampicin also effectively reduced the S. aureus cells in biofilms in the murine wound infection model. The blood and histochemical analysis demonstrated the biosafety of the combined treatment. Our findings demonstrated that low-temperature gas plasma combined with antibiotics is a promising therapeutic strategy for wound infections

A comprehensive insight into the effects of acidification on varied-sized pores in different rank coals

Elucidating the evolution law of coal pore structure under acidification is crucial for guiding the practical application of acidizing technology and improving the production of coalbed methane. To comprehensively investigate the influence of acidification on varied-sized pores in different rank coals, in this study, fat coal, meagre coal and anthracite coal were collected and acidified with a mixed solution composed of hydrochloric acid (9 wt%) and hydrofluoric acid (3 wt%). An approach integrating low-pressure CO2 adsorption (LPGA-CO2), low-temperature N2 adsorption (LTGA-N2) and Mercury intrusion porosimetry (MIP) was adopted to fully characterize the varied-sized pore structure before and after acidification to eliminate the limitations of single method. The results demonstrated that acid treatment improved the pore opening degree and connectivity in coal, but had essentially no effect on the pore shape. After acidification, all the coal samples showed significant increases in the porosity and total pore volume, which was mainly contributed by the numerous newly formed large mesopores and macropores, especially the macropores (with an average contribution rate of 74.59%). Taken as a whole, acid treatment had the largest impact on macropores, followed by mesopores, and the smallest impact on micropores. In addition, the variation trend of total specific surface area (SSA) under acidification was primarily determined by micropores. For the three different rank coals selected in this study, the total SSA of fat coal (PM) was more easily affected by acidification and had the largest percentage increase after acid treatment, followed by anthracite coal (YM), while that of meagre coal (LA) decreased slightly. This difference was driven primarily by the different variation trend of micropore SSA in different rank coals. After acidification, the SSA of ultra-micropores and super-micropores all increased in fat coal (PM) and anthracite coal (YM), whereas for meagre coal (LA), although ultra-micropores SSA increased, super-micropores SSA decreased, which ultimately led to the slight decrease of its micropore SSA. Moreover, the total pore volume increment of coal was closely related to the macropore volume increment under acidification, but not significantly related to the coal maturity,which might indicate that, compared with coal rank, the mineral content in coal might be a more important consideration when measuring the applicability of acidification technology

Clinical Characteristics of 26 Human Cases of Highly Pathogenic Avian Influenza A (H5N1) Virus Infection in China

BACKGROUND: While human cases of highly pathogenic avian influenza A (H5N1) virus infection continue to increase globally, available clinical data on H5N1 cases are limited. We conducted a retrospective study of 26 confirmed human H5N1 cases identified through surveillance in China from October 2005 through April 2008. METHODOLOGY/PRINCIPAL FINDINGS: Data were collected from hospital medical records of H5N1 cases and analyzed. The median age was 29 years (range 6-62) and 58% were female. Many H5N1 cases reported fever (92%) and cough (58%) at illness onset, and had lower respiratory findings of tachypnea and dyspnea at admission. All cases progressed rapidly to bilateral pneumonia. Clinical complications included acute respiratory distress syndrome (ARDS, 81%), cardiac failure (50%), elevated aminotransaminases (43%), and renal dysfunction (17%). Fatal cases had a lower median nadir platelet count (64.5 x 10(9) cells/L vs 93.0 x 10(9) cells/L, p = 0.02), higher median peak lactic dehydrogenase (LDH) level (1982.5 U/L vs 1230.0 U/L, p = 0.001), higher percentage of ARDS (94% [n = 16] vs 56% [n = 5], p = 0.034) and more frequent cardiac failure (71% [n = 12] vs 11% [n = 1], p = 0.011) than nonfatal cases. A higher proportion of patients who received antiviral drugs survived compared to untreated (67% [8/12] vs 7% [1/14], p = 0.003). CONCLUSIONS/SIGNIFICANCE: The clinical course of Chinese H5N1 cases is characterized by fever and cough initially, with rapid progression to lower respiratory disease. Decreased platelet count, elevated LDH level, ARDS and cardiac failure were associated with fatal outcomes. Clinical management of H5N1 cases should be standardized in China to include early antiviral treatment for suspected H5N1 cases

Remote sensing inversion of lake water quality parameters based on ensemble modelling

In this paper, combined with water quality sampling data and Landsat8 satellite remote sensing image data, the inversion model of Chl-a and TN water quality parameter concentration was constructed based on machine learning algorithm. After the verification and evaluation of the inversion results of the test samples, Chl-a TN inversion model with high correlation between model test results and measured data was selected to participate in remote sensing inversion ensemble modelling of water quality parameters. Then, the ensemble remote sensing inversion model of water quality parameters was established based on entropy weight method and error analysis. By applying the idea of ensemble modelling to remote sensing inversion of water quality parameters, the advantages of different models can be integrated and the precision of water quality parameters inversion can be improved. Through the evaluation and comparative analysis of the model results, the entropy weight method can improve the inversion accuracy to some extent, but the improvement space is limited. In the verification of the two methods of ensemble modelling based on error analysis, compared with the optimal results of a single model, the determination coefficient (R2) of Chlorophyll a and TN concentration inversion results was increased from 0.9288 to 0.9313 and from 0.8339 to 0.8838, and the root mean square error was decreased from 14.2615 μ/L to 10.4194 μ/L and from1.1002mg/L to 0.8621mg/L. At the same time, with the increase of the number of models involved in the set modelling, the inversion accuracy is higher