This study is designed to isolate and molecular identification of C. gattii, C. gattii is pathogenic yeast and effect immunocomposed and immunocompetent, Methods: collect 50 samples from eucalyptus leaves. The collection time was extended from November 2021 to February 2022 and then culture at SDA, Cryptococcus Differential Agar esculin agar and Eucalyptus leaves agar, Brain heart infusion agar with methyldopa and Brain heart infusion agar with methyldopa media, biochemical test including urease test, and then confirm identification by molecular identification by PCR technique sequencing and genetic analysis. The results showed that 4 swaps taken from eucalyptus leaves included cryptococcus neoformans. This study indicated that the virulenc

JM Karhoot, AA Noaimi, WF Ahmad, The Iraqi Postgraduate Medical Journal, 2012 - Cited by 7

This study was aimed to one of the most prevalent causes for endodontic treatment failure is the presence of Enterococcus faecalis bacterium within teeth root canals. To achieve successful treatment, it is so important to study E. faecalis behavior. The aim of study was to investigate biofilm production and antibiotic sensitivity of E. faecalis isolated from root canals. Results showed isolation of E. feacalis (65%) of samples, identified by specific gene by PCR technique. Most isolates were sensitive to Imipenem and resistant to Erythromycin, Clindamycin, Tetracycline and Trimethoprim. Strong biofilm production was detected among 29.5% of highest antibiotic resistant isolates. The results may indicate that infected root canals with E. feac

Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τ_i ) which  has

We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.

The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F