Retinal detachments due to traumatic tears in the pars plana ciliaris

Hypothermia during orthotopic liver transplantation (OLT) is common despite measures to prevent this complication. We retrospectively analyzed two groups of patients; those managed with (n = 113) or without (n = 109) a heat exchanger (HE) incorporated in the venovenous bypass (VVB) circuit to test the hypothesis that normothermia before liver reperfusion minimizes hypotension during reperfusion and decreases neohepatic transfusion requirements. Use of the HE resulted in significantly warmer patients during reperfusion and at the end of surgery (P < .001). An increase in neohepatic transfusion requirement was observed in patients with HE use: packed red blood cells, 4 +/- 4 versus 3 +/- 3 units; fresh-frozen plasma, 5 +/- 5 versus 4 +/- 4 units; platelets, 8 +/- 8 versus 6 +/- 7 units; and cryoprecipitate, 5 +/- 7 versus 3 +/- 5 units. There was no difference between the two groups in the untoward hemodynamic events during reperfusion of the liver (P = .31). We conclude that during OLT, the use of an HE in a nonheparinized VVB circuit helps maintain normothermia. Our limited experience suggests that its use is safe but does not improve hemodynamic stability during reperfusion or decrease blood loss during the neohepatic period.     

Profit maximization based task scheduling in hybrid clouds using whale optimization technique

ABSTRACT

In cloud computing system, task scheduling plays an important key role. The tasks provided by the user to allocate in cloud have to pay for the share of resources that are used by them. The requirement of task scheduling in the cloud environment has become more and more complex, and the amount of resources and tasks is growing rapidly. Therefore, an efficient task-scheduling algorithm is necessary for allocating the task efficiently in the cloud, which can achieve minimum resource utilization, minimum processing time, high efficiency, and maximum profit. In hybrid clouds to maximize the profit of a private cloud while guaranteeing the service delay bound of delay-tolerant tasks is studied in this article. Here, a new metaheuristic technique inspired from the bubble-net hunting technique of humpback whales, namely whale optimization algorithm (WOA), has been applied to solve the task-scheduling problem. Then WOA algorithm is compared with existing algorithms such as artificial bee colony algorithm (ABC) and Genetic algorithm (GA). The experimental result shows that the proposed WOA algorithm greatly increases the efficiency and achieves maximum profit for the private cloud.