The effect of exposure to COVID-19 on life satisfaction: The mediating role of hyperarousal and moderating/mediating role of affective forecasting.

BACKGROUND: As a global trauma event, the Coronavirus disease (COVID-19) hugely impacts people's mental health and well-being. The purpose of our study is threefold: first, investigate the relationship between exposure to COVID-19 and life satisfaction among a large sample in China; second, test the mediating role of hyperarousal in the association between exposure to COVID-19 and life satisfaction; third, explore the moderating/mediating role of affective forecasting in the association between hyperarousal and life satisfaction. METHOD: The current study recruited 5546 participants to complete a set of self-report questionnaires online from April 22, 2020 to April 24, 2020. The moderated mediation and chain mediation model analyses were conducted using the SPSS software and PROCESS macro program. RESULTS: Exposure to COVID-19 negatively predicted life satisfaction (Effect = -0.058, p < 0.001). This relationship was partially mediated by the hyperarousal level (Effect = -0.018, CI = [-0.024, -0.013]). The moderating role of forecasted positive affect (PA)/forecasted negative affect (NA) between hyperarousal and life satisfaction was significant (ß = 0.058, CI = [0.035, 0.081]; ß = 0.037, CI = [0.014, 0.06]). The chain mediating effect of hyperarousal and forecasted PA/forecasted NA on the relationship between exposure to COVID-19 and life satisfaction was also significant (Effect = -0.003, CI = [-0.004, -0.002]; Effect = -0.006, CI = [-0.008, -0.004]). LIMITATIONS: The cross-sectional design precludes causal inference. CONCLUSION: Greater exposure to COVID-19 was associated with more severe hyperarousal symptoms, decreased life satisfaction. Forecasted PA and forecasted NA could moderate and mediate the negative impact of hyperarousal on life satisfaction. The moderating/mediating role of forecasted PA/NA implied that future interventions targeting at improving affective forecasting and reducing hyperarousal might be helpful to improve life satisfaction during the post-COVID-19 era.

Revealing the Impact of COVID-19 on Urban Residential Travel Structure Based on Floating Car Trajectory Data: A Case Study of Nantong, China

The volume of residential travel with different purposes follows relatively stable patterns in a specific period and state;therefore, it can reflect the operating status of urban traffic and even indicate urban vitality. Recent research has focused on changes in the spatiotemporal characteristics of urban mobility affected by the pandemic but has rarely examined the impact of COVID-19 on the travel conditions and psychological needs of residents. To quantitatively assess travel characteristics during COVID-19, this paper proposed a method by which to determine the purpose of residential travel by combining urban functional areas (UFAs) based on machine learning. Then, the residential travel structure, which includes origin-destination (OD) points, residential travel flow, and the proportion of flows for different purposes, was established. Based on taxi trajectory data obtained during the epidemic in Nantong, China, the case study explores changes in travel flow characteristics under the framework of the residential travel structure. Through comparison of the number and spatial distribution of OD points in the residential travel structure, it is found that residential travel hotspots decreased significantly. The ratios of commuting and medical travel increased from 43.8% to 45.7% and 7.1% to 8.1%, respectively. Conversely, the ratios of other travel types all decreased sharply. Moreover, under Maslow's hierarchy of needs model, further insights into the impacts of COVID-19 on changes in residential psychological needs are discussed in this paper. This work can provide a reference for decision makers to cope with the change in urban traffic during a public health emergency, which is beneficial to the sustainable healthy development of cities.

Understanding Digital Identity during the Pandemic: An Investigation of Two Chinese Spanish Teachers

During combatting the COVID-19 pandemic, the most widespread change in Spanish as a foreign language instruction is imperative online teaching. It demands that language teachers move all teaching activities to virtual platforms, facilitating the construction of their digital identities. However, there is scarce attention on Spanish teachers' professional development, given the necessity of understanding the evolvement of their identities across virtual learning platforms. Through the lens of a case study, this research explores the digital identities of Spanish as a foreign language teachers during the school lockdown in 2022. The data includes semi-structured interviews, virtual classroom discourse, lesson plans, and reflective writing. The results show that Spanish teachers formed multiple digital identities, including curriculum innovators, vulnerable actors, involuntary team workers, overseas returnees, and academic researchers. Among them, the first three are core identities, while overseas returnees and academic researchers are peripheral identities. Regardless, they were formed and negotiated under the influence of teachers' past experiences, the exercise of agency, emotional vulnerability, and social context. In addition, a contradictory belief in teaching was also identified during the formation of Chinese Spanish teachers' digital identities.

Development of the TOA-Related Models for PM2.5 Prediction Pre- and Post-COVID-19 Outbreak over Yangtze River Delta Region of China

The lockdown and the strict regulation measures implemented by Chinese government due to the outbreak of the COVID-19 pandemic not only decelerated the spread of the virus but also brought a positive effect on the nationwide atmospheric quality. In this study, we extended our previous research on remotely sensed estimation of PM2.5 concentrations in Yangtze River Delta region (i.e., YRD) of China from 2019 to the strict regulation period of 2020 (i.e., 24 Jan, 2020-31 Aug, 2020). Unlike the method using aerosol optical depth (AOD) developed in previous studies, we validated the possibility of moderate resolution imaging spectroradiometer (MODIS) top-of-atmosphere (TOA) reflectance (i.e., MODIS TOA) at 21 bands in estimating the PM2.5 concentrations in YRD region. Two random forests (i.e., TOA-sig RF and TOA-all RF) incorporated with different MODIS TOA datasets were developed, and the results showed that the TOA-sig RF model performed better with R2 of 0.81 (RMSE=8.07 μg/m3) than TOA-all RF model with R2 of 0.79 (RMSE=9.13 μg/m3). The monthly averaged PM2.5 exhibited the highest value of 50.81 μg/m3 in YRD region in January 2020 and sharply decreased from February to August 2020. The annual mean PM2.5 concentrations derived by TOA-sig RF model were 47.74, 32.14, and 21.04 μg/m3 in winter, spring, and summer in YRD during the strict regulation period of 2020, respectively, showing much lower values than those in 2019. Our research demonstrated that the PM2.5 concentrations could be effectively estimated by using MODIS TOA reflectance at 21 bands and the random forest.

Metacognitive Strategies, Language Learning Motivation, Self-Efficacy Belief, and English Achievement During Remote Learning: A Structural Equation Modelling Approach

Metacognitive strategies, language learning motivation, and self-efficacy belief are crucial to online or remote learning success. The purpose of the present study was to evaluate the interrelationship among metacognitive strategies, language learning motivation, self-efficacy belief, and English learning achievement. The data were collected from three surveys and an English test. The participants were 590 Chinese university students. The findings revealed that self-efficacy belief predicts English learning achievement. In particular, metacognitive strategies and language learning motivation mediate the predictive effects of self-efficacy belief on English learning achievement. The findings show the potential of enhancing online English learning achievement by facilitating learners’ self-efficacy belief, motivation, and metacognitive strategies. Implications can be gained for remote learning within and beyond the coronavirus (COVID-19) context. [ABSTRACT FROM AUTHOR] Copyright of RELC Journal is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Guest editorial

First and the foremost, universities and businesses will need to address new or amplified existing societal issues, such as poverty, unemployment, isolation, mental health problems, a lack of digital literacy and many others and re-invent their institutional roles in society. For organisations to embrace ethically and socially responsible thinking, the provision of social responsibility education is essential (Cornelius et al., 2007). [...]education providers and particularly business schools have a duty to embrace their responsibility not only by implementing ethical processes but also by providing responsible education, which would ideally act as a catalyst to stimulate socially and ethically managed business organisations (Cornelius et al., 2007). [...]the studies could and should be replicated in other national, cultural and industry contexts and their conclusions be validated through the employment of different methodologies. [...]other relevant themes should be explored, such as ethical consumption, green marketing, ethical and servant leadership and responsible and inclusive education;to develop a holistic view on the role of HE, universities and businesses in relation to responsibility and sustainability in the modern post-pandemic society.

Isolation and identification of two strains of severe acute respiratory syndrome coronavirus 2 from coronavirus disease 2019 patients in Shanghai

Objective To isolate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from nasal/throat swabs of coronavirus disease 19 (COVID-19) patients. Methods Three nasal/throat swab samples from COVID-19 patients in Shanghai were treated with TPCK trypsin and were used to treat Vero E6 cells inoculated in 96-well plates. When most of the cells showed obvious cytopathy, the cell culture supernatants were collected. We then detected the viral nucleic acid by fluorescent quantitative real-time polymerase chain reaction, and amplified the gene fragment of the virus receptor binding domain (RBD) by reverse transcription polymerase chain reaction. After amplification and culture, the virus was used to infect the Vero E6 cells inoculated in 96-well plates. The cytopathy was observed and the virus protein was detected by immunofluorescence. Results The Vero E6 cells that cultured with two of three nasal/pharyngeal swab samples showed obvious cytopathic effect and newly synthesized viral nucleic acid was detected in the supernatants of the cell culture. The amplified RBD sequence was completely consistent with the corresponding fragment of SARS-CoV-2 isolated earlier. Virus-infected Vero E6 cells showed cytopathies rapidly and could react with the monoclonal antibody against nucleocapsid protein (N protein) and spike protein (S protein) of SARS-CoV-2, and convalescence sera of COVID-19 patients. Conclusion Two SARS-CoV-2 strains were successfully isolated from two nasal/throat swab samples of COVID-19 patients in Shanghai, which provides evidence for the mechanism research on the infection and pathogenesis of SARS-CoV-2 as well as the development of drugs and vaccines against SARS-CoV-2.