ABSTRACT
COVID-19, caused by the novel coronavirus SARS-CoV-2, has put most of the world under lockdown. Despite approved vaccines, COVID-19 cases, hospitalizations, and deaths have remained on the rise. Rapid diagnosis and necessary public health measures are still key parts to contain the pandemic. Here, the colorimetric isothermal nucleic acid amplification tests (iNAATs) for SARS-CoV-2 detection based on loop-mediated isothermal amplification (LAMP), cross-priming amplification (CPA), and polymerase spiral reaction (PSR) were designed and compared in performance for the first time. The findings showed that, for the detection of SARS-CoV-2 genomic-RNA, LAMP outperformed both CPA and PSR, reaction mix exhibiting the limit of detection (LOD) of roughly 43.14 copies/reaction. The results can be read with the naked eye within 45 minutes, without cross-reactivity to closely related coronaviruses. The direct detection of SARS-CoV-2 RNA in simulated specimens by iNAATs was also successful. Additionally, the lyophilized reagents for LAMP reactions maintained the sensitivity and LOD of the liquid assays. The colorimetric LAMP assay was validated using clinical samples, showing 98.1% sensitivity and 100% specificity upon using extracted samples and 82.4% sensitivity and 86.2% specificity upon using unextracted specimens. The results indicate that the direct colorimetric LAMP assay developed is highly suitable for detecting SARS-CoV-2 at point-of-care.
ABSTRACT
The COVID-19 pandemic has had a massive impact on the global aviation industry. As a result, the airline industry has been forced to embrace new technologies and procedures in order to provide a more secure and bio-safe travel. Currently, the role of smart technology in airport systems has expanded significantly as a result of the contemporary Industry 4.0 context. The article presents a novel construction of an intelligent mobile robot system to guide passengers to take the plane at the departure terminals at busy airports. The robot provides instructions to the customer through the interaction between the robot and the customer utilizing voice communications. The usage of the Google Cloud Speech-to-Text API combined with technical machine learning to analyze and understand the customer's requirements are deployed. In addition, we use a face detection technique based on Multi-task Cascaded Convolutional Networks (MTCNN) to predict the distance between the robot and passengers to perform the function. The robot can guide passengers to desired areas in the terminal. The results and evaluation of the implementation process are also mentioned in the article and show promise.
ABSTRACT
The purpose of the present study is to evaluate the relationship between socio-economic development and environmental degradation. The analysis spans the years 1990 to 2018. Long-term causality of CO2 emissions is observed, but a short-term basis exists between feedback variables. The results demonstrated a favorable association between the selected constructs. In addition, Variance decomposition analysis results revealed that GDP contributed 3% to 14% to future CO2 emissions fluctuations;energy consumption was 3% to 14%;renewable energy use ranged from 1% to 3.4%;the proportion of tourism ranged from 4.2% to 10%;and the proportions of receiving improved water, sanitation, and electricity were 33.3%, 1.12%, and 2.01%, respectively. In addition, the research concludes with substantial policy implications for sustainable development that would assist practitioners in enhancing sustainable growth © 2022,Sadra Medical Sciences Journal. All Rights Reserved.
ABSTRACT
This chapter, written by Nghiem-Phu and Tran, examines how hotel businesses in Vietnam overcome the challenges caused by COVID-19 by transforming lodgings into quarantine facilities. Analysing press and user-generated content, it was found that both positive and negative images were attached to the quarantine hotels. The findings have demonstrated that corporate social responsibility (CSR) could be implemented to sustain business in the current circumstances while preparing for brand strengthening for recovery.
ABSTRACT
Since 2020, COVID-19 has completely changed the daily activities of almost all nations, and education has been heavily affected. Becauseof school closures, face-to-face classrooms were halted or replaced with onlineclasses in which both lecturers and learners had to adjust their teaching andlearning styles to cope with unexpected situations. The ‘new normal’ of learningfrom homes, spending hours staring at screens, and struggling with piles ofonline tasks has somehow demotivated students to continue learning. This studyexplores factors affecting students’ desire to take online courses after experiencinge-learning during COVID-19. Nine hundred fifty-five students of VietnamNational University took part in the survey via an online questionnaire. Datawere analyzed using SPSS 20;correlation, hierarchical regression was employedto examine how online factors influence students’ decision. The research resultsshowed that skill enhancement, self-regulated learning, lecturer interactionduring the course were among the most important predictors of students’ desire totake more online courses. In contrast, student interaction imposed no significantinfluence. This study gives the theoretical background for other studies in thesame field and suggests practical implications for governments and universitiesto implement online training better to cope with the pandemic © 2022, International Journal of Interactive Mobile Technologies. All Rights Reserved.
ABSTRACT
Poverty is a global issue and a lot of attention and efforts of the international community have been made to deal with this problem. Especially in the context of the COVID-19 pandemic, when a part of the population could fall into poverty due to rising unemployment and income deduction, identifying the factors affecting poverty becomes particularly important. Financial inclusion has been recognized as one important factor affecting poverty reduction. This research is conducted to investigate the impact of financial inclusion and other control variables on poverty reduction. The study employs Principal Component Analysis (PCA) to build a financial inclusion index. Using 2SLS and the GMM regressions for a panel data of 29 European countries during the period from 2011 to 2017, the results show that financial inclusion has a negative impact on poverty at all three poverty lines of USD1.9, 3.2, and 5.5 per day. The proportion of the population aged 15-64 and the ratio of service employment to the total number of employment also have a negative effect on all three levels of POV1.9, POV3.2, and POV5.5. In contrast, GDP per capita, trade openness and the proportion of the population aged from 25 with at least secondary school education have a positive impact on poverty at three levels of poverty. The results confirm that financial inclusion plays an important role in reducing poverty. The study provides a number of recommendations to governments to promote financial inclusion and reduce poverty in the countries. © 2021 Walter de Gruyter GmbH, Berlin/Boston.
ABSTRACT
Environmental protection and high economic growth are the global requirement and have attracted the special attention of researchers and policymakers. Thus, the current study is also going to examine the impact of green finance that includes green investment and green loan on the economic growth of Vietnam. The data have been obtained from the central bank of Vietnam and World Bank Indicators (WDI) from 1986 to 2019. This study also executed the Autoregressive Distributed Lag (ARDL) approach to examine the links among the variables. The results exposed that green finance along with all control variables have a positive association with economic growth. These outcomes have guided regulators to increase their focus on green finance that could increase the economic growth in the country.
ABSTRACT
Purpose: The purpose of this study is to examine the impact of green finance (i.e. green investment, green security and green credit) along with capital formation and government educational expenditures on the economic development of (ASEAN) countries. Design/methodology/approach: The data were gathered from the central banks of all ASEAN countries and the World Bank Indicators between 2008 and 2019. The fixed-effect model and generalized method of moments were used to check the nexus between the constructs. Findings: The results revealed that green finance along with capital formation and government educational expenditures have a positive association with the economic development of ASEAN countries. Research limitations/implications: The study carries some limitations, even though it addresses the underlying variables comprehensively. These limitations provide opportunities to future researchers and authors to expand the scope and accuracy of their study. This research investigation has been supported by the data collected from a single source. Though data collection is maintained correctly, it is still recommended to the upcoming scholars to acquire data to reconfirm the same findings using multiple data sources. The data collected from using some specific data source may be limited in scope and may hinder the comprehensive elaboration of the underlying variables and their mutual relationship. Therefore, the utilization of multiple sources of data collection gives data sufficient to meet the requirement of an okay quality research study. The study is about the economies of ASEAN countries. It checks the influences of green finance development on economic activities and the country's economic growth in ASEAN countries' economies. Thus, its results are valid only in the economies of these countries, and this research investigation lacks generalizability. For generalizability, the authors must consider the underlying variables in the world's vast economies. They must adopt a standard scale to judge the impacts of green financial development on economic development. Besides, the study analyzes the economic factors, economic conditions and their effects on the country's position in the world economy in the face of a severe epidemic like COVID-19. Thus, the results may be different in the case of the normal situation. So, a general standardized study is recommended to be conducted in the upcoming days. Originality/value: Green finance has significant capability to improve the global economy, especially amidst the COVID-19 pandemic. This study is beneficial for policymakers to develop policies related to economic development with reference to green finance and also helps future research on a similar topic. © 2021, Emerald Publishing Limited.
ABSTRACT
The article aims to develop an empirical approach to identifying the key factors in the political elite behavior effectiveness in combating the COVID-19 pandemic propagation exemplified by Vietnam. Using regression analysis and the Chow test, we identified the key behavioral factors that affect the effectiveness of the fight against the COVID-19 pandemic in terms of mortality rates and the state of the economy. The study sample was formed by data from 67 countries worldwide for 2020. The results suggest that the Rule of Law significantly influences the state of the economy in a pandemic. Their impact on economic efficiency does not depend on the world leaders' gender. The COVID-19 mortality rate is also significantly affected by the Global Health Security Index, gender, and cultural factors. Based on the constructed linear multivariate regression models, we calculated the contribution of significant factors to the effectiveness of combating the pandemic in Vietnam, their stimulating and de-stimulating effects compared to the average values of these indicators for the sample countries. © 2021, Institute of Eastern Europe and Central Asia. All rights reserved.