The present study aimed at identifying the role of supervisory and training practices in the field   education program in achieving course objectives from the perspective of the student teachers in the Faculty of Science and Arts in sharourah, and its relationship to some variables (gender, specialization,estimation). To achieve this, the researcher used the descriptive-analytical method, and the study tool was designed, which consists of (24) items distributed on two axes: the objectives of field education and supervisory and training practices.Then, the study tool was applied to the research sample represented in the entire study community, which consists of (65) male and female students in the Faculty of Sciences and Arts in

This research is considered one of the important researches in Maysan Governorate, as it focuses on the construction of helicopter airport project in the oil fields of the Maysan Oil Company, where the oil general companies in Maysan Governorate suffer from the cost of transporting the foreign engineering experts and the governing equipment of sustaining oil industry from Iraq's international airports to oil fields and vice versa. Private international transport companies transport foreign engineering from the oil fields to Iraqi airports and vice versa, and other international security companies take action to provide protection for foreign engineering experts during transportation. Hence, this process is very costly.

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The current study aims to identify the level of adaptation of the curriculum for visually handicapped pupils from the point of view of their teachers as well as to identify the level of adaptation of the educational programs offered to visually handicapped pupils from the point of view of their teachers. In order to achieve the goals of the research, the researcher developed two tools to measure the adaptation of curricula and educational programs for pupils with visual handicapped from the point of view of teachers. The sample included (60) teachers from Al Noor Institute for Blinders in Baghdad, the two tools were applied to them, and then the Reliability and Validity coefficients were extracted. The results sh

This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

Molecular dynamics (MD) simulations were carried out in order to investigate the binding mode of axillaridine-A at the active site of human acetylcholinesterase (AChE) enzyme. 2.0 nanosecond of MD simulations was made for the protein and the complex to dynamically explore the active site and the behavior of the ligand at the peripheral AChE binding site. These calculations for the enzyme alone showed that the active site of AChE is located at the bottom of a deep and narrow cavity whose surface is lined with rings of aromatic residues and Tyr72 is almost perpendicular to the Trp286 ring and forms a stable - interaction. The size of the active site of the complex decreases with time due to increase the interaction. Axillaridine-A forms

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise