<strong>Background</strong>: In December 2019, the COVID-19 outbreak originated in Wuhan, China. Since then, this virus has spread at a very rapid rate affecting many countries. The World Health Organization (WHO) subsequently declared a global pandemic, and a range of precautions have been implemented to reduce the spread of the virus. Some of these precautions included social distancing, self-isolation, and quarantine of those who have contracted or potentially contracted COVID-19. Healthcare workers (HCWs) are at high risk because of the constant contact with infected patients for extended periods or by exposure to a patient’s environment or biological samples. This may cause fear of transmitting the infection to their families. Also, the extended working hours put them under severe stress, fatigue, and adverse social life. All of these factors affect their behaviors and attitudes. <strong>Purpose:</strong> to explore the mental health impact of COVID-19 on HCWs as this will be reflected on their performance on such crisis. Besides, we aim to investigate HCWs' coping strategies during the pandemic and provide coping recommendations based on evidence. <strong>Methods:</strong> A systematic review using PRISMA methodology was used through three electronic databases, including PubMed, ScienceDirect, and Scopus. All cross-sectional studies that were published in English and that assessed the mental health impact of COVID-19 on HCWs or/and coping strategies adopted by them were included. <strong>Results</strong>: A total of one hundred and forty articles total were retrieved from the three databases and were reviewed for relevance. reviews for relevance after remove duplicate. We Ended up with twenty-four recent studies from 2020 that were included in the analysis. As COVID-19 has started in China, our review identified many studies that were done there on the subject of HCWs mental health due to the crisis. Italy took the second place in the number of studies. Nurses and physicians were the populations targeted in many studies. <strong>Conclusion: </strong>COVID-19 has created much pressure on HCWs. This pressure has increased the following mental health complaints: anxiety, depression, insomnia, and stress. Many studies have emphasized the effects of social support as an effective way of coping with COVID-19.
This exploratory study is carried out in April, 2020, when corona virus is spread all over the world and become Economic crisis 2020.The objective of this study is to answer some questions arise in mind, how many countries infected and reduce their economic activities? What are effective fiscal and monetary policies at international level to address the crisis? Is monetary and fiscal policy used as vaccine to prevent the world economy from crisis? It is a hot topic these days when world is facing this covid-19. Researcher get information from different website, international monetary fund(IMF), Organization of economic cooperation and development (OECD) Standard& poor’s, (S&P) rating agencies, and some past papers to explain the impact of Corona virus on world economy. Further explain the losses from one industry to another industry. And finally concluded that world economy is fighting with dual nature crisis. On one hand Death of million people from corona, other is fall down of economy. First challenge is to save the people from death, and secondly to save the world from economic crisis. But these two challenges are contradicted. If want to save people lives then implemented stay at home, social distancing policy, and shut down the country. But we can save our people live but economy fall down sharply because of shut down all businesses in the country. If save economic crisis then people should go out and work as usual, world economy will boost but soon we will lose million or billion of people live which also effect the fall down economy. Policy maker, doctors and health care manufacturer should sit together find ways which is benefits for both people live and save economic crisis.
The l -lysine fermentation process is a complex, nonlinear, dynamic biochemical reaction process with multiple inputs and multiple outputs. There is a complex nonlinear dynamic relationship between each state variable. Some key variables in the fermentation process that directly reflect the quality of the fermentation cannot be measured online in real-time which greatly limits the application of advanced control technology in biochemical processes. This work introduces a hybrid ICS-MLSSVM soft-sensor modeling method to realize the online detection of key biochemical variables (cell concentration, substrate concentration, product concentration) of the l -lysine fermentation process. First of all, a multi-output least squares support vector machine regressor (MLSSVM) model is constructed based on the multi-input and multi-output characteristics of l -lysine fermentation process. Then, important parameters ( , , ) of MLSSVM model are optimized by using the Improved Cuckoo Search (ICS) optimization algorithm. In the end, the hybrid ICS-MLSSVM soft-sensor model is developed by using optimized model parameter values, and the key biochemical variables of the l -lysine fermentation process are realized online. The simulation results confirm that the proposed regression model can accurately predict the key biochemical variables. Furthermore, the hybrid ICS-MLSSVM soft-sensor model is better than the MLSSVM soft-sensor model based on standard CS (CS-MLSSVM), particle swarm optimization (PSO) algorithm (PSO-MLSSVM) and genetic algorithm (GA-MLSSVM) in prediction accuracy and adaptability.
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