Thirty one  samples of gum swabs were collected from patients with tooth caries (5-30 years old)  from the College of Science (Biology department )- University of Baghdad- Iraq for the period from October 2018 to December 2018. , The samples were transported, after inoculation in a transport media (nutrient broth), to the laboratory of the College of Science and then cultured on mannitol salt agar and  blood agar). The isolates belonging to Staphylococcus spp. were identified by biochemical tests and Vitek 2 compact system, while the more antibiotic resistant isolates were identified by using Polymerase Chain Reaction(ï´¾PCR)  and sequencing of 16SrRNA . The results showed sharp UV absorption peaks at 330 - 340nm and AFM at 5

Removable dental prostheses remain a reliable treatment for edentulous patients. Conventional fabrication requires multiple steps, whereas computer-aided design and manufacturing (CAD-CAM), particularly 3D printing, offers faster and more cost-effective alternatives. This in vitro study aimed to evaluate the effect of sandblasting on surface roughness and shear bond strength of silicone soft liner bonded to 3D-printed and heat-cured acrylic denture base materials. Eighty specimens were divided into four groups: heat-cured control, 3D-printed control, heat-cured sandblasted, and 3D-printed sandblasted. Surface roughness was measured using a profilometer, while shear bond strength was tested with a universal testing machine. D

In this paper, some relations between the flows and the Enveloping Semi-group were studied. It allows to associate some properties on the topological compactification to any pointed flows. These relations enable us to study a number of the properties of the principles of flows corresponding with using algebric properties. Also in this paper proofs to some theorems of these relations are given.

wind load coefficient

Contents IJPAM: Volume 116, No. 3 (2017)

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial