Background: Cross contamination of dental appliances in the dental clinics and laboratories may potentially be a health hazard to the dental team and the patient. This study aimed to evaluate bacterial contamination of acrylic complete denture as received from dental laboratory before delivery to the patient, and then to evaluate the effectiveness of disinfection with 2% chlorhexidine and Kin denture cleaner tablet. Materials and methods: 45 newly made upper complete dentures undergone biaacterial examination for contamination before delivered to the patient. Samples were examined in two stages, first after finishing and polishing; when collected from the laboratory and before inserting to the patient mouth, second; after the samples were

Nanoparticles are a special group of materials with unique features and extensive applications in diverse fields. The use of nanoparticles of some metals is a viable solution to stop infectious diseases due to the antimicrobial properties of these nanoparticles. The present work demonstrates the effect of silver nanoparticles (AgNPs) on the antibacterial activity of four different antibiotics (amoxicillin, ceftriaxone, chloramphenicol, and penicillin) against eleven Gram-positive and Gram-negative isolates. Disk diffusion method was used to determine the antibacterial activity of various classes of antibiotics in the absence and presence of sub-inhibitory silver nanoparticles of concentration (80 microgram/ml). A synergistic effect was o

Ninety eight mobile samples, (54) galaxy phone and (44) I phone, were swabbed for bacterial culture determination by culturing on MacConky agar , Blood agar , Mannitol salt agar , Muller Hinton agar .Staphylococcuswas the highest frequent isolated bacteria from Galaxy phone (33%) and I phone (37%). This study revealed that galaxy phone appears less contaminated with bacteria, the ratio of non-contaminated devices is (44%) when compared with I phone (9%). Sensitivity test showed that Ogmintin have the lowest effect on Staphylococcusisolated from both type of devices while cefitriaxone have the highest effect. DNA of isolate from galaxy 31 that exhibit highest resistance against antibiotics was extracted and 16S rRNA gene was polymerized by P

Global Navigation Satellite Systems (GNSS) have become an integral part of wide range of applications. One of these applications of GNSS is implementation of the cellular phone to locate the position of users and this technology has been employed in social media applications. Moreover, GNSS have been effectively employed in transportation, GIS, mobile satellite communications, and etc. On the other hand, the geomatics sciences use the GNSS for many practical and scientific applications such as surveying and mapping and monitoring, etc.

In this study, the GNSS raw data of ISER CORS, which is located in the North of Iraq, are processed and analyzed to build up coordinate time series for the purpose of detection the

The detection for Single Escherichia Coli Bacteria has attracted great interest and in biology and physics applications. A nanostructured porous silicon (PS) is designed for rapid capture and detection of Escherichia coli bacteria inside the micropore. PS has attracted more attention due to its unique properties. Several works are concerning the properties of nanostructured porous silicon. In this study PS is fabricated by an electrochemical anodization process. The surface morphology of PS films has been studied by scanning electron microscope (SEM) and atomic force microscope (AFM). The structure of porous silicon was studied by energy-dispersive X-ray spectroscopy (EDX). Details of experimental methods and results are given and discussed

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet