Trends and issues of social annotation in education: A systematic review from 2000 to 2020

Background: Social annotation (SA) allows users to collaboratively highlight important texts, make comments and discuss with each other on the same online document. This would not only accelerate and deepen learners' cognitive understanding of information, but also help build a sense of rapport, which is critical especially because of the worldwide shift from face‐to‐face class to remote education as a response to the COVID‐19 pandemic. Objective: To provide a systematic review of empirical SA studies, so that current development as well as issues in SA practices and research are identified. Methods: A total of 32 studies were identified and bibliometrical, instructional, and methodological analysis were conducted. Results and Conclusions: The United States has published the most SA research and technology‐related journals are most receptive of SA research;one‐shot quantitative designs with a sample size between 30 and 100 have been adopted most often;there is a lack of theoretical support for SA studies;higher education settings have been more frequently researched than other educational levels;SA technological features and activities have focused more on student uses and outcomes than on those of instructors;self‐designed technologies were more preferred than commercial ones;both cognitive and affective outcomes were emphasized and nearly all studies reported positive findings. Implications: Future SA studies may conduct blended designs with larger sample sizes that is grounded upon solid theoretical frameworks;more customized and affordable SA technologies that support both students and teachers should be developed. Learning analytics and emotional design may be capitalized more to meet the demand of remote education during the pandemic. Lay Description: What is Already Known About this Topic: The behaviour of annotating often helps learners obtain deeper understanding and retain longer memorization of learning content.Social annotation, which capitalizes the advantage of digital tools and collaboration, allows learners to annotate on the same document, and view each other's annotations to ignite discussion and maximize their individual learning.Social annotation has been widely used in educational settings amongst all ages of learners. What this Paper Adds: Provides a systematic review of empirical social annotation studies between 2000 and 2020, highlighting the analysis of bibliometrics, research designs, and learning outcomes and effects.Proposes a conceptual framework (the WIRE model) to guide the design and assessment of social annotation activities.Identifies challenges and gaps in existing research designs as well as instructional practices. Implications for Practice: Instructors can use the results to locate desirable social annotation technologies and design effective activities.Researchers may utilize the trend and research gaps to design future social annotation studies.Programmers can use WIRE to make an initial assessment of social annotation tool designs, and develop more customized products for formal education.

Trends and issues of social annotation in education: A systematic review from 2000 to 2020

Background Social annotation (SA) allows users to collaboratively highlight important texts, make comments and discuss with each other on the same online document. This would not only accelerate and deepen learners' cognitive understanding of information, but also help build a sense of rapport, which is critical especially because of the worldwide shift from face-to-face class to remote education as a response to the COVID-19 pandemic. Objective To provide a systematic review of empirical SA studies, so that current development as well as issues in SA practices and research are identified. Methods A total of 32 studies were identified and bibliometrical, instructional, and methodological analysis were conducted. Results and Conclusions The United States has published the most SA research and technology-related journals are most receptive of SA research;one-shot quantitative designs with a sample size between 30 and 100 have been adopted most often;there is a lack of theoretical support for SA studies;higher education settings have been more frequently researched than other educational levels;SA technological features and activities have focused more on student uses and outcomes than on those of instructors;self-designed technologies were more preferred than commercial ones;both cognitive and affective outcomes were emphasized and nearly all studies reported positive findings. Implications Future SA studies may conduct blended designs with larger sample sizes that is grounded upon solid theoretical frameworks;more customized and affordable SA technologies that support both students and teachers should be developed. Learning analytics and emotional design may be capitalized more to meet the demand of remote education during the pandemic. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Children and adolescents' positive youth development qualities and internet addiction during the COVID-19 pandemic: A longitudinal study in China.

