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https://www.selleckchem.com/products/anacetrapib-mk-0859.html The COVID-19 pandemic is the defining health crisis of the world in 2020 and the world economy is affected as well. Bangladesh is also one of the impacted countries, which needs to conduct sufficient tests to identify patients and accordingly adopt measures to limit the massive outbreak of this viral infection. But due to economic drawbacks and also unavailability of testing equipment, Bangladesh is lagging critically behind in test numbers. This study shows a pool testing method named Conditional Cluster Sampling (CCS) that utilizes soft computing and data analysis techniques to reduce the expense of total testing equipment. The proposed method also demonstrates its effectiveness compared to the traditional individual testing method. Firstly, according to patients' symptoms and severity of their conditions, they are classified into four classes- Minor, Moderate, Major, Critical. After that Random Forest Classifier (RFC) is used to predict the class. Then random sampling is done from each class according to CCS. Finally, using Monte Carlo Simulation (MCS) for 100 cycles, the effectiveness of CCS is demonstrated for different probability levels of infection. It is shown that the CCS method can save up to 22% of the test kits that can save a huge amount of money as well as testing time.This article analyses how border guards as members of a state organisation shape the movement of non-nationals into the territory of a nation state. Based on ethnographic fieldwork on the Swiss Border Guard (SBG), it explores the rationalities-understood as stabilised ways of reasoning and acting-that characterise practices within this state organisation. Combining organisational and structuration theory with a street-level bureaucracy perspective allows for a differentiated analysis of the various facets of border guards' everyday work. Four rationalities of border-control practices are identified and compared security, huma

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