The BEK family of flows have many important practical applications such as centrifugal pumps, steam turbines, turbo-machinery and rotor-stator devices. The Bödewadt, Ekman and von Kármán flows are particular cases within this family. The convective instability of the BEK family of rotating boundary-layer flows has been considered for generalised Newtonian fluids, power-law and Carreau fluids. A linear stability analysis is conducted using a Chebyshev collocation method in order to investigate the effect of shear-thinning and shear-thickening fluids for generalised Newtonian fluids on the convective Type I (inviscid crossflow) and Type II (viscous streamline curvature) modes of instability. The results reveal that shear-thinning power-law

Background: Bowel preparation prior to
colonic surgery usually includes antibiotic
therapy together with mechanical bowel
preparation which may cause discomfort to the
patients, prolonged hospitalization and water
& electrolyte imbalance.
Objective: to assess whether elective colon
and rectal surgery may be safely performed
without preoperative mechanical bowel
preparation.
Method: the study includes all patients who
had elective large bowel resection at Medical
City – Baghdad Teaching Hospital between
Feb, 2007 to Jan, 2010. Emergency operations
were not included. The patients were randomly
assigned to the 2 study groups (with or without
mechanical bowel preparation.
Results: A to

This work deals with thermal cracking of three samples of extract lubricating oil produced as a by-product from furfural extraction process of lubricating oil base stock in AL-Dura refinery. The thermal cracking processes were carried out at a temperature range of 325-400 ºC and atmospheric pressure by batch laboratory reactor. The distillation of cracking liquid products was achieved by general ASTM distillation (ASTM D -86) for separation of gasoline fraction up to 220 ºC from light cycle oil fraction above 220 ºC. The comparison between the conversions at different operating conditions of thermal cracking processes indicates that a high conversion was obtained at 375°C, according to gasoline production. According to gasoline produ

The investment government expenditure is considered the fundamental of enhancing the economic activity as it has become a mean for achieving capital accumulation in all economic  sectors, The Iraqi economy is characterized of being yield unilateral depending petroleum  revenues as an essential  resource of financing government expenditure , as  the contribution of petroleum  sector in GDP is large in proportions to other economic sectors  contribution.

 The relationship between investing government expenditure, and non-oil GDP  is about to be not existent during the

This paper studies a novel technique based on the use of two effective methods like modified Laplace- variational method (MLVIM) and a new Variational method (MVIM)to solve PDEs with variable coefficients. The current modification for the (MLVIM) is based on coupling of the Variational method (VIM) and Laplace- method (LT). In our proposal there is no need to calculate Lagrange multiplier. We applied Laplace method to the problem .Furthermore, the nonlinear terms for this problem is solved using homotopy method (HPM). Some examples are taken to compare results between two methods and to verify the reliability of our present methods.

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl