n each relapse. Objjec tt iiv es :: To sttudy diifffferentt ffacttors whiich miightt be associiatted or lleadiing tto
tthe occurrence off rellapse iin nephrottiic syndrome
Metthods:: A retrospective study of seventy patients with nephrotic syndrome with age range of 1-14 years, who were diagnosed and treated in Child's Central Teaching Hospital over the period of 1st of January and 1st of July 2008.
The patients were divided into three groups; frequent relapses group, infrequent relapses group and undetermined group. We compared between frequent relapses group and infrequent relapses group in regard to age, sex, type of presentation, biochemical findings which include; total serum protein, serum albumin and renal function test,

Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

This study was aimed to evaluate the effect of spraying nano chitosan loaded with NPK fertilizer and nettle leaf and green tea extracts on the growth and productivity of potato for the spring and fall seasons of 2021.It was conducted at private farm in Wasit Governorate, Iraq, as a factorial experiment (5 × 5) within randomized complete block design using three replicates. The first factor included spraying with four concentrations of chitosan nanoparticles loaded with NPK fertilizer 0, 10. 15 and 20% in addition to chemical fertilization treatment, the second factor was spraying nettle leaf extract 25 and 35 gL-1 and green tea extract with 2 and 4 g.L-1, in addition to the control treatment, spraying with distilled water only. The

Background: The autism spectrum disorder (ASD) describes a wide range of symptoms, including difficulty with social interaction and communication skills. Controversial thinking about oral health of children with ASD, in general may have a lower hygiene level than healthy individuals, low caries rate and high body weight in comparison to healthy children. This study was conducted to assess the oral health status in relation to nutritional status among institutionalized autistic children and adolescents. Materials and methods: From 12 institutes in Baghdad, the study group contained 364 child and adolescent with ASD (Male= 294, Female=70), while control group included 441 normal child and adolescent (Male=357, Female=84) from primary and seco

The problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, t

       Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty