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bsj-1456
Detection of Type 2 Diabetes Mellitus in Serum from Women with Polycystic Ovarian Syndrome
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Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorder. To determine the metabolic disorders in women with PCOS, (25) women with PCOS ages (15 - 47) years have been investigated and compared with (20) healthy individuals. All the studied groups were carried out to measure fasting blood sugar, (anti-GAD Ab, anti ?-islet cell Ab by IFAT) and measured insulin level by ELISA. There was significant elevation in the concentration of fasting blood sugar than in control groups (p ? 0.05) and there was negative results for anti-GAD Ab and anti ?-islet cell Ab by IFAT test for serum of women with PCOS, while there was significant differences in the insulin level for women with PCOS compared with control groups (p ? 0.05), these indicated that women with PCOS are at high risk for type -2 Diabetes mellitus and reflecting insulin resistance.

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Publication Date
Sun Dec 06 2009
Journal Name
Baghdad Science Journal
Best estimation for the Reliability of 2-parameter Weibull Distribution
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This Research Tries To Investigate The Problem Of Estimating The Reliability Of Two Parameter Weibull Distribution,By Using Maximum Likelihood Method, And White Method. The Comparison Is done Through Simulation Process Depending On Three Choices Of Models (?=0.8 , ß=0.9) , (?=1.2 , ß=1.5) and (?=2.5 , ß=2). And Sample Size n=10 , 70, 150 We Use the Statistical Criterion Based On the Mean Square Error (MSE) For Comparison Amongst The Methods.

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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preliminary Cytotoxic Study of Some Novel Furo-2-quinolone Compounds
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In this research, new series of Furo-2-quinolone [FQ] compounds have been synthesized. These novel [FQ] compounds were prepared from coumarin derivatives (Furocoumarins: psoralen and isopsoralen).Identifications of these FQ compounds were performed by using infrared spectrum (I.R), Ultraviolet spectrum (U.V) and Nuclear Magnetic Resonance spectrum (H1-NMR) besides some physical data. The cytotoxic screening involves ;using HEP-2 cell line which gave differential responses against tested compounds : 4,6 Dimethyl furo[2, 3-g] coumarin (C1), 1-(2`, 4`, Dimethoxy benzylideneimino)-2,6-dimethyl Furo [2, 3-g] quinoline-2-one (C3) and the angular psoralen of the same derivative

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
SARS-CoV-2 and other Coronaviruses: A matter of variations
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Since the appearance of COVID-19 disease as an epidemic and pandemic disease, many studies are performed to uncover the genetic nature of the newly discovered coronavirus with unique clinical features. The last three human coronavirus outbreaks, SARS-CoV, MERS-CoV and SARS-CoV-2 are caused by Beta-Coronaviruses. Horizontal genetic materials transfer was proven from one coronavirus to the other coronavirus of non-human origin like infectious bronchitis virus (IBV) of avian. Horizontal genetic materials transfer was also from non-corona viruses like astroviruses and equine rhinovirus (ERV-2) or from coronavirus-unrelated viruses, like influenza virus type C. However, SARS-CoV-2 is identical to SARS-CoV and MERS-CoV. Interestingly, Wuhan ci

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Publication Date
Thu Feb 28 2019
Journal Name
The Open Rheumatology Journal
The Value of Soluble Transferrin Receptor and Soluble Transferrin Receptor-ferritin Index in Discriminating Iron Deficiency Anaemia from Anaemia of Chronic Disease in Patients With Rheumatoid Arthritis
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Background:

Anaemia is a common extra-articular manifestation of rheumatoid arthritis (RA) where anaemia of chronic disease (ACD) and iron deficiency anaemia (IDA) are the two most frequent types. The distinction between these two types of anaemia has always been challenging requiring sophisticated techniques. Serum transferrin receptor (sTfR) a truncated soluble form of the transferrin receptor is one of the parameters that is influenced by the Iron content and supply to the erythrons and is not affected by inflammatory status and therefore the use of the sTfR/log ferritin (sTfR-F) index can be a reliable indicator of functional iron deficiency.

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Publication Date
Sat Mar 08 2025
Journal Name
Fusion: Practice And Applications
Fast Numeric Sign Detection Using Adaptive Thresholding and Geometry of Optimized Fingers
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A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Detection of Nutrients and Major Ions at Al Muthanna Storage Site Soil
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In the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO4), potassium (K), sodium (Na), magnesi

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Detection and interpretation of clouds types using visible and infrared satellite images
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One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

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