Backgrounds: Recent studies have shown that the qualities of children and adolescents' positive youth development (PYD) enable them to cope with developmental challenges in an adaptive manner and maintain healthy functioning. During the COVID-19 pandemic, there is still a lack of reporting on changes in children and adolescents' PYD qualities and Internet addiction and their relationship. This study investigated the association between PYD qualities and Internet addiction among the children and adolescents who have experienced the COVID-19 lockdown. Methods: A school-based cohort survey was launched in December 2019 (Wave 1, before COVID-19 lockdown) and followed up in June 2020 (Wave 2, after COVID-19 lockdown). The Chinese PYD scale (80 items, scoring 80-480) and Young's Internet addiction test (20 items, scoring 20-100) were used to evaluate the children and adolescents' PYD qualities and the degree of their Internet addiction, respectively. Cross-sectional regressions, longitudinal regressions, and cross-lagged panel model were used to examine the association between PYD qualities and Internet addiction. Results: 7,985 children and adolescents completed both waves of surveys. Compared with children and adolescents before lockdown (Wave 1), their total PYD quality dropped from 4.99 to 4.96 after COVID-19 lockdown (Wave 2), and the mean score for Internet addiction rose from 35.56 to 36.16. Cross-sectional analysis showed that after controlling for basic characteristics such as age and gender, the total PYD quality of children and adolescents in two waves was negatively correlated with the degree of Internet addiction during the same period, with ß of -6.10 and -6.95, respectively. Longitudinal analysis showed that after controlling for basic characteristics, children and adolescents' total PYD quality in Wave 1 was negatively correlated with the Wave 2 of Internet addiction and the change between the two waves of Internet addiction, with ß of -3.35 and -0.26, respectively. Cross-lagged panel models showed a negative bilateral relationship between total PYD quality and Internet addiction. Conclusion: During the COVID-19 pandemic, the qualities of children and adolescents' PYD declined, which makes children and adolescents more vulnerable to Internet addiction. Therefore, it is necessary to widely implement programs in China that can comprehensively improve the qualities of children and adolescents' positive development to prevent Internet addiction, especially after the blockade due to public health emergencies.

Trends and issues of social annotation in education: A systematic review from 2000 to 2020

Background Objective Methods Results and Conclusions Implications Social annotation (SA) allows users to collaboratively highlight important texts, make comments and discuss with each other on the same online document. This would not only accelerate and deepen learners' cognitive understanding of information, but also help build a sense of rapport, which is critical especially because of the worldwide shift from face‐to‐face class to remote education as a response to the COVID‐19 pandemic.To provide a systematic review of empirical SA studies, so that current development as well as issues in SA practices and research are identified.A total of 32 studies were identified and bibliometrical, instructional, and methodological analysis were conducted.The United States has published the most SA research and technology‐related journals are most receptive of SA research;one‐shot quantitative designs with a sample size between 30 and 100 have been adopted most often;there is a lack of theoretical support for SA studies;higher education settings have been more frequently researched than other educational levels;SA technological features and activities have focused more on student uses and outcomes than on those of instructors;self‐designed technologies were more preferred than commercial ones;both cognitive and affective outcomes were emphasized and nearly all studies reported positive findings.Future SA studies may conduct blended designs with larger sample sizes that is grounded upon solid theoretical frameworks;more customized and affordable SA technologies that support both students and teachers should be developed. Learning analytics and emotional design may be capitalized more to meet the demand of remote education during the pandemic. [ FROM AUTHOR]

How culture orientation influences the COVID-19 pandemic: An empirical analysis.

Purpose: This study aims to investigate the mediational path of the influence of cultural orientation on the COVID-19 pandemic outcome at the national level and find out whether some culture-related factors can have a moderating effect on the influence of culture. Methodology: Cultural dimension theory of Hofstede is used to quantify the degree of each dimension of culture orientation. The cross-section regression model is adopted to test if culture orientations affect the pandemic outcome, controlling for democracy, economy, education, population, age, and time. Then, a mediational analysis is conducted to examine if policy response is the mediator that culture makes an impact on the pandemic outcome. Finally, a moderation analysis is carried out to determine how each control variable has moderated the influence. Findings: The cross-section regression results showed that culture orientation influences the outcome of the COVID-19 pandemic at the 99% confidence level and that among the six cultural dimensions, collectivism-individualism has the most significant impact. It has also been found that policy response is the mediator of cultural influence, and culture-related factors can moderate the influence. Contribution: The contribution of this research lies in developing the assertion that culture influences pandemic outcomes. Our findings indicate that collectivism-individualism culture orientation affects the effectiveness of epidemic controls the most among the six culture dimensions. Additionally, our research is the first to study the mediating effect of policy responses and the moderating effect of culture-related factors on the influence of cultural orientation on the pandemic outcome.

How culture orientation influences the COVID-19 pandemic: An empirical analysis

Purpose This study aims to investigate the mediational path of the influence of cultural orientation on the COVID-19 pandemic outcome at the national level and find out whether some culture-related factors can have a moderating effect on the influence of culture. Methodology Cultural dimension theory of Hofstede is used to quantify the degree of each dimension of culture orientation. The cross-section regression model is adopted to test if culture orientations affect the pandemic outcome, controlling for democracy, economy, education, population, age, and time. Then, a mediational analysis is conducted to examine if policy response is the mediator that culture makes an impact on the pandemic outcome. Finally, a moderation analysis is carried out to determine how each control variable has moderated the influence. Findings The cross-section regression results showed that culture orientation influences the outcome of the COVID-19 pandemic at the 99% confidence level and that among the six cultural dimensions, collectivism-individualism has the most significant impact. It has also been found that policy response is the mediator of cultural influence, and culture-related factors can moderate the influence. Contribution The contribution of this research lies in developing the assertion that culture influences pandemic outcomes. Our findings indicate that collectivism-individualism culture orientation affects the effectiveness of epidemic controls the most among the six culture dimensions. Additionally, our research is the first to study the mediating effect of policy responses and the moderating effect of culture-related factors on the influence of cultural orientation on the pandemic outcome.

Exploring Blood Donation Challenges and Mobilization Mechanisms in North China During the COVID-19 Pandemic: A Qualitative Study.

Purpose: The coronavirus disease 2019 (COVID-19) pandemic disrupted the supply of blood globally, resulting in numerous studies focusing on the challenges in maintaining blood supply, and the responses to it, in countries with a mixed blood donation model. This study explored blood donation challenges and mobilization mechanisms in North China, which employs a non-remunerative donation model, during the COVID-19 pandemic's first wave. Materials and Methods: A qualitative approach was adopted to investigate blood donation practices in Chengde from April to June 2020. Data were collected from eight blood donors, six potential donors, three blood donation station leaders, and two government officials, through semi-structured interviews. Results: The major challenge for blood supply was decreased blood donations, owing to lockdown restrictions, and individual and familial apprehensions. Mobilization mechanisms included bureaucratic and ideological mobilization. However, although group blood donation alleviates the pressure on supply chains during emergencies, it is detrimental to the cultivation of civic engagement in the long run. Conclusion: This study contributes to the understanding of how countries with uncompensated blood donation models respond to public health emergencies. It suggests that striking a balance between the society's and the state's perception of blood donation would allow the state to incorporate the different "voices" of society, and devise an inclusive blood donation policy.

Real-time detection of viruses in aerosols with weak light imaging based on Tesla discharge

The analysis and detection of nucleic acid and specific antigens and antibodies are the most basic technologies for virus monitoring. However, the potential window for applying these technologies exists within a late specific period in the early monitoring and control of unknown viruses, especially human and animal pathogenic viruses transmitted via aerosols, e.g., SARS-CoV-2 and its variants. This is because early, real-time, and convenient monitoring of unknown viruses in the air or exhaled gas cannot be directly achieved through existing technologies. Herein, we report a weak light spectral imaging technology based on Tesla discharge (termed T-DAI) that can quickly monitor for viruses in real time in simulated aerosols with 71% sensitivity and 76% specificity for aerosol virus concentrations exceeding approximately 2800 vp/μl. This technology realizes the rapid detection of low concentrations of viruses in aerosols and could provide an important means for predicting, screening, and monitoring unknown or pandemic pathogenic viruses in the air or exhaled breath of humans and animals. [ FROM AUTHOR] Copyright of Applied Physics Letters is the property of American Institute of Physics 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 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 . (Copyright applies to all s.)

Novel Insights Into the Sulfated Glucuronic Acid-Based Anti-SARS-CoV-2 Mechanism of Exopolysaccharides From Halophilic Archaeon Haloarcula hispanica.

The pandemic caused by SARS-CoV-2 is the most widely spread disease in the 21st century. Due to the continuous emergence of variants across the world, it is necessary to expand our understanding of host-virus interactions and explore new agents against SARS-CoV-2. In this study, it was found exopolysaccharides (EPSs) from halophilic archaeon Haloarcula hispanica ATCC33960 can bind to the spike protein of SARS-CoV-2 with the binding constant KD of 2.23 nM, block the binding of spike protein to Vero E6 and bronchial epithelial BEAS-2B cells, and inhibit pseudovirus infection. However, EPSs from the gene deletion mutant △HAH_1206 almost completely lost the antiviral activity against SARS-CoV-2. A significant reduction of glucuronic acid (GlcA) and the sulfation level in EPSs of △HAH_1206 was clearly observed. Our results indicated that sulfated GlcA in EPSs is possible for a main structural unit in their inhibition of binding of SARS-CoV-2 to host cells, which would provide a novel antiviral mechanism and a guide for designing new agents against SARS-CoV-2.

Structural Comparison and Drug Screening of Spike Proteins of Ten SARS-CoV-2 Variants.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has evolved many variants with stronger infectivity and immune evasion than the original strain, including Alpha, Beta, Gamma, Delta, Epsilon, Kappa, Iota, Lambda, and 21H strains. Amino acid mutations are enriched in the spike protein of SARS-CoV-2, which plays a crucial role in cell infection. However, the impact of these mutations on protein structure and function is unclear. Understanding the pathophysiology and pandemic features of these SARS-CoV-2 variants requires knowledge of the spike protein structures. Here, we obtained the spike protein structures of 10 main globally endemic SARS-CoV-2 strains using AlphaFold2. The clustering analysis based on structural similarity revealed the unique features of the mainly pandemic SARS-CoV-2 Delta variants, indicating that structural clusters can reflect the current characteristics of the epidemic more accurately than those based on the protein sequence. The analysis of the binding affinities of ACE2-RBD, antibody-NTD, and antibody-RBD complexes in the different variants revealed that the recognition of antibodies against S1 NTD and RBD was decreased in the variants, especially the Delta variant compared with the original strain, which may induce the immune evasion of SARS-CoV-2 variants. Furthermore, by virtual screening the ZINC database against a high-accuracy predicted structure of Delta spike protein and experimental validation, we identified multiple compounds that target S1 NTD and RBD, which might contribute towards the development of clinical anti-SARS-CoV-2 medicines. Our findings provided a basic foundation for future in vitro and in vivo investigations that might speed up the development of potential therapies for the SARS-CoV-2 variants.

What are the risk factors of hospital length of stay in the novel coronavirus pneumonia (COVID-19) patients? A survival analysis in southwest China.

