Facing social crises: A research exploring on the impact of COVID-19 to the Taiwan cinema industry

This research presents an overview of the film distribution changes caused by the COVID-19 impact on Taiwan's cinema market and shows a preliminary comparison between numbers of film released, the number of theaters, screening days, tickets sold and box office and film production countries during the period. The goal of this study is to address the factors that affect the strategy to engage the present film distribution market in Taiwan. The result indicates there are significant differences between film release stage and box office. It is proposed for applying an appropriate reduction in Hollywood films' release, such as total quantity control. The result provides domestic films with opportunities to arrange a movie release schedule. This study explores further film distribution policymaking research. © 2023 Author(s).

Chemo- and Regioselective Construction of Functionalized Isocoumarin, Flavone, and Isoquinolinedione via a One-pot Reaction of o-Quinol Acetate and Soft Nucleophiles

A one-pot strategy for the synthesis of substituted isocoumarin, flavone, and isoquinolinedione derivatives through a switchable C-arylation/lactonization or SNAr reaction from a wide range of soft nucleophiles and o-quinol acetates has been developed. This base-mediated protocol proceeds under transition-metal-free conditions and selectively affords various heteroarenes in 13–98% yields from readily prepared or commercially available 1,3-dicarbonyl and α-EWG-substituted carbonyl compounds. The synthetic utility is further demonstrated in the synthesis of potential anti-HIV and anti-coronavirus derivatives and COX-2 inhibitors. In addition, detailed experimental and computational studies are performed to provide an intensive understanding and strong support of the reaction mechanism. © 2023 Wiley-VCH GmbH.

Factors Influencing the Teaching Beliefs of University Faculty Members during Covid-19 Pandemic

Taiwanese university educators’ efficacy is traditionally associated with the belief in aligning teaching and learning outcomes. However, existing research on teacher efficacy involving modern university educators is limited. We bridge this gap by exploring university educators’ perceived efficacy and the factors that influence those perceptions. We surveyed teachers from a national university in southern Taiwan using the Teacher Efficacy Scale and interviews about the source of efficacy beliefs. We obtained 74 survey responses and descriptive statistics and analysis of variance were performed. During the interviews, four qualitative data sets were collected, and we analyzed the data using a continuous comparison analysis method. Generally, participants had medium-to high-levels of perceived efficacy;however, levels differed by gender. Efficacy scores were also higher in course design, technology usage, and classroom management, compared to instructional strategies and learning assessments. The main sources of efficacy perception included mastery experience, role models, student-teacher relationship, professional growth, and student support. Our findings suggest several strategies for follow-up research to promote university educators’ sense of efficacy. © 2022, Editura Lumen. All rights reserved.

The short-term impact of COVID-19 on lung cancer screening participation and adherence

Objective: Screening with low-dose CT (LDCT) effectively reduces mortality from lung cancer. Elective imaging procedures, including lung cancer screening (LCS) LDCT exams, were paused during the height of the COVID-19 pandemic at our institution to conserve healthcare resources and minimize risk as we learned how to mitigate the spread of COVID-19. We aimed to investigate the short-term impact of this COVID-related screening pause on patient participation and adherence to LCS. Methods: We analyzed data of 5133 LDCT screening exams performed at our institution from 2961 patients who were aged 50-80 at each screen between July 31, 2013 and Dec 30, 2020. Independent t-test, Pearson's chi-square and Fisher's exact tests were used to compare monthly average number of LDCTs, on-time adherence rates (i.e., completion of recommended or more invasive follow-up within 15, 9, 5, and 3 months for Lung-RADS 1/2, 3, 4A, and 4B/4X, respectively), percentages of positive screens (Lung-RADS 3 and 4), and lung cancer diagnoses across pre- (July 31, 2013 ∼ Mar 18, 2020), during (Mar 19, 2020 ∼ May 19, 2020), and post-COVID screening pause (May 20, 2020 and after) periods. Results: As expected, compared with the pre-COVID screening pause, there was a significant decrease in monthly average number of LDCTs during the COVID screening pause period (total monthly mean ± sd: pre 55±28 vs during 17±1, p<0.05;new patient monthly mean ± sd: pre 34±16 vs during 6±2, p<0.05). However, a surge in LCS activities was observed after the COVID screening pause period (total: during 17±1 vs post 89±10, p<0.05;new: during 6±2 vs post 42±8, p<0.05), surpassing monthly means in the pre-COVID period (total: pre 55±28 vs post 89±10, p<0.05;new: pre 34±16 vs post 42±8, p<0.05). Overall on-time adherence decreased in the post-COVID period as opposed to the pre-COVID period (p<0.05). There were no significant changes in the percent of positive screens across the three periods (p>0.05). Among the 88 patients diagnosed with lung cancers, 76 diagnoses were made before COVID, 12 diagnoses were made after the COVID pause, and no lung cancer diagnoses were made during the COVID screening pause period. There were no significant differences in terms of the rate of lung cancer (pre 2.9% vs post 1.9%, p>0.05) and the percent of advanced lung cancers (pre 20% vs post 0%, p>0.05) during the two periods. Conclusion: The rate of LCS exams performed at our institution declined during the early days of the COVID-19 pandemic, as elective exams were paused. Once screening resumed, we experienced a surge in the rate of LCS that surpassed pre-COVID rates. Although there were no significant changes in the percentages of positive screens and lung cancer diagnoses shortly after the COVID screening pause period, long-term follow-up is needed to monitor these trends. Additionally, interventions may be needed to improve rates of patients' timely adherence to LCS follow-up recommendations, which decreased in the post-COVID period.

Online Teaching Practice in Chinese Culture Course

In the pandemic of Covid-19, online teaching becomes an important method in education. Different online teaching resources are available such as Tencent (QQ) course groups, Tencent conferences, and Massive Open Online Course (MOOCs). The traditional teaching has also been converted into online platforms. Thus, teachers need to learn and use many information technology applications and training skill packages. This research mainly discusses online teaching and students' response to the online course of Chinese culture. Online teaching is simple to operate and achieve the practical purpose of teaching. © 2020 IEEE.

Latent Retrieval for Large-Scale Fact-Checking and Question Answering with NLI training

Passage retrieval is a part of fact-checking and question answering systems that is critical yet often neglected. Most systems usually rely only on traditional sparse retrieval. This can have a significant impact on the recall, especially when the relevant passages have few overlapping words with the query sentence. Recent approaches have attempted to learn dense representations of queries and passages to better capture the latent semantic content of text. While dense retrieval models have been proven effective in question answering, there is no relevant work for improving evidence retrieval in fact-checking. In this work, we show that training a dense retriever is sufficient to outperform traditional sparse representations in both question answering and fact-checking. We constructed a new dataset called Factual-NLI, comprised of factual claims and their supporting evidence, and demonstrate that using it to train a dense retriever can improve evidence retrieval significantly. Experimental results on the MSMARCO dataset indicate that pre-Training with Factual-NLI, and other NLI datasets, is also effective for large-scale passage retrieval in question answering. Our model is incorporated in a real world semantic search engine that returns snippets containing evidence related to questions and claims about the COVID-19 pandemic. © 2020 IEEE.

Probabilistic Decision Modeling in Social Networks

Bayesian approaches have been successfully applied in social network analysis to study group behaviors such as online information dissemination and voting pattern. The focus has been on estimating the structure and strength of peer influence and its impact on the decisions of an individual. Less attention has been given to incorporating contextual information and individuals' hidden characteristics (or bias). In this work, we examine the social dynamics where social influence and contextual information play pivotal roles in driving one's decision. We design a probabilistic graphical model called CLAP to understand users' decision behavior in a social network, with an emphasis on both social-level and individual-level factors. To this end, the proposed model introduces hidden bias states associated with each actor and jointly estimates each actor's hidden bias state together with the social influence network. We demonstrate the effectiveness of CLAP on two types of social networks, a real-world US Congress network where senators vote on new bills, and online Twitter networks where users debate on the effectiveness of vaccine and lockdown policy during COVID-19. The experiment results show that CLAP outperforms state-of-The-Art game theoretic approaches in predicting user decision. Further, the estimated social influence networks by CLAP has high edge homogeniety ratios. © 2020 IEEE.

Correlation of population mortality of COVID-19 and testing coverage: a comparison among 36 OECD countries.

Although testing is widely regarded as critical to fighting the COVID-19 pandemic, what measure and level of testing best reflects successful infection control remains unresolved. Our aim was to compare the sensitivity of two testing metrics - population testing number and testing coverage - to population mortality outcomes and identify a benchmark for testing adequacy. We aggregated publicly available data through 12 April on testing and outcomes related to COVID-19 across 36 OECD (Organization for Economic Development) countries and Taiwan. Spearman correlation coefficients were calculated between the aforementioned metrics and following outcome measures: deaths per 1 million people, case fatality rate and case proportion of critical illness. Fractional polynomials were used to generate scatter plots to model the relationship between the testing metrics and outcomes. We found that testing coverage, but not population testing number, was highly correlated with population mortality (rs = -0.79, P = 5.975 × 10-9vs. rs = -0.3, P = 0.05) and case fatality rate (rs = -0.67, P = 9.067 × 10-6vs. rs = -0.21, P = 0.20). A testing coverage threshold of 15-45 signified adequate testing: below 15, testing coverage was associated with exponentially increasing population mortality; above 45, increased testing did not yield significant incremental mortality benefit. Taken together, testing coverage was better than population testing number in explaining country performance and can serve as an early and sensitive indicator of testing adequacy and disease burden.