Online Learning Engagement Recognition Using Bidirectional Long-Term Recurrent Convolutional Networks

Background: Online learning is currently adopted by educational institutions worldwide to provide students with ongoing education during the COVID-19 pandemic. However, online learning has seen students lose interest and become anxious, which affects learning performance and leads to dropout. Thus, measuring students' engagement in online learning has become imperative. It is challenging to recognize online learning engagement due to the lack of effective recognition methods and publicly accessible datasets. Methods: This study gathered a large number of online learning videos of students at a normal university. Engagement cues were used to annotate the dataset, which was constructed with three levels of engagement: low engagement, engagement, and high engagement. Then, we introduced a bi-directional long-term recurrent convolutional network (BiLRCN) for online learning engagement recognition in video. Result: An online learning engagement dataset has been constructed. We evaluated six methods using precision and recall, where BiLRCN obtained the best performance. Conclusions: Both category balance and category similarity of the data affect the performance of the results;it is more appropriate to consider learning engagement as a process-based evaluation;learning engagement can provide intervention strategies for teachers from a variety of perspectives and is associated with learning performance. Dataset construction and deep learning methods need to be improved, and learning data management also deserves attention.

Alexithymia and post-traumatic stress disorder symptoms in Chinese undergraduate students during the COVID-19 national lockdown: The mediating role of sleep problems and the moderating role of self-esteem

Objective This study examined whether sleep disturbance was a mediator between alexithymic traits and post-traumatic stress disorder (PTSD) COVID-19 pandemic-related stress symptoms, and explored whether self-esteem moderated the alexithymic contribution to poor sleep and PTSD symptoms. Method A representative sample of young adults (N = 2,485) from six universities in Southwest China completed online self-report surveys on alexithymia, sleep, PTSD, self-esteem, sociodemographic information, and health-related behaviors. Results High alexithymic young adults were found to be more likely to have higher sleep problems and higher PTSD symptoms. The moderated mediation model showed that sleep problems mediated the associations between alexithymia and PTSD symptoms. Alexithymic people with lower self-esteem were more likely to have elevated PTSD symptoms and sleep problems than those with higher self-esteem. Conclusion Targeted psychological interventions for young people who have difficulty expressing and identifying emotions are recommended as these could assist in reducing their post-traumatic psychophysical and psychological problems. Improving self-esteem could also offer some protection for trauma-exposed individuals.

Modeling of a coronavirus disease outbreak at the beginning of 2021 in Shijiazhuang, Hebei Province, China

Objective: To model an outbreak of coronavirus disease 2019 (COVID-19) in Shijiazhuang and forecast its spread trend. Method: We collected confirmed COVID-19 cases from the Health Commission of Hebei Province during the period of January 2 to January 27, 2021. We built a new model (SEIaIcRK), including the contribution of asymptomatic cases, based on the traditional SEIR model to explore and analyze the transmission of COVID-19.

Comparative study of confirmed and suspected undiagnosed cases of COVID-19 in Changning District, Shanghai

Objective: To analyze and compare the differences between the epidemiological data and clinical indicators of confirmed and suspected undiagnosed cases of COVID-19 in Changning District, Shanghai.

Extracorporeal Hemoperfusion Therapy for Sepsis: Multi-Lamellar Microspheres towards Cascade Endotoxin Removal and Broad-Spectrum Radical Eliminating

Sepsis is a life-threatening condition originated from the accumulation of endotoxin in blood in response to infection (e.g., bacterial infection, COVID-19), and then aggravating by the systemic inflammatory responses, microcirculation disorders and oxidative stress, ultimately resulting in the dysfunction of multiple organs. Herein, advanced multi-lamellar microspheres (CPG-Ln-MSs) with cascade endotoxin adsorption and oxidative stress relief functions are constructed as an alternative adsorbent for hemoperfusion therapy towards sepsis. The CPG-Ln-MSs achieve effective endotoxin absorption (nearly 455.3 EU/g) and show excellent broad-spectrum radical scavenging activity for treating oxidative stress triggered by endotoxin accumulation. Specifically, the structural integrity of the multi-layered structure plays a vital role in promoting the efficiency of endotoxin removal and the subsequently scavenging of reactive oxygen species. Hemoperfusion simulation experiments demonstrate that the CPG-Ln-MSs could effectively remove endotoxin with a ratio of 92%, and the following oxidative stress state could be well alleviated, as confirmed by the reduced H2O2 and MDA levels in septic blood. Furthermore, endogenous antioxidants could be restored (recover SOD and CAT activity to 96.9 and 10.1 U/mL, respectively) and the red blood cells could be protected from oxidative damage. This study provides a promising therapeutic strategy and guides the design of future for septic blood purification.

Mathematical Modeling for COVID-19 with Focus on Intervention Strategies and Cost-Effectiveness Analysis (preprint)

The development of appropriate mathematical models and realistic assessments of public health intervention strategies are of great significance to effectively combat the COVID-19 epidemic. In this paper, a novel COVID-19 epidemic model is devised based on the epidemiological states of the individuals and intervention strategies. Some dynamic behaviors of the model, such as forward and backward bifurcation, are analyzed. Specifically, we calibrate the model parameter values using actual COVID-19 data in Brazil by Markov Chain Monte Carlo algorithm such that we can study the effects of interventions on a practical case. Sensitivity analysis shows that non-pharmaceutical interventions are more effective than pharmaceutical interventions in the early stages of the COVID-19 outbreak, and the interventions, namely home isolation, face-mask wearing and media publicity, can effectively reduce the risk of COVID-19 transmission. Based on the new epidemic model, we formulate an optimal control model for studying the control of COVID-19 and then present a cost-effectiveness analysis to unravel the cost and effectiveness of the combination of intervention strategies. The results show that, when taking both the economic cost and the control effectiveness into account, strategy 7 appears to be preferred in inhibiting the COVID-19 outbreak, followed by strategy 5 and strategy 4. By assessing the consequences of these interventions in the real case, we obtain the effective non-pharmaceutical interventions that provide some management implications of controlling COVID-19.

Escaping to nature during a pandemic: A natural experiment in Asian cities during the COVID-19 pandemic with big social media data

As global communities respond to the spread of coronavirus disease 2019 (COVID-19), urban residents worldwide have reduced their mobility, which may have incidentally kept people away from greenspaces. Surprisingly, anecdotal evidence suggests greenspace use surged in Asian cities. In this study, we used the COVID-19 pandemic as a natural experiment to investigate individuals' behavioral changes in greenspace use before and during the pandemic. We created a longitudinal panel dataset comprising Instagram posts from 100,232 users relating to 1185 greenspaces in four Asian cities: Hong Kong, Singapore, Tokyo, and Seoul. We found a 5.3% increase in the odds of people using greenspaces for every 100-case increase in weekly new cases. The models also revealed that people prefer nature parks that are large and close to city centers. In summary, because of the established physical and mental health benefits of greenspaces, people have been escaping to nature to cope with the pandemic in Asian cities. Graphical Unlabelled Image

Is Coronavirus-Related Research Becoming More Interdisciplinary? A Perspective of Co-occurrence Analysis and Diversity Measure of Scientific Articles (preprint)

The outbreak of coronavirus disease 2019 (COVID-19) has had a significant repercussion on the health, economy, politics and environment, making coronavirus-related issues more complicated and difficult to solve adequately by relying on a single field. Interdisciplinary research can provide an effective solution to complex issues in the related field of coronavirus. However, whether coronavirus related research becomes more interdisciplinary still needs corroboration. In this study, we investigate interdisciplinary status of the coronavirus-related fields via the COVID-19 Open Research Dataset (CORD-19). To this end, we calculate bibliometric indicators of interdisciplinarity and a co-occurrence analysis method. The results show that co-occurrence relationships between cited disciplines have evolved dynamically over time. The two types of co-occurrence relationships, Immunology and Microbiology & Medicine and Chemical Engineering & Chemistry, last for a long time in this field during 1990-2020. Moreover, the number of disciplines cited by coronavirus-related research increases, whereas the distribution of disciplines is uneven, and this field tends to focus on several dominant disciplines such as Medicine, Immunology and Microbiology, Biochemistry, Genetics and Molecular Biology. We also gauge the disciplinary diversity of COVID-19 related papers published from January to December 2020; the disciplinary variety shows an upward trend, while the degree of disciplinary balance shows a downward trend. Meanwhile, the comprehensive index 2Ds demonstrates that the degree of interdisciplinarity in coronavirus field decreases between 1990 and 2019, but it increases in 2020. The results help to map the interdisciplinarity of coronavirus-related research, gaining insight into the degree and history of interdisciplinary cooperation.