BACKGROUND: The global epidemic of novel coronavirus pneumonia (COVID-19) has resulted in substantial healthcare resource consumption. Since patients' hospital length of stay (LoS) is at stake in the process, an investigation of COVID-19 patients' LoS and its risk factors becomes urgent for a better understanding of regional capabilities to cope with COVID-19 outbreaks. METHODS: First, we obtained retrospective data of confirmed COVID-19 patients in Sichuan province via National Notifiable Diseases Reporting System (NNDRS) and field surveys, including their demographic, epidemiological, clinical characteristics and LoS. Then we estimated the relationship between LoS and the possibly determinant factors, including demographic characteristics of confirmed patients, individual treatment behavior, local medical resources and hospital grade. The Kaplan-Meier method and the Cox Proportional Hazards Model were applied for single factor and multi-factor survival analysis. RESULTS: From January 16, 2020 to March 4, 2020, 538 human cases of COVID-19 infection were laboratory-confirmed, and were hospitalized for treatment, including 271 (50%) patients aged ≥ 45, 285 (53%) males, and 450 patients (84%) with mild symptoms. The median LoS was 19 (interquartile range (IQR): 14-23, range: 3-41) days. Univariate analysis showed that age and clinical grade were strongly related to LoS (P<0.01). Adjusted multivariate analysis showed that the longer LoS was associated with those aged ≥ 45 (Hazard ratio (HR): 0.74, 95% confidence interval (CI): 0.60-0.91), admission to provincial hospital (HR: 0.73, 95% CI: 0.54-0.99), and severe illness (HR: 0.66, 95% CI: 0.48-0.90). By contrast, the shorter LoS was linked with residential areas with more than 5.5 healthcare workers per 1,000 population (HR: 1.32, 95% CI: 1.05-1.65). Neither gender factor nor time interval from illness onset to diagnosis showed significant impact on LoS. CONCLUSIONS: Understanding COVID-19 patients' hospital LoS and its risk factors is critical for governments' efficient allocation of resources in respective regions. In areas with older and more vulnerable population and in want of primary medical resources, early reserving and strengthening of the construction of multi-level medical institutions are strongly suggested to cope with COVID-19 outbreaks.

Can infectious disease pandemic impact the long-term volatility and correlation of gold and crude oil markets?

Infectious disease pandemic has been proved to have deep effects on financial and commodity markets. Gold and crude oil as two commonly used commodities to diversify a wide variety of uncertainties are both very susceptible to public health emergencies. The aim of this paper is to quantify the impacts of infectious disease pandemic on the long-term volatility and correlation of gold and crude oil markets by using the DCC-MIDAS approach. The empirical results show that infectious disease pandemic does has prominent positive impacts on the long-run volatilities of both gold and crude oil markets, and these impacts are strengthened with the time lags of infectious disease pandemic. Furthermore, crude oil market is more vulnerable to public health emergencies than gold market. Finally, infectious disease pandemic also has significantly positive effects on the long-term correlation between gold and crude oil markets. These findings have profound implications for gold and crude oil traders in terms of risk management and portfolio allocation.

dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data.

The last 18 months, or more, have seen a profound shift in our global experience, with many of us navigating a once-in-100-year pandemic. To date, COVID-19 remains a life-threatening pandemic with little to no targeted therapeutic recourse. The discovery of novel antiviral agents, such as vaccines and drugs, can provide therapeutic solutions to save human beings from severe infections; however, there is no specifically effective antiviral treatment confirmed for now. Thus, great attention has been paid to the use of natural or artificial antimicrobial peptides (AMPs) as these compounds are widely regarded as promising solutions for the treatment of harmful microorganisms. Given the biological significance of AMPs, it was obvious that there was a significant need for a single platform for identifying and engaging with AMP data. This led to the creation of the dbAMP platform that provides comprehensive information about AMPs and facilitates their investigation and analysis. To date, the dbAMP has accumulated 26 447 AMPs and 2262 antimicrobial proteins from 3044 organisms using both database integration and manual curation of >4579 articles. In addition, dbAMP facilitates the evaluation of AMP structures using I-TASSER for automated protein structure prediction and structure-based functional annotation, providing predictive structure information for clinical drug development. Next-generation sequencing (NGS) and third-generation sequencing have been applied to generate large-scale sequencing reads from various environments, enabling greatly improved analysis of genome structure. In this update, we launch an efficient online tool that can effectively identify AMPs from genome/metagenome and proteome data of all species in a short period. In conclusion, these improvements promote the dbAMP as one of the most abundant and comprehensively annotated resources for AMPs. The updated dbAMP is now freely accessible at http://awi.cuhk.edu.cn/dbAMP.

Identifying anti-coronavirus peptides by incorporating different negative datasets and imbalanced learning strategies.

