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The Use of Left Ventricular Myocardial Stiffness Index as a Predictor of Myocardial Performance in Patients with Systemic Hypertension
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Our aim was to investigate the changes in the myocardium stiffness index for patients suffering from systemic hypertension, and to assess their left ventricular performance. We studied 263 hypertensive patients and 166 healthy subjects as a control group. By using conventional Doppler echocardiography, the following parameters were measured—Left ventricular end diastolic diameter, left ventricular end systolic diameter, transmitral early velocity, isovolumic relaxation time, and isovolumic contraction time. Tissue Doppler imaging (TDI) was used in the measurements of the early mitral annular velocity (Ea) and the diastolic stiffness was obtained by calculating the ratio E\Ea\LVIDd. Index myocardial performance (IMP) was calculated according to following equation (IVCT + IVRT)/ET for both the control group and hypertensive group. Results reveal that the differences in the average value of transmitral early filling velocity (E) between patients and control groups for age range (20 - 49) and (50 - 80) were (−1.91%) and (−3.69%) respectively with p value >0.05 for both groups, and the changes in LVIDd between patients and control groups were 0.42% and 1.29% for age ranges (20 - 49) and (50 - 80) respectively with p value >0.05 for both age groups. A significant difference in IMP between patients and controls has also been observed and the changes were 29.54% and 30.43% for age range (20 - 49) and (50 - 80) respectively with p value <0.05 for both groups. The mean values for E/Ea ratio and for the measured LV stiffness index were significantly higher in hypertensive patients compared with control group (p value < 0.05) for both age groups. In conclusion, LV myocardial diastolic stiffness index and IMP are increased in hypertensive patients.

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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
Fri Jan 01 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Structural and Electrical Properties Dependence on annealing temperature of a-Ge: Sb/c-Si Heterojunction
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Publication Date
Tue Oct 01 2024
Journal Name
Esic
Comparative Analysis of Economic Policy Stability between Monarchical and Republican Systems: A Theoretical Fundamental Research
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Comparative Analysis of Economic Policy Stability between Monarchical and Republican Systems: A Theoretical Fundamental Research

Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Design and construction of anair pollution detection system using a laser beam and absorption spectroscopy
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Air pollution is one of the important problems facing Iraq. Air pollution is the result of uncontrolled emissions from factories, car exhaust electric generators, and oil refineries and often reaches unacceptable limits by international standards. These pollutants can greatly affect human health and regular population activities. For this reason, there is an urgent need for effective devices to monitor the molecular concentration of air pollutants in cities and urban areas. In this research, an optical system has been built consisting of aHelium-Neonlaser,5mWand at 632.8 nm, a glass cell with a defined size, and a power meter(Gentec-E-model: uno) where a scattering of the laser beam occurs due to air pollution. Two pollutants were examin

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Publication Date
Wed Sep 01 2021
Journal Name
Acta Pharmaceutica Sinica B
Discovery of a potent and dual-selective bisubstrate inhibitor for protein arginine methyltransferase 4/5
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Publication Date
Tue Mar 18 2025
Journal Name
Physica Scripta
Design and Analysis of a highly sensitive open trapezoidal channel PCF-based Plasmonic Refractometric Sensor
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Abstract<p>This study introduces a highly sensitive trapezium-shaped PCF based on an SPR refractometric sensor with unique design features. The structure of a sensor was designed and analyzed using COMSOL Multiphysics v5.6 based on Finite Element Method (FEM) with a focus on investigating the influence of various geometric parameters on its performance. The two channels were coated with a metallic gold layer to provide chemical stability, and a thin layer of TiO₂ improved the gold's adhesion to the fiber. The findings indicate that the proposed sensor achieves maximum amplitude and wavelength sensitivities of 1,779 RIU⁻¹ and 30,500 nm/RIU, respectively, with corresponding resolutions of 3.2</p> ... Show More
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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Treatment of Al-Muthanna Petroleum Refinery Wastewater by Electrocoagulation Using a Tubular batch Electrochemical Reactor
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Abstract<p>An electrocoagulation process has been used to eliminate the chemical oxygen demand (COD) from wastewaters discharged from the Al-Muthanna petroleum refinery plant. In this process, a circular aluminum bar was used as a sacrificial anode, and hallow cylinder made from stainless steel was used as a cathode in a tubular batch electrochemical Reactor. Impacts of the operating factors like current density (5-25mAcm<sup>-2</sup>), NaCl addition at concentrations (0-2g/l), and pH at values (3-11) on the COD removal efficiency were studied.</p><p>Results revealed that the increase in current density increases the COD removal efficiency, whereas an increase</p> ... Show More
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Publication Date
Thu Jun 10 2010
Journal Name
Iraqi Journal Of Laser
Experimental Investigation of a Laser Wireless Video Communication System Using Intensity Modulated /Direct Detection Technique
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In this work Laser wireless video communication system using intensity modualtion direct
detection IM/DD over a 1 km range between transmitter and receiver is experimentally investigated and
demonstrated. Beam expander and beam collimeter were implemented to collimete laser beam at the
transmitter and focus this beam at the receiver respectively. The results show that IM/DD communication
sysatem using laser diode is quite attractive for transmitting video signal. In this work signal to noise
ratio (S/N) higher than 20 dB is achieved in this work.

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Publication Date
Fri Nov 22 2019
Journal Name
Chalcogenide Letters
CONCENTRATION EFFECTS ON ELECTRONIC AND SPECTROSCOPIC PROPERTIES OF ZnCdS WURTZOIDS: A DENSITY FUNCTIONAL THEORY STUDY
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