Aims: The aim of this study was to evaluate the value and accuracy of longitudinal strain in detection of coronary artery disease compared to coronary angiography. Results: The left ventricular longitudinal strain-speckle tracking showed evidence of stenosis of left anterior descending artery, circumflex artery and right coronary artery in (86.1%), (76.4%), and (84.7%) respectively. For the stenosis in left anterior descending artery, the current study showed that the longitudinal strain was a good predictor for presence of significant stenosis with a sensitivity of (93.8%), specificity (75%) and accuracy (91.7%) compared with coronary angiography. For the stenosis in right coronary artery, the left ventricular longitudinal strain had

The research problem focused through the researcher's experience in the gymnastics game and the lack of use of educational models that give the student an important role in the educational process, so it became necessary to identify the type of prevailing style for students, and the need for diversity in the use of educational models based on scientific theories, including the Daniel Document model. Based on three theories of learning, which are structural, behavioral, and meaningful learning. The research aimed to identify the effect of using the Daniel model for people with two types of brain control (left and right) to learn the skill of the Cartwheel in artistic gymnastics for students of the second stage. The researcher used the experi

Abstract

The current research aims to examine the effectiveness of a training program for children with autism and their mothers based on the Picture Exchange Communication System to confront some basic disorders in a sample of children with autism. The study sample was (16) children with autism and their mothers in the different centers in Taif city and Tabuk city. The researcher used the quasi-experimental approach, in which two groups were employed: an experimental group and a control group. Children aged ranged from (6-9) years old. In addition, it was used the following tools: a list of estimation of basic disorders for a child with autism between (6-9) years, and a training program for children with autism

       unacceptable social behaviors, particularly withdrawal behavior that appears in children with autism represent a major problem hindering the process of communication with those around them and therefore the process of mergence  with them be difficult.

     The withdrawal causes a real affect deficit for children with autism limits the possibility of development of their intellectual and mental growth due to their solitude and the weakness of their focus in the acquisition of pedagogical skills and lack the necessary social skills to maintain the relations of friendship and enjoyment of them.

      withdrawal children fail to participate

AA Noaimi, BM Fadheel, Saudi medical journal, 2008 - Cited by 25

The discussion in this paper gives several theorems and lemmas on the Sums of Squares of  consecutive Carol Numbers. These theorems are proved by using the definition of carol numbers and mathematical induction method. Here the matrix form and the recursive form of sum of squares of  consecutive Carol numbers is also given. The properties of the Carol numbers are also derived.

The research problem is that most of the construction projects exceed the planned value, due to the failure to implement the plans on time. The current study aims to monitor the implementation of the project and for each of the executed tasks of the table of quantities in order to detect deviations at the time they occur, evaluate the time and cost performance, and then identify the areas of waste and analyze the implementation of each task in order to diagnose the underlying problems and find possible and applicable solutions in the environment Iraqi. The research was applied in one of the companies specialized in the field of construction projects, and one of the most important conclusions reached is the possibility of applying

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings