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In this study, a brief instrument (the Mental Health Change Indicator Scale, MHCIS) was developed for use in assessing the impact of a negative event on mental health. The instrument was then used to compare the reported impact of the COVID-19 pandemic on the mental health of Chinese university students studying either in China (n = 734) or Australia (n = 108). Perceived discrimination and social support were also evaluated as possible mediators of the relationship between country of residence (Australia vs China), and mental health impact. Results suggested that the 10-item MHCIS was unidimensional and psychometrically sound, and that the pandemic had a significantly (p < 0.001) more negative impact on the mental health of Chinese students studying in Australia than on those studying in China. Perceived discrimination was identified as a key mediating factor in this relationship. Possible implications for higher education institutions in Australia are discussed.

A relatively fast pursuit algorithm in face recognition is proposed, compared to existing pursuit algorithms. More stopping rules have been put forward to solve the problem of slow response of OMP, which can fully develop the superiority of pursuit algorithm—avoiding to process useless information in the training dictionary. For the test samples that are affected by partial occlusion, corruption, and facial disguise, recognition rates of most algorithms fall rapidly. The robust version of this algorithm can identify these samples automatically and process them accordingly. The recognition rates on ORL database, Yale database, and FERET database are 95.5%, 93.87%, and 92.29%, respectively. The recognition performance under various levels of occlusion and corruption is also experimentally proved to be significantly enhanced.

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