Preventing COVID-19 from the perspective of industrial information integration: Evaluation and continuous improvement of information networks for sustainable epidemic prevention

COVID-19 and its impact on the profit of mango value chain actors

The unprecedented impact of the pandemic on both activities and profit of actors draws out the various areas of the value chain that need to be strengthened to ensure resilience in the face of global shock. This study fills the gap by assessing the extent at which COVID-19 impacted the profit of mango value chain actors in southern Ghana. It also analyzed the governance structure and the existing linkages in the dissemination of market information in relation to the profit of the actors. A two-year panel survey on 240 respondents was conducted in 2020 through a multi-stage sampling technique in Greater Accra, Eastern and Volta regions of Ghana. Net Farm Income, Social Network Analysis and Difference-in-Difference models were used in analyzing the data. Findings revealed that mango processors have more bargaining power and make the most profit while producers receive more information than other actors. Farmer-based organizations were found to be the prominent node and influential in the dissemination of market information within the value chain. The outbreak of COVID-19 negatively impacted the profit of mango producers and distributors; however, processors had a positive impact on their profit. The study therefore demonstrated that producers and distributors were vulnerable to the effect of the COVID-19 shock, whilst processors were robust to the shocks. Thus, reformed policies by all stakeholders for emergency preparedness should be targeted especially at those vulnerable actors in the chain. Additionally, FBOs, retailers and other key stakeholders should be considered in policy development to enhance market information dissemination.

Investigating the spatiotemporal characteristics and medical response during the initial COVID-19 epidemic in six Chinese cities

In the future, novel and highly pathogenic viruses may re-emerge, leading to a surge in healthcare demand. It is essential for urban epidemic control to investigate different cities' spatiotemporal spread characteristics and medical carrying capacity during the early stages of COVID-19. This study employed textual analysis, mathematical statistics, and spatial analysis methods to examine the situation in six highly affected Chinese cities. The findings reveal that these cities experienced three phases during the initial outbreak of COVID-19: "unknown-origin incubation", "Wuhan-related outbreak", and "local exposure outbreak". Cities with a high number of confirmed cases exhibited a multicore pattern, while those with fewer cases displayed a single-core pattern. The cores were distributed hierarchically in the central built-up areas of cities' economic, political, or transportation centers. The radii of these cores shrank as the central built-up area's level decreased, indicating a hierarchical decay and a core-edge structure. It suggests that decentralized built environments (non-clustered economies and populations) are less likely to facilitate large-scale epidemic clusters. Additionally, the deployment of designated hospitals in these cities was consistent with the spatial distribution of the epidemic; however, their carrying capacity requires urgent improvement. Ultimately, the essence of prevention and control is the governance of human activities and the efficient management of limited resources about individuals, places, and materials through leveraging IT and GIS technologies to address supply-demand contradictions.

Dynamic risk spillover effect and path of risk transmission across industrial sectors in China during COVID-19 epidemic

Understanding the dynamic link between the development of COVID-19 pandemic and industry sector risk spillovers is crucial to explore the underlying mechanisms by which major public health events affect economic systems. This paper applies ElasticNet method proposed by Diebold and Yilmaz (2009, 2012, 2014) to estimate the dynamic risk spillover indicators of 20 industrial sectors in China from 2016 to 2022, and systematically examines the impact of industry risk network fluctuations and the transmission path caused by COVID-19 shock. The findings reveal that risk spillovers of Chinese industries show a dynamic change of "decline-fluctuation-rebound" with the three phases of COVID-19 epidemic. At the beginning of the epidemic, machinery and equipment, paper and printing, tourism and hotels, media and information services, and agriculture were the exporters of epidemic risk, while materials, transportation equipment, commercial trade, health care, and environmental protection were the importers of epidemic risk; However, as the epidemic developed further, the direction and effect of risk transmission in the industry was reversed. Examining the network characteristics of the pair sectors, we found that under the epidemic shock, the positive risk spillover from tourism and hotels, culture, education and sports to consumer goods, finance, and energy industries was significantly increased, and finance and real estate industries were affected by the risk impact of more industries, while the number of industries affected by information technology and computer industry was significantly reduced. This paper shows that there is inter-industry risk transmission of the COVID-19 epidemic shock, and the risk transmission feeds back in a cycle between industries as the epidemic develops, driving the economy into a vicious circle. The role of the service sector in blocking the spread of negative shocks from the epidemic should be emphasized and brought into play to avoid increasing the overall economic vulnerability. This study will help to deepen the understanding of scholars and policy makers on the network transmission effects of the epidemic.

The impact of healthcare industry convergence on the performance of the public health system: a geospatial modeling study of provincial panel data from China

Objective

This paper examines the impact of healthcare industry convergence on the performance of the public health system in the eastern, central, and western regions of China.

Methods

Public health performance was measured by a composite index of three standards: average life expectancy at birth, perinatal mortality, and maternal mortality. The healthcare industry convergence was measured using a coupling coordination degree method. The spatial lag, spatial error, and spatial Durbin models were used to estimate the effect of healthcare industry convergence on public health system performance and this effect's spatial dependence and heterogeneity across eastern, central, and western China using panel data from 30 Chinese provinces from 2002 to 2019.

Results

The convergence of the healthcare industry significantly promotes regional public health [β =0.576, 95% CI: (0.331,0.821)]. However, the convergence does not have a spatial spillover effect on the public health system at the national level. Additionally, analysis of regional heterogeneity shows that the direct effects of healthcare industry convergence on public health are positive and statistically significant for Eastern China, statistically insignificant for Central China, and positive and statistically significant for Western China. The indirect effects are negative, statistically significant, positive, statistically significant, and statistically insignificant for these three regions, respectively.

Conclusion

Policy efforts should strengthen the convergence between the healthcare industry and relevant industries. It can produce more current healthcare services to improve public health and reduce regional health inequality.

The Evaluation of the Departmental Resources and Positions Within the Inter-Departmental Collaborative Networks: A Case Study on the Joint Prevention and Control Mechanism in China

Introduction

This study examines the inter-departmental emergency response dynamics within China's Joint Prevention and Control Mechanism (JPCM). Departments' positions in the network are fundamental to understanding the overall structure and operation of the collaborative emergency response. Moreover, understanding the influence of departmental resources on departmental positions promotes efficient inter-departmental collaboration.

Methods

The study uses regression analysis to empirically investigate the departmental resources to departments' participation in the JPCM collaboration. The independent variable adopts the departments' positions by statistically presenting the departments' centrality using social network analysis. The dependent variables employ departmental resources, including departmental duties, staffing levels, and approved annual budgets based on data from the government website.

Results

The result of social network analysis shows that in JPCM inter-departmental collaboration, the Ministry of Transport, Health Commission, Ministry of Public Security, Ministry of Emergency Management, Ministry of Culture and Tourism, Ministry of Education, and Development and Reform Commission are mainly involved. The regression analysis result indicates that the department's engagement in collaborative actions is determined and influenced by the department's statutory duties. The more statutory duties department has, the more it is in a critical position and role for JPCM.

