An experimental study was performed to estimate the forced convection heat transfer performance and the pressure drop of a single layer graphene (GNPs) based DI-water nanofluid in a circular tube under a laminar flow and a uniform heat flux boundary conditions. The viscosity and thermal conductivity of nanofluid at weight concentrations of (0.1 to 1 wt%) were measured. The effects of the velocity of flow, heat flux and nanoparticle weight concentrations on the  enhancement of the heat transfer are examined. The Nusselt number of the GNPs nanofluid was enhanced as the heat flux and the velocity of flow rate  increased, and the maximum Nusselt number  ratio (Nu nanofluid/ Nu base fluid)   and thermal performance factor

Objectives To determine the prevalence of oral lesions by age and gender among the pediatric population in Iraq. Materials and methods A review of the archives of the oral pathology department of Baghdad University from, 1970 Materials and Methods: A review of the archives of the oral pathology department of Baghdad University from 1970 to 2013 for all biopsies from children aged 0–15 years old. Results A total of 1286 child specimens represented 11.98% of all biopsied lesions. The pyogenic granuloma was the most frequent lesion in children, and the periapical cyst was the most frequent lesion from an odontogenic origin. The incidence of malignant lesions was higher in the 0–3 age group than other groups. Conclusions The majority of les

composition,depiction,antibacterial,antioxidant,and cytotoxicity activities studies of a new nano-sized binuclear metal(||) schiff base complexes

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

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

Recently, numerous the generalizations of Hurwitz-Lerch zeta functions are investigated and introduced. In this paper, by using the extended generalized Hurwitz-Lerch zeta function, a new Salagean’s differential operator is studied. Based on this new operator, a new geometric class and yielded coefficient bounds, growth and distortion result, radii of convexity, star-likeness, close-to-convexity, as well as extreme points are discussed.