Hypoxic training, which in turn is one of the methods adopted in sports training methods, especially in activities that depend on the aerobic system in its performance, which includes training with a lack of oxygen by reducing its molecular pressure, since this method targets functional organs and works temporary responses during training and permanent responses After training as an adaptation to these devices as a result of training in this way, the study aimed to identify the effect of hypoxic exercises using the training mask and the extent of the change in some biochemical indicators, in addition to that to identify the effect of these exercises on the indicator of energy expenditure and )VMA) and the achievement of the effectiveness of

The purpose of this research work is to synthesize conjugates of some NSAIDs with sulfamethoxazole as possible mutual prodrugs to overcome the local gastric irritation of NSAID with free carboxyl group by formation of ester linkage that supposed to remain intact in stomach and may hydrolyze in intestine chemically or enzymatically; in addition to that attempting to target the synthesized derivative to the colon by formation of azo group that undergo reduction only by colonic bacterial azo reductaze enzyme to liberate the parent compound to act locally (treatment of  inflammation and infections in colon).

Key words: Mutual prodrug, Ester linkage, Azo bond, Colon targeting

In Computer-based applications, there is a need for simple, low-cost devices for user authentication. Biometric authentication methods namely keystroke dynamics are being increasingly used to strengthen the commonly knowledge based method (example a password) effectively and cheaply for many types of applications. Due to the semi-independent nature of the typing behavior it is difficult to masquerade, making it useful as a biometric. In this paper, C4.5 approach is used to classify user as authenticated user or impostor by combining unigraph features (namely Dwell time (DT) and flight time (FT)) and digraph features (namely Up-Up Time (UUT) and Down-Down Time (DDT)). The results show that DT enhances the performance of digraph features by i

The aerodynamic characteristics of general three-dimensional rectangular wings are considered using non-linear interaction between two-dimensional viscous-inviscid panel method and vortex ring method. The potential flow of a two-dimensional airfoil by the pioneering Hess & Smith method was used with viscous laminar, transition and turbulent boundary layer to solve flow about complex configuration of airfoils including stalling effect. Viterna method was used to extend the aerodynamic characteristics of the specified airfoil to high angles of attacks. A modified vortex ring method was used to find the circulation values along span wise direction of the wing and then interacted with sectional circulation obtained by Kutta-Joukowsky theorem of

Abstract: Facial defects resulting from neoplasms, congenital, acquired malformations or trauma can be restored with facial prosthesis using different materials and retention methods to achieve life-like look and function. A nasal prosthesis can re-establish aesthetic form and anatomic contours for mid-facial defects, often more effectively than by surgical reconstruction as the nose is relatively immobile structure. For successful results, lot of factors such as harmony, texture, color matching and blending of tissue interface with the prosthesis are important. The aim of this study is to describe the non-surgical rehabilitation with nasal prosthesis for an Iraqi patient who received rhinectomy as a result of squamous cell carcinoma of the

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D