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Today’s organisations are under pressure to cut the ICT infrastructure energy costs and also use of ICT infrastructure resources in efficient manners. On other hand organisations ICT infrastructures are expanding rapidly and demands agility in ICT infrastructure solutions, business requirements and in technology change. Virtualization is the most effective way to reduce the energy cost while enhancing efficient utilization of resources and agility. To fulfill these demands organisations are migrating from physical infrastructures to the virtual infrastructures. Where organisations are migrating to virtual infrastructures to deliver the services to business there is also need to consider the right virtual infrastructure fundamentals for efficient service delivery. If the virtual infrastructure is unreliable or experience poor performance such issues are not only causing the problems for virtual infrastructure but also can damage the organisation reputation. This research is based upon Information Technology Infrastructure Library (ITIL), to find the key goals of capacity management and align the capacity management within virtual infrastructure to ensure virtual infrastructure is utilize in the most efficient, predictable and cost effective manner. This research will also investigate the how to apply capacity management best practices to improve performance, reduce operating cost, analyse current capacity, predict future capacity and make sure service level agreements are met

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Smoking causes about 6 million deaths annually, increases the risk for many diseases and alters hematological parameters. Thus, the aim of this study was to evaluate the negative impact of cigarette smoking on the hematological parameters of healthy smokers in Libya. A total of 145 smokers and 145 non-smokers, with age range 39-45 years, were recruited. Blood samples were collected from each participant and were analysed for complete blood count. The obtained results were statically analysed using descriptive statistics and ANOVA. The mean for all study variables for smokers (except for MCHC) was greater than that for nonsmokers. The coefficient of variation (CV%) showed that the smokers group was more homogeneous for most variables than the non-smokers group, except for BMI and LYMP. The results of ANOVA test showed that only in the case of MCHC the non-smokers had a significantly higher mean (p < 0.05). For other variables, the smokers had significantly higher means (p < 0.05), except for the RBC, where the mean was non-significantly higher compared to the non-smokers. There was no statistically significant effect for the age variable or for the interaction between smoking and age on all variables. In conclusion, the study revealed that cigarette smoking has a significant impact on most haematological parameters; confirming that smoking has severe adverse effects on most haematological parameters

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