The influence of COVID-19 on agricultural economy and emergency mitigation measures in China: A text mining analysis.

Understanding the influence of COVID-19 on China's agricultural economy and the Chinese government's emergency measures to ease the economic impacts of viral spread can offer urgently-needed lessons while this virus continues to spread across the globe. Thus, this study collected over 750,000 words upon the topic of COVID-19 and agriculture from the largest two media channels in China: WeChat and Sina Weibo, and employed web crawler technology and text mining method to explore the influence of COVID-19 on agricultural economy and mitigation measures in China. The results show that: (1) the impact of COVID-19 on China's agricultural economy at the very first phase is mainly reflected in eight aspects as crop production, agricultural products supply, livestock production, farmers' income and employment, economic crop development, agricultural products sales model, leisure agriculture development, and agricultural products trade. (2) The government's immediate countermeasures include resuming agricultural production and farmers' work, providing financial support, stabilizing agricultural production and products supply, promoting agricultural products sale, providing subsidies, providing agricultural technology guidance and field management, and providing assistance to poor farmers to reduce poverty. (3) The order of government's immediate countermeasures is not all in line with the order of impact aspects, which indicates that more-tailored policies should be implemented to mitigate the strikes of COVID-19 on China's agricultural economy in the future.

Determinants of Public-Private Partnership Adoption in Solid Waste Management in Rural China.

Rural solid waste management is a severe challenge in China. The Public-Private Partnership (PPP) is an effective method for rural solid waste management. However, policy efforts aimed at stimulating the adoption of PPP in rural solid waste management have been limited in their success. This study aims to empirically investigate the determinants of rural solid waste management PPP adoption in China. First, this study builds a theoretical model that consists of factors related to the institutional environment and market and proposes theoretical hypotheses. Then, using the balanced provincial panel data of 150 samples from 2015 to 2019, this study applies various count regression models and truncated regression models to empirically test the theoretical hypotheses. The results show that provinces with higher fiscal transparency, financial burdens, and market demand tend to adopt more PPP, while provinces with lower per capita GDP and market openness index ratings have a stronger motivation to initiate more PPP. In contrast, investment institutional environment factors have no impact on PPP adoption. To stimulate the development of PPP in rural solid waste management, this study proposed that a good-governed government and a strong market demand are critical foundations, and also a debt-risk prevention and evaluation system should be established to avoid local debt risks resulting from over-adoption of PPP.

Gold colloid-bienzyme conjugates for glucose detection utilizing surface-enhanced Raman scattering.

It is difficult to detect glucose by surface-enhanced Raman spectroscopy (SERS) due to the small normal Raman cross-section and the weak adsorption of glucose molecules on the surface of noble metal. A simple and fast method is proposed in this paper for the detection of glucose based on SERS signal of the enzyme reaction product and the difficulties have been circumvented. Gold colloids modified by horseradish peroxidase and glucose oxidase (HRP/GOD-gold colloids) are added to the mixture of o-phenylenediamine and glucose, and the resulting solution is allowed to react at room temperature for 5min. Azoaniline, an azo compound with strong Raman scattering, is generated and the Raman scattering of this reaction product is enhanced when adsorbed on gold colloids. The intensity of the SERS spectrum is used for assessment of glucose content. The dynamic signal range provided by this analytical system is 0.50-32mM, which covers the normal clinical range for glucose in blood from 3.5 to 6.1mM. The detection limit is about 0.46mM. The interference effect of several proteins on glucose detection is also investigated and has shown to have no effect on the measurement of glucose by the described technique.