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Lipid Profile and Fasting Blood Sugar Analysis in Patients with Cholelithiasis
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Cholelithiasis is one of the commonest surgical problems and one of the most common gastrointestinal diseases throughout the world but its pathogenesis remains unclear. Many theories have been proposed forward to explain the mechanism of stone formation. It is not fully clear if symptomatic gallstone disease is associated with a specific pattern of some biochemical abnormalities, as lipid profile and fasting blood sugar in serum of patients.

This study was designed to estimate lipid profile and fasting blood sugar in the sera of patients with cholelithiasis in comparison with normal individuals (control).

In this study, 104(male=16, female=88) were symptomatic gallstone patients (aged 42.79± 12.18 years), and 38(male=6 and female=32) were apparently healthy controls (aged 40.03± 7.47 years).

Blood samples were collected from symptomatic gallstones patients before their cholecystectomy operation. Over night fasting, blood samples were collected from all subjects to evaluate serum lipid profile: Total cholesterol (TC), triglyceride (TG), high density lipoprotein-cholesterol (HDL-c), low density lipoprotein-cholesterol (LDL-c), very low density lipoprotein-cholesterol (VLDL-c) and fasting serum glucose (FSG). There was a significant increase (P<0.05) in serum: TC, TG, LDL-c, VLDL-c and FSG of patients with cholelithiasis compared to the apparently healthy controls. The study also showed  that there was a significant decrease (P<0.05) in serum HDL-c in gallstone patients compared to control.

In conclusion, cholelithiasis was associated with lipid profile and fasting serum glucose abnormality that be the cause or the effect of gallstone formation. These findings should be taken into consideration while treating gallstone patients.

Key words: Gallstones, Cholesterol, Cholecystectomy.

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Relation & effect of Human resources management strategic with at work stress : Explorative study
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Abstract

The mine object for this research is determine the nature of the relation and effect between Human resources management strategic to less the  work stress , Human resources management strategic represent a set of procedures and practices to manage the human resources   at the organization. the stress of work effect on the performance of the human resources , al rasheed bank select to applied the qustioneer on the 32 person the work on the sebaa branch , using the qustioneer as a tool to collect data that is design  according some of the standards and make the validity and stability. to analyses this data by using spss for computation " percentage , mean , standard , deriation

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Publication Date
Sun Dec 01 2019
Journal Name
Al-nahrain Journal Of Science
Adsorption of P-Aminodiphenylamine with Iodine Charge Transfer Complex on Surface Arundo Plant
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charge transfer complex formed by interaction between the p- aminodiphenylamine (PADPA) as electron donor with iodine as electron acceptor in ethanol at 250C as evidenced by color change and absorption. The spectrum obtained from complex PADPA – Iodine shows absorptions bands at 586 nm. All the variables which affected on the stability of complex were studies such as temperature, pH, time and concentration of acceptor. The linearity of the method was observed within a concentration rang (10–165) mg.L-1 and with a correlation coefficient (0.9996), while the molar absorbitivity and sandell sensitivity were (4643.32) L.mol-1.cm-1 and (0.0943) μg.cm-2, respectively. The adsorption of complex PADPA–I2 was studied using adsorbent surfaces

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Mechanical Science And Technology
Optimization of a rectangular pin fin using elliptical perforations with different inclination angles
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Publication Date
Thu Jan 30 2014
Journal Name
Al-kindy College Medical Journal
Discrimination of Malignant from Acute Benign Compression Spinal Fractures with Magnetic Resonance imaging
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Background: Differentiation between malignant and benign vertebral compression fracture is often problematic. This is precisely difficult in elderly who are predisposed to benign compression caused by osteoporosis .Establishing correct diagnosis is of great importance in determining the treatment andprognosis.A study was performed to determine which magnetic resonance imaging findings are useful in discrimination between metastatic and acute osteoporotic compression fractures of the spine. Recently MRI is being increasingly used for evaluation of these fractures.Objectives: The aim of this study is to establish the correct diagnosis of malignant and benign compression vertebral fracture by MRI to determine treatment and prognosis.Methods

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Publication Date
Mon Feb 23 2026
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Sat Dec 11 2021
Journal Name
Engineering, Technology &amp; Applied Science Research
Post-Fire Behavior of Non-Prismatic Beams with Multiple Rectangular Openings Monotonically Loaded
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The main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope

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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental Simulation of Natural Heat Convection from Finned Vertical Plate with Different Inclinations
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In this work an experimental simulation is made to predict the performance of steady-state natural heat convection along heated finned vertical base plate to ambient air with different inclination angles and configurations of fin array. Two types of fin arrays namely vertical fins array and V-fins array on heated vertical base plate are used with different heights and spaces. The influence of inclination angle of the plate , configuration of fins array and fin geometrical parameters such as fin height and fin spacing on the temperature distribution, base convection heat transfer coefficient and average Nusselt number have been plotted and discussed. The experimental data are correlated to a formula between average Nusselt number versus R

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

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Publication Date
Thu Jun 29 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications (ijnaa)
Applying a suitable approximate-simulation technique of an epidemic model with random parameters
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Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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