As the current worldwide outbreaks of the SARS-CoV-2, it is urgently needed to develop effective therapeutic agents for inhibiting the pathogens or treating the related diseases. Antimicrobial peptides (AMP) with functional activity against coronavirus could be a considerable solution, yet there is no research for identifying anti-coronavirus (anti-CoV) peptides with the computational approach. In this study, we first investigated the physiochemical and compositional properties of the collected anti-CoV peptides by comparing against three other negative sets: antivirus peptides without anti-CoV function (antivirus), regular AMP without antivirus functions (non-AVP) and peptides without antimicrobial functions (non-AMP). Then, we established classifiers for identifying anti-CoV peptides between different negative sets based on random forest. Imbalanced learning strategies were adopted due to the severe class-imbalance within the datasets. The geometric mean of the sensitivity and specificity (GMean) under the identification from antivirus, non-AVP and non-AMP reaches 83.07%, 85.51% and 98.82%, respectively. Then, to pursue identifying anti-CoV peptides from broad-spectrum peptides, we designed a double-stages classifier based on the collected datasets. In the first stage, the classifier characterizes AMPs from regular peptides. It achieves an area under the receiver operating curve (AUCROC) value of 97.31%. The second stage is to identify the anti-CoV peptides between the combined negatives of other AMPs. Here, the GMean of evaluation on the independent test set is 79.42%. The proposed approach is considered as an applicable scheme for assisting the development of novel anti-CoV peptides. The datasets and source codes used in this study are available at https://github.com/poncey/PreAntiCoV.

AVPIden: a new scheme for identification and functional prediction of antiviral peptides based on machine learning approaches.

Antiviral peptide (AVP) is a kind of antimicrobial peptide (AMP) that has the potential ability to fight against virus infection. Machine learning-based prediction with a computational biology approach can facilitate the development of the novel therapeutic agents. In this study, we proposed a double-stage classification scheme, named AVPIden, for predicting the AVPs and their functional activities against different viruses. The first stage is to distinguish the AVP from a broad-spectrum peptide collection, including not only the regular peptides (non-AMP) but also the AMPs without antiviral functions (non-AVP). The second stage is responsible for characterizing one or more virus families or species that the AVP targets. Imbalanced learning is utilized to improve the performance of prediction. The AVPIden uses multiple descriptors to precisely demonstrate the peptide properties and adopts explainable machine learning strategies based on Shapley value to exploit how the descriptors impact the antiviral activities. Finally, the evaluation performance of the proposed model suggests its ability to predict the antivirus activities and their potential functions against six virus families (Coronaviridae, Retroviridae, Herpesviridae, Paramyxoviridae, Orthomyxoviridae, Flaviviridae) and eight kinds of virus (FIV, HCV, HIV, HPIV3, HSV1, INFVA, RSV, SARS-CoV). The AVPIden gives an option for reinforcing the development of AVPs with the computer-aided method and has been deployed at http://awi.cuhk.edu.cn/AVPIden/.

Alteration of Autonomic Nervous System Is Associated With Severity and Outcomes in Patients With COVID-19.

BACKGROUND: Previous studies suggest that coronavirus disease 2019 (COVID-19) is a systemic infection involving multiple systems, and may cause autonomic dysfunction. OBJECTIVE: To assess autonomic function and relate the findings to the severity and outcomes in COVID-19 patients. METHODS: We included consecutive patients with COVID-19 admitted to the 21st COVID-19 Department of the east campus of Renmin Hospital of Wuhan University from February 6 to March 7, 2020. Clinical data were collected. Heart rate variability (HRV), N-terminal pro-B-type natriuretic peptide (NT-proBNP), D-dimer, and lymphocytes and subsets counts were analysed at two time points: nucleic-acid test positive and negative. Psychological symptoms were assessed after discharge. RESULTS: All patients were divided into a mild group (13) and a severe group (21). The latter was further divided into two categories according to the trend of HRV. Severe patients had a significantly lower standard deviation of the RR intervals (SDNN) (P < 0.001), standard deviation of the averages of NN intervals (SDANN) (P < 0.001), and a higher ratio of low- to high-frequency power (LF/HF) (P = 0.016). Linear correlations were shown among SDNN, SDANN, LF/HF, and laboratory indices (P < 0.05). Immune function, D-dimer, and NT-proBNP showed a consistent trend with HRV in severe patients (P < 0.05), and severe patients without improved HRV parameters needed a longer time to clear the virus and recover (P < 0.05). CONCLUSION: HRV was associated with the severity of COVID-19. The changing trend of HRV was related to the prognosis, indicating that HRV measurements can be used as a non-invasive predictor for clinical outcome.

