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Neonatal bacterial sepsis: risk factors, clinical features And short term outcome
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Background: Neonatal infections are afrequent and important causes of neonatal morbidity and mortality especially in the developing countries.
Objective: The aim of the study is to determine the clinical picture, risk factors associated with neonatal sepsis and to estimate short term outcome from neonatal sepsis and its relation to birth weight, gestational age, onset of sepsis and type of bacteria.
Patients and Methods: A prospective study was conducted on 80 neonates presented with sepsis who had been admitted to intensive care unit in Children Welfare Teaching hospitals in Baghdad over six months period between (15th of January 2008 to 15th of June 2008).A thorough history and physical examination were carried out, and samples of blood were taken for blood culture and sensitivity.
Results: Eighty neonates were studied, sepsis was confirmed by clinical and laboratory measures. Fifty five (68.7%) neonates were males and 25(31.2%) were females. Fifty four (67.5%) were preterm and 26 (32.5%) were full term. Fifty nine (73.25%) neonates were still alive during period of hospitalization and discharged home, while 21 (26.25%) neonates died. Early onset sepsis was detected in 26 (32.5%) neonates while late onset sepsis was detected in 54 (67.5%) neonates, However, the death rate was higher in early onset sepsis (57.7%) compared to late onset sepsis (18.5%). The death rate was higher in neonates with maternal history of prolonged rupture of membrane >18 hours (54.8%), also it was increased when there was fever or infection during pregnancy.
Conclusions: The study showed that the most common neonatal risk factors that increase the incidence of mortality were early neonatal sepsis, home delivery, prolonged rupture of membrane more than 18 hours and maternal fever or infection, and the most common features were lethargy, absence or weak moro reflex and reluctant to feed, The most common bacteria isolated from blood cultures was E. coli.

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
Diagnosis of Malaria Infected Blood Cell Digital Images using Deep Convolutional Neural Networks
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     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of Engineering
Numerical Investigation of the Effect of Inserted Twisted Tape inside Submerged Bundle Tubes on its Thermal Performance
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Twisted tape insertion in the smooth plain tube is one of the types of passive methods that are used to enhance heat transfer. Swirl fluid flow inside the tube and related heat transfer characteristics are very complex. ANSYS FLUENT (V 16.1) and ASPEN industrial program are used in analyzing this technique for enhancement heat transfer. A circular plain tube has length L=8534mm and 17 mm inner diameter with a twisted tape of twist ratio of y = (H/D) = (150/17) =8.8 along the plain tube were considered for this study. Eight Reynolds numbers (Re) of 784, 1000, 2000, 3000, 4000, 5000, 6000 and 7000 are used to analyze the response of thermal performance. Crude oil API 28 exit temperature, film heat transfer coefficient, Nus

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Publication Date
Mon May 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Study of the Anti-Diuretic Hormone (ADH) on End Stage Renal Failure Disease (ESRD) Pre-Hemodialysis in Iraqi Patients
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     Chronic renal disease (CRD) is a pathophysiologic process with multiple etiologies, resulting in the inexorable attrition of Nephron number and function and frequently leading to end-stage renal disease (ESRD). In turn, ESRD represents a clinical state or condition in which there has been an irreversible loss of endogenous renal function, of a degree sufficient to render the patient permanently dependent upon renal replacement therapy (dialysis of transplantation) in order to avoid life threatening uremia, reflecting a dysfunction of all organ systems as a result of untreated or under treated acute or chronic renal failure. The current study was involved 80 patients, the age range within 25-70 ye

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Publication Date
Sun May 07 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Theoretical Calculation of Reorientation Energy in Metal /Semiconductor Interface
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A theoretical calculation of the reorientation energy for non adiabatic electron transfer at
interface between metal and semiconductor system was carried out. The continuum outer
sphere theory of electron transfer reaction has been extensively used for electron transfer
between metal/semiconductor interface .It is found that in these calculations the reorientation
energy is proportional to the optical and statistical dielectric constant of semiconductor ,
properties of metal ,and the distance between metal and semiconductor .Results of
reorientation energy show that ZnO semiconductor with metal Au possess a good matching as
compared with ZnS and ZnSe . Theoretical calculation showed a good agreement with
ex

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Publication Date
Sat Aug 01 2020
Journal Name
Key Engineering Materials
Compressive Strength Performance of Reactive Powder Concrete Using Different Types of Materials as a Partial Replacement of Fine Aggregate
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Reactive Powder Concrete (RPC) can be incorporate as a one of the most important and progressive concrete technology. It is a special type of ultra-high strength concrete (UHSC) that’s exclude the coarse aggregate from its constitutive materials. In this research an experimental study had been carried out to investigate the effect of using three types of materials (porcelain aggregate) and others sustainable materials (glass waste and granular activated carbon) as a partial replacement of fine aggregate. Four percentages had considered (0, 10, 15 and 20) % to achieve better understanding for the influence of these materials upon the compressive strength of RPC. Four curing ages had included in this study, these are; 7, 28, 60 and

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Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Journal Of Science
The Plasma Characteristics of the Earth's Ionosphere in F-layer
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Publication Date
Mon Jan 30 2023
Journal Name
Iraqi Journal Of Science
Periodic Solutions For Nonlinear Systems of Multiple Integro-differential Equations that Contain Symmetric Matrices with Impulsive Actions
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This paper examines a new nonlinear system of multiple integro-differential equations containing symmetric matrices with impulsive actions. The numerical-analytic method of ordinary differential equations and Banach fixed point theorem are used to study the existence, uniqueness and stability of periodic solutions of impulsive integro-differential equations with piecewise continuous functions. This study is based on the Hölder condition in which the ordering ,  and  are real numbers between 0 and 1.

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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
Plants Leaf Diseases Detection Using Deep Learning
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     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

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Publication Date
Thu Sep 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Corrosion Inhibition of Steel Reinforcement in Concrete
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