Social alignment matters: Following pandemic guidelines is associated with better wellbeing (preprint)

Background: In response to the Covid-19 pandemic, most countries implemented physical distancing measures. Many mental health experts warned that through increasing social isolation and anxiety, these measures could negatively affect psychosocial wellbeing. However, socially aligning with others by adhering to these measures may also be beneficial for wellbeing. Methods: We examined these two contrasting hypotheses using cross-national survey data (N=6675) collected fortnightly from participants in 115 countries over 3 months at the beginning of the pandemic. Participants reported their wellbeing, perceptions of how vulnerable they were to Covid-19 (i.e., high risk of infection) and how much they, and others in their social circle and country, were adhering to the distancing measures. Results: Linear mixed-effects models showed that being a woman, having lower educational attainment, living alone and perceived high vulnerability to Covid-19 were risk factors for poorer wellbeing. Being young (18-25) was associated with lower wellbeing, but longitudinal analyses showed that young people’s wellbeing improved over 3 months. In contrast to widespread views that physical distancing measures negatively affect wellbeing, results showed that following the guidelines was positively associated with wellbeing even for people in high-risk groups. Conclusions: These findings provide an important counterpart to the idea that pandemic containment measures such as physical distancing negatively impacted wellbeing unequivocally. Despite the overall burden of the pandemic on psychosocial wellbeing, social alignment with others can still contribute to positive wellbeing. The pandemic has manifested our propensity to adapt to challenges, particularly highlighting how social alignment can forge resilience.

Digital contact does not promote wellbeing, but face-to-face dDoes: A cross-national survey during the Covid-19 pandemic (preprint)

With restrictions on opportunities for face to face (FtF) interactions, Covid-19 lockdowns test the promises of digitally mediated communication (DMC) to foster social contact and wellbeing. In a multinational sample (n= 6436), we investigated how different modes of contact relate to wellbeing during a global pandemic. DMC was more popular than FtF and Covid-19 death rates played a bigger role in DMC use than state stringency measures. FtF contact was positively associated and messaging negatively associated with wellbeing. FtF was especially positive for people who did not perceive any loved ones in their household as vulnerable to the disease, yet did not vary with people’s perception of their own vulnerability. The results suggest that, in the face of the pandemic, men and women of all ages relied on DMC over FtF contact. Despite tangible costs to wellbeing, during the pandemic, people endeavoured to be physically distanced but not socially isolated.

Statistical Assessment of Replicability via Bayesian Model Criticism (preprint)

Assessment of replicability is critical to ensure the quality and rigor of scientific research. In this paper, we discuss inference and modeling principles for replicability assessment. Targeting distinct application scenarios, we propose two types of Bayesian model criticism approaches to identify potentially irreproducible results in scientific experiments. They are motivated by established Bayesian prior and posterior predictive model-checking procedures and generalize many existing replicability assessment methods. Finally, we discuss the statistical properties of the proposed replicability assessment approaches and illustrate their usages by simulations and examples of real data analysis, including the data from the Reproducibility Project: Psychology and a systematic review of impacts of pre-existing cardiovascular disease on COVID-19 outcomes.

Facing the pandemic with trust in science (preprint)

How essential is trust in science to prevent the spread of COVID-19? Previous work shows that people who trust in science are more likely to comply with official guidelines, which suggests that higher levels of compliance could be achieved by improving trust in science. However, analysis of a global dataset (n=4341) suggests otherwise. Trust in science had a small, indirect effect on adherence to the rules. It affected adherence only insofar as it predicted people's approval of prevention measures such as social distancing. Trust in science also mediated the relationship between political ideology and approval of the measures (more conservative people trusted science less and in turn approved of the measures less). These effects varied across countries, and were especially different in the USA. Overall, these results mean that any increase in trust in science is unlikely to yield strong immediate improvements in following COVID-19 rules. Nonetheless, given its relationships with both ideology and individuals' attitudes to the measures, trust in science may be leveraged to yield longer-term and more sustained social benefits.

