In this paper Alx Ga1-x As:H films have been prepared by using new deposition method based on combination of flash- thermal evaporation technique. The thickness of our samples was about 300nm. The Al concentration was altered within the 0 x 40.
The results of X- ray diffraction analysis (XRD) confirmed the amorphous structure of all AlXGa1-x As:H films with x  40 and annealing temperature (Ta)<200°C. the temperature dependence of the DC conductivity GDC with various Al content has been measured for AlXGa1-x As:H films.
We have found that the thermal activation energy Ea depends of Al content and Ta, thus the value of Ea were approximately equal to half the value of optical gap.

The objective of this in vivo study is to investigate the effects of 337.1 nm pulsed N2 laser on cellular immune response represented by lymphocyte transformation capacity and phagocytosis activity in laboratory animals. The samples include 60 adult male BALB/c mice, were divided into control group and experimental groups. The experimental groups were divided into two main groups according to the time period after N2 laser irradiation. Each group was divided into 9 subgroups which exposed to N2 laser radiation at different values of pulse repetition rates and exposure times. The results of immunological tests demonstrated that the exposure to 180 J/cm2 of N2 laser radiation induce adverse effect to cellular immune response. The results o

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Omentin (or intelectin) is a main visceral fat secretory adipokine.  There is a growing interest to link omentin, obesity and co-morbidity factors. The aim of the present study is to evaluate serum omentin and its association to insulin resistance biomarkers, lipid profile and atherogenic indies. This cross – sectional study was conducted in Obesity Research and Therapy Unit-Alkindy College of Medicine by recruiting (115) individuals; 49 males /66 females. Subjects between (20 to 60) years of age were selected and classified into two groups according to their Body mass index (BMI). Group1 involved healthy lean volunteers (25 male/ 36 female; BMI 18.5 - 24.9). Group2 involved obese subjects; (24 male / 36 female with BMI ≥ 30). The s

Background: The demand for esthetic orthodontic appliances is increasing; so the esthetic orthodontic archwires were introduced. Among them, Teflon and Epoxy coated stainless steel archwires. The amount of force available from the archwire depends on the structural properties and susceptibility to corrosion. All metallic alloys are changed during immersion in artificial saliva, chlorhexidine mouthwash andtoothpaste, but their behaviors differ from one type to another. They corrode at different rates, which lead to decrease the amount of force applied to the teeth. This in vitro study was designed to evaluate the corrosion pits in stainless steel archwires coated with Teflon and with Epoxy in dry and after immersion in artificial saliva, chl

ABSTRACT

This research included the preparation and characterization of new demulsifies from natural and synthetic polymers of chitosan and polyvinyl alcohol that are environmentally friendly and at the same time have high efficacy comparable to emulsifiers. imported foreign. The prepared compounds were examined using infrared spectroscopy and nuclear magnetic resonance spectroscopy, and all the spectral signals of the polymers were in good agreement with the chemical composition of the polymers. And the melting and decomposition that occur on polymers at high temperatures. The effect of the length and type of side chain in the compositions of polymers on the process of water separation of oil emulsions w

       Due to the importance of the relationship between the phenomenon of inflation and the exchange rate in the formulation of monetary policy in Iraq, the exchange rate plays a strategic role in limiting the inflation caused by the monetary expansion due to government spending, as a point of a view, the inefficiency of interest to achieve the monetary market balance and stability of the general level of prices as an overall goal of monetary policy in Iraq, the exchange rate has emerged as a brake on inflation in Iraq, as the research found that the monetary authority in the period 2003-2018 provided a methodical development in the formulation of monetary policy towards realizing the effects of inf

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi