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Impacts of Androgen Abuse and Overtraining on Endocrine Profile in Bodybuilders
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Abuse of androgens and overtraining expose bodybuilders to multifactorial stress influences related to endocrine activity. Endocrine responses in 23 bodybuilder athletes were investigated after a strength training period, during which they were taking high doses of androgenic-anabolic steroids. Serum concentrations of TSH, T3, and T4 were unchanged significantly. Serum LH and FSH concentrations decreased dramatically (P<0.05). In addition, low mean concentration of serum testosterone was recorded, with more substantial reduction in participants of elder ages. The multiple regression model used in this analysis supported this inference. On the other hand, a positive association was observed between levels of blood lipids (total cholesterol, triglyceride) and the outcome predictor (mean serum testosterone level). The results also suggested a negative correlation between testosterone level and each of age and HDL level. The current study shows that excessive bodybuilding exercise has an impact on the hypothalamic–pituitary–thyroid (HPT) axis in top-level athletes. Also, simultaneous usage of anabolic steroids induces extreme shifts in the hypothalamic-pituitary–gonadal (HPGA) axis, which is reflected as changes in testosterone level, development of the overtraining syndrome, and adverse influences on hormonal control.

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Biometric Identification System Based on Contactless Palm-Vein Using Residual Attention Network
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Palm vein recognition technology is a one of the most effective biometric technologies for personal identification. Palm acquisition techniques are either contact-based or contactless-based. The contactless-based palm vein system is considered more accurate and efficient when used in modern applications, but it may suffer from problems like pose variations and the delay in the matching process. This paper proposes a contactless-based identification system for palm vein that involves two main steps; First, the central region of the palm is cropped using fast extract region of interest algorithm, then the features are extracted and classified using altered structure of Residual Attention Network, which is a developed version of convolution

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Publication Date
Fri Jul 19 2019
Journal Name
Iraqi Journal Of Science
A Comparative Study on Meta-Heuristic Algorithms For Solving the RNP Problem
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The continuous increases in the size of current telecommunication infrastructures have led to the many challenges that existing algorithms face in underlying optimization. The unrealistic assumptions and low efficiency of the traditional algorithms make them unable to solve large real-life problems at reasonable times.
The use of approximate optimization techniques, such as adaptive metaheuristic algorithms, has become more prevalent in a diverse research area. In this paper, we proposed the use of a self-adaptive differential evolution (jDE) algorithm to solve the radio network planning (RNP) problem in the context of the upcoming generation 5G. The experimental results prove the jDE with best vecto

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Publication Date
Tue Apr 24 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Very High Q-Factor Based On G-Shaped Resonator Type Metamaterial Absorber
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High Q-factor based on absorption can be achieved by tuning (the reflection and the transition percentage). In this work, the simple design and simulated in S-band have been investigated. The simulation results of G-shape resonator are shown triple band of absorption peaks 60%, 91.5%, and 70.3%) at resonance frequency 2.7 GHz, 3.26 GHz, and 4.05 GHz respectively. The results exhibited very high of the Q-factor ( 271 ) at resonance frequency ( 3.26 GHz ).  The high Q-factor can be used to enhance the sensor sensing, narrowband band filter and  image sensing.

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Quantifying Suicidal Ideation on Social Media using Machine Learning: A Critical Review
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Suicidal ideation is one of the severe mental health issues and a serious social problem faced by our society. This problem has been usually dealt with through the psychological point of view, using clinical face to face settings. There are various risk factors associated with suicides, including social isolation, anxiety, depression, etc., that decrease the threshold for suicide. The COVID-19 pandemic further increases social isolation, posing a great threat to the human population. Posting suicidal thoughts on social media is gaining much attention due to the social stigma associated with the mental health. Online Social Networks (OSN) are increasingly used to express the suicidal thoughts. Recently, a top Indian actor industry took th

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
Commutativity Results for Multiplicative (Generalized) (α,β) Reverse Derivations on Prime Rings
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Let  be a prime ring,  be a non-zero ideal of  and   be automorphism on. A mapping  is called a multiplicative (generalized)  reverse derivation if  where  is any map (not necessarily additive). In this paper, we proved the commutativity of a prime ring R admitting a multiplicative (generalized)  reverse derivation  satisfying any one of the properties:

 

 

 for all x, y  

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Publication Date
Fri Jan 01 2021
Journal Name
Agrosystems, Geosciences &amp; Environment
Cover crop influence on soil water dynamics for a corn–soybean rotation
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Abstract<p>Crop production is reduced by insufficient and/or excess soil water, which can significantly decrease plant growth and development. Therefore, conservation management practices such as cover crops (CCs) are used to optimize soil water dynamics, since CCs can conserve soil water. The objective of this study was to determine the effects of CCs on soil water dynamics on a corn (<italic>Zea mays</italic> L.)–soybean [<italic>Glycine max</italic> (L.) Merr.] rotation at three soil depths over 3 yr. The study was conducted at the Chariton County Cover Crop Soil Health Research and Demonstration Farm (CCSH) in Missouri. Initial CC establishment occurred in 2012. Volumetric soil water </p> ... Show More
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Publication Date
Sat Jul 31 2021
Journal Name
Iraqi Journal Of Science
On Sandwich Theorems Results for Certain Univalent Functions Defined by Generalized Operators
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In this present paper, we obtain some differential subordination and superordination results, by using generalized operators for certain subclass of analytic functions in the open unit disk. Also, we derive some sandwich results.

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Publication Date
Tue Sep 29 2020
Journal Name
Iraqi Journal Of Science
A Jordan Higher Reverse Left (resp. right) Centralizer on Prime -Rings
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In this paper,  we introduce the concepts of  higher reverse left (resp.right)   centralizer, Jordan higher reverse left (resp. right) centralizer, and Jordan triple higher reverse left (resp. right) centralizer of  G-rings. We prove that every Jordan higher reverse left (resp. right) centralizer of a 2-torsion free prime G-ring M is a higher reverse left (resp. right) centralizer of  M.

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Publication Date
Wed Jan 12 2022
Journal Name
Iraqi Journal Of Science
Face Detection by Using OpenCV’s Viola-Jones Algorithm based on coding eyes
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Facial identification is one of the biometrical approaches implemented for identifying any facial image with the use of the basic properties of that face. In this paper we proposes a new improved approach for face detection based on coding eyes by using Open CV's Viola-Jones algorithm which removes the falsely detected faces depending on coding eyes. The Haar training module in Open CV is an implementation of the Viola-Jones framework, the training algorithm takes as input a training group of positive and negative images, and generates strong features in the format of an XML file which is capable of subsequently being utilized for detecting the wanted face and eyes in images, the integral image is used to speed up Haar-like features calc

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