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1.
Contemporary Educational Research Quarterly ; 30(1):119-147, 2022.
Article in Chinese | Scopus | ID: covidwho-1912066

ABSTRACT

During the outbreak of the new coronavirus disease COVID-19 (Coronavirus Disease 2019) epidemic, online learning has changed the traditional learning model. The purpose of this research was to explore how the antecedent of self-directed learning approach and attitudes of online learning can affect participants’ perceptions of cognitive fatigue and immersion during online learning that reflect their perceptions of the learning ineffectiveness of online learning. Design/methodology/approach This research adopted convenience sampling to collect data. During the period of the COVID-19 epidemic, the target participants were higher education students who adopted distance learning in the lockdown area of China. A questionnaire was posted on the Tencent questionnaire system for participants to fill out. The sample data of 155 college students were validly collected and subjected to test reliability and structural equation modeling using the SmartPLS 3.0 software to verify the research model proposed in this study. Findings/results The study found that self-directed learning attitudes were negatively related to online learning cognitive fatigue, but were positively related to cognitive presence;the self-directed learning approach was negatively related to online learning cognitive fatigue, but was positively related to cognitive presence. Moreover, online learning cognitive fatigue was positively related to perceived learning ineffectiveness, whereas cognitive presence was negatively related to perceived learning ineffectiveness. Originality/value In the new learning mode under the threat of the COVID-19 epidemic, this study explored the interaction between students' selfdirected learning, focused learning, and cognitive fatigue during the online learning process. Although there is no in-depth discussion on related research that affects learners’ perception of their learning outcomes, based on TAT (Trait activation theory), this study first divided self-directed learning into two categories: approach and attitude, and found how self-directed learning traits can predict online learning mental state, such as deactivator-cognitive fatigue and activator–immersion that affected the perceived effectiveness of online learning during the COVID-19 epidemic. Suggestions/implications The results of this study divided self-directed learning into approach and attitudes and indicated that both approach and attitudes of self-directed learning should be promoted by school teachers. Moreover, to design good distance learning programs, it is necessary to stimulate students’ mental state to learn and explore actively. Teachers can design interactive prompts or a reminding service in the teaching process to promote students’ cognitive presence and reduce their Internet cognitive fatigue, and to strengthen the overall learning effect. © 2022. Contemporary Educational Research Quarterly.All Rights Reserved

2.
Embase; 2020.
Preprint in English | EMBASE | ID: ppcovidwho-337379

ABSTRACT

The metagenome embedded in urban sewage is an attractive new data source to understand urban ecology and assess human health status at scales beyond a single host. Analyzing the viral fraction of wastewater in the ongoing COVID-19 pandemic has shown the potential of wastewater as aggregated samples for early detection, prevalence monitoring, and variant identification of human diseases in large populations. However, using census-based population size instead of real-time population estimates can mislead the interpretation of data acquired from sewage, hindering assessment of representativeness, inference of prevalence, or comparisons of taxa across sites. Here, we show that taxon abundance and sub-species diversisty in gut-associated microbiomes are new feature space to utilize for human population estimation. Using a population-scale human gut microbiome sample of over 1,100 people, we found that taxon-abundance distributions of gut-associated multi-person microbiomes exhibited generalizable relationships with respect to human population size. Here and throughout this paper, the human population size is essentially the sample size from the wastewater sample. We present a new algorithm, MicrobiomeCensus, for estimating human population size from sewage samples. MicrobiomeCensus harnesses the inter-individual variability in human gut microbiomes and performs maximum likelihood estimation based on simultaneous deviation of multiple taxa's relative abundances from their population means. MicrobiomeCensus outperformed generic algorithms in data-driven simulation benchmarks and detected population size differences in field data. New theorems are provided to justify our approach. This research provides a mathematical framework for inferring population sizes in real time from sewage samples, paving the way for more accurate ecological and public health studies utilizing the sewage metagenome.

3.
MEDLINE;
Preprint in English | MEDLINE | ID: ppcovidwho-326588

ABSTRACT

Reports of new-onset diabetes and diabetic ketoacidosis in individuals with COVID-19 have led to the hypothesis that SARS-CoV-2, the virus that causes COVID-19, is directly cytotoxic to pancreatic islet beta cells. This would require binding and entry of SARS-CoV-2 into host beta cells via cell surface co-expression of ACE2 and TMPRSS2, the putative receptor and effector protease, respectively. To define ACE2 and TMPRSS2 expression in the human pancreas, we examined six transcriptional datasets from primary human islet cells and assessed protein expression by immunofluorescence in pancreata from donors with and without diabetes. ACE2 and TMPRSS2 transcripts were low or undetectable in pancreatic islet endocrine cells as determined by bulk or single cell RNA sequencing, and neither protein was detected in alpha or beta cells from these donors. Instead, ACE2 protein was expressed in the islet and exocrine tissue microvasculature and also found in a subset of pancreatic ducts, whereas TMPRSS2 protein was restricted to ductal cells. The absence of significant ACE2 and TMPRSS2 co-expression in islet endocrine cells reduces the likelihood that SARS-CoV-2 directly infects pancreatic islet beta cells through these cell entry proteins.

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