A Comparison of Country Performances with Sovereign Credit Ratings using the TOPSIS Model

This study aims to rank 66 countries according to their macroeconomic and governance performance to compare that rating with the credit ratings for the countries. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model is based on Multi Criteria Decision Making approach was used to compare the credit ratings of 66 developed and developing countries assigned by (Standard and Poor's) S & P in July 2011 with the governance and macroeconomic data for the year 2010. The results show that the ranking according to credit ratings assigned by S&P in 2011 is open to complaints of developing countries when evaluated only according to macroeconomic performance. However, when the rankings consider governance variables, the results are very closely matched with the ranking according to the credit rating scores

The relationship between hemoglobin in the first blood gas and hemoglobin in hemogram in patients with a diagnosis of gastrointestinal system bleeding

GİS kanama gibi; çeşitli nedenlere bağlı ciddi kanamalarda tedaviye başlamak için laboratuvar sonuçlarının beklenmesi hasta için zaman kaybına neden olmaktadır. Acil servislerde yakın hemoglobin takibi gerektiren hastalar için güvenilir ve hızlı laboratuvar sonuçlarına ihtiyaç vardır. Acil servislerde ve yoğunbakım ünitelerinde kan gazı cihazlarının sayısı giderek artmaktadır. Ancak, kan gazı cihazları ile hematoloji laboratuvarı arasında, hemoglobin ölçümleriyle ilgili olarak farklılıklar ortaya çıkmaktadır. Bu çalışma, kan gazı ve hematoloji hemoglobin sonuçlarının birbiri yerine kullanılıp kullanılamayacağını belirlemek için yapılmıştır. Yöntem: Çalışmaya, 15 Mart 2020 - 31 Aralık 2020 tarihleri arasında acil servise GİS kanama semptomları ile başvurup takiplerinde GİS kanama tanısı kesinleşen hastalardan, ilk başvurusunda hemogram ve kan gazı örneği alınan hastalar dahil edildi. Bulgular: Çalışmaya dahil ettiğimiz 237 hastanın hematoloji laboratuvarındaki ortalama hemoglobin değeri 8,86±2,88 g/dl iken kan gazındaki ortalama hemoglobin değeri 9,43±3,84 g/dl çıkmıştır. Hemogramın ortalama çıkış süresi 14,04±11,27 dakika iken kan gazları için bu süre 8,05±7,84 dakika olarak hesap edilmiştir. Kan gazı ve hemogramlardan elde edilen hgb değerlerinin Pearson korelasyon katsayısı 0,837 olarak hesaplandı (p<;0,001, çok yüksek düzeyde pozitif ilişki). Elde edilen hgb değerleri arasındaki ortalama fark (kan gazı hgb– hemogram hgb) 0,58±2,13 g/dl olarak tespit edildi. Ortalama hgb farkının % 95 güven aralığı 0,31-0,85 olarak tespit edildi. Sonuçlanan hgb değerleri arasındaki ortalama yüzde fark %2,95±26,06 olarak tespit edildi. Sonuç: İki ölçüm yöntemi ile elde edilen hemoglobin sonuçlarının yüksek korelasyon katsayısı ile desteklenmesinden dolayı kan gazındaki hemoglobinin, hastanın hemoglobini hakkında fikir verebileceğini düşünüyoruz. Ancak hematoloji laboratuvar sonuçları elimize ulaştığında tedavi kontrol edilmeli ve buna göre tanı, tedavi ve gözlem basamaklarına yön verilmelidir. Anahtar kelimeler: kan gazı, hemoglobin, gastrointestinal kanamaSuch as GIS bleeding; waiting for laboratory results to start treatment in severe bleeding due to various reasons causes a loss of time for the patient. In such cases, the medical intervention to the patient is made according to the patient's clinic and laboratory tests. The number of blood gas devices is increasing in emergency departments and intensive care units. However, there are differences between blood gas devices and the hematology laboratory regarding hemoglobin measurements. This study was conducted to determine whether blood gas and hematology hemoglobin results can be used interchangeably. Methods: Patients who applied to the emergency department with GIS bleeding symptoms between March 15, 2020 and December 31, 2020 and whose GIS bleeding was confirmed in their follow-up, were included in the study, whose hemogram and blood gas samples were taken at the first application. Results: While the mean hemoglobin value in the hematology laboratory of the 237 patients we included in the study was 8.86±2.88 g/dl, the mean hemoglobin value in the blood gas was 9.43±3.84 g/dl. While the mean exit time of the hemogram was 14.04±11.27 minutes, this time was calculated as 8.05 ±7.84 minutes for blood gases. The Pearson correlation coefficient of hgb values ​​obtained from blood gases and hemograms was calculated as 0.837 (p<;0.001, a very high level of positive correlation). The mean difference between the obtained hgb values ​​(blood gas hgb–hemogram hgb) was determined as 0.58±2.13 g/dl. The 95% confidence interval of the mean hgb difference was found to be 0.31-0.85. The mean percentage difference between the resulting hgb values ​​was found to be 2.95±26.06%. Conclusion: Since hemoglobin results obtained with two measurement methods are supported by a high correlation coefficient; we think that the hemoglobin in the blood gas can give an idea about the patient's hemoglobin. However, when the hematology laboratory results are available, the treatment should be checked and the diagnosis, treatment and observation steps should be guided accordingly. Key words: blood gas, hemoglobin, gastrointestinal bleedin

