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Improving an Ovulation Rate in Women with Polycystic Ovary Syndrome by Using Silymarin
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Polycystic ovary syndrome(PCOS) is a heterogeneous disorder of uncertain etiology , it is the most common endocrinopathy in women and most common cause of anovulatery infertility ,characterized by chronic anovulation and hyperandrogenemia .The present study was designed to investigate the effect of silymarin which is known to have antioxidant and insulin sensitivity effects on the  levels of glucose, insulin ,testosterone ,leutinizing hormone(LH) and progesterone .Ovulation rate and Homeostasis Model Assessment of insulin Resistance (HOMA) ratio were determined .A 3-months of treatment were conducted in 60 PCOS patients in three well-matched groups .The first one (n=20),received silymarin(750mg/day)  .The second group received metformin(1500mg/day) while the third group treated by combination of metformin (1500mg/day )and silymarin (750mg/day). All these groups  had taken the drugs in divided doses. The results showed significant improvement in all parameters at the end of treatment .The percentage of increment in progesterone levels after completion of treatment were 12.12, 15.9, and 17.51 in groups 1, 2, and 3 respectively and the number of patients  ovulated after 3 months of treatment  were 4,5, and 10 in groups 1,2, and 3 respectively. However they are more better in group of patients who were treated with combination of silymarin  with metformin.In conclusion the addition of silymarin to metformin in treatment of PCOS patients has improving effect on disturbed hormones and ovulation rate.

Key words: Polycystic ovary syndrome, silymarin, ovulation rate,metformin

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in </p> ... Show More
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Publication Date
Fri Mar 01 2024
Journal Name
International Journal Of Medical Informatics
An artificial intelligence approach to predict infants’ health status at birth
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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Discharge Coefficient of Contracted Rectangular Sharp-Crested Weirs, an Experimental Study
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An experimental study is made here to investigate the discharge coefficient for contracted rectangular Sharp crested weirs. Three Models are used, each with different weir width to flume width ratios (0.333, 0.5, and 0.666). The experimental work is conducted in a standard flume with high-precision head and flow measuring devices. Results are used to find a dimensionless equation for the discharge coefficient variation with geometrical, flow, and fluid properties. These are the ratio of the total head to the weir height, the ratio of the contracted weir width to the flume width, the ratio of the total head to the contracted width, and Reynolds and Weber numbers. Results show that the relationship between the discharge co

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Tue Mar 01 2022
Journal Name
Asian Journal Of Applied Sciences
Comparison between Expert Systems, Machine Learning, and Big Data: An Overview
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Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

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Publication Date
Thu Dec 31 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EVALUATING THE QUALITY OF IMPORTED AND LOCAL FLOUR IN TERMS OF QUALITY WITH IRON AND FOLIC ACID AND ITS COMPLIANCE WITH IRAQI STANDARD: EVALUATING THE QUALITY OF IMPORTED AND LOCAL FLOUR IN TERMS OF QUALITY WITH IRON AND FOLIC ACID AND ITS COMPLIANCE WITH IRAQI STANDARD
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Food fortification has an important and necessary role in compensating for the shortage of nutritional micronutrients, especially in developing and least developed countries. So, 12 samples of flour available in the local market, whether imported or locally produced flour, were obtained during 2019. The amount of base metal of the necessary iron element in the flour models studied which are available in local markets, measured by spot testing and was compared with the values ​​that should be added according to the specification Iraqi standard. Results revealed the qualitative evaluation of iron in locally produced flour does not conform to the Iraqi standard and is almost free of any reinforcement. While the percentage of imp

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Publication Date
Thu Apr 25 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ECONOMIC LOSSES CAUSED BY ROSE BEETLE MALADERA INSANABILIS (BRENSKE) ON FRUIT AND ORNAMENTAL PLANTS AND ITS CONTROL BY PATHOGENIC FUNGI: ECONOMIC LOSSES CAUSED BY ROSE BEETLE MALADERA INSANABILIS (BRENSKE) ON FRUIT AND ORNAMENTAL PLANTS AND ITS CONTROL BY PATHOGENIC FUNGI
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The study aimed to evaluate injuries and economic losses which caused by rose beetle Maladerainsanabilis (Brenske) on ornamental and fruit plants as introduced insect in Iraq during 2015 and determine infested host plants in addition to evaluate efficacy of pathogenic fungi Metarhiziumanisopiliae (1x10⁹ spore/ ml) and Beauvariabassiana (1x10⁸spore/ ml) in mortality of insect larvae in laboratory and field.The results showed that the insect was polyphagous infested many host plants (20 host plant)Which caused degradation and dead the plants through adult feeding on leaves and flower but large injury caused by larvae feeding on root plants which caused obligate dead to infested plant, the percentage mortality of rose plants 68.6%, pear

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Publication Date
Sat May 14 2022
Journal Name
Oral And Maxillofacial Surgery
Evaluation of crestal sinus floor elevations using versah burs with simultaneous implant placement, at residual bone height ≥ 2.0 _ &lt; 6.0 mm. A prospective clinical study
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