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The aryl hydrocarbon receptor: a new frontier in male reproductive system
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Background: The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor historically recognized for its role in the regulation of toxicity mediated by environmental chemicals. Recent research points to AhR's critical participation in male reproductive physiology, particularly in spermatogenesis, hormone signaling, and the maintenance of sperm quality. Both endogenous ligands (e.g., dietary and gut microbiota-derived metabolites) and exogenous pollutants (e.g., dioxins and benzo-α-pyrene) influence AhR-mediated pathways, making it a key link between environmental exposures and male fertility. Results: This review highlights AhR's influence on the male reproductive system, emphasizing the role of endogenous AhR ligands and AhR expression in the maturation and function of male reproductive organs. Environmental AhR agonists have been shown to induce oxidative stress, hormonal imbalance, and sperm DNA damage, which impact harmfully on the spermatogenesis process, which leads to reproductive abnormalities. Conversely, certain natural compounds such as resveratrol, curcumin, and lycopene appear to antagonize AhR activation and reduce its negative effects, thus offering potential protective benefits against male reproductive toxicity. Nevertheless, discrepancies persist regarding the exact interplay between AhR signaling and critical reproductive hormones such as testosterone and LH, and it remains unclear how transgenerational epigenetic changes triggered by AhR activation might affect long-term male fertility. Conclusion: AhR is pivotal in male reproductive physiology, influencing spermatogenesis, sperm quality, and hormone regulation through its interactions with both endogenous and environmental ligands. Persistent pollutants such as dioxins and polycyclic aromatic hydrocarbons cause oxidative damage and hormonal disturbances via AhR, contributing to reduced sperm quality and fertility.

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Publication Date
Thu Jun 26 2014
Journal Name
Engineering Optimization
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
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The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A new technique for solving fractional nonlinear equations by sumudu transform and adomian decomposition method
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A novel technique Sumudu transform Adomian decomposition method (STADM), is employed to handle some kinds of nonlinear time-fractional equations. We demonstrate that this method finds the solution without discretization or restrictive assumptions. This method is efficient, simple to implement, and produces good results. The fractional derivative is described in the Caputo sense. The solutions are obtained using STADM, and the results show that the suggested technique is valid and applicable and provides a more refined convergent series solution. The MATLAB software carried out all the computations and graphics. Moreover, a graphical representation was made for the solution of some examples. For integer and fractional order problems, solutio

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Tue Jul 01 2014
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
A NEW SPECIES OF GRAPE-VINE LEAFHOPPERS, GENUS ARBORIDIA ZAKHVATKIN, 1946 (HOMOPTERA: CICADELLIDAE) FROM IRAQ
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Among a collection of leafhoppers from Erbil Province in Kurdistan/Iraq, a new species of the genus Arboridia Zakhvatkin, 1946 was designated and described here as a new species  to  the science. The erection of this species was mainly built on the external characters included the male genitalia. Sites and dates of collections so as the host-plants were verified.

 

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Publication Date
Sun Jun 01 2008
Journal Name
Baghdad Science Journal
A New Derivatives of Benzodiazepine, Imidazole, Isatin, Maleimide, Pyrimidine and 1,2,4-Triazole: Synthesis and Characterization
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The synthesis of new benzodiazepine, imidazole, isatin, maleimide, pyrimidine and 1,2,4-triazole derived from 2-amino-4-hydroxy-1,3,5-triazine, via its cyclocondensation reaction with different organic reagents, is described. FT-IR, 1H-NMR and as well as 13C-NMR spectra disclosed the structures of the precursors and heterocyclic derivatives formed.

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A new Technique For Solving Fractional Nonlinear Equations By Sumudu Transform and Adomian Decomposition Method
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A novel technique Sumudu transform Adomian decomposition method (STADM), is employed to handle some kinds of nonlinear time-fractional equations. We demonstrate that this method finds the solution without discretization or restrictive assumptions. This method is efficient, simple to implement, and produces good results. The fractional derivative is described in the Caputo sense. The solutions are obtained using STADM, and the results show that the suggested technique is valid and applicable and provides a more refined convergent series solution. The MATLAB software carried out all the computations and graphics. Moreover, a graphical representation was made for the solution of some examples. For integer and fractional order problems, solu

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Competitiveness of an enterprise under a flexible manufacturing system. Manufacturing strategy and flexibility - Case study
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The research has designed for studying the relationship between manufacturing strategy and its flexibility under the flexible manufacturing system with their reflection on the competitive environmental performance of the firm. To interpret and tackle the problem, a hypothesis has formulated stating that “ the competitive performance of a firm is interpreted by the manufacturing strategy and flexibility which are derived from the firm and its business  strategies under the flexible manufacturing system”. Related literatures with their theoretical dissertations, which enhanced the thoughtful content, have analyzed. An illustrative case study on the flexible manufacturing system at Toyota Motors Corporation working at the g

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Publication Date
Sat Jan 01 2011
Journal Name
Iraqi Journal Of Physics
Transfocation Technique to Overcome Atmospheric Scintillation Effect on a Laser Detection and Tracking System (LDTS)
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Atmospheric transmission is disturbed by scintillation, where scintillation caused more beam divergence. In this work target image spot radius was calculated in presence of atmospheric scintillation. The calculation depend on few relevant equation based on atmospheric parameter (for Middle East), tracking range, expansion ratio of applied beam expander's, receiving unit lens F-number, and the laser wavelength besides photodetector parameter. At maximum target range Rmax =20 km, target image radius is at its maximum Rs=0.4 mm. As the range decreases spot radius decreases too, until the range reaches limit (4 km) at which target image spot radius at its minimum value (0.22 mm). Then as the range decreases, spot radius increases due to geom

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