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Abstract: We investigated the dynamics of the microfauna community in activated sludge, with special reference to sludge bulking, in two parallel municipal wastewater treatment systems in Beijing, China over a period of 14 months. Annual cyclic changes in microfauna community structures occurred in both systems. RELATE analysis based on Spearman's Rank correlation indicated that microfauna community structures were highly correlated with the sludge volume index (SVI) (p <0.001), which indicates sludge settleability. Nutrient conditions of raw sewage (p <0.01) and hydraulic retention time (HRT) (p <0.05) were also related to microfauna community structures. Abundances of the species Epistylis plicatilis and Vorticella striata increased significantly with an increase in SVI (p <0.001) and decrease in water temperature (p <0.001), suggesting that sludge bulking may have created favorable conditions for the two species, even under unfavorable temperature conditions. Sludge de-flocculation primarily due to the excessive growth of Microthrix parvicella-like filaments could be an important driving force for the microfauna community changes. The release of flocculated non-filamentous bacteria may represent a suitable food source for these species. The two species may be considered as potential bioindicators for sludge bulking. [Copyright &y& Elsevier]

Various geostatistical models have been used in epidemiological research to evaluate ambient air pollutant exposures at a fine spatial scale. Few studies have investigated the performance of different exposure models on population-weighted exposure estimates and the resulting potential misclassification across various modeling approaches. This study developed spatial models for NO2 and PM2.5 and conducted exposure assessment in Beijing, China. It explored three spatial modeling approaches: variable dimension reduction, machine learning, and conventional linear regression. It compared their model performance by cross-validation (CV) and population-weighted exposure estimates. Specifically, partial least square (PLS) regression, random forests (RF), and supervised linear regression (SLR) models were developed based on an ordinary kriging (OK) framework for NO2 and PM2.5 in Beijing, China. The mean squared error-based R2 (R2mse) and root mean squared error (RMSE) in leave-one site-out cross-validation (LOOCV) were used to evaluate model performance. These models were used to predict the ambient exposure levels in the urban area and to estimate the misclassification of population-weighted exposure estimates in quartiles between them. The results showed that the PLS-OK models for NO2 and PM2.5, with the LOOCV R2mse of 0.82 and 0.81, respectively, outperformed the other models. The population-weighted exposure to NO2 estimated by the PLS-OK and RF-OK models exhibited the lowest misclassification in quartiles. For PM2.5, the estimates of potential misclassification were comparable across the three models. It indicated that the exposure misclassification made by choosing different modeling approaches should be carefully considered, and the resulting bias needs to be evaluated in epidemiological studies. [ABSTRACT FROM AUTHOR]

Concerns about China's ambitions to return to the global centre stage as a great power have recently begun to focus on the Digital Silk Road (DSR), an umbrella term for various activities – commercial and diplomatic – of interest to the Chinese government in the cyber realm. Part of (or a spin-off from) the 2013 Belt and Road Initiative, by 2020 the DSR had become a focal point of China's foreign policy. But the DSR remains ill-defined and poorly understood. At the heart of such concerns is not that Chinese technology companies are becoming globally competitive, but rather that Beijing could use them to 'rewire' the global digital architecture, from physical cables to code. Dominance by Chinese technology could shift global norms from a free cyber commons to competing systems of cyber sovereignty or cyber freedom. This Adelphi book brings together eight experts to examine the development of the DSR; explore its impact on economics, security and governance in recipient countries; and assess its broader impact on patterns of economic and technological dependence, on the emerging rules and norms of tech globalisation, and on global geopolitics and great-power relations. Beijing has grasped the opportunity to leverage the entrepreneurial strengths of its private tech sector to gain prominence in the world's digital ecosystem. But the more interventionist Beijing becomes, the more Chinese firms will be seen as instruments of the state, and the greater the pushback against Chinese technology and the DSR may be. To achieve great-power status and global centrality, Beijing might ultimately need to change tack. How it innovates in further rolling out Chinese tech across the world, and what the DSR will then look like, will have far-reaching impacts on global economics, politics and security. [ABSTRACT FROM AUTHOR]

No abstract received. [ABSTRACT FROM AUTHOR]