In this paper, Pentacene based-organic field effect transistors (OFETs) by using different layers (monolayer, bilayer and trilayer) for three different gate insulators (ZrO2, PVA and CYEPL) were studied its current–voltage (I-V) characteristics by using the gradual-channel approximation model. The device exhibits a typical output curve of a field-effect transistor (FET). Source-drain voltage (Vds) was also investigated to study the effects of gate dielectric on electrical performance for OFET. The effect of capacitancesemiconductor in performance OFETs was considered. The values of current and transconductance which calculated using MATLAB simulation. It exhibited a value of current increase with increasing source-drain voltage.

In this paper, Pentacene based-organic field effect transistors (OFETs) by using different layers (monolayer, bilayer and trilayer) for three different gate insulators (ZrO2, PVA and CYEPL) were studied its current–voltage (I-V) characteristics by using the gradual-channel approximation model. The device exhibits a typical output curve of a field-effect transistor (FET). Source-drain voltage (Vds) was also investigated to study the effects of gate dielectric on electrical performance for OFET. The effect of capacitance semiconductor in performance OFETs was considered. The values of current and transconductance which calculated using MATLAB simulation. It exhibited a value of current increase with increasing source-drain voltage.

This work involves separating and studying the aminoacylase-1 (ACY1) of amniotic fluid from healthy pregnant, mainly one peak with higher activity has been isolated by DEAE-Cellulose ion exchange from the proteinous supernatant produced by deposition of proteins using ammonium sulfate  (65%) after dialysis. The purification folds reaching to 19 folds also gave one protein peak when injected into the gel filtration column, a high ACY1 purity was obtained, with 38 folds of purification. It was found that the molecular weight of the isolated ACY1 was up to 46698 Dalton when using gel chromatography technique.The effect of ACY1 isolate was studied on rats with oxidative stress caused by lead acetate(LA) at 40 mg / kg body weight and compare

Background: Early detection of subclinical left ventricular (LV) systolic dysfunction is crucial and could influence patients' prognosis by aiding the clinician to candidate patients for better management.

Objective: To detect early LV systolic dysfunction in asymptomatic patient with chronic aortic regurgitation by two dimensional speckle tracking echocardiography.

 Methods:  Sixty one asymptomatic patients with chronic aortic regurgitation, with no ischemic heart diseases (by coronary angiography) or conductive heart diseases, no diabetes mellitus, no hypertension, and no other valvular heart diseases (group 1) and fifty age and sex-matched healthy subjects (

This paper aims to investigate the flexural behavior of reinforced concrete beams considering fire resistance by adding Lightweight Expanded Clay Aggregates (LECA) to the concrete mix as partial coarse aggregate replacement. LECA is a type of porous clay with a uniform pore structure with fine, closed cells and hard, tightly sintered skin. The experimental work comprised four reinforced self-compacted concrete beams. All the specimens were identical in their geometrical layout of 1600×240×200 mm, reinforcement details, and support condition (simply supported). For all the beams, the main reinforcement was provided by two bars, each having a diameter of 12 mm, while a bar of 6 mm diameter was employed for the top and shear reinforc

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class