Discussion

The study can assist emergency management practitioners and academic departments in utilizing evidence-based approaches to justify the collaboration and involvement of participating departments. The analysis of the collaborative networks considering JPCM in China by the participation and organization logic is of fundamental significance for arguing for complementing COVID emergency management and inter-departmental emergency collaboration studies.

How to effectively prevent alienation behavior of prefabricated construction developers: an optimization analysis of regulatory strategies

Prefabricated buildings (PBs) contribute to sustainable development, and their development largely depends on the active participation of developers. However, based on the characteristics of different stages of PBs' development and the goals of "14th Five-Year Plan" for architecture in China, it is an urgent practical problem for the government to encourage developers' active participation while regulating their alienation behavior. To address such problem, this paper uses the evolutionary game method to explore the government's reasonable regulatory strategies for developers' behavior in different development stages of PBs. Meanwhile, this paper explores the boundary of government's regulatory strength on PBs based on actual situation in China, which help the government to drive high-quality development of PBs with effective policy resources. Results reveal that the strict regulatory strategies have limited effects in the incubation stage of PBs. In the growth stage, it is necessary to adjust the regulatory strategies appropriately. The dynamic linear regulatory strategy can enable the PBs to achieve the phased goal, and the dynamic nonlinear regulatory strategy can help to achieve the optimal goal of PBs in China. In the maturity stage, the government does not need to deliberately regulate due to the considerable profits of developers. The regulatory strategy of "light reward and heavy punishment" is better when it is adopted to promote the development of PBs in the growth stage. The research also provides valuable suggestions for government regulators to formulate reasonable and dynamic regulatory policies for PBs.

COVID-19 health policy evaluation: integrating health and economic perspectives with a data envelopment analysis approach

The COVID-19 pandemic is a global challenge to humankind. To improve the knowledge regarding relevant, efficient and effective COVID-19 measures in health policy, this paper applies a multi-criteria evaluation approach with population, health care, and economic datasets from 19 countries within the OECD. The comparative investigation was based on a Data Envelopment Analysis approach as an efficiency measurement method. Results indicate that on the one hand, factors like population size, population density, and country development stage, did not play a major role in successful pandemic management. On the other hand, pre-pandemic healthcare system policies were decisive. Healthcare systems with a primary care orientation and a high proportion of primary care doctors compared to specialists were found to be more efficient than systems with a medium level of resources that were partly financed through public funding and characterized by a high level of access regulation. Roughly two weeks after the introduction of ad hoc measures, e.g., lockdowns and quarantine policies, we did not observe a direct impact on country-level healthcare efficiency, while delayed lockdowns led to significantly lower efficiency levels during the first COVID-19 wave in 2020. From an economic perspective, strategies without general lockdowns were identified as a more efficient strategy than the full lockdown strategy. Additionally, governmental support of short-term work is promising. Improving the efficiency of COVID-19 countermeasures is crucial in saving as many lives as possible with limited resources.

Enhancing engineering ethics education (EEE) for green intelligent manufacturing: Implementation performance evaluation of core mechanism of green intelligence EEE

The characteristics of green intelligent (GI) engineering ethics emphasize the necessity of GI engineering ethics education (EEE). The ethics education of GI engineering is in the development stage, and it is urgent to fully understand the significance of evaluating the development of GI EEE. Only based on the GI manufacturing situation system to understand the implementation status of the core education of EEE can we objectively grasp the improvement space of GI EEE. In this study, the corresponding indicators were selected from three dimensions of cultivation education, collaborative education, and situational education to form the element community of evaluation indicators. The fuzzy analytic hierarchy process and the fuzzy comprehensive evaluation method were used to empirically evaluate the implementation of the key mechanism of GI EEE. The results are as follows. (1) The key education of GI EEE includes cultivation education of micro dimension, collaborative education of medium dimension, and situational education of macro dimension. (2) The most important education is to strengthen the ethics education of GI engineering in the training process of college students. The coordination of GI EEE is becoming more and more important, and the integration and construction are the important pursuit of GI EEE. (3) The cultivation education, collaborative education, and situational education of GI EEE are all at a general level. (4) There is not only a gap between theory and practice in GI EEE but also insufficient attention to localization and coordination issues. The willingness of the government to participate in the ethical education of GI engineering is very insufficient. The optimized space of training education includes teaching cases and full-cycle ethical education.

Analysis and Forecast of the Use of E-Commerce in Enterprises of the European Union States

This study analyzes the use of e-commerce by European Union enterprises. Based on an analysis of the evolution of the percentage of enterprises that perform e-commerce and the share of total turnover obtained from e-commerce, for the period of 2003–2020, a forecast for 2025 was made. These aspects were analyzed for 2015–2020 from the perspective of the Digital Economy and Society Index (DESI), highlighting the importance of e-commerce in the economic growth of each country by analyzing the share of gross domestic product (GDP) obtained from e-commerce in GDP. For studying the evolution of the indicators, a comparative analysis of the situation of individual and aggregate EU countries was performed, highlighting the evolution trends and determining the annual average growth rate indicator, used later for the short-term forecast. For the 2025 forecast, six regression models were used for the empirical estimation of the data. The results of the analysis show that the share of companies performing e-commerce and the turnover in e-sales vary significantly depending on the size of enterprises, and the results of the forecast estimate that by 2025 there will be a significant increase in e-commerce in most European countries.

Developing a Conceptual Partner Matching Framework for Digital Green Innovation of Agricultural High-End Equipment Manufacturing System Toward Agriculture 5.0: A Novel Niche Field Model Combined With Fuzzy VIKOR

Digital green innovation (DGI) is the core factor that affects the digitalization and decarbonization strategy of agricultural high-end equipment manufacturing (AHEM) system. Although AHEM enterprises actively cooperate with academic research institutes to develop agricultural high-end equipment, there are many obstacles in the process of DGI. Moreover, the integration of digital technology and green innovation from the perspective of partner matching for the AHEM system has not been fully introduced in current literature. Hence, this study aimed to (i) establish a suitable framework system for the AHEM system in general, (ii) quantify the selection of DGI by academic research institutions based on niche theory, and (iii) propose an extended niche field model combined with fuzzy VIKOR model. First, a theoretical framework consisting of three core elements of technology superposition, mutual benefit, and mutual trust, and technological complementarity was constructed based on niche intensity and niche overlap degree. DGI ability superposition of technology, mutual trust, and technical complementarity are beneficial for transferring DGI knowledge from academic research institutes to the AHEM industry. Second, triangle fuzzy number and prospect theory combined with the VIKOR method were introduced into the field theory to construct the complementary field model of DGI resources. The niche field model has been successfully applied to practical cases to illustrate how the model can be implemented to solve the problem of DGI partner selection. Third, the results of a case study show that the criteria framework and the niche field model can be applied to real-world partner selection for AHEM enterprises. This study not only puts forward the standard framework of niche fitness evaluation based on niche theory but also establishes the niche domain model of innovation partner selection management based on niche theory. The standard framework and novel niche field model can help enterprises to carry out digital green innovation in the development of high-end agricultural equipment. The study has the following theoretical and practical implications: (i) constructing a criteria framework based on niche theory; (ii) developing a novel niche field model for DGI partner selection of AHEM enterprises; and (iii) assisting AHEM enterprises to perform DGI practice.