Civilian Powers and the Use of Force: The Evolution of Germany as a ‘Realist Civilian Power’

Because of Germany’s rising economic and political clout not only in European but also in global politics, it is worth analysing the dynamics of change and continuity in Germany’s policy towards the use of force. This article aims to critically examine the evolution of Germany’s civilian power characteristics based on three case studies of Kosovo, Afghanistan, and the uprisings in the Middle East, by using the theoretical framework of realist constructivism. The article tries to answer the following research questions: To what extent has Germany been able to maintain its traditional peaceful foreign policy in the new “global disorder”? Which factors affect its decision to be involved or not in military interventions in various regional and global conflicts? What does the German case tell us about the evolution of civilian powers in the current global circumstances

Nonoverlay Heterogeneous Network Planning for Energy Efficiency

In this paper, we introduce nonoverlay microcell/macrocell planning that is optimally designed for improving energy efficiency of the overall heterogeneous cellular network. We consider two deployment strategies. The first one is based on a fixed hexagonal grid and the second one is based on a stochastic geometry. In both of our models, microcells are placed in those areas where the received signal power levels of macrocell common pilot channels are below a certain threshold. Thus, interference between microcells and macrocells is minimized. As a result, addition of microcells increases the achieved number of bits per unit energy. Under such deployment assumptions, we investigate the effects of certain parameters on the energy efficiency. These parameters include the user traffic, the Intersite Distance (ISD), the size of microcells and the number of microcells per macrocell for the grid model, and macrocell density and microcell density for the stochastic model. The results of our performance analyses show that utilizing microcells in a sparse user scenario is worse for the energy efficiency whereas it significantly improves both energy and spectral efficiencies in a dense user scenario. Another interesting observation is that it is possible to choose an optimum number of microcells for a given macrocell density

A Comparison of Country Performances with Sovereign Credit Ratings using the TOPSIS Model

This study aims to rank 66 countries according to their macroeconomic and governance performance to compare that rating with the credit ratings for the countries. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model is based on Multi Criteria Decision Making approach was used to compare the credit ratings of 66 developed and developing countries assigned by (Standard and Poor's) S & P in July 2011 with the governance and macroeconomic data for the year 2010. The results show that the ranking according to credit ratings assigned by S&P in 2011 is open to complaints of developing countries when evaluated only according to macroeconomic performance. However, when the rankings consider governance variables, the results are very closely matched with the ranking according to the credit rating scores