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Prevalence of Pathogenic Bacteria from Contaminated Yemeni Currency Notes in Taiz City
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ABSTRACT: Pathogenic bacteria responsible for the causation of many common diseases have been identified on currency notes. The present investigation was carried out on one hundred currency notes of all the denominations (50, 100, 250, 500 and 1000RY), obtained from different occupational mainly bus drivers, hawker street, vegetable vendor, restaurants and butchers and fish seller groups in Taiz city,Yemen. Identification and characterization revealed active participation of the following species of organisms in the ascending order of percentage as E. coli(50.28 %),Staphylococci aureus(14.04 %), Klebsiellaspp(4.39 %),proteus(4.39 %), salmonella(1.25 %), shigella(0.72 %), Coagulase negative staphylococcus(0.60 %), pseudomonas(0.50 %), beta haemolytic streptococcus(0.30 %),spore forming gram positive bacilli(0.30%) and alpha haemolytic streptococcus(0.10%). The study suggested that yemenicurrency notes is commonly contaminated withpathogenic microorganisms and this contamination may play a significant role in the transmission of potentiallyharmful microorganisms or different diseases such as cholera, diarrhea, skin infections and also poses antibioticresistant, so great care should be taken during handling of money and the preparation and handling of foodto avoid cross contamination.

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
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        In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through  Monte Carlo simulation technique were made depend on mean squared error (MSE)  criteria

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