Background: The genetic polymorphisms of vitamin D receptor (VDR) have an association with thalassemia development, additionally to the environmental elements that elicited the disorder in the genetically predisposed individuals. As well, VDR functions responsible for the regulation of bone metabolism, such its part in immunity. Aim: The sitting study intended to inspect the association between thalassemia disease and the genetic polymorphisms of VDR among the Iraqi population then compared these findings to other findings of thalassemia patients in other different ethnic populations. Materials and methods: The restriction enzymes Bsm-I and Fok-I were applied to determine the genetic polymorphisms frequencies of VDR by a Polymerase Chain Re

A simple, economical and selective method employing ion pair dispersive liquid−liquid microextraction (DLLME) coupled with spectrophotometric determination of carbamazepine (CBZ) in pharmaceutical preparations and biological samples was developed. The method is based on reduction of Mo(VI) to Mo(V) using a combination of ammonium thiocyanate and ascorbic acid in acidic medium to form a red binary Mo(V) thiocyanate complex. After addition of CBZ to the complex, extraction of the formed CBZ−Mo(V)−(SCN)6 was performed using a mixture of methylene chloride and methanol. Then, the measurement of target complex was performed at the wavelength of 470 nm. The important extraction parameters affecting the efficiency of DLLME were studied and o

The problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, t

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.

Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte