Mohamed Zaki

Concentrations of amino acid neurotransmitters were assessed in the hippocampus and cortex using HPLC. Control data showed slight differences from normal animals in the delta, theta and alpha waves while an increase in the beta wave was obtained. After 24 h of PSD, delta relative power increased and the rest of EEG wave’s power decreased with respect to control. After 48 h and 72 h the spectral power analysis showed non-significant changes to control. The amino acid neurotransmitter analysis revealed a significant increase in cortical glutamate, glycine and taurine levels while in the hippocampus, glutamate, aspartate, glutamine and glycine levels increased significantly. Both the waking EEG and neurotransmitter analyses suggest that PSD induced neurochemical and electrophysiological changes that may affect brain proper functionality. © 2011 Elsevier B.V. All rights reserved.

Effective task scheduling is essential for obtaining high performance in Heterogeneous Distributed Computing Systems (HeDCSs). However, finding an effective task scheduling in HeDCSs should take into consideration the heterogeneity of processors and inter-processor communication over head, which results from non-trivial data movement between tasks scheduled on different processors. In this paper, a new high performance task scheduling algorithm called Sorted Nodes in Leveled DAG Division (SNLDD) is presented for HeDCSs with considering a bounded number of processors. The main concept of the proposed algorithm is to divide the Directed Acyclic Graph DAG into levels and tasks in each level are sorted in descending order according to their computation size. A new attribute has been introduced and used to efficiently select tasks for scheduling in HeDCSs. This selection of tasks enables the proposed SNLDD algorithm to generate high-quality task schedule in a heterogeneous computing environment. To evaluate the performance of the proposed SNLDD algorithm, a comparison study has been done between it and the Longest Dynamic Critical Path (LDCP) algorithm which is considered the most efficient algorithm. According the comparative results, it is found that the performance of the proposed algorithm provides better performance than the LDCP algorithm in terms of speedup, efficiency, complexity, and quality.