Objectives: Severe head injury is the most devastating neurosurgical condition and it is only next to cancers as the leading cause of death in developed countries.
Because trace elements (TEs) are involved in most of enzymes that drives the biochemical reactions, so they are considered as a window to the biochemical
environment of the body in general and in brain in specific.
Aim of the Study: This study measured six TEs (Fe, Zn, Mg, Cu, Mn and Co) in 29 patients with severe head injury (GCS Score 3-9); their ages between 5-50 years.
Collection and estimation performed at both Neurosurgical Hospital (NH) in Baghdad and Medical Research Center (MRC) of College of Medicine, Kadhimiyah between January 2004 and August 2004. 17 of healthy Iraqi volunteers of age- and sex- matched were used as a comparable control group in TEs measurement.
Results: The analysis showed that serum Cu level has a striking significant positive correlation with GCS (P<0.01) followed by serum Mg (P<0.01), serum Fe
(P<0.05) with mode of correlation is linear except for that of serum Fe has three phases of correlation. Serum Mg is the only TE showed statistical significant lower value in patient group than the control group (P<0.01). Zn is the only TE that is correlated with the mode of intake, significantly lower among patient on IVF than those on N/G (P<0.01). Serum zinc correlated in linear relation with serum Mg (P<0.05), serum Fe with serum Mg (P<0.05).
Recently, the development and application of the hydrological models based on Geographical Information System (GIS) has increased around the world. One of the most important applications of GIS is mapping the Curve Number (CN) of a catchment. In this research, three softwares, such as an ArcView GIS 9.3 with ArcInfo, Arc Hydro Tool and Geospatial Hydrologic Modeling Extension (Hec-GeoHMS) model for ArcView GIS 9.3, were used to calculate CN of (19210 ha) Salt Creek watershed (SC) which is located in Osage County, Oklahoma, USA. Multi layers were combined and examined using the Environmental Systems Research Institute (ESRI) ArcMap 2009. These layers are soil layer (Soil Survey Geographic SSURGO), 30 m x 30 m resolution of Digital Elevati
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A fault is an error that has effects on system behaviour. A software metric is a value that represents the degree to which software processes work properly and where faults are more probable to occur. In this research, we study the effects of removing redundancy and log transformation based on threshold values for identifying faults-prone classes of software. The study also contains a comparison of the metric values of an original dataset with those after removing redundancy and log transformation. E-learning and system dataset were taken as case studies. The fault ratio ranged from 1%-31% and 0%-10% for the original dataset and 1%-10% and 0%-4% after removing redundancy and log transformation, respectively. These results impacted direct
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Electricity consumption for household purposes in urban areas widely affects the general urban consumption compared to other commercial and industrial uses, as household electricity consumption is affected by many factors related to the physical aspects of the residential area such as temperature, housing unit area, and coverage ratio, as well as social and economic factors such as family size and income, to reach the extent of the influence of each of the above factors on the amount of electricity consumed for residential uses, a selected sample of a residential area in the city of Baghdad was studied and a field survey conducted of the characteristics of that sample and the results analyzed and modeled statistically in relation to the amo
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In this paper, some estimators for the reliability function R(t) of Basic Gompertz (BG) distribution have been obtained, such as Maximum likelihood estimator, and Bayesian estimators under General Entropy loss function by assuming non-informative prior by using Jefferys prior and informative prior represented by Gamma and inverted Levy priors. Monte-Carlo simulation is conducted to compare the performance of all estimates of the R(t), based on integrated mean squared.
In this paper, we study a single stress-strength reliability system , where Ƹ and ƴ are independently Exponentiated q-Exponential distribution. There are a few traditional estimating approaches that are derived, namely maximum likelihood estimation (MLE) and the Bayes (BE) estimators of R. A wide mainframe simulation is used to compare the performance of the proposed estimators using MATLAB program. A simulation study show that the Bayesian estimator is the best estimator than other estimation method under consideration using two criteria such as the “mean squares error (MSE)” and “mean absolutely error (MAPE)”.
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