Background: A role for vitamin D deficiency in Parkinson disease (PD) has recently been suggested.

Objective:: To estimate the state of vitamin D in PD with an age-matched healthy control.

Type of the study: A case control study.

Method: The study randomly comparison of plasma 25-hydroxyvitamin D (25[OH] D) concentrations of collected samples in a clinical neurology department ward / Baghdad teaching hospital / Medical City and Parkinson disease movement disorder clinic. Participants were registered into the study from October 2015 to October 2016. We was study   serum vitamin D level in 40 consecutive patients with

This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

This study aimed at identifying the counseling needs for classroom teachers specialization in
Jerash university. The sample of the study consisted (112) students. To achieve this goal a
scale with (39) items was built by the researcher, this scale has four domains they are as
follows; family, social, psychological and academic domain. The results of this study showed
that counseling needs obtain the heighest average. As well as, the results of the study revealed
that there were statistical differences in favor of gender and teaching year variable. Finally the
study stated a list of recommendations.

       The current research aims to build a training program for chemistry teachers based on the knowledge economy and its impact on the productive thinking of their students. To achieve the objectives of the research, the following hypothesis was formulated:

   There is no statistically significant difference at (0.05) level of significance between the average grades of the students participating in the training program according to the knowledge economy and the average grades of the students who did not participate in the training program in the test of productive thinking. The study sample consisted of (288) second intermediate grade students divided into (152) for the control group

Background: Dental implants act as infrastructure for fixed restoration to look like as a natural tooth. Osseointegration is a biological events and considered as a base for success of dental implant. The aim of this study is to evaluate the bond strength between bone and Ti implant coated with mixture of nano hydroxyapatite-chitosan-collagen compared with Ti implants coated with nano hydroxyapatite implanted in rabbit tibia, after different period of implantation time (two and six weeks) by torque removal test. Material and methods: 36 screws of commercially pure titanium; 8mm in length and 3mm diameter , 18 screws coated with mixture of nano hydroxyapatite-chitosan-collagen and18 screws coated with nano hydroxyapatite by dip coating. St

This research aims to:
1 – Make a proposed module for (aesthetics) for the second stage - Department of Art Education under education theories.
2 - Verification from the effect of the proposed module on student achievement and motivation towards learning aesthetics material.
To verification the second goal we wording these two hypotheses:
1- There are no individual differences with statistically significant at level (0.05) between the student's scores average. (Experimental group ) who studied according to the proposed module and the average student's scores (control group) who studied in the usual way for the achievement test for the Aesthetics material.
2- There are no individual differences with statistically signifi

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati