Objectives: The aim of our study was to compare the effect of low and high-flow desflurane anesthesia between genders and on muccociliary clearance changes.\nMatherial and methods: Fifty patients between the ages 18 and 61 with risk group ASA I-II that were previously planned for middle ear surgery under general anesthesia were included to the study after approval from the hospital ethical comittee and written consent were obtained. The patients were randomly assigned into two different groups; (Group I, n=25) for low flow anesthesia and (Group II, n=25) for standart flow anesthesia. The nasal mucociliary clearance was measured with Saccharin nasal transit time (SNTT). The first measurement was for control, before the anesthesia, and the second one was after waking from anesthesia and gaining orientation. \nResults: There was no statistical significance in terms of demographical features and operation duration between the patient groups. The average of postoperative saccharin nasal transit time (SNTT) was significantly longer in both groups compared to the preoperative transit time (p<0.05). The average SNTT of group I was statistically longer than group II (p=0.002). There were no differences between the groups. \nConclusion: Administration of desflurane anesthesia in two different flows prolongs saccharin nasal transit time. However, this prolongation was found to be within the normal limits, whereas compared between genders it was significantly longer in female group.
Let G be a non-abelian finite group and Z(G) be the center of G. Associate a graph NC(G) called non-commuting graph of G as follows (see[5]): Take G-Z(G) as the vertices of NC(G) and join two distinct vertices x and y, whenever xy≠yx. In [3,4,5] some properties of a group G with using non-commutig graph NC(G) was obtained. By programing with Fortran , we obtain the adjcency matrix of NC(G) and explore some properties of group G and NC(G) on this matrix.
Cloud computing is currently one of the fastest-growing emerging areas in information technology, and it has piqued the interest of the entire world. One of the key promises of cloud-delivered service is its high availability. Evaluation of the availability of cloud services is one of the main points in offering the best service and gaining client satisfaction. It can also help in establishing an agreement that ensures the desired service level is attained by the service provider. Using service protection may help in improving the service availability. This paper proposes a many: many protection model in hybrid cloud computing architecture to achieve cloud service availability. Two referenced techniques were used for the evaluation: the Markov model, as well as a discrete event simulator that was developed to determine the availability of service in this protection model. Experiments were done to test the impact of some factors that may affect availability: MTTR, MTTF, the number of competitors, and the number of protection resources. The results were graphed to show a comparison between these factors. Validation and verification of the simulator result was carried out, and a statement of validity was written.
Emergence of cloud computing encourages the local organizations to oriented and provision resources and Virtual Machines VMs dynamically from public cloud. One of the important objectives of provisioning resources is speeding up the execution time of distributed application for meeting applications with deadline constraints. The researchers have been worked hardly to suggest different algorithms and approaches for dynamic resources provisioning in order to meet application deadline. These researches concentrate on some factors to prevent deadline violation, but they ignore other factors. In this paper, we aim to evaluate what is the effect of most important factors together on meeting deadline when resources are provisioned from public cloud. These factors such as different time factors, VMs deployment time, data set size and data locality and data transmission time. Also, we evaluate the impact of these factors on the number of cloud resources estimations and the latency time that exceeds the deadline in case of deadline violation. To confirm results, CloudSim toolkit is used. The results show how all these factors together impact on the ability of meeting deadline. It also showed that to avoid deadline violation the importance of provisioning resources of the closet providers in case short deadline or large data set.
Mobile Cloud Computing combines cloud computing and mobile computing. It has turned into one of the business trendy expressions and a real exchange string in the IT world. As MCC is still at the early phase of advancement, it is important to handle a careful understanding of the innovation to call attention to the bearing of future research. In this paper, a review on various techniques of offloading for mobile clouds has been presented. The review has shown that graph partitioning during software deployment plays a critical role in energy consumption of cloud computing environment. The overall objective of this paper is to study and explore various graph partitioning algorithms to deploy software in mobile clouds in optimistic manner. This paper ends up with various limitations of exiting mobile cloud computing techniques.