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Kafkas Universitesi Veteriner Fakultesi Dergisi ; 28(4):507-514, 2022.
Article in English | EMBASE | ID: covidwho-2006516


In this study, it was aimed to evaluate the relationship between the clinical course of the disease and hematological data, serum 25-hydroxyvitamin D (25 (OH) D), iron (Fe), free iron-binding capacity (UIBC), and D-dimer levels in calves with diarrhea in the neonatal period. Within the scope of the study, 10 healthy calves (group-I) and 30 diarrheal calves in the neonatal period of different races, ages and genders were used. Calves with diarrhea were divided into mild (group-II, n=10), moderate (group-III, n=10) and severe (group-IV, n=10) groups. Blood samples were taken from calves in all groups at once. Hematological analyzes were performed using a veterinary-specific hematology analyzer device. In serum samples, 25 (OH) D3, Fe and UIBC levels were determined with an autoanalyzer, and D-dimer levels were determined with an automatic immunoassay analyzer. In the hematological analysis, an increase was observed in the number of LYMs (lymphocytes) in group-II (5.04±1.3) and III (5.2±3.3) compared to group-I (4.47±1.2), and a decrease was observed in group IV (2.76±0.9) (P<0.05). Fe levels in group-II (59±56), group III (56±52) and group IV (72±63) were found to be decreased compared to group-I (131±66) (P<0.05). It was determined that the 25 (OH) D3 level of group IV (13.4±8.5) was higher than that of group-I (6.12±2.73) (P<0.05). D-dimer levels of group-III (1.15±1.13) and group-IV (0.96±0.88) were found to be higher than group-I (0.10±1.46) (P<0.05).

Concurrency and Computation: Practice and Experience ; 2022.
Article in English | Scopus | ID: covidwho-1653209


The rapid growth in the airline industry, which started in 2009, continued until the COVID-19 era, with the annual number of passengers almost doubling in 10 years. This situation has led to increased competition between airline companies, whose profitability has decreased considerably. They aimed to increase their profitability by making services like seat selection, excess baggage, Wi-Fi access optional under the name of ancillary services. To the best of our knowledge, there is no recommendation system for recommending ancillary services for airline companies. Also, to the best of our knowledge, there is no testing framework to compare recommendation algorithms considering their scalabilities and running times. In this paper, we propose a framework based on Lambda architecture for recommendation systems that run on a big data processing platform. The proposed method utilizes association rule and sequential pattern mining algorithms that are designed for big data processing platforms. To facilitate testing of the proposed method, we implement a prototype application. We conduct an experimental study on the prototype to investigate the performance of the proposed methodology using accuracy, scalability, and latency related performance metrics. The results indicate that the proposed method proves to be useful and has negligible processing overheads. © 2022 John Wiley & Sons Ltd.