This study reflected on the relationship between contactin associated protein-like
2 gene (CNTNAP2) and autism spectrum disorders. The study includes forty autistic
patients and forty non autistic children as control groups (twenty unaffected sibling
and twenty unrelated children). DNA was extracted from Blood samples for
molecular detection of CNTNAP2 mutations associated with ASDs by using
Polymerase Chain Reaction (PCR) technique and sequencing analysis. PCR reaction
was performed to amplify exon 20 of CNTNAP2 gene. The PCR results revealed that
identical bands related to exon 20 of CNTNAP2 gene were present in all samples.
Therefore, five samples (four from autistic patients and one from control sibling)
we

Orthodontic tooth movement is characterized by tissue reactions, which consist of an inflammatory response in periodontal ligament and followed by bone remodeling in the periodontium depending on the forces applied. These processes trigger the secretion of various proteins and enzymes into the saliva. The purpose of this study was to evaluate the activity of the lactate dehydrogenase (LDH) in saliva during orthodontic tooth movement using different magnitude of continuous orthodontic forces. Thirty orthodontic patients (12 males and 18 females) with ages 17-23 years with class II division I malocclusion all requiring bilateral maxillary first premolar extractions. Those patients were randomly divided into 3 groups according to the magnitude

In this paper, the effects of hematocrit of red blood cells on blood flow through a stenosed human carotid artery was considered by taking blood as a Newtonian fluid. The governing equations on blood flow were derived. The mathematical content involved in the equations are the variables of interest such as number of stenosis , percentage of hematocrit  of red blood cells in the blood, flow rate, wall shear stress, and viscosity of the blood. Guided by medical data collected on the constraint of blood flow in stenosed human carotid arteries, the governing equations were used to check the effects of pressure gradient, wall shear stress, velocity, and volumetric flow rate of blood in the human carotid arteries. Also, the one-dimensiona

John Updike’s use of setting in his fiction has elicited different and even conflicting reactions from critics, varying from symbolic interpretations of setting to a sense of confusion at his use of time and place in his stories.  The present study is an attempt at examining John Updike’s treatment of binary settings in Pigeon Feathers and Other Stories (1962) to reveal theme, characters’ motives and conflicts.  Analyzing Updike’s stories from a structuralist’s perspective reveals his employment of two different places and times in the individual stories as a means of reflecting the psychological state of the characters, as in “The Persistence of Desire”, or expressing conflicting views on social and political is

Congenital absence of anterior cruciate ligament is highly uncommon occurrence. It has since been documented as a standalone anatomical entity or, more frequently, in conjunction with other congenital anomalies. Surgical treatment for this patient population has only been reported in very few cases. In this article, we share our experience in managing a case of unilateral congenital deficiency of anterior cruciate ligament (ACL) in a 13 years old female patient by physeal sparing arthroscopic ACL reconstruction, using All-inside technique.

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

The aims of the paper are to present a modified symmetric fuzzy approach to find the best workable compromise solution for quadratic fractional programming problems (QFPP) with fuzzy crisp in both the objective functions and the constraints. We introduced a modified symmetric fuzzy by proposing a procedure, that starts first by converting the quadratic fractional programming problems that exist in the objective functions to crisp numbers and then converts the linear function that exists in the constraints to crisp numbers. After that, we applied the fuzzy approach to determine the optimal solution for our quadratic fractional programming problem which is supported theoretically and practically. The computer application for the algo

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class