ABSTRACT
Background: The societal challenges presented by fear related to the coronavirus disease (COVID-19) pandemic may present unique challenges for an individual's mental health. However, the moderating role of compassion in the relationship between fear of COVID-19 and mental health has not been well-studied. The present study aimed to explore the association between fear of COVID-19 and mental health, as well as test the buffering role of compassion in this relationship. Methods: The participants in this study were 325 Iranian undergraduate students (228 females), aged 18-25 years, who completed questionnaires posted on social networks via a web-based platform. Results: The results showed that fear of COVID-19 was positively related with physical symptoms, social function, depressive symptoms, and anxiety symptoms. The results also showed that compassion was negatively associated with physical symptoms, social function, depressive symptoms, and anxiety symptoms. The interaction-moderation analysis revealed that compassion moderated the relationship between fear of COVID-19 and subscale of mental health. Conclusion: Results highlight the important role of compassion in diminishing the effect of fear of COVID-19 on the mental health (physical symptoms, social function, depressive symptoms, and anxiety symptoms) of undergraduate students.
ABSTRACT
Background The societal challenges presented by fear related to the coronavirus disease (COVID-19) pandemic may present unique challenges for an individual's mental health. However, the moderating role of compassion in the relationship between fear of COVID-19 and mental health has not been well-studied. The present study aimed to explore the association between fear of COVID-19 and mental health, as well as test the buffering role of compassion in this relationship. Methods The participants in this study were 325 Iranian undergraduate students (228 females), aged 18–25 years, who completed questionnaires posted on social networks via a web-based platform. Results The results showed that fear of COVID-19 was positively related with physical symptoms, social function, depressive symptoms, and anxiety symptoms. The results also showed that compassion was negatively associated with physical symptoms, social function, depressive symptoms, and anxiety symptoms. The interaction-moderation analysis revealed that compassion moderated the relationship between fear of COVID-19 and subscale of mental health. Conclusion Results highlight the important role of compassion in diminishing the effect of fear of COVID-19 on the mental health (physical symptoms, social function, depressive symptoms, and anxiety symptoms) of undergraduate students.
ABSTRACT
Accepting the fact that there is a huge number of virus particles in food that lead to several infectious diseases, eliminating of the foodborne virus from food is tangible. In 2020, the appearance of new SARS-CoV-2 variants had remarked the importance of food safety in our lives. Detection virus is a dynamic domain. Recently, many papers have tried to detect several foodborne viruses by using conventional sensing platforms including ELISA (enzyme-linked immunosorbent assay), PCR (polymerase chain reaction-based methods) and NASBA (nucleic acid sequence-based amplification). However, small sizes, low infective doses and discrete distribution of the foodborne virus have converted these microorganisms into the most challengeable pathogen in the food samples matrix. Foodborne virus detection exploiting aptamer-based biosensors has attracted considerable attention toward the numerous benefits of sourcing from aptamers in which a variety of viruses could be detected by conjugation of aptamer-virus. The development of multiple sensing methodologies and platforms in terms of aptasensor application in real food and environment samples has demonstrated promising results. In this review, we present the latest developments in myriad types of aptasensors (including electrochemical, optical and piezoelectric aptasensor) for the quantification of foodborne viruses. Working strategies, benefits and disadvantages of these platforms are argued.
ABSTRACT
In today's world, the most prominent public issue in the field of medicine is the rapid spread of viral sickness. The seriousness of the disease lies in its fast spreading nature. The main aim of the study is the proposal of a framework for the earlier detection and forecasting of the COVID-19 virus infection amongst the people to avoid the spread of the disease across the world by undertaking the precautionary measures. According to this framework, there are four stages for the proposed work. This includes the collection of necessary data followed by the classification of the collected information which is then taken in the process of mining and extraction and eventually ending with the process of decision modelling. Since the frequency of the infection is very often a prescient one, the probabilistic examination is measured as a degree of membership characterised by the fever measure related to the same. The predictions are thereby realised using the temporal RNN. The model finally provides effective outcomes in the efficiency of classification, reliability, the prediction viability etc.