The self-assembly of diblock copolymers under soft confinement is studied systematically using a simulated annealing method applied to a lattice model of polymers. The soft confinement is realized by the formation of polymer droplets in a poor solvent environment. Multiple sequences of soft confinement-induced copolymer aggregates with different shapes and self-assembled internal morphologies are predicted as functions of solvent-polymer interaction and the monomer concentration. It is discovered that the self-assembled internal morphology of the aggregates is largely controlled by a competition between the bulk morphology of the copolymer and the solvent-polymer interaction, and the shape of the aggregates can be non-spherical when the internal morphology is anisotropic and the solvent-polymer interaction is weak. These results demonstrate that droplets of diblock copolymers formed in poor solvents can be used as a model system to study the self-assembly of copolymers under soft confinement.

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With the speedy growth of economic development, the imbalance of energy supply and demand pose a critical challenge for the energy security of our country. Meanwhile, the increasing and excessive energy consumption lead to the greenhouse effect and atmospheric pollution, greatly threatening the survival and development of human beings. This study integrated two nighttime light remote sensing datasets, namely Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) data, to extend the temporal coverage of the study. Then, the distributions of China’s energy consumption from 1995 to 2016 at a 1-km resolution were estimated using different models and the spatiotemporal variations of energy consumption were explored on the basis of the best estimated results. Next, the factors influencing China’s energy intensity on the provincial level were investigated based on the spatial econometric model. The results show that: (1) The integrated nighttime light datasets can be successfully applied to estimate the dynamic changes of energy consumption. Moreover, the panel data model established in our research performed better than the quadratic polynomial model. (2) During the observation period, the energy consumption in China significantly increased, especially in the Yangtze River Delta, the Pearl River Delta, the Beijing–Tianjin–Hebei region, eastern coastal cities, and provincial capitals. (3) Different from the random spatial distribution pattern of energy consumption on the provincial level, the spatial distribution of energy consumption on the prefectural level has significant clusters, and its spatial agglomeration was strengthened year by year during the research period. (4) The spatial Durbin model (SDM) with a spatial fixed effect has been proved to be more suitable to explore the impact mechanism of China’s energy consumption. Among the four socio-economic factors, industrial structure has the greatest impact on the provincial energy intensity in China. Moreover, the changes in industrial structure and foreign direct investment (FDI) can not only influence the local energy intensity but also affect the energy intensity of the neighboring provinces.

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In this bench-scale study, two promising processes for minimizing excess activated sludge (EAS) production, i.e., membrane bioreactor (MBR) and sludge ozonation (SO), were coupled in this study into the MBR-SO process to treat domestic wastewater for 80 days, and the vital related operational factors were also investigated. Mathematical models were developed to elucidate the relationships among process control parameters and the actually operational effects of these parameters on the performance of MBR-SO process. As a consequence, the ratio of flow-rate draining to ozonation unit (q) to influent wastewater flow-rate (Q) was the mainly operational parameter, which was significantly affected by the sludge lysing ratio in ozonation unit (xi), produced COD per unit mass lysed MLSS (eta), observed sludge yield coefficient for wastewater (Y(obs)) and intrinsic yield coefficient for COD produced by lysed sludge (Y(2)). To keep the mixed liquid suspended solid concentration (MLSS) in MBR around 8,000 mg/L, the ratio of q/Q and xi for each batch ozonation was set at 0.0067 and 0.72, respectively. The generated EAS was continuously drained into ozonation unit at a frequency of 2 batch/d for lysing cells, and almost constant MLSS concentration with zero observed sludge yield coefficient (Y(obs)) and excellent effluent quality could be achieved in MBR except for TP concentration (only approximately 3.62% TP removal efficiency rate obtained in Test stage). The calculation of sludge disintegration number (SDN) and the maximum SDN (SDN(max)) indicated that the higher xi could reduce apparently the sludge amount needed for ozonation. The low input ozone gas concentration and high flow-rate could enhance the sludge lysing effects at same ozone dosage, and therefore lower energy consumption of 0.041Yuan (USD 0.0053)/m(3) wastewater was obtained. Overall, mass balance showed that the preset value of operation parameters listed in mathematical models matched well with trends of sludge reduction found in this experimental result.

This study examines anxiety-related postings on Sina Weibo to gain insight into social networking about mental health. The themes of a random sample of anxiety-related postings (n = 1000) were assessed. The disclosure of anxiety was the most common theme. The prevalence of anxiety was higher in certain areas where the economy is stronger than others, and the people living there suffered from more stress. Users who talked about feeling anxious tended to be more active on social media during leisure hours and less active during work hours. Our findings may be developed to detect and help individuals who may suffer from anxiety disorders at a low cost.