Background: Friedreich ataxia (FRDA) is the most common form of inherited ataxia, comprising one-half of all hereditary ataxias with a carrier rate between 1 in 60 to 1 in 90 and with a disease prevalence of 1 per 29,000. It can occur in two forms the classic form or in association with a vitamin E dependent ataxia. The precise role of Vitamin E in the nervous system is unknown; An Oxidative attack is suspected to play a role in Ataxia with Vitamin E deficiency, as well as in Friedreich ataxia. Vitamin E is the major free-radical-trapping antioxidant.

Objective: Theobjectives of the study is to asses vitamin E level in patients with Friedreichs ataxia phenotype in Iraqi patients.

The aim of the current research is to reveal the effect of using brain-based learning theory strategies on the achievement of Art Education students in the subject of Teaching Methods. The experimental design with two equal experimental and control groups was used. The experimental design with two independent and equal groups was used, and the total of the research sample was (60) male and female students, (30) male and female students represented the experimental group, and (30) male and female students represented the control group. The researcher prepared the research tool represented by the cognitive achievement test consisting of (20) questions, and it was characterized by honesty and reliability, and the experiment lasted (6) weeks

This study aimed to identify the role of school administration in achieving educational and learning goals from the point of view of educational supervisors in the stage of basic education. The descriptive method was adopted. As for the sample size, it has reached (59) educational supervisors. A questionnaire consisting of 29 paragraphs divided into four areas was used. The data were statistically analyzed on the Chi-square test, the percentage, and the mono-variance analysis. The result showed that the school administration contributes to achieving educational goals. It also works to solve problems in democratic ways, and in modern methods, there are differences in the criteria for choosing the headmaster. The study recommended that sch

   Organizational learning is one of the most important means of human resource development in organizations, but most of the organizations, especially public ones do not realize the importance of organizational learning enough, and estimated his role accurately in building intellectual capital, the resource competitive importantly for organizations of the third millennium and who suffers is other end of lack of understanding of its meaning and how to prove its presence and measured in public organizations, so there is the need for this research, which aims to investigate the effect of organizational learning its processes (knowledge acquisition, Information transfer, Interpreting the information, Organizational me

Inspite of the renovation and development that occurred on the

mathematics curricula and its teaching styles (methods), the teaching methods and the evaluation styles that the teachers of the country

follow  are  still  traditionaL It depends  on  the  normal distribution approach and the principle of individual differences among students in

addition the traditional tests that are used to evaluate student achievement are built on standard-referenced system. These types of tests focus on comparing the student's  performance with his peers'

performance. The limitary of this type of evaluation in diagnosing the

students'  acquisition  of  the  stu

     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

The theme of causal attribution has generated a great deal of work and focuses on the factors to which people attribute their behavior. However, its use to explain the results of the evaluation and the support for the regulation of teaching and learning acts has rarely been raised. Indeed, in the evaluation act, which is a privileged moment for reframing the learning process, teachers attribute the results obtained to the student himself, without worrying about the factors to which the student attribute itself these failures. This can distort the regulatory process and increase failure factors. The teacher's attributions of failure often relate to the results of the evaluations and are often explained by factors external to him: such as