ABSTRACT
The effect of financial liberalization implementation and technological development, especially after 1980's in financial globalization process,trust has begun to get more important both governments and private firms. In this process, rapid developed and integration in financial markets and variety of financial instruments, countries credit risks are increased. Due to this credit risk measurument is getting more important. In this study we aim to examine10 countries which credit risks are diffrent each other, the effects of macroeconomic and fiscal determinants on credit ratings and credit default swaps by using ordered probit model between 2007-2021.
ABSTRACT
Declared a pandemic disease, COVID-19 has affected the lives of millions of people and had significant effects on public health. Despite the development of effective vaccines against COVID-19, cases continue to increase worldwide. According to studies in the literature, artificial intelligence methods are used effectively for the detection of COVID-19. In particular, deep-learning-based approaches have achieved very good results in clinical diagnostic studies and other fields. In this study, a new approach using x-ray images is proposed to detect COVID-19. In the proposed method, the angle transform (AT) method is first applied to the x-ray images. The AT method proposed in this study is an important novelty in the literature, as there is no such approach in previous studies. This transformation uses the angle information created by each pixel on the image with the surrounding pixels. Using the AT approach, eight different images are obtained for each image in the dataset. These images are trained with a hybrid deep learning model, which combines GoogleNet and long short-term memory (LSTM) models, and COVID-19 disease detection is carried out. A dataset from the Mendeley database is used to test the proposed approach. A high classification accuracy of 98.97% is achieved with the AT + GoogleNet + LSTM approach. The results obtained were also compared with other studies in the literature. The presented results reveal that the proposed method is successful for COVID-19 detection using chest x-ray images. Direct transfer methods were also applied to the data set used in the study. However, worse results were observed according to the proposed approach. The proposed approach has the flexibility to be applied effectively to different medical images.
ABSTRACT
In this study, it is aimed that the experiences of post-traumatic growth in individuals treated for coronavirus (COVID-19) are examined. In this research, in-depth individual interviews were carried out with those over the age of 18 years old who had been diagnosed and completed treatment for COVID 19 and agreed to participate to the research. The research was conducted with 16 individuals (22-45 years) who met the research criteria. A phenomenological qualitative research method was used for this study. The data was gathered over the internet-based teleconferencing programs (Zoom, Google Meeting, Skype, etc.) in order to prevent the spread of COVID-19. The thematic analysis method was used in the data analysis. In consequence of the qualitative data analysis, two categories were obtained as " Effects of COVID-19" and "Post Traumatic Growth." In the category of the effects of COVID-19, three themes and five subordinate themes were established, and in the category of post-traumatic growth, two themes and eight subordinate themes were established. As a result of the research, it was established that the perspectives of individuals who experienced this sickness on life and their self-perception were positively developed, their relationships were strengthened, and the support resources surrounding them positively affected them during the period. The research presents significant experiences with regard to planning and implementing interventions aimed at the factors that promote psychological growth in COVID-19 patients. © 2022, Cyprus Mental Health Institute. All rights reserved.
ABSTRACT
Objective: The Coronavirus disease-2019 (COVID-19) pandemic has caused the death of many people worldwide. Treatment protocol had to be developed as soon as possible so drug combinations, whose reliability has not been fully disclosed, have started to be used. In this study, we aimed to evaluate the effect of azithromycin (AZT), hydroxychloroquine (HCQ), and favipiravir (FVR) combination on the corrected QT (QTc) interval. Material and Methods: Eighty-four consecutive COVID 19 patients were enrolled in the study. All patients received AZT and HCQ, however, FVR was added to the combination in 32 patients with severe pneumonia at the beginning. ECG characteristics of all patients before treatment and on the fifth day of treatment were compared. Results: There was no significant difference between the HCQ+AZT group (n=52) and HCQ+AZT+FVR groups (n=32) in terms of baseline clinical characteristics. QTc interval significantly prolonged on the fifth day of treatment in the HCQ+AZT group (413,75±30,13;440,27±36,11 p<0.001) and in the HCQ+AZT+FVR group (426,65±32,83;468,22±42,13 p<0.001). When both groups were compared in terms of ΔQTc, a significant increase was observed in the HCQ+AZT+FVR group compared to the HCQ+AZT group (40(-14/175), 23(-28/213) respectively, p=0.042). In seven of the patients, QTc> 500 ms was detected after the treatment, four patients in the HCQ+AZT+FVR group and three patients in the HCQ+AZT group. Conclusion: We observed that FVR caused more prolongation in the QTc interval when used with the combination of HCQ+AZT. We recommend that patients who receive this treatment be monitored more closely for QTc.