COVID-19 Sentiment and the Chinese Stock Market: Evidence from the Official News Media and Sina Weibo.

This study quantitatively measures the Chinese stock market's reaction to sentiments regarding the Novel Coronavirus 2019 (COVID-19). Using 6.3 million items of textual data extracted from the official news media and Sina Weibo blogsite, we develop two COVID-19 sentiment indices that capture the moods related to COVID-19. Our sentiment indices are real-time and forward-looking indices in the stock market. We discover that stock returns and turnover rates were positively predicted by the COVID-19 sentiments during the period from December 17, 2019 to March 13, 2020. Consistent with this prediction, margin trading and short selling activities intensified proactively with growth sentiment. Overall, these results illustrate how the effects of the pandemic crisis were amplified by the sentiments.

How Does Digital Competence Preserve University Students' Psychological Well-Being During the Pandemic? An Investigation From Self-Determined Theory.

This study conceptualized digital competence in line with self-determined theory (SDT) and investigated how it alongside help-seeking and learning agency collectively preserved university students' psychological well-being by assisting them to manage cognitive load and academic burnout, as well as increasing their engagement in online learning during the coronavirus disease 2019 (COVID-19) pandemic. Moreover, students' socioeconomic status and demographic variables were examined. Partial least square modeling and cluster analysis were performed on the survey data collected from 695 students. The findings show that mental load and mental effort were positively related to academic burnout, which was significantly negatively associated with student engagement in online learning. Digital competence did not directly affect academic burnout, but indirectly via its counteracting effect on cognitive load. However, help-seeking and agency were not found to be significantly negatively related to cognitive load. Among the three SDT constructs, digital competence demonstrated the greatest positive influence on student engagement. In addition, female students from humanities and social sciences disciplines and lower-income families seemed to demonstrate the weakest digital competence, lowest learning agency, and least help-seeking behaviors. Consequently, they were more vulnerable to high cognitive load and academic burnout, leading to the lowest learning engagement. This study contributes to the ongoing arguments related to the psychological impact of the COVID-19 pandemic and informs the development of efficient interventions that preserve university students' psychological well-being in online learning.

Detecting SARS-CoV-2 in the Breath of COVID-19 Patients.

In the COVID-19 outbreak year 2020, a consensus was reached on the fact that SARS-CoV-2 spreads through aerosols. However, finding an efficient method to detect viruses in aerosols to monitor the risk of similar infections and enact effective control remains a great challenge. Our study aimed to build a swirling aerosol collection (SAC) device to collect viral particles in exhaled breath and subsequently detect SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR). Laboratory tests of the SAC device using aerosolized SARS-CoV-2 pseudovirus indicated that the SAC device can produce a positive result in only 10 s, with a collection distance to the source of 10 cm in a biosafety chamber, when the release rate of the pseudovirus source was 1,000,000 copies/h. Subsequent clinical trials of the device showed three positives and 14 negatives out of 27 patients in agreement with pharyngeal swabs, and 10 patients obtained opposite results, while no positive results were found in a healthy control group (n = 12). Based on standard curve calibration, several thousand viruses per minute were observed in the tested exhalations. Furthermore, referring to the average tidal volume data of adults, it was estimated that an exhaled SARS-CoV-2 concentration of approximately one copy/mL is detectable for COVID-19 patients. This study validates the original concept of breath detection of SARS-CoV-2 using SAC combined with RT-PCR.