Insight into the Balancing Effect of a Digital Green Innovation (DGI) Network to Improve the Performance of DGI for Industry 5.0: Roles of Digital Empowerment and Green Organization Flexibility

Under the background of double carbon target and digital intelligence era, the innovation resources and innovation environment that manufacturing enterprises rely on have shown exponential growth. Digital green innovation (DGI) has gradually become the mainstream paradigm of innovation. How to achieve a balance between a local DGI network (LDGIN) and a remote DGI network (RDGIN) and how to use the role of digital empowerment and green organization flexibility to improve the performance of DGI are very important issues facing manufacturing enterprises at present. However, this problem has not been fully addressed in the existing research. In this study, the influence mechanism of LDGIN and RDGIN on the DGI performance of manufacturing enterprises was revealed, considering the moderating role of digital empowerment and green organization flexibility. The linear regression method was used to analyze the 562 valid data obtained by questionnaire survey. The results of this study are as follows. The effect of the DGI network on manufacturing enterprises’ DGI performance is heterogeneous because of LDGIN and RDGIN. The establishment of embedded links in a DGI network inevitably requires manufacturing enterprises to pay the corresponding costs. The over-embedding of manufacturing enterprises into RDGIN will have a negative impact on DGI performance. The balance between LDGIN and RDGIN has an important impact on manufacturing enterprises’ operation. The comprehensive balance and relative balance indexes constructed in this paper show that an appropriate balance can promote the improvement of the DGI performance of manufacturing enterprises. Digital transformation and organizational structure innovation are changing the business model of manufacturing enterprises and can regulate the relationship between the LDGIN and RDGIN and the DGI performance of manufacturing enterprises. The balance of DGI network embedding in practice shows the important role and enlightening significance of local and remote search in developing countries.

Assessing the Capability of Government Information Intervention and Socioeconomic Factors of Information Sharing during the COVID-19 Pandemic: A Cross-Country Study Using Big Data Analytics

(1) Background: This study introduces a novel computational approach to examine government capabilities in information intervention for risk management, influential agents in a global information network, and the socioeconomic factors of information-sharing behaviors of the public across regions during the COVID-19 pandemic. (2) Methods: Citation network analysis was employed to gauge the online visibility of governmental health institutions across regions. A bipartite exponential random graph modeling (ERGM) procedure was conducted to measure network dynamics. (3) Results: COVID-19 response agencies in Europe had the highest web impact, whereas health agencies in North America had the lowest. Various stakeholders, such as businesses, non-profit organizations, governments, and educational institutions played a key role in sharing the COVID-19 response by agencies’ information given on their websites. Income inequality and GDP per capita were associated with the high online visibility of governmental health agencies. Other factors, such as population size, an aging population, death rate, and case percentage, did not contribute to the agencies’ online visibility, suggesting that demographic characteristics and health status are not predictors of sharing government resources. (4) Conclusions: A combination of citation network analysis and ERGM helps reveal information flow dynamics and understand the socioeconomic consequences of sharing the government’s COVID-19 information during the pandemic.

Collaborative elicitation process for sustainable manufacturing: A novel evolution model of green technology innovation path selection of manufacturing enterprises under environmental regulation

Due to promote manufacturing enterprises to carry out green technology innovation practice smoothly, achieve the goal of energy conservation and emission reduction, and win green competitive advantage, this paper first divides the green technology innovation path into two types, namely internal independent R&D of green technology (IIGT) and external green technology introduction (EGTI), and analyzes the operation mechanism of these two types of paths. Secondly, a two-agent game model of different types of environmental regulation tools on the choice of green technology innovation path of manufacturing enterprises is constructed. To be sure, the manufacturing enterprises include the leader enterprise A and the follower enterprise B. It is assumed that the two groups of manufacturing enterprises produce the same products or provide the same services in the natural state without considering other influencing factors. Finally, stability analysis and numerical simulation are employed to compare and analyze the heterogeneous effects of different environmental regulation tools on the path selection of green technology innovation in manufacturing enterprises.The simulation shows that when the government adopts or does not adopt environmental regulation means, the system, leader enterprise A and follower enterprise B will eventually choose the path of IIGT or EGTI respectively after a long-term evolution process. However, the effects of subsidy for green technology innovation and carbon tax rate on the path selection of green technology innovation are different among the three parties. Specifically, when the government adopts the means of subsidy for green technology innovation, the leader enterprise A will actively choose the the path of IIGT earlier than the follower enterprise B. On the contrary, when the government adopts the means of carbon tax, the leader enterprise A will actively choose the the path of IIGT later than the follower enterprise B. The research of this paper is helpful to explore the green and sustainable development mode of China’s manufacturing industry under the dual constraints of environment and resources, and provides decision support for the relevant national departments to make relevant policies.

Enhancing Digital Innovation for the Sustainable Transformation of Manufacturing Industry: A Pressure-State-Response System Framework to Perceptions of Digital Green Innovation and Its Performance for Green and Intelligent Manufacturing

Low carbon and digitalization are the general trends of manufacturing upgrading and transformation. Digital technology enables the whole process of green manufacturing and breaks down the spatial barrier. To achieve the dual carbon goals, the pressure-state-response (PSR) model, in which digital technology enables the green innovation of the manufacturing industry, was theoretically analyzed in this study. The measurement system of the digital green innovation (DGI) in the manufacturing industry was constructed according to the PSR framework. An evaluation model based on the analytic hierarchy process and the deviation maximization technique for order preference by similarity to an ideal solution method was constructed to measure the level of DGI. The results of this study from Chinese manufacturing are as follows. (i) The measurement system of the level of DGI in manufacturing industry includes a pressure system, state system and response system. (ii) In the past five years, the comprehensive index of the DGI in manufacturing industry has generally shown a trend of fluctuating rise. There are overall low and unbalanced phenomena in all regions. The gap decreased from 0.1320 to 0.1187, showing a gradually narrowing trend. (iii) Compared with other regions, the composite index of DGI is generally higher in the regions with a better ecological environment in the east and a more developed economy in the north. State parameters are higher than pressure and response parameters in most areas. (iv) Compared with other regions, the composite index of DGI in western and southern regions is lower, and the parameters of pressure, status and response are basically coordinated. (v) The application degree of digital technology, the emission intensity of waste water/exhaust gas of output value of one hundred million yuan and the expenditure intensity of digital technology adopted by enterprises are the key influencing factors of DGI in the manufacturing industry. This study not only proposed an evaluation index system of the digital green innovation level, but also puts forward policy guidance and practical guidance of digital technology to accelerate the green and intelligent manufacturing industry.

Developing a Conceptual Partner Selection Framework: Digital Green Innovation Management of Prefabricated Construction Enterprises for Sustainable Urban Development

Digital green innovation management activities are the core of low-carbon intelligent development of prefabricated construction enterprises (PCEs) for sustainable urban development. PCEs have to seek joint venture partners to avoid the financial risk of digital green innovation projects. The purpose of this study is to develop a conceptual partner selection framework for the digital green innovation management of prefabricated construction towards urban building 5.0. In this study, first, symbiosis theory and six analysis methods were integrated to innovatively build a 3W1H-P framework system for the joint venture capital partner selection of digital green innovation projects. Second, the dual combination weighting method was innovatively proposed to avoid subjective and objective deviation in attribute weight and time weight. Finally, empirical research was carried out to verify the scientific nature, reliability, and practicability of the framework system and selection model. The results of this study show that the framework system and selection model proposed can be used to assist PCEs to select joint investment partners of digital green and innovative projects for sustainable urban development.

Advanced data integration in banking, financial, and insurance software in the age of COVID-19

This study contributes to our understanding of how the emergence of the COVID-19 pandemic changes the global Banking Financial Services and Insurance (BFSI) landscape. Before the COVID-19 pandemic, BFSIs corporate strategy was solely aligned to the quest for operational efficiency. However, during the ongoing COVID-19 pandemic, global BFSIs are forced to adopt digital transformation in their operations due to a rise in transaction volumes. The ongoing COVID-19 pandemic already triggers holistic innovations concerning the global BFSI's product, process, concept, trend, or idea. Thus, the BFSI cannot survive without efficient and innovative system software for global operations. The study plots the hype cycle to identify relevant technologies to deal with real-world business problems. The hype cycle indicates that the need for advanced data integration is growing and COVID-19 pandemic has already triggered it. The study argues that the incorporation of data integration might be challenging initially for BFSIs but eventually it may result in an efficient model to handle these types of pandemic or unexpected circumstances.

CoCross: An ICT Platform Enabling Monitoring Recording and Fusion of Clinical Information Chest Sounds and Imaging of COVID-19 ICU Patients

Monitoring and treatment of severely ill COVID-19 patients in the ICU poses many challenges. The effort to understand the pathophysiology and progress of the disease requires high-quality annotated multi-parameter databases. We present CoCross, a platform that enables the monitoring and fusion of clinical information from in-ICU COVID-19 patients into an annotated database. CoCross consists of three components: (1) The CoCross4Pros native android application, a modular application, managing the interaction with portable medical devices, (2) the cloud-based data management services built-upon HL7 FHIR and ontologies, (3) the web-based application for intensivists, providing real-time review and analytics of the acquired measurements and auscultations. The platform has been successfully deployed since June 2020 in two ICUs in Greece resulting in a dynamic unified annotated database integrating clinical information with chest sounds and diagnostic imaging. Until today multisource data from 176 ICU patients were acquired and imported in the CoCross database, corresponding to a five-day average monitoring period including a dataset with 3477 distinct auscultations. The platform is well accepted and positively rated by the users regarding the overall experience.

Prevention schemes for future fresh agricultural products (FAPs) supply chain: mathematical model and experience of guaranteeing the supply of FAPs during the COVID-19 pandemic

BACKGROUND

The COVID-19 outbreak caused short-term disruptions in the supply chain of fresh agricultural products (FAPs), which exposed the vulnerability of the existing FAP supply chain. With pandemic control being widely coordinated, the supply chain of FAPs was gradually optimized and improved. However, after the outbreak of COVID-19, achieving an effective supply of FAPs in future pandemics has become a key issue. The present work therefore aimed to construct a three-level supply chain based on the Stackelberg game model, consisting of suppliers, third-party logistics (TPL), and retailers, to guarantee the supply of FAPs. COVID-19 pandemic factors such as virus infection coefficients and pandemic prevention efforts were fully integrated into the model.

RESULTS

Compared with the wholesale prices of FAPs, preservation efforts and pandemic prevention efforts have huge impacts on the retail prices of FAPs. When suppliers are in the leading position, the quality assurance effort level is positively correlated with the optimal profit. Compared with this situation, when FAP retailers are in the leading position, TPL providers show higher levels of pandemic prevention effort and FAP preservation effort. With an increase in consumer preference for pandemic prevention, the profits of supply-chain members when FAP retailers are in the leading position will gradually increase.

CONCLUSION

This study reveals an effective supply mechanism for FAPs in metropolitan areas during the COVID-19 pandemic and describes the authors' experience of guaranteeing the quality and safety of FAPs for future pandemic cases. © 2021 Society of Chemical Industry.

Pedagogy and innovative care tenets in COVID-19 pandemic: An enhancive way through Dentistry 4.0

The global oral healthcare sector has now woken to implement Dentistry 4.0. The implementation of this revolution is feasible with extensive digital and advanced technologies applications and the adoption of new sets of processes in dentistry & its support areas. COVID-19 has bought new challenges to dental professionals and patients towards their customised requirements, regular dental health checkups, fast-paced and safe procedures. People are not visiting the dentist even for mild cases as they fear COVID-19 infection. We see that this set of technologies will help improve health education and treatment process and materials and minimise the infection. During the COVID-19 pandemic, there is a need to understand the possible impact of Dentistry 4.0 for education and innovative care. This paper discusses the significant benefits of Dentistry 4.0 technologies for the smart education platform and dentistry treatment. Finally, this article identifies twenty significant enhancements in dental education and effective care platforms during the COVID-19 pandemic by employing Dentistry 4.0 technologies. Thus, proper implementation of these technologies will improve the process efficiency in healthcare during the COVID-19 pandemic. Dentistry 4.0 technologies drive innovations to improve the quality of internet-connected healthcare devices. It creates automation and exchanges data to make a smart health care system. Therefore, helps better healthcare services, planning, monitoring, teaching, learning, treatment, and innovation capability. These technologies moved to smart transportation systems in the hospital during the COVID-19 Pandemic. Modern manufacturing technologies create digital transformation in manufacturing, optimises the operational processes and enhances productivity.

Evaluating Supply Chain Collaboration Barriers in Small- and Medium-Sized Enterprises

The disruption has a significant impact on supply chain collaboration (SCC) which is an important task to improve performance for many enterprises. This is especially critical for small- and medium-sized enterprises (SMEs). We developed a decision-modeling framework for analyzing SCC barriers in SMEs for the emerging economy in Bangladesh. Through literature review and expert opinion survey, we have identified a comprehensive list of SCC barriers under four main categories, namely, information-related, communication-related, intra-organizational, and inter-organizational barriers. Then we applied the Grey DEMATEL and Fuzzy Best-Worst methods to evaluate these SCC barriers and compared the results. We also conducted a sensitivity analysis to assess the robustness of the proposed approach. The study reveals that lack of communication is the most crucial barrier in SCC, providing a model for assessing barriers in other emerging economies. This study contributes to the literature by analyzing SCC barriers and by comparing the results obtained from two different MCDM methods. The findings of this study can help decision-makers to plan for overcoming the most prioritized SCC barriers which ultimately contribute to improving the resilience and sustainability performances of SMEs.

