Abstract

Objective(s): to Evaluation of Parents’ Knowledge about Nutritional Management of kids with Phenylketonuria; to Identify the association between parents’ Knowledge about nutritional management then their demographic variables of fathers, mothers (parents age, residence then socioeconomic position).

Methodology: A non-experimental project; was accompanied on parents of phenylketonuria kid in Baghdad town since the period 3 June to 5 October 2022. A Non-probability sample (convenience) of 35 PKU children and their parents (father and mother) was selected Purposively from the hospitals that are select for the study. A survey is built for the purpose of the educa

Increasing world demand for renewable energy resources as wind energy was one of the goals behind research optimization of energy production from wind farms. Wake is one of the important phenomena in this field. This paper focuses on understanding the effect of angle of attack (α) on wake characteristics behind single horizontal axis wind turbines (HAWT). This was done by design three rotors different from each other in value of α used in the rotor design process. Values of α were (4.8˚,9.5˚,19˚). The numerical simulations were conducted using Ansys Workbench 19- Fluent code; the used turbulence model was (k-ω SST). The results showed that best value for extracted wind energy was at α=19˚, spread distance of wak

Background: Joint hypermobility  was first mentioned by Hippocrates as an isolated feature, when he described the Celts' Incapacity to Pull a Bowstring or Throw a Dart, Due to The Slackness of Their Limbs

Objective: to determine the prevalence of mitral valve prolapse(MVP)in patients with benign hypermobility syndrome (BJHS).

Type of the study: Cross –sectional study.

Methods: Ninety patients with BJHS were included in this study. Full cardiological assessment was done for all of them,  which  include clinical examination, electrocardiography and echocardiography. Cardiac assessment was done for another sixty age and sex matched (

      The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc :  COVID-19 patients ( without vaccine ) , Gp₁: COVID-19 patients took one dose of Pfizer Biontech, Gp₂ : COVID-19 patients took two doses of Pfizer Biontech, Ga₁ : patients took one dose of AstraZeneca Oxford vaccine , Ga₂: patients took two doses of AstraZeneca Oxford vaccine , Gs₁ : patients took one dose of Sinopharm vaccine and Gs₂:

تعتبر شبكية العين جزءًا مهمًا من العين لأن الأطباء يستخدمون صورها لتشخيص العديد من أمراض العيون مثل الجلوكوما واعتلال الشبكية السكري وإعتام عدسة العين. في الواقع، يعد تصوير الشبكية المجزأ أداة قوية للكشف عن النمو غير العادي في منطقة العين بالإضافة إلى تحديد حجم وبنية القرص البصري. يمكن أن يؤدي الجلوكوما إلى إتلاف القرص البصري، مما يغير مظهر القرص البصري للعين. تعمل تقنيتنا على الكشف عن الجلوكوما وتصنيفه

This paper represents an experimental study on the application of smart control represented by the use of the fuzzy logic controller. Two-link flexible manipulators that are used in airspace and military applications are made of flexible materials characterized by low frequency and damping ratio. To solve this problem, this paper proposes the use of smart materials (piezoelectric transducers), where each link is bonded with a pair of piezoelectric transducers that act as a sensor and another as an actuator. As the arm vibrates because of the movement generated by the motor, this voltage is controlled by a regulator inside the LABVIEW® 2020 software and sends the output control voltage to the piezoelectric actuator. Experimental results

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu