Filed experiment was conducted to test the effect of saline water and potassium fertilizers rate on proline and water potential of Pisum sativum L. (Var.Senador Cambados ) leaves . Treatments of the experiment included two levels of water salinity( 2, 7 dSm-1) as a main plot and fertilizer rates as a sub plot. Results indicated that irrigation of plant with saline water 7 dSm-1 and fertilization 150 kg/donum increased proline accumulation and water potential 0.31 mmol/g,-17.00 bar at 9 AM morning and 0.62 mmol/g , -21.00 bar at 3 PM afternoon ,Irrigating plant with a 2 dSm-1 and fertilization 300 kg/donum decreased proline accumulation and water potential of leaves 0.22 mmol/g, -16.00 bar at 9 A

This paper investigated the treatment of textile wastewater polluted with aniline blue (AB) by electrocoagulation process using stainless steel mesh electrodes with a horizontal arrangement. The experimental design involved the application of the response surface methodology (RSM) to find the mathematical model, by adjusting the current density (4-20 mA/cm2), distance between electrodes (0.5-3 cm), salt concentration (50-600 mg/l), initial dye concentration (50-250 mg/l), pH value (2-12 ) and experimental time (5-20 min). The results showed that time is the most important parameter affecting the performance of the electrocoagulation system. Maximum removal efficiency (96 %) was obtained at a current density of 20 mA/cm2, distance be

Leinamycin is a thiol dependent DNA alkylating agent which shows very potent activity against various cancer cell lines. This natural compound forms guanine adducts (N7) in DNA which are converted into a basic sites and simultaneously generates Reactive Oxygen Species (ROS), to produce DNA strand breaks in human cancer cells. In present study, eight different strains isolated from Iraqi soils were taxonomically assigned as Streptomyces.atroolivaceous. Remarkably the strain named as THS-44 was distinguished in productivity in comparison with other strains; the amount of leinamycin was 50.98 mg/l. In this study, we assessed the cytotoxic activity of leinamycin against RD and ANM3 cancer cell line in compare with REF cell line as a normal cont

The current research aims to determine the extent of the impact of the strategic direction to the  business process reengineering, in the Office of the Ministry of Oil To reach that goal was a sample of community research study consisted (50) members of the senior leadership represent the problem in organization researched in the ambiguity of the strategic direction of knowledge of the compatibility of the strategic direction with Business Process Reengineering and   used questionnaire, interview and  observation to obtain the information needed to search was addressing data by the statistical system spss percentage  and the arithmetic mean, standard deviation and coefficient of variation .

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

This paper addresses the factors responsible for changes in crude oil prices, in real market and financial sector. In order to prepare the analytical background for further investigation, it highlights the patterns of correlations of the real oil price and the most related prices of assets, exchange rate and government bond yield. The paper reviews the statistical behavior of oil price, quantities and the  global macroeconomic environment. Topics discussed include the theory of differential rent and scarcity effect ,the role of  future market and speculation, strategies of energy of the major economies to investigate the prospects of oil market and the potential demand for  OPEC's oil.  The paper explores the