New IT driven rapid manufacturing for emergency response

COVID-19, which is rampant around the world, has seriously disrupted people's normal work and living. To respond to public urgent needs such as COVID-19, emergency supplies are essential. However, due to the special requirements of supplies, when an emergency occurs, the supply reserve mostly cannot cope with the high demand. Given the importance of emergency supplies in public emergencies, rapid response manufacturing of emergency supplies is a necessity. The faster emergency supplies and facilities are manufactured, the more likely the pandemic can be controlled and the more human lives are saved. Besides, new generation information technology represented by cloud computing, IoT, big data, AI, etc. is rapidly developing and can be widely used to address such situations. Therefore, rapid response manufacturing enabled by New IT is presented to quickly meet emergency demands. And some policy suggestions are presented.

Reacting to the COVID-19 pandemic through digital connectivity with customers: the Italian experience

The COVID-19 has deeply impacted the firm’s competitiveness because of the restrictions that limited the relationships with existing and new customers. The pandemic has pushed firms to rely on digital technologies to redefine business processes as well as customer relationships and marketing strategies. The digital technological portfolio firms may rely on to face the COVID-19 related challenges spanning from the established web-based technologies to the more recent Industry 4.0 tools related to the fourth industrial revolution. In this regard, the paper aims at exploring which digital technologies allowed firms to positively react to the pandemic to overcome their constraints in managing the market relationships. Based on an original qualitative analysis on 26 Italian SMEs carried out during the first Italian lockdown in 2020, the paper identifies three strategies in the use of digital technologies to support customer relationship management and market expansion. It emerges specifically the strategic importance of web-based technologies (videoconferencing, CRM and e-commerce) to support firm competition and performance through customer interactions and digital experience, advancing the literature on firms’ reaction strategies during turbulent and crisis times.

Advancements in Biosensor Technologies for Medical Field and COVID-19 Pandemic

World health organization (WHO) has declared the COVID-19 outbreak as a public health emergency of international concern and then as a pandemic on 30th of January and 11th of March 2020, respectively. After such concern, the world scientific communities have rushed to search for solutions to bring down the disease’s spread, fast-paced vaccine development, and associated medical research using modern technologies. Biosensor technologies play a crucial role in diagnosing various medical diseases, including COVID-19. The present paper describes the major advancement of biosensor-based technological solutions for medical diagnosis, including COVID-19. This review-based work covers the biosensors and their working principles in the context of medical applications. The paper also discusses different biosensors and their applications to tackle medical issues, including this ongoing pandemic.

Technological Resources for Fighting COVID-19 Pandemic Health Issues

The COVID-19 pandemic has had a global effect with several people dying daily due to the dreaded disease. Therefore, each individual has a duty to support the efforts of their countries either financially, socially, technically, or by any other means to contribute to the fight against the COVID-19 pandemic. During this crisis, engineers can come up with innovations to fight the pandemic. One of the reasons for the death of a patient suffering from COVID-19 was the lack of resources required for patient care. The doctors who are taking care of COVID patients could get infected due to lack or the deficiency of available safety kits. Some of the resources required to fight COVID-19 are personal protective equipment (PPE) (e.g. gloves, gowns, face masks and shields for respiratory and eye protection respectively), mechanical ventilators and body vital monitoring devices. Engineers can contribute to the fight against COVID-19, by developing compact size ventilators, 3D printed face shield, masks, door handles, hand sanitizer, etc. The available medicines to fight the disease are still under development and trials with limited options at present has led to deaths among patients mostly those who are elderly or having any co-morbid condition. The deficiency of medicine availability can be resolved up to some extent by applying tools of supply chain management.

Tissue Engineering and its Significance in Healthcare During COVID-19 Pandemic: Potential Applications and Perspectives

In the present times of the COVID-19 pandemic, there is a great need for new therapeutic and diagnostic strategies to prevent infectious diseases worldwide. Tissue engineering covers the phenomenon of the evolution of tissue, its behavior and growth factors that are better supported in the medical environment. This area of tissue engineering can support the treatment of infected patients of COVID-19 and can help fight the current crisis and viral outbreaks in general. This study aims to identify the significant advancement of tissue engineering for taking up the challenges posed by COVID-19. Major challenges faced during the COVID-19 pandemic situation in the current scenario are discussed. The significant advancements of tissue engineering in the medical field are listed in chronological order. The positive impacts of tissue engineering during the COVID 19 crisis are discussed and finally its useful applications during the ongoing COVID-19 pandemic situation are identified and briefed. This branch of science’s primary importance is to provide biological alternatives that can perform full or partial functions of the damaged, malfunctioned and failing organs or tissues in humans. It is helpful for the supply of convalescent plasma to patients especially during COVID-19. A donor is selected strictly based on a validated case of COVID-19 contagion. The donor must confirm a negative follow-up molecular examination, free from manifestations; usual good health and other pre-donation screening procedures are to be followed.

COVID-19 Pandemic and Debates on the Design of Operating Theatre Ventilation Systems in Healthcare Facilities

COVID-19 pandemic had a significant impact on providing Trauma and Orthopedic surgery around the world. The orthopedic community had to reconfigure emergency and urgent trauma services safely but also support strategies to prevent person-to-person coronavirus transmission. Various organizations including British Orthopedic Association (BOA), American Academy of Orthopedic Surgeons (AAOS) and Public Health England (PHE) have provided guidelines for conducting safe essential surgery in operating theatres. One of the areas that have not been debated enough is the type of ventilation systems that should be used in operating theatres during this global pandemic. We review the current evidence in the literature particularly in the challenges faced by health care professionals in current COVID-19 pandemic in deciding and implementing an effective operating theatre ventilation system protecting both our patients and operating room personnel.

Prevention schemes for future pandemic cases: mathematical model and experience of interurban multi-agent COVID-19 epidemic prevention

To enhance the effectiveness of epidemic prevention (EP) in urban sustainability transformation, joint prevention and control mechanism should be established to prevent and control the COVID-19 epidemic. The interurban multi-agent EP strategy, as a key component of this mechanism, includes the spontaneous EP model, the superior leading EP model, and the collaborative EP model. In this study, firstly, the theoretical mechanism of the interurban multi-agent EP strategy was analyzed. Then, we proposed a three-party differential game model including factors such as the risk coefficient for the virus infection and EP experience teaching. Finally, prevention strategies, prevention efficiency, and prevention losses were compared under the three models based on theoretical analysis and numerical analysis. The results of this study are as follows. COVID-19 EP should be guided by a model of central government (CG) leadership, interurban collaboration, and social participation. The CG and urban governments (UGs) should comprehensively carry out COVID-19 EP from various aspects, including EP experience teaching, mass EP comfort, the utilization rate of EP funds, and the ability to implement strategies. During the course of the COVID-19 EP, when the CG and UGs transition from spontaneous EP model to a higher-level EP model, the UG's EP efforts will be enhanced. Under the collaborative EP model, the CG and UGs undergo the highest levels of EP effort. Compared with spontaneous EP model, the superior leading EP model can promote a Pareto improvement for all parties. From the perspective of total loss, the collaborative EP model is superior to the other two EP models. This study not only provides practical guidance for coordinating interurban relationships and enabling multi-agents to fully form joint forces, but also provides theoretical support for the establishment of an interurban joint EP mechanism under unified leadership.

Bioengineering Technology in Context of COVID-19 Pandemic: Potential Roles and Applications

Bioengineering (BE) technology has significant influence on the healthcare environment. This has grown steadily particularly since the medical practice has become more technology based. We have tried to assess the impact of bioengineering in tackling the COVID-19 pandemic. The use of bioengineering principles in healthcare has been evaluated. The practical implications of these technologies in fighting the current global health pandemic have been presented. There has been a shared drive worldwide to harness the advancements of bioengineering to combat COVID-19. These efforts have ranged from small groups of volunteers to large scale research and mass production. Together the engineering and medical fields have worked to address areas of critical need including the production and delivery of personal protective equipment, ventilators as well as the creation of a viable vaccine. The fight against COVID-19 has helped highlight the work and contributions of so many professionals in the bioengineering fields who are working tirelessly to help our health services cope. Their innovation and ingenuity are paving the way to successfully beat this virus. We must continue to support these fields as we evolve our health systems to deal with the challenges of healthcare in the future.

Nanomedicine Technology and COVID-19 Outbreak: Applications and Challenges

The coronavirus (COVID-19) pandemic is one of the biggest challenges in the field of healthcare. Nanomedicine is a developing area that has the potential to treat various diseases and control infections. Now, its applications are open for the treatment of COVID-19. We have studied relevant papers through Scopus, Google Scholar, Science Direct and ResearchGate on nanomedicine in context of COVID-19. This paper provides detailed information about nanomedicine in the context of healthcare. It further identifies the primary challenges faced in the current situation. This study provides details about the advancements in the area of nanomedicine in healthcare for fighting the COVID-19 pandemic. Finally, we have identified and discussed various significant applications of nanomedicine in solving challenges thrown by the COVID-19 pandemic. Researchers can work on developing applications of nanoparticles with the size of the novel Coronavirus. Nanomedicine is helpful to repair the cells of an infected patient the help of repair proteins. It also plays a vital role in testing medicine and helps many clinical trials get approval from healthcare agencies. In the future, nanomedicine will be helpful for fighting against this pandemic and creating advancements in healthcare.

Exploring the Impact of COVID-19 Pandemic on Medical Supply Chain Disruption

The COVID-19 outbreak is a worldwide disaster that has disrupted several aspects of human life and its community living. This pandemic has also affected the existing supply chain and the way it was being managed. Therefore, this study’s primary objective is to identify and discuss the significant impact of COVID-19 on the current supply chain, with specific reference to the medical supply chain. This article then recommends the potential solution measures that can reduce the impact of COVID-19 on the existing supply chain during and after the COVID-19 pandemic. In order to do so, we have identified and discussed various significant impacts of COVID-19 on the supply chain. Identifying the impacts helps the policy planner formulate the policies to mitigate these impacts and recover the supply chain at their functional level. Further, this study also suggests possible solution measures that can be adopted to reduce the disruption of the supply chain. These solution measures help management develop the action plan for early recovery from the COVID-19 disruption.

IoT-based GPS assisted surveillance system with inter-WBAN geographic routing for pandemic situations

BACKGROUND

Worldwide pandemic situations drive countries into high healthcare costs and dangerous conditions. Hospital occupancy rates and medical expenses increase dramatically. Real-time remote health monitoring and surveillance systems with IoT assisted eHealth equipment play important roles in such pandemic situations. To prevent the spread of a pandemic is as crucial as treating the infected patients. The COVID-19 pandemic is the ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

METHODS

We propose a surveillance system especially for coronavirus pandemic with IoT applications and an inter-WBAN geographic routing algorithm. In this study, coronavirus symptoms such as respiration rate, body temperature, blood pressure, oxygen saturation, heart rate can be monitored and the social distance with 'mask-wearing status' of persons can be displayed with proposed IoT software (Node-RED, InfluxDB, and Grafana).

RESULTS

The geographic routing algorithm is compared with AODV in outdoor areas according to delivery ratio, delay for priority node, packet loss ratio and bit error rate. The results obtained showed that the geographic routing algorithm is more successful for the proposed architecture.

CONCLUSION

The results show that the use of WBAN technology, geographic routing algorithm, and IoT applications helps to achieve a realistic and meaningful surveillance system with better statistical data.

Cloud Computing in Solving Problems of COVID-19 Pandemic

Cloud computing facilitates collaboration, communication, and essential online services during the COVID-19 crisis. The current situation of the COVID-19 pandemic has compelled people to work from their homes, but they have to communicate, collaborate online. Thus, we see an essential role of cloud computing in taking up this challenge of working from home and delivering efficiently. A brief review of Cloud Computing service in the context of COVID-19 pandemic is done using recent papers’ by searching keywords such as “Cloud Computing” and “COVID-19” from PubMed’s database SCOPUS and Google Scholar. During the lockdown situation, cloud computing technology helps provide commendable service in the healthcare domain. It provides an advanced infrastructure for facilitating digital transformation. A brief discussion has been made on how cloud computing components are vital for overcoming the ongoing situation. This paper also studies the remote working of cloud computing for the COVID-19 pandemic and finally identified significant cloud computing applications for the COVID-19 pandemic. All countries focus on reducing this virus’s spread, so this technology helps minimize the spread of this virus by providing online services. It provides an innovative environment that enhances the creativity and productivity of healthcare workers. This technology is efficient in detecting, tracking, and monitoring newly infected patients. In the future, this technology will insight and provide control over this infection to save millions of lives worldwide. This technology is also quite helpful to forecast the future impact of the SARS-Co-2 virus.

Vision of China's future urban construction reform: In the perspective of comprehensive prevention and control for multi disasters

The COVID-19 pandemic has caused huge deaths, massive damage and losses around the world. Looking back in history, the motivation for construction and development of cities was to enhance disaster prevention capacity, while modern cities are built and developed to improve health and wellness for human beings. Each disaster would pose some new challenges to the urban planning and architectural design, such as COVID-19. Therefore, the dilemma of future multi disasters (e.g. epidemics) would lead to reflections on the revision or change of urban design regulations. For the post-epidemic era, a comprehensive and integrated prevention system should be established for multi urban disasters, which requires to be optimally formulated based on multiple objectives, i.e., on the balancing of disaster occurrence probability and stop loss cost. This will be realized thanks to the rapid development of digital alike advanced technologies. Thus, this paper aims to provide a reference for the prevention and control of future city epidemics and disasters in responding to strategies of urban planning and design by considering the reform of urban construction related regulations, further to facilitate the creation of healthy and safe urban environments.

Prevention schemes for future pandemic cases: mathematical model and experience of interurban multi-agent COVID-19 epidemic prevention

To enhance the effectiveness of epidemic prevention (EP) in urban sustainability transformation, joint prevention and control mechanism should be established to prevent and control the COVID-19 epidemic. The interurban multi-agent EP strategy, as a key component of this mechanism, includes the spontaneous EP model, the superior leading EP model, and the collaborative EP model. In this study, firstly, the theoretical mechanism of the interurban multi-agent EP strategy was analyzed. Then, we proposed a three-party differential game model including factors such as the risk coefficient for the virus infection and EP experience teaching. Finally, prevention strategies, prevention efficiency, and prevention losses were compared under the three models based on theoretical analysis and numerical analysis. The results of this study are as follows. COVID-19 EP should be guided by a model of central government (CG) leadership, interurban collaboration, and social participation. The CG and urban governments (UGs) should comprehensively carry out COVID-19 EP from various aspects, including EP experience teaching, mass EP comfort, the utilization rate of EP funds, and the ability to implement strategies. During the course of the COVID-19 EP, when the CG and UGs transition from spontaneous EP model to a higher-level EP model, the UG's EP efforts will be enhanced. Under the collaborative EP model, the CG and UGs undergo the highest levels of EP effort. Compared with spontaneous EP model, the superior leading EP model can promote a Pareto improvement for all parties. From the perspective of total loss, the collaborative EP model is superior to the other two EP models. This study not only provides practical guidance for coordinating interurban relationships and enabling multi-agents to fully form joint forces, but also provides theoretical support for the establishment of an interurban joint EP mechanism under unified leadership.

Green Innovation Risk Identification of the Manufacturing Industry under Global Value Chain Based on Grounded Theory

Green innovation in the manufacturing industry has been widely recognized. Although green innovation can create economic, social, and ecological value, it is also a high-risk activity. We must facilitate and protect the value of green innovation through scientific and systematic management of the risks generated in the process of innovation. The primary task of risk management is risk identification. Therefore, based on the perspective of the global value chain, this paper identifies the risk of green innovation in the manufacturing industry using the research method of grounded theory. By examining the interview records of 25 manufacturing enterprise executives, we summarize and identify the four major risks and 31 risk factors of green innovation. The empirical results of this paper are as follows: (1) the green innovation risks of the manufacturing industry under the global value chain include green R&D risks under the global value chain; manufacturing risks under the global value chain; marketing risks under the global value chain; service risks under the global value chain. (2) Green R&D risks under the global value chain include seven risk factors; green manufacturing risks under the global value chain include 10 risk factors; green marketing risks under the global value chain include nine risk factors; green service risks under the global value chain include five risk factors.

Additive Manufacturing Enabled Supply Chain in Combating COVID-19

Additive manufacturing (AM) is a method in which three-dimensional structures are successively laid down to create a solid object. The inherent advantages of AM technology are successfully drafted and exploited by the different organization across the globe. During the time of pandemic i.e. COVID-19, 3D printing has come to rescue and has been used for manufacturing critical medical supplies. 3D printing has been used in manufacturing some of the critical items like ventilators valves, face shields, swabs, oxygen valves, hand sanitizer holders, 3-DP lung models, etc. The main reason for its success has been the ability of 3D printing to print locally by using digital designs and thus reducing the number of supply chain actors. Also, the ability of 3D printing to manufacture/print complex geometrical designs locally is the main reason for its successful adoption during COVID-19. In this paper, we have discussed how AM has come to the forefront in fighting this pandemic. Various AM techniques have played a critical role in bridging the supply chain gap in the medical industry and locally printing critical devices. There were certain apprehensions before the pandemic along with slow adoption but this pandemic has also increased the adoption of AM due to its ability to overcome the demand created by COVID-19.

Significant Applications of Machine Learning for COVID-19 Pandemic

Machine learning is an innovative approach that has extensive applications in prediction. This technique needs to be applied for the COVID-19 pandemic to identify patients at high risk, their death rate, and other abnormalities. It can be used to understand the nature of this virus and further predict the upcoming issues. This literature-based review is done by searching the relevant papers on machine learning for COVID-19 from the databases of SCOPUS, Academia, Google Scholar, PubMed, and ResearchGate. This research attempts to discuss the significance of machine learning in resolving the COVID-19 pandemic crisis. This paper studied how machine learning algorithms and methods can be employed to fight the COVID-19 virus and the pandemic. It further discusses the primary machine learning methods that are helpful during the COVID-19 pandemic. We further identified and discussed algorithms used in machine learning and their significant applications. Machine learning is a useful technique, and this can be witnessed in various areas to identify the existing drugs, which also seems advantageous for the treatment of COVID-19 patients. This learning algorithm creates interferences out of unlabeled input datasets, which can be applied to analyze the unlabeled data as an input resource for COVID-19. It provides accurate and useful features rather than a traditional explicitly calculation-based method. Further, this technique is beneficial to predict the risk in healthcare during this COVID-19 crisis. Machine learning also analyses the risk factors as per age, social habits, location, and climate.

Exploring Smart Material Applications for COVID-19 Pandemic Using 4D Printing Technology

Today, in the medical field, innovative technological advancements support healthcare systems and improve patients’ lives. 4D printing is one of the innovative technologies that creates notable innovations in the medical field. For the COVID-19 pandemic, this technology proves to be useful in the manufacturing of smart medical parts, which helps treat infected patients. As compared to 3D printing, 4D printing adds time as an additional element in the manufactured part. 4D printing uses smart materials with the same printing processes as being used in 3D printing technology, but here the part printed with smart materials change their shape with time or by the change of environmental temperature, which further creates innovation for patient treatments. 4D printing manufactures a given part, layer by layer, by taking input of a virtual (CAD) model and uses smart material. This paper studies the capability of smart materials and their advancements when used in 4D printing. We have diagrammatically presented the significant parts of 4D printing technology. This paper identifies 11 significant applications of 4D printing and then studies which one provides innovative solutions during the COVID-19 pandemic.

Medical 4.0 and Its Role in Healthcare During COVID-19 Pandemic: A Review

Medical 4.0 is now emerging as the fourth medical revolution. It represents the applications of electronically supported Information Technology, microsystem, high level of automation, personalized therapy, and Artificial Intelligence (AI)-enabled intelligent devices enabled through the Internet of Medical Things (IoMT). In the current scenario, the COVID-19 pandemic has a significant effect on global healthcare, and this impact is also observed in associated fields. There is a requirement for proper telehealth management and remote monitoring systems in healthcare. Medical 4.0, if implemented, can adequately handle the ongoing situation in the medical field as it will provide applications of advanced technologies to take care of the challenges of the COVID-19 outbreak. This paper studies Medical 4.0 exclusively and also in the context of COVID-19. The paper provides a brief of the significant medical revolution that has happened so far and identifies the significant supporting technologies of Medical 4.0. It also discusses the primary capabilities of Medical 4.0 for healthcare during the COVID-19 pandemic crisis. The roles of Medical 4.0 in healthcare during the COVID-19 pandemic are studied, and finally, this paper identifies 10 significant applications of Medical 4.0 in healthcare during COVID-19-type pandemics. We observe that the contemporary phase of development and mass-level production of intelligent medical devices has not happened in the same way as it has happened for smart electronic devices and application devices. Engineers will have a prominent role in taking up the healthcare challenges that can reach the common man.

