The objective of this study is to evaluate the level of parathyroid hormone, Co enzyme Q and total antioxidant status in serum’s women with fibromyalgia syndrome firstly, then to demonstrate if these biochemical markers affected by age and obesity.

      This study was performed at Rheumatology and Rehabilitation Consultation Unit in Baghdad Teaching Hospital. Venous blood sample were drawn from (59) female with FMS and (30) control (without FMS). The serum was obtained after on standing in order to coagulate then centrifuged. The mean age± SD of FMS group was (42.22±15.34) years and for control was (40.7±18.22) years. Those participants were subdivided into four different groups acc

Each phenomenon contains several variables. Studying these variables, we find mathematical formula to get the joint distribution and the copula that are a useful and good tool to find the amount of correlation, where the survival function was used to measure the relationship of age with the level of cretonne in the remaining blood of the person. The Spss program was also used to extract the influencing variables from a group of variables using factor analysis and then using the Clayton copula function that is used to find the shared binary distributions using multivariate distributions, where the bivariate distribution was calculated, and then the survival function value was calculated for a sample size (50) drawn from Yarmouk Ho

    Alzheimer’s Disease (AD) is the most prevailing type of dementia. The prevalence of AD is estimated to be around 5% after 65 years old and is staggering 30% for more than 85 years old in developed countries. AD destroys brain cells causing people to lose their memory, mental functions and ability to continue daily activities. The findings of this study are likely to aid specialists in their decision-making process by using patients’ Magnetic Resonance Imaging (MRI) to distinguish patients with AD from Normal Control (NC). Performance evolution was applied to 346 Magnetic Resonance images from the Alzheimer's Neuroimaging Initiative (ADNI) collection. The Deep Belief Network (DBN) classifier was used to fulfill classification f

Recently, Malaysia has been recognized as one of the most popular destinations for Foreign Direct Investment (FDI) in Southeast Asia. But how do these FDI inflows affect Malaysia economy? This paper aims to identify the role of FDI inflows in Malaysia economic growth through a proposed endogenous growth model. Annual data covers from 1975 to 2010. Unit root test and Johansen Co-integration test are adopted to respectively verify the time series data is stable and the linear combination of the variables is stationary. Hierarchical Multiple Regressions (HMR) Analysis is then conducted to find out the momentum of the Malaysia economic growth including FDI inflows. The results show that the FDI inflows together with the human capital deve

Public spending represents the government’s financial leverage and has a significant impact on real and monetary economic variables, and one of these effects is the effect of public spending on the exchange rate as an important monetary variable for monetary policy, As we know that public spending in Iraq is financed from oil revenues sold in US dollars, and the Ministry of Finance converts the US dollar into Iraqi dinars to finance the government's need to spend within the requirements and obligations of the state's general budget, And converting the US dollar into Iraqi dinars has an impact on the parallel exchange market, even if there is a contractual exchange rate between the Ministry of Finance and the Central Bank of Iraq to

Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate

Abstract

Heavy-duty diesel vehicle idling consumes fossil fuel and reduces atmospheric quality at idle period, but its restriction cannot simply be proscribed. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from DI multi-cylinders Fiat diesel engine. Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NOx), smoke opacity, carbon dioxide (CO₂) and noise have been reported, when three EGR ratios (10, 20 and 30%) were added to suction manifold.

CO₂ concentrations increased with increasing idle time and engine idle speed, but it didn’t show clear effect for IT adva

The main objectives of this research is to extract essential oil from: orange ( citrus sinensis), lemon( citrus limon) and mandarin( citrus reticulata) peels by two methods: steam distillation (SD) and microwave assisted steam distillation (MASD), study the effect of extraction conditions (weight of the sample, extraction time, and microwave power, citrus peel type) on oil yield and compare the results of the two methods, the resulting essential oil was analyzed by Gas Chromatography (GC).

   Essential oils are highly concentrated substances used for their flavor and therapeutic or odoriferous properties, in a wide selection of products such as foods, medicines and cosmetics. Extracti

     Foreign Object Debris (FOD) is defined as one of the major problems in the airline maintenance industry, reducing the levels of safety. A foreign object which may result in causing serious damage to an airplane, including engine problems and personal safety risks. Therefore, it is critical to detect FOD in place to guarantee the safety of airplanes flying. FOD detection systems in the past lacked an effective method for automatic material recognition as well as high speed and accuracy in detecting materials. This paper proposes the FOD model using a variety of feature extraction approaches like Gray-level Co-occurrence Matrix (GLCM) and Linear Discriminant Analysis (LDA) to extract features and Deep Learning (DL) for classifi

      This study has applied digital image processing on three-dimensional C.T. images to detect and diagnose kidney diseases.  Medical images of different cases of kidney diseases were compared with those of   healthy cases. Four different kidneys disorders, such as stones, tumors (cancer), cysts, and renal fibrosis were considered in additional to healthy tissues. This method helps in differentiating between the healthy and diseased kidney tissues. It can detect tumors in its very early stages, before they grow large enough to be seen by the human eye. The method used for segmentation and texture analysis was the k-means with co-occurrence matrix. The k-means separates the healthy classes and the tumor classes, and the affected