Reduction and Resumption of Solid Organ Transplants in the COVID-19 Pandemic (preprint)

Background: Reduction of solid organ transplant (SOT) became notable while limited data are available regarding its resumption during the novel coronavirus disease 2019 (COVID-19) pandemic.Methods: Based on the SOT and COVID-19 diagnosis data collected from open-access official organizations, we studied the trend changes of SOT in the U.S.A. since the COVID-19 outbreak, and made the validation using the U.K. dataset. Trend curves were divided into virus-free, restrictive, and/or recovery phases. Kruskal-Wallis H test was performed to assess the differences among those phases with significance set at adjusted P < 0.05 (two-sided).Findings: In a 30-week (January 5 to August 1, 2020) observing period for the U.S.A. dataset, there was an obvious association between the trends of SOT and COVID-19 diagnosis (both overall and death cases) in the 10-week restrictive phase; significant reduction of overall SOTs per day were found in the restrictive phase (median 78.0, IQR 64.6-91.4) compared with the virus-free phase (median 115.0, IQR 97.5-132.5; P < 0.001); The most affected organ transplants were kidney (35.5% reduction) and lung (35.4% reduction), and the most affected U.S. region was Northeast (62.2% reduction). Resumption occurred with no significant difference found between the comparison of recovery (median 118.5, IQR 99.3-137.8) versus virus-free phases (P = 1.000) in overall SOTs per day, as well as those stratified by donor type (deceased and living), organ, and region. The SOT reduction and resumption were validated by the U.K. dataset.Interpretation: Using the U.S.A. and U.K. datasets, our study thoroughly presented the reduction and resumption patterns of SOT during the COVID-19 pandemic. It is essential that transplant units, based on the gained experience, make adequate preparations for any further possible COVID-19 attack.Funding Statement: This study received no external funding.Declaration of Interests: The authors declare no conflicts of interest.Ethics Approval Statement: Exemptions of ethics approval, institutional review board, and informed consent were granted as data used in this study were publicly available.

Could the Ambient Higher Temperature Decrease the Transmissibility of COVID-19 in China? (preprint)

Background: Existing literatures demonstrated that meteorological factors could be of importance in affecting the spread patterns of the respiratory infectious diseases. However, how ambient temperature may influence the transmissibility of COVID-19 remains unclear. Objectives: We explore the association between ambient temperature and transmissibility of COVID-19 in different regions across China. Methods: : The surveillance data on COVID-19 and meteorological factors were collected from 28 provincial level regions in China, and estimated the instantaneous reproductive number ( R t ). The generalized additive model was used to assess the relationship between mean temperature and R t . Results: : There were 12745 COVID-19 cases collected in the study areas. We report the effect of temperature on R t is not of statistical significance, which holds for most of included regions except for those in North China. Conclusions: We found little statistical evidence for that the higher temperature may reduce the transmissibility of COVID-19.

Social influence matters: We follow pandemic guidelines most when our close circle does (preprint)

Why do we adopt new rules, such as social distancing? Although human sciences research stresses the key role of social influence in behaviour change, most COVID-19 campaigns emphasise the disease’s medical threat. In a global dataset (n= 6675), we investigated how social influences predict people’s adherence to distancing rules during the pandemic. Bayesian regression analyses controlling for stringency of local measures showed that people distanced most when they thought their close social circle did. Such social influence mattered more than people thinking distancing was the right thing to do. People’s adherence also aligned with their fellow citizens’, but only if they felt deeply bonded with their country. Self-vulnerability to the disease predicted distancing more for people with larger social circles. Collective efficacy and collectivism also significantly predicted distancing. To achieve behavioural change during crises, policymakers must emphasise shared values and harness the social influence of close friends and family.