Industry 5.0: Potential Applications in COVID-19

Industry 5.0, the fifth industrial revolution, consists of smart digital information and manufacturing technologies. This industrial revolution generates effective processes and makes rapid improvement in industries and healthcare. Solutions to challenges posed by COVID-19 pandemic can be identified with the deployment of Industry 5.0-based technologies. It helps to provide personalized therapy and treatment processes to the COVID-19 patients if a detailed patient’s information is available. The aim of Industry 5.0 technologies is to create a smart healthcare environment with real-time capabilities. During the COVID-19 pandemic, these technologies can provide a remote monitoring system in healthcare. This paper identifies and studies major technologies of Industry 5.0 helpful for the COVID-19 pandemic. The supportive features of Industry 5.0 for the COVID-19 pandemic are discussed diagrammatically. Finally, we identified and studied significant challenges faced in the context of Industry 5.0 technologies for the COVID-19 pandemic. The literature revealed that this technological innovation allows a high personalization level to fulfill personal specific demands of the patient and doctors. These technologies play a significant role in making the life of doctors better. Further, doctors can use this technology to focus on critically infected patients and provide proper appropriate information regarding their better treatment. Moreover, Industry 5.0 technologies can help doctors and medical students for required medical training during this COVID-19 outbreak.

Significance of Health Information Technology (HIT) in Context to COVID-19 Pandemic: Potential Roles and Challenges

Health information technology (HIT) refers to the concept of applying cloud-based services, internet, connected network, etc. in healthcare. It mainly utilizes electronic health records, information, and data related to the patients for providing the treatment and services in a more effective and advanced manner. This study attempts to propose roles and applications and identify the impact of the concept of HIT on serving the patients during the ongoing COVID-19 pandemic period. This paper also assesses the significant impact of HIT in the healthcare sector during the COVID-19 crisis. The medical decision support, e-sign-off tools, bar-coding approach, advanced medicine dispensing, e-patient portals, etc. are numerous data-sharing and network system-based HIT services. It has many capabilities to shift the working culture of medical facilities while serving and treating patients with a higher care level and impressive satisfaction, especially so during this COVID-19 pandemic. Interoperability and tele-healthcare have also become practicable with the proposed HIT approach.

Robotics Applications in COVID-19: A Review

The COVID-19 outbreak has resulted in the manufacturing and service sectors being badly hit globally. Since there are no vaccines or any proven medical treatment available, there is an urgent need to take necessary steps to prevent the spread of this virus. As the virus spreads with human-to-human interaction, lockdown has been declared in many countries, and the public is advised to observe social distancing strictly. Robots can undertake human-like activities and can be gainfully programmed to replace some of the human interactions. Through this paper, we identify and propose the introduction of robots to take up this challenge in the fight against the COVID-19 pandemic. We did a comprehensive review of the literature to identify robots’ possible applications in the management of epidemics and pandemics of this nature. We have reviewed the available literature through the search engines of PubMed, SCOPUS, Google Scholar, and Research Gate. A comprehensive review of the literature identified different types of robots being used in the medical field. We could find several vital applications of robots in the management of the COVID-19 pandemic. No doubt technology comes with a cost. In this paper, we identified how different types of robots are used gainfully to deliver medicine, food, and other essential items to COVID-19 patients who are under quarantine. Therefore, there is extensive scope for customising robots to undertake hazardous and repetitive jobs with precision and reliability.

A Review of the Role of Smart Wireless Medical Sensor Network in COVID-19

The new global predicament situation has raised questions on our healthcare systems and its endurance to deliver quality medical services. It is for those tormented with COVID-19 and other patients suffering from other chronic, acute, trauma, and other communicable diseases while shielding the doctors, nurses, and other associated medical employees when treating the patients. The immense adaptation to sensors networks demonstrates its usefulness as a tool for the present so-called social distancing in the clinical monitoring of COVID-19 patients or other settings. The utilization of Wireless Medical Sensor Network (WMSN) upsurges the prominence for those who work for long hours treating COVID-19 patients, exposing themselves while risking their lives. This paper attempts to explore few good practices identified from the current pandemic, with a precise and robust vision of deploying sensor networks to accomplish quality healthcare while reducing the potential threat of COVID-19 transmission to general masses while treating others.

Telemedicine Technologies for Confronting COVID-19 Pandemic: A Review

Telemedicine (TM) is used to treat patients in a remote location by using telecommunication technology. It exchanges the medical information and data from one location to another through advanced technological innovation. During this COVID-19 pandemic, there is a lockdown in almost all countries. TM is beneficial to healthcare to minimize social distance. This review paper briefs about TM and discusses how this technology works for the COVID-19 pandemic and its significant benefits. An extensive search is made on the known research engines of PubMed, SCOPUS, Google Scholar, and ResearchGate using the appropriate keywords to extract meaningful and relevant articles. Ten major applications of TM for COVID-19 are identified and discussed with a brief description of each provided. The major technological processes involved in TM, which create advancement in the medical field, are also discussed. This technology helps avoid visits to the doctor and hospital during the lockdown and provides a suitable treatment option. It collects the medical information and data, which can be helpful for better treatment of the patient. Telemedicine adopts virtualized treatment approaches for the patient. Now patients can receive better quality treatment without leaving their homes during COVID-19 lockdown.

A Three-Player Game Model for Promoting the Diffusion of Green Technology in Manufacturing Enterprises from the Perspective of Supply and Demand

Taking the rational use of environmental regulations to promote the diffusion of green technology innovation in China’s manufacturing enterprises as the starting point, this study analyzed the benefits to the government, innovation-supplying enterprises, and potential demand-oriented enterprises. In addition, a tripartite evolutionary model was constructed to examine the impact of command-and-control environmental regulation and market-driven environmental regulation on the diffusion of green technology innovation in manufacturing enterprises. Finally, the study compared and analyzed the heterogeneous effects of different types of environmental regulation tools on the diffusion of green technology innovation in manufacturing enterprises using local stability analysis and numerical simulation. The results are as follows: (i) When the government does not implement environmental regulation tools or the regulation intensity is relatively small, the diffusion depth of green technology innovation in manufacturing enterprises is zero. (ii) When government regulation reaches a certain level, the system of manufacturing enterprises, innovation-supplying enterprises, and potential demand-oriented enterprises will choose to actively promote the diffusion of green technology innovation following a long evolution process. (iii) Increasing the punishment intensity and subsidy rate of green technology innovation can stimulate the diffusion of green technology innovation in manufacturing enterprises. (iv) The comprehensive use of the two kinds of environmental regulation tools has a heterogeneous influence on the strategic choice of green technology innovation diffusion subjects of manufacturing enterprises, and its incentive effect on potential demand-oriented enterprises is relatively poor.