Background: Diabetic mellitus (DM) is a collection of metabolic disorder identified by hyperglycemia. The heterogeneous etiology includes defects either in insulin secretion, or in insulin action, or the both. In addition to the distraction in carbohydrate, fat and protein metabolism. Inflammatory reaction that caused by many pro-inflammatory cytokines play a central role in the pathogenicity of T2DM, these cytokines can enhance insulin resistance which led to impaired glucose homeostasis. Subjects: The study included 75 patients (38 males and 37 females) suffering from T2DM with age mean ± SE 52.30 ± 1.60, and 70 individuals as healthy controls (35 males and 35 females) with age mean ± SE 48.88 ± 0.64. Evaluation of immunological marke

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

Abstract: This research was performed to study the effect of some amino acids and vitamins on the growth of bacteria Staphylococcus aureas and its sensitivity against UV light. The results showed low inhibition in bacterial growth because amino acids repairs the damges caused by UV light. Besides the effect of two groups of antibiotics (β-lactame and tetracycline) on the growth of S. aureus and the possible interference of amino acids and vitamins in the activity of the antibiotics against this bacteria in the presence of UV light were studied. The result show increase in the sensitivity towards these antibiotics and provided protection against the antibiotics.

This study dealt with IL-13 1024 (C/T) gene genotyping among patients with Thyroid goiter in Iraq. Forty blood samples from patients with Thyroid goiter were collected and compared with 30 healthy persons as controls. The genotyping results of IL-13 1024 (C/T) gene using ARMS-PCR revealed presence TT, CC and CT genotypes beside T and C alleles. The T allele and TT genotype frequency were higher in Thyroid goiter patients compared to the same genotype and allele in healthy persons (P = 0.060). These increasing results were related with increasing risk factor of Thyroid goiter (odds ratio [OR] 2.15; 95% confidence interval [CI] 0.99–71.4). No significant differences between genotypes for Thyroid goiter patients and controls were revealed by

    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima

In this paper, the reliability and scheduling of maintenance of some medical devices were estimated by one variable, the time variable (failure times) on the assumption that the time variable for all devices has the same distribution as (Weibull distribution.

The method of estimating the distribution parameters for each device was the OLS method.

The main objective of this research is to determine the optimal time for preventive maintenance of medical devices. Two methods were adopted to estimate the optimal time of preventive maintenance. The first method depends on the maintenance schedule by relying on information on the cost of maintenance and the cost of stopping work and acc

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-