In this study 77 human isolates of Staphylococcus aureus were obtain from different clinical sources. The results showed that the number of isolates producing α-hemolysin was 32 isolates (41.55%) , while non- hemolysin producing was 45 isolates (58.45%) .The minimum inhibitory concentration (MIC) of methicillin which were 32 micrograms \ ml. The effect of CD-Cholesterol ,Cholesterol ,Cyclodextran(CD) ,Methicillin and Phosphate Buffer Saline(PBS) on α- hemolysin activity was study and the hemolytic Titer was:8 ، 32.768 ,65.536 ,
140.737.488.355.32 , 4.961408E + 25 respectively, while the effect of the same effect with Titer 67.108.864 and low Titer with PBS 3.96140812E + 25. The α – hemolysin toxin was partialy purified by ammonium sulfate precipitation. partial purified toxin was injected inside the cornea of rabbit's eye and the erosion of cornea formed with diameter: 8 mm after 8 hours of injection while the erosion of cornea which injected with CD-Cholesterol that mixed with partial purified toxin was 4 mm. CD-Cholesterol was used in treatment as a drops which added to the affected eye and led to a decrease in corneal erosion area from 8 mm to 4 mm.
Effect of Some Materials on Productivity and Activity of -Hemolysin which Produced by Methicillin Ressistant Staphylococcus Aureus
-hemolysin
Methicillin- ressistant Staphylococcus aureus
CD-Cholesterol
Cholesterol
Cyclodextran (CD)
Methicillin and PBS
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
Exponentiated Weibull Distribution (EWD)
Reliability of multi-component Stress – Strength models R(s
k)
Maximum likelihood estimator (MLE)
Moment estimator (MOM)
shrinkage method (Sh)
Least Squares Estimator (LS)
Rank Set Sampling (RSS). and mean squared error (MSE).
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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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Theoretical And Applied Information Technology
Factors affecting global virtual teams’ performance in software projects
Today the trend is to perform software development work via distributed geographical area among team
individual or even as an organization. However
due to the global market and international presence of many companies
there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space
time and organizational boundaries via information and communication technologies. A global virtual team relies on communication
collaboration
and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study
we investigated factors that affect global virtual teams’ performance
factors considered include cultural differences
language problems
time-zone differences
team size
technical problems
lack of trust
lack of sufficient training
and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand
team size is the lowest level of effect on global virtual teams’ performance. © 2005 - 2016 JATIT & LLS. All rights reserved.
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