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Assessment of mandibular radiomorphometric indices as predictors of osteoporosis in postmenopausal women (Cephalometric reconstructed computed tomographical study)
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Background: Osteoporosis affects almost all of the bones in the female body; the most important one in the facial bone is mandible. Menopause is defined as an absence of the menses for one year. During this time, estrongen, progesterone and ovarian androgens production are diminished due to adult onset ovarian failure which leads to osteoporosis. This study aimed to evaluate the use of computed tomography mandibular morphometric indices for the assessment of pre and postmenopausal osteoporotic women. Subjects and material: This study conducted on 50 Iraqi females divided into 2 groups 20 -30years old as a control group and over50 years old as a study group attending Al-Karkh hospital, Department of Computed Tomography.(each group25 female). Information from each female was recorded and mentioned on a case sheet specially prepared. Data collected, when analysed, using SPSS version 13 program loaded on a computer machine. Results: All the measurements in this study( gonial angle in degree, antigonial angle in degree and depth in millimetre, mandibular and mental thickness in millimetre, bone mineral density in HU and mandibular cortex index),there were no statically significant differences between right and left side P-value <0.001. Gonial angle had statistically positive linear correlation with age in the study group P-value <0.001. Bone mineral density and mandibular and mental thickness had statically negative linear correlation with age. Antigonial angle increased as age increased till reach 180 degree in some cases and the depth decreased correlated to the age till reach zero mm in some cases P-value <0.001. Mandibular cortex index increased in bone irregularity related to increase in age. Conclusion: It was concluded that osteoporosis and osteoporosis risk in postmenopausal females could be detected by using CT scan through measuring certain mandibular radiomorphometric indices.

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Publication Date
Mon Sep 01 2025
Journal Name
Civil Engineering Journal
Pre- and Post-Cracking Resistance of Steel Fiber Reinforced Concrete Flexural Members with GFRP Bars
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This research investigates the pre- and post-cracking resistance of steel fiber-reinforced concrete specimens with Glass Fiber Reinforced Polymer (GFRP) bars subjected to flexural loading. The purpose is to modify the ductility and cracking resistance of GFRP-reinforced beams, which are prone to early cracking and excessive deflections instigated by the low modulus of elasticity of GFRP. Six self-compacting concrete specimens (1500×240×200 mm), incorporating steel fibers of two lengths (25 mm and 40 mm) with varying distribution depths, were tested to assess their structural performance. The results indicate significant enhancements in cracking resistance, stiffness, energy absorption, ductility, and flexural strength. Tested beam

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Publication Date
Sat Jun 01 2024
Journal Name
Annals Of Applied Sport Science
The Psychological Well-being and Its Relationship with the Functional Creativity of Female Gymnastics’ Trainers
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Publication Date
Wed Jan 04 2023
Journal Name
Frontiers In Chemestry
Thermal and flow performance analysis of a concentrated linear Fresnel solar collector with transverse ribs
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This article deals with the impact of including transverse ribs within the absorber tube of the concentrated linear Fresnel collector (CLFRC) system with a secondary compound parabolic collector (CPC) on thermal and flow performance coefficients. The enhancement rates of heat transfer due to varying governing parameters were compared and analyzed parametrically at Reynolds numbers in the range 5,000–13,000, employing water as the heat transfer fluid. Simulations were performed to solve the governing equations using the finite volume method (FVM) under various boundary conditions. For all Reynolds numbers, the average Nusselt number in the circular tube in the CLFRC system with ribs was found to be larger than that of the plain abs

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Publication Date
Fri Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
An update on Nanoparticle Formulation Design of Piperine to Improve its Oral bioavailability: A Review
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Piperine, a crystalline alkaloid compound isolated from Piper nigrum, piper longum, and other types of piper, has had many fabulous pharmacological advantages for preventing and treating some specific diseases, such as analgesic, anti-inflammatory, hepatoprotective, antimetastatic, antithyroid, immunomodulatory, antitumor, rheumatoid arthritis, osteoarthritis, Alzheimer's, and improving the bioavailability of other drugs. However, its potential for clinical use through oral usage is hindered by water solubility and poor bioavailability. The low level of oral bioavailability is caused by low solubility in water and is photosensitive, susceptible to isomerization by UV light, which causes piperine concentration to decrease. Many different

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Advanced Pharmacy Education And Research
Co-surfactant effect of polyethylene glycol 400 on microemulsion using BCS class II model drug
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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
A Magnetic Field Concentration Method for Magnetic Flux Leakage Detection of Rail-Top Surface Cracks
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Publication Date
Tue Dec 08 2020
Journal Name
Acs Infectious Diseases
Antileishmanial Chemotherapy through Clemastine Fumarate Mediated Inhibition of the <i>Leishmania</i> Inositol Phosphorylceramide Synthase
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Publication Date
Tue Jun 01 2021
Journal Name
Electric Power Systems Research
Electromagnetic transient modeling of form-wound stator coils with stress grading system under PWM excitation
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The insulation system of a machine coil includes several layers made of materials with different characteristics. The effective insulation design of machine coils, especially in the machine end winding, depends upon an accurate model of the stress grading system. This paper proposes a modeling approach to predict the transient overvoltage, electric field, and heat generation in machine coils with a stress grading system, considering the variation of physical properties in the insulation layers. A non-uniform line model is used to divide the coil in different segments based on material properties and lengths: overhang, stress grading and slot. The cascaded connection of chain matrices is used to connect segments for the representation of the

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Synthesis and Evaluation of Platinum Nanoparticles Using F. Carica Fruit Extract and Their Antimicrobial Activities
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Abstract

In this manuscript, a simple new method for the green synthesis of platinum nanoparticles (Pt NPs) utilizing F. carica Fig extract as reducing agent for antimicrobial activities was reported. Simultaneously, the microstructural and morphological features of the synthesized Pt NPs were thoroughly investigated. In particular, the attained Pt NPs exhibited spherical shape with diameter range of 5-30 nm and root mean square of 9.48 nm using Transmission Electron Microscopy (TEM) and Atomic Force Microscopy (AFM), respectively. Additionally, the final product (Pt NPs) was screened as antifungal and antibacterial agent against Candida and Aspergillus species as well as Gram-positive Staphyllococcus aureus and G

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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