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Air pollution and infectious diseases (such as the COVID-19 pandemic) have attracted considerable attention from governments and scientists worldwide to find the best solutions to address these issues. In this study, a new simultaneous antibacterial and particulate matter (PM) filtering Ag/graphene-integrated non-woven polypropylene textile was fabricated by simply immersing the textile into a Ag/graphene-containing solution. The Ag/graphene nanocomposite was prepared by reducing Ag ions on the surface of graphene nanoplatelets (GNPs) using the leaf extract. The prepared Ag/graphene textile was characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), Energy Dispersive X-ray (EDX), and contact angle measurements. The results showed excellent integration of the Ag/GNP nanocomposite into the non-woven polypropylene textile matrix. The prepared textile exhibited superhydrophobicity with a contact angle of 152°. The maximum PM removal percentage of the Ag/GNP-integrated textile was determined to be 98.5% at an Ag/GNP content of 1.5% w/w and a silicon adhesive of 1% w/w. The Ag/GNP textile exhibited high antibacterial activity toward Escherichia coli with no sign of bacteria on the surface. Remarkably, the as-prepared Ag/GNP textile was highly durable and stable and could be reused many times after washing. Graphical : [Figure not available: see fulltext.] © 2023, The Author(s), under exclusive licence to Springer Nature B.V.
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We investigate whether, and to what extent, banks exploit their discretion over loan loss provisions to achieve their management purposes during the pandemic. Using a sample of US banks during the current COVID-19 outbreak, we find that banks are more eager to use discretionary loan loss provisions in response to the worsening pandemic situation. We find in particular that banks use discretionary loan loss provisions to manage regulatory capital, smooth income and signal private information to outsiders. Overall, this paper enriches the literature on bank discretionary behaviour during the difficult time, especially during the current COVID-19 pandemic, and therefore, it has important implications for banking supervisor and bank stakeholders.
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The outbreak of the COVID-19 pandemic has impacted the development of the global economy. As most developing and third world countries are heavily dependent on agriculture and agricultural imports, the agricultural supply chains (ASC) in all these countries are exposed to unprecedented risks following COVID-19. Therefore, it is vital to investigate the impact of risks and create resilient ASC organizations. In this study, critical risks associated with ASC were assessed using a novel Analytical Hierarchy Process based on spherical fuzzy sets (SF-AHP). The findings indicated that depending on the scope and scale of the organization, supply risks, demand risks, financial risks, logistics and infrastructure risks, management and operational risks, policy and regulatory risks, and biological and environmental risks all have a significant impact on ASC. This research highlighted that themost significant criterion is specified as Transportation (TP), followed by Market (MA) and Policy (PO), respectively. Meanwhile, Technology (TL) is the least significant criterion. The study's findings can help managers with a holistic view of the agriculture supply chain risk mitigation. Furthermore, this study may assist managers in sharing information about the processing of agricultural products from top to bottom to manage risk in the supply chain.
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The main objective of this study is to comprehensively investigate individuals' vaccination intention against COVID-19 during the second wave of COVID-19 spread in Vietnam using a novel hybrid approach. First, the Decision-Making Trial and Evaluation Laboratory based on Grey Theory (DEMATEL-G) was employed to explore the critical factors of vaccination intention among individuals. Second, Partial Least Squares-Structural Equation Modeling (PLS-SEM) was applied to test the hypotheses of individual behavioral intention to get the vaccine to prevent the outbreak of COVID- 19. A panel of 661 valid respondents was collected from June 2021 to July 2021, and confidentiality was maintained for all data obtained. The results identified that perception of COVID-19 vaccination and trust in vaccination strategy directly associated with individuals' COVID-19 immunization. Hence, the perceived severity of COVID-19 has an indirect impact onCOVID- 19 vaccination intentions via the perception of the COVID-19 vaccine. These findings indicated that the government's information about vaccines is necessary for the new phase of vaccination intervention strategies in Vietnam. Therefore, the study suggests that the government needs to give complete information about the role of vaccines prioritizes transparency in official information about COVID-19 vaccines to allay concerns about side effects, allowing for the most appropriate policy formulation and implementation to encourage public vaccination. Future studies can apply PLS-SEM and other MCDMmodels with the fuzzy, hesitant numbers to re-evaluate the feasibility, validity and reliability of this research's proposed model. © 2022 Tech Science Press. All rights reserved.
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Recently, the Covid-19 pandemic has become very complicated and seriously affecting the economy as well as society in every countries in the world. In this chapter, we explore the solution of Computer Vision for handling the Covid-19 pandemic situation. The given scenarios based on deep learning techniques are used to monitor the traffic of people and vehicles through the checkpoints to control the in-out movement in significant areas. In addition, we also need to pay attention to complying with the regulations on wearing masks and ensuring a safe social distance in public places. From there, the proposed system will effectively support organizations to deal with the Covid-19 pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.
Subject(s)
COVID-19 , COVID-19/epidemiology , Contact Tracing , Humans , PandemicsABSTRACT
We present the design and development of a data visualization service (RAMPVIS) in response to the urgent need to support epidemiological modeling workflows during the COVID-19 pandemic. Facing a set of demanding requirements and several practical challenges, our small team of volunteers had to rely on existing knowledge and components of services computing, while thinking on our feet in configuring services composition and adopting suitable approaches to services engineering. Through developing the RAMPVIS service, we have gained useful experience of ensuring conformation to services computing standards, enabling rapid development and early deployment, and facilitating effective and efficient maintenance and operation with limited resources. This experience can be valuable to the ongoing effort for combating the COVID-19 pandemic, and provides a blueprint for visualization service development when future needs for visual analytics arise during emergency response. IEEE
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Purpose: Covid-19 has caused an unprecedented situation for the tourism industry with slumping demand during the outbreak and many uncertainties about tourist behavior in the post-pandemic. This study is aimed to discover the distribution in the behavior of tourists in Vietnam, whose government has taken serious and early actions towards the health crisis and among the earliest to reopen the economy. Research design, data, and methodology: We adopted a mixed-method approach - combining qualitative interviews with quantitative research using a questionnaire survey. Through the form of the online survey through social networking channels: Facebook, Gmail. The study received 261 valid responses for analysis. Multivariate analysis techniques were used: descriptive statistics, exploratory factor analysis (EFA). Results: From the data and result of EFA, the result showed that the distribution of tourist behavior could be grouped into four main factors, including (1) the general impacts, (2) travel-related behaviors;(3) attitudes and preferences regarding modes of tours and destinations;(4) awareness of safety and hygiene. Conclusions: These results highlighted the importance of the theory of perceived risks in explaining the travelers’ prudent decisions. In addition, this study provides practical implications for policymakers and various stakeholders of Vietnam’s tourism industry in formulating the recovery strategy. © 2021. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://Creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
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As an essential and exciting topic in financial management, MCDM has been widely used in evaluating financial performance to improve the suitability and reliability of financial indicators with respect to the impacts of both qualitative and quantitative information. This chapter aims to present a hybrid MCDM approach to evaluate the Vietnamese banking sector's performance under COVID-19 impacts. The proposed method utilizes The Criteria Importance Through Intercriteria Correlation (CRITIC) technique to determine objective weights of financial ratios. Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is employed to obtain the cause-effect relationship and the subjective weights based on experts’ judgments. Bank alternatives’ ranking is estimated using the
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The COVID 19 pandemic has led to a new global recession and is still causing a lot of issues because of the delays in the employment of people. This scenario has severe consequences for many countries’ labor markets in the world. This problem’s complexity and importance requires an integrated method of subjective and objective evaluation rather than intuitive decisions. This research aims to investigate sustainable indexes for assessing the unemployment problem by using a Multi-Criteria Decision-Making Model (MCDM). Grey theory and Decision Making Trial and Evaluation Laboratory (GDEMATEL) are deployed to transform the experts’ opinions into quantitative data. The analysis based on 20 crucial criteria is employed to determine the weights of sustainability of unemployment problems. The results revealed that the top ten of determinants are Economic growth, Industrialization, Foreign direct investment, Real GDP per capita, Education level, Trade Openness, Capacity Utilization Rate, Urbanization, Employability skills, Education system expansion, which have the most significant effects on the unemployment rate under COVID 19 impacts. Furthermore, GDEMATEL could effectively assess the sustainable indicators for unemployment problems in “deep and wide”aspects. The study proposes the Grey MCDM model, contributes to the literature, provides future research directions, and helps policymakers and researchers achieve the best solutions to the unemployment problems under “economic shocks.” © Copyright: The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.