The objective was to study the effect of prepared ginkgo biloba extracts against Candida albicans isolated from healthy persons. Conducting susceptibility test, biofilm formation test, phytochemical screening test, and antioxidant activity test. One hundred oral swabs sample were obtained from healthy persons with oral lesion attending dentistry teaching hospital in dentistry college, their age ranged from 1-30 years of both sexex. The studied samples collected through 8 months (April - December / 2018). This study included two different types of ginkgo bilola extracts were prepared as aqueous and ethanolic extracts. Many tests were used, which included isolation and identification of C.albicans, conduct susceptibility test, biofilm form

Background: Stress urinary incontinence is a frequent urological disease in women; it has a great influence on an individual’s wellbeing and places a significant economic strain on any health service. The placement of urodynamic diagnostic tests in the evaluation route is an important clinical research concern in this field.

Objective: to find out whether the duration of stress urinary incontinence is associated with the finding of bladder outlet obstruction in urodynamic study or not.

Subjects and Methods: A descriptive study. With enrolled female patients had symptomatic Stress urinary incontinence as their primary complain. All the included patients w

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

Among the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For highe

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