Comorbidity and its impact on 1,590 patients with COVID-19 in China: A Nationwide Analysis (preprint)

Objective: To evaluate the spectrum of comorbidities and its impact on the clinical outcome in patients with coronavirus disease 2019 (COVID-19). Design: Retrospective case studies Setting: 575 hospitals in 31 province/autonomous regions/provincial municipalities across China Participants: 1,590 laboratory-confirmed hospitalized patients. Data were collected from November 21st, 2019 to January 31st, 2020. Main outcomes and measures: Epidemiological and clinical variables (in particular, comorbidities) were extracted from medical charts. The disease severity was categorized based on the American Thoracic Society guidelines for community-acquired pneumonia. The primary endpoint was the composite endpoints, which consisted of the admission to intensive care unit (ICU), or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared among patients with COVID-19 according to the presence and number of comorbidities. Results: Of the 1,590 cases, the mean age was 48.9 years. 686 patients (42.7%) were females. 647 (40.7%) patients were managed inside Hubei province, and 1,334 (83.9%) patients had a contact history of Wuhan city. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 399 (25.1%) reported having at least one comorbidity. 269 (16.9%), 59 (3.7%), 30 (1.9%), 130 (8.2%), 28 (1.8%), 24 (1.5%), 21 (1.3%), 18 (1.1%) and 3 (0.2%) patients reported having hypertension, cardiovascular diseases, cerebrovascular diseases, diabetes, hepatitis B infections, chronic obstructive pulmonary disease, chronic kidney diseases, malignancy and immunodeficiency, respectively. 130 (8.2%) patients reported having two or more comorbidities. Patients with two or more comorbidities had significantly escalated risks of reaching to the composite endpoint compared with those who had a single comorbidity, and even more so as compared with those without (all P<0.05). After adjusting for age and smoking status, patients with COPD (HR 2.681, 95%CI 1.424-5.048), diabetes (HR 1.59, 95%CI 1.03-2.45), hypertension (HR 1.58, 95%CI 1.07-2.32) and malignancy (HR 3.50, 95%CI 1.60-7.64) were more likely to reach to the composite endpoints than those without. As compared with patients without comorbidity, the HR (95%CI) was 1.79 (95%CI 1.16-2.77) among patients with at least one comorbidity and 2.59 (95%CI 1.61-4.17) among patients with two or more comorbidities. Conclusion: Comorbidities are present in around one fourth of patients with COVID-19 in China, and predispose to poorer clinical outcomes.

Correlation Analysis Between Disease Severity and Inflammation-related Parameters in Patients with COVID-19 Pneumonia (preprint)

Aim: The new coronavirus pneumonia (COVID-19) outbreaking at the end of 2019 is highly contagious. Crude mortality rate reached 49% in critical patients. Inflammation matters on disease progression. This study analyzed blood inflammation indicators among mild, severe and critical patients, helping to identify severe or critical patients early. Methods: In this cross-sectional study, 100 patients were included and divided to mild, severe or critical groups. Correlation of peripheral blood inflammation-related indicators with disease criticality was analyzed. Cut-off values for critically ill patients were speculated through the ROC curve. ResultsSignificantly, disease severity were associated with age (R=-0.564, P<0.001), interleukin-2 receptor (IL2R) (R=-0.534, P<0.001), interleukin-6 (IL-6) (R=-0.535, P<0.001), interleukin-8 (IL-8) (R=-0.308, P<0.001), interleukin-10 (IL-10) (R=-0.422, P<0.001), tumor necrosis factor (TNF) (R=-0.322, P<0.001), C-reactive protein (CRP) (R=-0.604, P<0.001), ferroprotein (R=-0.508, P<0.001), procalcitonin (R=-0.650, P<0.001), white cell counts (WBC) (R=-0.54, P<0.001), lymphocyte counts (LC) (R=-0.56, P<0.001), neutrophil count (NC) (R=-0.585, P<0.001) and eosinophil counts (EC) (R=-0.299, P=0.01). ConclusionWith following parameters such as age >67.5 years, IL2R >793.5U/mL, CRP >30.7ng/mL, ferroprotein >2252g/L, WBC>9.5*10^9/L or NC >7.305*10^9/L, the progress of COVID-19 to critical stage should be closely observed and possibly prevented. Inflammation is closely related to severity of COVID-19, and IL-6, TNF and IL-8 might be promising therapeutic targets.