Résumé
As a consequence of the COVID-19 pandemic, Korea's economy has experienced significant setbacks. Thus, this article examines the implications of the COVID-19 pandemic on Korea's key macroeconomic indicators via the transmission channels of oil prices and production technology. Using Bayesian estimation and impulse response functions for empirical investigation, the results suggest that the COVID-19 pandemic has intensified the reduction in firm production, consumption of oil-based goods, employment, and investment. Increasingly, households rely on non-oil goods rather than oil-based ones. Similarly, the results suggest that the drop in production technology levels brought on by the COVID-19 pandemic has a stronger impact on business output and investment but a lesser influence on household employment. The COVID-19 pandemic has led to a decline in household non-oil consumption as well as household and business consumption of oil-based goods. To sum up, the existing Korean literature on this issue might be improved by including the findings offered in this article. [ FROM AUTHOR] Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
Résumé
As preventive, curative and restorative measures in modern conditions of the spread of infectious diseases (Covid 19), the use of sorption materials and detoxification methods with their use in hemosorption are of particular importance. It is known that hemosorption is an effective method of detoxification of the body, and no less important is the use of safe sorbents in relation to the shaped elements of blood, both time-tested sorbents and new, less studied, but more promising from the point of view of their safe production technology. The purpose of this work is to study with the help of scanning flow cytometry the effect of a sorbent with carbon nanofiber A1203@PDMS/CNF in comparison with a carbon-free sorbent A1203@PDMS on morphofunctional parameters erythrocytes. The study of the physico-chemical properties of sorbents was carried out according to standard methods. The biological properties of sorbents were evaluated by its effect on erythrocytes of erythrocyte concentrate during hemoperfusion of blood through columns with sorbents using the method of scanning flow cytometry according to the standard method. The data obtained using the method of scanning flow cytometry made it possible to conclude that the studied sorbents do not have a traumatic effect on the morphofunctional parameters of erythrocytes. The introduction of carbon nanofiber into the composition of the sorbent in an amount of 0.02% improves the functional parameters of blood erythrocytes both in comparison with the initial donor blood and compared to the sorbent without carbon. © 2022 IEEE.
Résumé
This paper proposes an approach for medical resource allocation among hospitals under public health emergencies based on data envelopment analysis (DEA). First, the DEA non-regressive production technology is adopted to ensure that the DMU can always refer to the most advanced production technology throughout all production periods. Based on the non-regressive production technology, two efficiency evaluation models are presented to calculate the efficiencies of DMUs before and after resource allocation. Our theoretical analysis shows that all the DMUs can be efficient after medical resource allocation, and thus a novel resource allocation possibility set is developed. Further, two objectives are considered and a bi-objective resource allocation model is developed. One objective is to maximize the output target realizability of the DMUs, while the other is to ensure the allocated resource to each DMU fits with its operation size, preperformance, and operation practice (i.e., proportion of critically ill patients). Additionally, a trade-off model is proposed to solve the bi-objective model to obtain the final resource allocation results. The proposed approach contributes by ensuring that the medical resources are allocated in such a way that they can all be efficiently used as well as considering multiple objectives and practical constraints that make the approach more fitted with the practical application scenarios. Finally, a case study of 30 hospitals in Wuhan during the COVID-19 epidemic is applied to illustrate the proposed approach.