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BackgroundThe ongoing COVID-19 pandemic has led to an increase in anxiety, depression, posttraumatic stress disorder, and psychological stress experienced by the general public in various degrees worldwide. However, effective, tailored mental health services and interventions cannot be achieved until we understand the patterns of mental health issues emerging after a public health crisis, especially in the context of the rapid transmission of COVID-19. Understanding the public's emotions and needs and their distribution attributes are therefore critical for creating appropriate public policies and eventually responding to the health crisis effectively, efficiently, and equitably. ObjectiveThis study aims to detect the temporal patterns in emotional fluctuation, significant events during the COVID-19 pandemic that affected emotional changes and variations, and hourly variations of emotions within a single day by analyzing data from the Chinese social media platform Weibo. MethodsBased on a longitudinal dataset of 816,556 posts published by 27,912 Weibo users in Wuhan, China, from December 31, 2019, to April 31, 2020, we processed general sentiment inclination rating and the type of sentiments of Weibo posts by using pandas and SnowNLP Python libraries. We also grouped the publication times into 5 time groups to measure changes in netizens’ sentiments during different periods in a single day. ResultsOverall, negative emotions such as surprise, fear, and anger were the most salient emotions detected on Weibo. These emotions were triggered by certain milestone events such as the confirmation of human-to-human transmission of COVID-19. Emotions varied within a day. Although all emotions were more prevalent in the afternoon and night, fear and anger were more dominant in the morning and afternoon, whereas depression was more salient during the night. ConclusionsVarious milestone events during the COVID-19 pandemic were the primary events that ignited netizens’ emotions. In addition, Weibo users’ emotions varied within a day. Our findings provide insights into providing better-tailored mental health services and interventions.

Developing efficient and green catalytic systems is highly desired in the syntheses of alicyclic amines via hydrogenation of nitroaromatics. Herein, we developed Ru-Pd dual active site catalysts in which Ru and Pd species were anchored and highly dispersed on air-exfoliated carbon nitride (Ru-Pd/C 3 N 4 -air). As-prepared catalysts were employed in the hydrogenation of nitrobenzene (NB) to cyclohexylamine (CHA). Compared with single Ru or Pd based catalysts, Ru-Pd dual active site catalysts obtained a higher CHA production rate of 26.7 mol CHA mol -1 Ru·Pd h -1 at 80 °C and 3 MPa H 2 . The activation energy for the hydrogenation of the nitro group and benzene ring was calculated as 26.26 kJ mol -1 and 66.30 kJ mol -1 , respectively. Intrinsic kinetic studies demonstrated that Pd was the dominant metal for hydrogenation of nitro group, while Ru was dominant for benzene ring. Thereinto, the corresponding non-dominant metals enhanced activation and dissociation of H 2 , thereby improving catalytic activity significantly. This excellent performance of Ru-Pd catalysts could be attributed to highly dispersed Ru-N x and Pd-N x at a nanoscale distance, which was conducive to metal-assisted hydrogenation. Stability investigation showed that the performance of Ru-Pd catalysts could be essentially maintained at a high level. Additionally, the substrate scope could be successfully extended to hydrogenation of other nitroaromatics with different substituents., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)