Background: Polycystic ovary syndrome is a heterogeneous disorder and its etiology appears to be complex and multifactorial; characterized by hyperandrogenism, chronic anovulation and infertility. It’s associated with evidence of low-grade chronic inflammation, as indicated by the presence of elevated levels of high sensitive C- reactive protein levels, interleukin-6 and tumor necrosis factor-α. The source of excess circulating tumor necrosis factor-α in obese Polycystic ovary syndrome patient is likely to be the adipose tissues while in lean women increased visceral adiposity has been proposed as a source of excess tumor necrosis factor-α.Objectives: to evaluate the levels of high sensitive C- reactive protein, tumor necrosis factor-α and interleukin-6 in patients with polycystic ovary syndrome before and after treatment with metformin; with emphasis on their relationship with the improvement in ovulation rate and body mass index in Iraqi women.Methods: 69 Iraqi females with PCOS, with mean age of 25.8±4.4 years, body mass index 31.14±2.23 kg/m2 and insulin resistant equal to 3.15±0.25. Additionally, 30 healthy fertile women BMI= 26.87±3.1 kg/m2 and mean age 23.4±2.8 years), the patients were treated with metformin 1500 mg/day for 3 months. Blood samples were obtained in the morning subsequent to an overnight fasting at baseline and at the end of the 12 weeks period of treatment, the samples were analyzed for plasma glucose level estimated by enzymatic colorimetric kit, while serum insulin , TNF-α, IL-6 , hs-CRP, Progesterone and sex hormone binding globulin . Results: BMI values were significantly increased at baseline value in patients (P<0.05) compared with healthy controls, then significantly decreased (12.9%) after treatment compared with baseline values, HOMA-IR index were significantly elevated in patients group at baseline compared with control, and significantly decreased by 17.4% after treatment. Regarding the influence of metformin on inflammatory markers, the present study demonstrated significant elevation of baseline levels (P<0.05) of TNF-α, hs-CRP and IL-6 compared with controls, and the baseline levels significantly decreased after treatment by 16%, 38% and 37% respectively. Meanwhile, sex hormone binding globulin levels were significantly decreased in PCOS patients compared with healthy controls, and significantly increased after treatment by 16.6%, also progesterone levels decline at baseline compared with control group, and it was increased significantly after treatment by 24%.Conclusions: The study detects an increased level of inflammatory cytokines, SHBG and decrease level of progesterone in Iraqi females with PCOS, and metformin therapy improves serum levels of the inflammatory cytokines associated with increased ovulation rate.
This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB ) to find the optimal solution
(5)
(12)
(15)
The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
... Show More
(12)
(4)
(12)
(10)
(3)
(2)
In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.
Abstract
The study aims to identify the common fears of preschool children and their relationship to the approaches to parental treatment in South Al Batinah Governorate from their mother’s point of view. Total of (466) mothers were selected as the study sample. The researcher used the scale of common fear and the scale of parental treatment approaches. The results of the study have shown that the most common fear among the study sample was (the fear of darkness) in the first level with a rate of 75.03%, and in the second level came the item (my child is afraid to sleep alone) by 72.74%, in the third level came to the item (fear of seeing insects) with a rate of 67.59%, and the last one was (the fear of rain) w
... Show MoreObjective(s): To assess parents' attitude toward immunization and its relation with their compliance and to find out the relationship between parents' attitude and their socio-demographic characteristics.
Methodology: A descriptive design is conducted from the period of 19th September 2020 to the 6th of March 2021. A non-probability (convenient) sample of (292) parents was selected from (5) primary health care centers in Karbala city. These centers are distributed throughout (2) primary health care sectors selected randomly as (20%) from each sectors. The questionnaire is developed and composed of three parts: First part: parent's socio-demographic characteristics, Second part: parents' attitude domain, which involves (13 items), and