To explore the durability of some local species of wood to fungal deterioration among the
storage period, this research has conducted on three species Eufcalyptus cammaldulensis,
Juglans regia, presence of some genus of fungi; Aspergillus, Penicillium,Botryoderma,
Chaetomium, Phoma, Cladosporium and Pacilomyces in different intensities.
The two fungi Aspergillus and Penicillium appeared more dominants than others, therefore
they were chosen for the pathogenicity test. The results showed that the two species of fungi
preferred Juglans wood firstly were the size of infection was more than 10 times of any of the
other two woods. Eucalyptus showed similar response to that of Morus, but with Aspergillus
it was few bett

The present study was included the isolation of Keratinophilic fungi from water samples taken from 19 indoor public swimming pools in Baghdad during four season (summer ,fall ,spring ,and winter). Isolation period was September 2011and September 2012 . Samples were collected from different places in swimming pool . Sixteen keratinophilic fungal species, belonging to twenty –one genera were isolated using Surface Dilution Plating (SDP) and Hair Bait Technique (HBT) . Aspergillus genus was the most frequent and occurrence (19.84%), followed by Trichophyton (11.60%) and Fusarium (7.59% ) . The most common fungal infection occurred in summer season (42.16%) , and the most frequent month manifestation of species occurred in August

    This study included isolation and identification of the fungi associated with Aloe vera (L.) in nurseries and plant gardens. The results showed that the fungi Alternaria alternata, Fusarium oxysporum, Fusarium solani, Nigrospora oryzae, Cladosporium herbarum, Stemphylium botryosum, Aspergillus niger, Penicillium sp. were isolated from the diseased leaves of Aloe vera showing spots and blight symptoms. The percentages of disease incidence in March, Jun and August were found to be 5, 50 and 60 %, respectively. Pathogenicity test of Alternaria alternata, Fusarium oxysporum, Nigrospora oryzae and Cladosporium herbarum showed that disease index were 50, 25,25and 12.5 %,

Background: Powerlifters and bodybuilders use anabolic androgenic steroids (AAS) especially – as many as 55 percent of elite powerlifters admitted using these agents. In contrast to numerous documented toxic and hormonal effects of AAS their impact on the structure and function of the left ventricular (LV) was not yet fully understood.

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers  , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg