This study is designed to isolate and molecular identification of C. neoformans, C. neoformans is pathogenic yeast and effect immunocompromised and immunocompetent. Methods: collect 50 samples from pigeon dropping and 50 samples from pigeon fanciers (sputum). The collection time was extended from November 2021 to February 2022, then culture at SDA, BSA, Cryptococcus Differential agar, esculin agar, Eucalyptus leaves agar media and Brain heart infusion agar with methyldopa, biochemical test including urease test and methyldopa, and then confirm identification by molecular identification by PCR technique sequencing and genetic analysis. The results showed that 3 swaps taken from sputum of human included cryptococcus neoformans and 6 s

The accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l

The aim of the present study was to isolated the Enterococcus spp. from milk samples of cow and vaginal swabs from aborted women and patient women in Baghdad during September 2016 to april 2017. All 100 milk sample collecting was carried out on California Mastitis Test (CMT) and the positive Percentage of CMT reactions was 5% and the percentage of Enterococcus isolates from mastitic milk was 60% and 30% from nonmasitic milk. The prevalence of Enterococcus spp was 31% of milk samples and the prevalence of Enterococcus spp. Isolates were 67.74% of the isolates of cow milk samples were Enterococcus faecalis, 25.80% was Group D and 6.45% was non groupable while Enterococcus spp. isolates from aborted women samples were 20% and all isolated was

Reishi Mushroom, Ganoderma, is considered one of important wood-decaying medicinal mushrooms. This study aimed to identify three samples of this genus in Mosul city in February and April 2019. Three species of Ganoderma were collected from three various trees including Eucalyptus, Morus, and Olea (olive) in Mosul City, Northern Iraq. Their identifications and their DNA sequences were genetically identified by using PCR techniques according to detect nuclear ribosomal internal transcribed spacer (ITS) regions. Results exhibited the finding of Ganoderma resinaceum, Ganoderma applanatum, and Ganoderma sp. This study is first attempt to identify Reishi Mushroom by molecular methods in Iraq. Thus, the current study is considered new good d

In a connected graph , the distance function between each pair of two vertices from a set vertex  is the shortest distance between them and the vertex degree  denoted by  is the number of edges which are incident to the vertex  The Schultz and modified Schultz polynomials of  are have defined as:

 respectively, where the summations are taken over all unordered pairs of distinct vertices in  and  is the distance between  and  in  The general forms of Schultz and modified Schultz polynomials shall be found and indices of the edge – identification chain and ring – square graphs in the present work.

Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted.

     Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrix of the regression model.

     to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure

The objective of study was determining the most prevalent Salmonella spp. and their antimicrobial susceptibility in broilers and laying chickens and their feed and drinking water in five chicken farms in Karbala, Iraq over the period from August to October 2020. A total of 289 samples, including 217 cloaca swabs, 46 water and 26 feed samples were collected. Salmonella spp. was identified firstly by routine diagnostic methods, followed by applying the API 20E kit, the Vitek2 system, and serology. There was significant differences in Salmonella prevalence among different types of samples, mainly cloaca swabs reported a high isolation rate (21.7%). In contrast, feed samples were completely free of contamination. The highest rate of isolation w

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