Changes in familial discussions among East Asian American families during the COVID-19 pandemic

Objective: We examined the degrees of change in familial discussions about racial issues (i.e., race, ethnicity, racism, and discrimination) due to the surge of anti-Asian discrimination during the COVID-19 pandemic.Background: Asian American family racial-ethnic socialization that teaches the values, information, and perspectives about racial-ethnic group membership and race relations carry great implications for youth development. However, little is known about how anti-Asian sentiments may have contributed to the degrees of change in racial issues.Method: The participants included 143 second-generation East Asian American youth (e.g., Chinese, Korean, Japanese, and Taiwanese) ages 11-18 years (M = 14.96, SD = 1.98). Youth were attending middle (38%) or high (62%) schools in the United States.Results: Latent profile analysis identified four profiles of degrees of change in familial discussions: (a) moderate change in racial discussions about other ethnicities, (b) much change in racial discussions, (c) moderate change in racial discussions about own ethnicities, and (d) little change in racial discussions.Conclusion: Our findings provide a snapshot of the ways East Asian American families' racial discussions are changing, which in turn shape youth's experiences in navigating their social contexts.Implications: The findings provide valuable directions for research and interventions to promote important racial discussion among East Asian American families.

Theoretical Study on Raman Characteristic Peaks of Coronavirus Spike Protein Based on Deep Learning

COVID-19, which has lasted for a year, has caused great damage to the global economy. In order to control COVID-19 effectively, rapid detection of COVID-19 (SARS-CoV-2) is an urgent problem. Spike protein is the detection point of Raman spectroscopy to detect SARS-CoV-2. The construction of spike protein Raman characteristic peaks plays an important role in the rapid detection of SARS-CoV-2 using Raman technology. In this paper, we used Deep Neural Networks to construct the amide I and III characteristic peak model of spike proteins based on simplified exciton model, and combined with the experimental structures of seven coronaviruses (HCoV-229E, HCoV-HKUl, HCoV-NL63, HCoV-OC43, MERS-CoV, SARS-CoV, SARS-CoV-2) spike proteins, analyzed the differences of amide I and III characteristic peaks of seven coronaviruses. The results showed that seven coronaviruses could be divided into four groups according to the amide I and III characteristic peaks of spike proteins: SARS-CoV-2, SARS-CoV, MERS-CoV form a group;HCoV-HKUl, HCoV-NL63 form a group;HCoV-229E and HCoV-OC43 form a group independently. The frequency of amide I and III in the same group is relatively close,and it is difficult to distinguish spike proteins by the frequency of amide I and III ;the characteristic peaks of amide I and III in different groups are quite different, and spike proteins can be distinguished by Raman spectroscopy. The results provide a theoretical basis for the development of Raman spectroscopy for rapid detection of SARS-CoV-2. © 2022 Science Press. All rights reserved.