Objective: To determine the effectiveness of hypothermia on renal functions for patients undergoing
coronary artery bypass graft CABG surgery.
Methodology: A purposive (non-probability) sample of (50) patients undergoing Isolated coronary artery
bypass graft surgery consecutively admitted to the surgical ward, and they were followed up in the
intraoperative, Intensive Care Unit (ICU) and in the postoperative (surgical ward). Post-operative renal function
test (glumeruler filteration rate (GFR) by using the Crockroft-Gault formula and serum creatinine level) was
determined first week post operative and post operative renal function was classified on the base of peak of
the serum creatinine level and decline of glomeruler filteration rate(GFR) as following : normal renal function
serum creatinine concentration and decline in(GFR) less than 25% from preoperative, moderate renal
dysfunction increase serum creatinine concentration and decline in(GFR) 25%-50% from preoperative, sever
renal dysfunction increase serum creatinine concentration and decline in(GFR) more than 50% from
preoperative test.
Results: results of this study show that (78%) from the sample develop post operative renal dysfunction and
the highly percentage of them are male (50%), advance age 60-70 (60%), smoking (47.0%), diabetes mellitus
DM (68%), cardiopulmonary bypass 180 and more (57.20%), New York Heart Association calcification NYHA
class III(47.5%) and patient without Intra Aortic Balloon Pump IABP(50,0%) . We conclude from the study that
highly percentage of patient undergoing isolated CABG may develop postoperative renal dysfunction even
when using hypothermic strategy as a protective measure and the patients with DM, male, advance age,
smoker, prolong time of CPB (more than 180 minutes), NYHA class III and patient without IABP are considered
as patient at high risk to develop postoperative renal dysfunction.
Recommendations: The researcher recommended that to find addition strategy rather than hypothermia
to protect renal function especially with the high risk patients during isolated CABG surgery.
Water pollution has created a critical threat to the environment. A lot of research has been done recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na3PO4) was investigated as a pollutant using liquid SERS based on colloidal Ag nanoflowers. The chemical method was used to synthesize nanoflowers from silver ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This nanoflowers SERS action in detecting Na3PO4 was reported and analyzed
... Show MoreThis paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ
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... Show MoreThe catalytic wet air oxidation (CWAO) of phenol has been studied in a trickle bed reactor
using active carbon prepared from date stones as catalyst by ferric and zinc chloride activation (FAC and ZAC). The activated carbons were characterized by measuring their surface area and adsorption capacity besides conventional properties, and then checked for CWAO using a trickle bed reactor operating at different conditions (i.e. pH, gas flow rate, LHSV, temperature and oxygen partial pressure). The results showed that the active carbon (FAC and ZAC), without any active metal supported, gives the highest phenol conversion. The reaction network proposed account
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... Show MoreHeavy oil is classified as unconventional oil resource because of its difficulty to recover in its natural state, difficulties in transport and difficulties in marketing it. Upgrading solution to the heavy oil has positive impact technically and economically specially when it will be a competitive with conventional oils from the marketing prospective. Developing Qaiyarah heavy oil field was neglected in the last five decades, the main reason was due to the low quality of the crude oil resulted in the high viscosity and density of the crude oil in the field which was and still a major challenge putting them on the major stream line of production in Iraq. The low quality of the crude properties led to lower oil prices in the global markets
... Show MoreMultiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
Criteria to be met in selecting the obtimal areas for generating alternative electric energy from wind