We discuss a pandemic management framework using symptom-based quick response (QR) codes to contain the spread of COVID-19. In this approach, symptom-based QR health codes are issued by public health authorities. The codes do not retrieve the location data of the users; instead, two different colors are displayed to differentiate the health status of individuals. The QR codes are officially regarded as electronic certificates of individuals’ health status, and can be used for contact tracing, exposure risk self-triage, self-update of health status, health care appointments, and contact-free psychiatric consultations. This approach can be effectively deployed as a uniform platform interconnecting a variety of responders (eg, individuals, institutions, and public authorities) who are affected by the pandemic, which minimizes the errors of manual operation and the costs of fragmented coordination. At the same time, this approach enhances the promptness, interoperability, credibility, and traceability of containment measures. The proposed approach not only provides a supplemental mechanism for manual control measures but also addresses the partial failures of pandemic management tools in the abovementioned facets. The QR tool has been formally deployed in Fujian, a province located in southeast China that has a population of nearly 40 million people. All individuals aged ≥3 years were officially requested to present their QR code during daily public activities, such as when using public transportation systems, working at institutions, and entering or exiting schools. The deployment of this approach has achieved sizeable containment effects and played remarkable roles in shifting the negative gross domestic product (–6.8%) to a positive value by July 2020. The number of cumulative patients with COVID-19 in this setting was confined to 363, of whom 361 had recovered (recovery rate 99.4%) as of July 12, 2020. A simulation showed that if only partial measures of the framework were followed, the number of cumulative cases of COVID-19 could potentially increase ten-fold. This approach can serve as a reliable solution to counteract the emergency of a public health crisis; as a routine tool to enhance the level of public health; to accelerate the recovery of social activities; to assist decision making for policy makers; and as a sustainable measure that enables scalability.

We evaluate a Bluetooth-based mobile contact-confirming app, COVID-19 Contact-Confirming Application (COCOA), which is being used in Japan to contain the spread of COVID-19, the disease caused by the novel virus termed SARS-COV-2. The app prioritizes the protection of users’ privacy from a variety of parties (eg, other users, potential attackers, and public authorities), enhances the capacity to balance the current load of excessive pressure on health care systems (eg, local triage of exposure risk and reduction of in-person hospital visits), increases the speed of responses to the pandemic (eg, automated recording of close contact based on proximity), and reduces operation errors and population mobility. The peer-to-peer framework of COCOA is intended to provide the public with dynamic and credible updates on the COVID-19 pandemic without sacrificing the privacy of their information. However, cautions must be exercised to address critical concerns, such as the rate of participation and delays in data sharing. The results of a simulation imply that the participation rate in Japan needs to be close 90% to effectively control the spread of COVID-19.

Energy consumption has become a necessity in today’s world, and economies in developing nations cannot thrive without it. Countries with less developed economies face the same challenges of achieving sustained economic growth as those with more advanced economies. Herein, we examine the environmental Kuznets curve (EKC) hypothesis by looking at the interplay between GDP growth, energy use, agricultural output, and the effects of carbon dioxide (CO₂) emissions. From 1991 to 2016, we used panel and quantile regression analyses to compare emissions in nine developing countries with those in 13 developed countries. There is the beginning of a reverse U-shaped relationship between agricultural energy use and greenhouse gas emissions. As a result, the verified EKC hypothesis paves the way for a watershed moment in the progress of industrialized nations’ economies. The estimated results of agriculture have a favorable impact on CO₂ emissions by 15.16 percent but a negative influence of 2.92 percent on CO₂ emissions from using liquid fuels, leading to more severe environmental deterioration. Additionally, in developing countries, feed cropping, deforestation, biomass burning, and deep soil and cropping all have detrimental consequences on the ecosystem. There is a negative correlation between CO₂ emissions and economic growth in developing countries and their energy consumption. Although the EKC hypothesis for CO₂ emissions was rejected at lower quantiles, it was validated for Qatar, Canada, China, and other high-emitting economies according to the empirical estimation of quantile regression. The findings of this study have important policy implications for reducing carbon dioxide emissions, suggesting that policymakers account for the stage of economic growth currently being experienced when formulating measures to cut energy use and protect the environment. Possible solutions to mitigate environmental degradation include enactment of policies to reduce energy consumption.

Interactionist and social-cultural perspectives on second language acquisition suggest that interactions between teachers and students offer promising avenues for acquiring Chinese as a second language, which the vast majority of international students consider difficult. Computer-mediated communication is far safer than face-to-face encounters during the present pandemic. Three aims are being investigated here. It is important to first analyze the differences between traditional classroom and online learning by different modes, then analyze the various ways teachers use computer-mediated communication, and finally analyze the challenges and opportunities presented by online Chinese as a second language courses using qualitative research methods. Three teachers and 84 students are analyzed statistically in terms of their multimodal interactions, and the quality of their weekly classroom exchanges is assessed through an interpretive analysis of questionnaire data, all in the name of a mixed-methods approach. Particular attention was paid to the challenges of online tutoring for students, the discrepancy between instructor and student understandings, and the use of several teaching strategies with international students. The online classroom environment places unique demands on the quality of student-teacher communication. Different strategies must be used when teaching non-native speakers of Chinese as a second language compared to teaching in a traditional classroom setting.

Big data analytics (BDA) is a wide and deep application in e‐commerce, which impacts positively on the global economy, especially the U.S. and China who have done well. This paper seeks to examine the relative influence of theoretical research and practical activities of BDA in e‐commerce to explain the differences between the U.S. and China according to the two main literature databases, Web of Science and CNKI, respectively, and by employing other samples that present retail e‐commerce sales and the number of some data companies founded in the U.S. and China each year. We further determine the reasons leading to the difference between the U.S. and China in BDA in e‐commerce, which can help managers devise appropriate business strategies in e‐commerce for each of them, and provide a proof of the significant relationship of theoretical research and practical activities in BDA in e‐commerce. In addition, the variables related to big data companies show a moderation effect rather than mediating effect relative to the practice of theoretical research in e‐commerce in the United States, but they show a moderate effect and mediating effects in China. The results of this study help clarify doubts regarding the development of China’s e‐commerce. Moreover, three orientations in e‐commerce using BDA and the use of quantum computing in e‐commerce to solve existing e‐commerce problems are explored to provide better evidence for decision‐making that could be valuable in future research.