Samples of Oxytricha falax were collected from Tigris River by 55µ. mesh net. Culturing of O. falax were cultivated in specific conditions (DO 3-5mg/l.; W.Temp. 24±1ºC; pH: 6.8-7.5).The effect of various furfural concentration 0, 20, 40, 80,100 and 124 ppm and toluene concentration 0, 15, 30, 34.2, 34.5 and 35 ppm after two periods of treatment (24 and 48 hr.) on the physiological parameters of O. falax ciliate were observed. This study showed that the lethal concentration of furfural was 124ppm and 80ppm after 24hr. and 48hr. from treatment which killed all the individual community respectively. Furthermore the treatment of O. falax individuals with different concentrations of toluene indicated that 34.5 ppm of it caused disappearance o

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

The study is concern on determine the effect of different temperatures (25, 28, 30 and 370C), and different pH values (4.5, 5.5, 6 and 8) on the radial growth (mm) of 15 dermatophyte isolates (Microsporum canis 7, Trichophyton rubrum 5, Trichophyton mentagropyhtes 3). The specimens for the current study were collected from nail infections in patients with different type of leukemia whom admitted at Baghdad Educational Hospital, 7th floor. The result revels that the optimum temperature for radial growth was 300C then 280C for all isolates, while the optimum pH for all isolates was 6.

    The present study was conducted in order to focus on the effect of the addition of Carnitine and Niacin on some blood serum parameters of Common Carp Cyprinus Carpio. 48 fish carp mean weight 44.13 gm were distributed randomly on four feeding treatments (12 fish each) with replicates (6 fish each) in 8 glass aquaria. Treatments were as follows: fish were fed on basic diet without any addition and conducted as control (T1); addition of 200 mg Carnitine/ Kg diet, (T2) addition of 28 mg Niacin/Kg diet (T3), addition of a mixture of 200 mg Carnitine and 28 mg Niacin/ Kg diet as (T4). The experiment was conducted for 70 days and the results showed an increase in the Cholesterol concentration of T1 (187.6 mg/ 100 ml) and differed s

Summary The aim of this study is the evaluation the resistance of S. marcescence obtained from soil and water to metals chlorides (Zn+2, Hg+2, Fe+2, Al+3, and Pb+2). Four isolates, identified as Serratia marcescence and S. marcescena (S4) were selected for this study according to their resistance to five heavy metals. The ability of S. marcescena (S4) to grow in different concentrations of metals chloride (200-1200 µg/ml) was tested, the highest concentration that S. marcescence (S4) tolerate was 1000 µg/ml for Zn+2, Hg+2, Fe+2, AL+3, pb+2 and 300 µg/ml for Hg+2 through 24 hrs incubation at 37 Co. The effects of temperature and pH on bacteria growth during 72 hrs were also studied. S. marcescence (S4) was affected by ZnCl2, PbCl2, FeC12

The question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.

In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes