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.
Objectives: To determine the impact of an educational program on nurses’ knowledge
and practices concerning neurogenic bladder rehabilitation for spinal cord injured persons
through a follow-up approach each two months post program implementation for six
months.
Methodology: "Follow-up" longitudinal design by using time series approach of data
analysis and the application of pre-post tests approach for the study and the control
groups. The study was carried out at Ibn Al-Kuff hospital for (SCI) in Baghdad governorate
from 5th of July 2010 to 15th of October 2011. To achieve the objectives of the study, a
non-probability (purposive) sample of (60) nurses (males and females) were working in SCI
units were selec
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In this work, a comparative analysis for the behavior and pattern of the variations of the IF2 and T Ionospheric indices was conducted for the minimum and maximum years of solar cycles 23 and 24. Also, the correlative relationship between the two ionospheric indices was examined for the seasonal periods spanning from August 1996 to November 2008 for solar cycle 23 and from December 2008 to November 2019 for solar cycle 24. Statistical calculations were performed to compare predicted values with observed values for the selected indices during the tested timeframes. The study's findings revealed that the behavior of the examined indices exhibited almost similar variations throughout the studied timeframe. The seasonal variations were
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Three mesoporous silica with different functional group were prepared by one-step synthesis based on the simultaneous hydrolysis and condensation of sodium silicate with organo - silane in the presence of template surfactant polydimethylsiloxane - polyethyleneoxide (PDMS - PEO). The prepared materials were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), atomic force microscopy (AFM) and nitrogen adsorption/desorption experiments. The results indicate that the preparation of methyl and phenyl functionalized silica were successful and the mass of methyl and phenyl groups bonded to the silica structure are 15, 38 mmol per gram silica. The average diameter of the silica particles are 103.51,
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— In light of the pandemic that has swept the world, the use of e-learning in educational institutions has become an urgent necessity for continued knowledge communication with students. Educational institutions can benefit from the free tools that Google provide and from these applications, Google classroom which is characterized by ease of use, but the efficiency of using Google classroom is affected by several variables not studied in previous studies Clearly, this study aimed to identify the use of Google classroom as a system for managing e-learning and the factors affecting the performance of students and lecturer. The data of this study were collected from 219 members of the faculty and students at the College of Administra
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme
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