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Prenatal Markers of Foetal Complications
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Prenatal markers are commonly used in practice to screen for some foetal abnormalities. They can be biochemical or ultrasonic markers in addition to the newly used cell free Deoxyribonucleic Acid (DNA) estimation. This review aimed to illustrate the applications of the prenatal screening, and the reliability of these tests in detecting the presence of abnormal chromosomes such as trisomy-21, trisomy-18, and trisomy-13 in addition to neural tube defects. Prenatal markers can also be used in the anticipation of some obstetrical complications depending on levels of these markers in the mother’s circulation. In the developed countries, prenatal screening tests are regularly used during antenatal care period. Neural tube defects, numerical and structural chromosomal abnormalities, in addition to some obstetrical problems are commonly screened for, by using prenatal tests. Maternal education about the importance of performing these tests should be done in order to improve the detection rate of foetal abnormalities and some pregnancy complications.

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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Use projection pursuit regression and neural network to overcome curse of dimensionality
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Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

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Publication Date
Fri Nov 01 2019
Journal Name
Journal Of Engineering
Analysis of Shell and Double Concentric Tube Heat Exchanger Using CFD Application
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This study focuses on CFD analysis in the field of the shell and double concentric tube heat exchanger. A commercial CFD package was used to resolve the flow and temperature fields inside the shell and tubes of the heat exchanger used. Simulations by CFD are performed for the single shell and double concentric tube.

This heat exchanger included 16 tubes and 20 baffles. The shell had a length of 1.18 m and its diameter was 220 mm. Solid Works 2014, ANSYS 15.0 software was used to analyze the fields of flow and temperature inside the shell and the tubes. The RNG k-ε model was used and it provided good results. Coarse and fine meshes were investigated, showing that aspect ratio has no significant effect. 14 million

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Detecting DNA of multispecies dinoflagellate cysts in the sediment from three estuaries of Makassar strait and fishing port using CO1 primer: Is it CO1 primer suitable for detecting DNA dinoflagellate?
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Most dinoflagellate had a resting cyst in their life cycle.  This cyst was developed in unfavorable environmental condition. The conventional method for identifying dinoflagellate cyst in natural sediment requires morphological observation, isolating, germinating and cultivating the cysts.  PCR is a highly sensitive method for detecting dinoflagellate cyst in the sediment.  The aim of this study is to examine whether CO1 primer could detect DNA of multispecies dinoflagellate cysts in the sediment from our sampling sites. Dinoflagellate cyst DNA was extracted from 16 sediment samples. PCR method using COI primer was running. The sequencing of dinoflagellate cyst DNA was using BLAST. Results showed that there were two clades of dinoflag

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Publication Date
Wed Jan 01 2020
Journal Name
Plant Archives
INVESTIGATION OFsHLA-GAND IT’S RECEPTOR (LILRB4) IN IRAQI PATIENTS INFECTED WITH L. INFANTUMAND THEIR EFFECTS ON THE LEVEL OF IL-12
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Visceral leishmaniasis(VL) or kala-azar is one of the world most neglected tropical diseases in mortality and fourth in morbidity, rK39 dipstick was used to diagnose the suspected infected patients as easiest and rapid technique for VL diagnostic, the disease out-coming required to the differentiation of cell mediated immunity either T-helper 1(Th-1) or (Th-2). One of main pointers that may be considered as one of immune evasion strategy in the host-parasite interplay is HLA-G level alteration. HLA-G Known as a special proteins (non-classical HLA class I) molecules which can suppress the immune system by T-cell functions impaired in the aid with target receptors as LILRB4. The development of the cell mediated immunity initiated with Interle

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Self-Localization of Guide Robots Through Image Classification
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The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Wear Parameters in AISI 4340 Steel
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Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Sat Jan 01 2022
Journal Name
Structures
Horizontal pushout tests and parametric analyses of a locking-bolt demountable shear connector
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A ‘locking-bolt’ demountable shear connector (LBDSC) is proposed to facilitate the deconstruction and reuse of steel-concrete composite structures, in line with achieving a more sustainable construction design paradigm. The LBDSC is comprised of a grout-filled steel tube and a geometrically compatible partially threaded bolt. The latter has a geometry that ‘locks’ the bolt in compatible holes predrilled on the steel flange and eliminates initial slip and construction tolerance issues. The structural behaviour of the LBDSC is evaluated through nine pushout tests using a horizontal test setup. The effects of the tube thickness, strength of concrete slab, and strength of infilled grout on the shear resistance, initial stiffness, and du

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Publication Date
Thu Jan 06 2022
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Nurse-Midwife's Knowledge and Performance Regarding Immediate Newborn Care in Delivery Rooms at Maternity Hospitals in Baghdad City
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Objectives: To assess nurses-midwives knowledge and performance regarding immediate newborn care in delivery rooms, and to identify the relationship between nurses-midwives knowledge and performance and their socio-demographic and professional variables regarding immediate newborn care.

 

 

 

Methodology: A descriptive study was conducted from 1st of October, 2019 to 20TH of October, 2020 at three maternity teaching hospitals in Baghdad city/Al-Russafa Health Directorate: Al-Elwiya Maternity Teaching Hospital, Fatema Al- Zahra Maternity and Pediatric Hospital, Al- Za'faraniyah General Hospital. Non-probability (purposive sample) include

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