The purpose of this work is to clarify the effect of the Active Galactic Nucleus (AGN) on the properties of the galaxy. A photometric study of two galaxies by surface optical measurements techniques and by using'griz filters' was performed. The scientific material that used in this work was obtained from ''SLOAN DIGITAL SKY SURVEY'' (DR7), a fuzzy color, contour maps, photometric parameters, and color indices were studied by using surface photometric technique. The work was done by Ellipse task in IRAF (Image Reduction and Analysis Facility) software from the National Optical Astronomy Observatory (NOAO).

A field experiment was conducted in an agricultural field in Al-Hindia district, Karbala governorate in a silty clay soil during the year 2020. The research included a study of two factors, the first is the depth of plowing at two levels, namely 13 and 20 cm, which represented the main blocks. The second is the tire inflation pressure at two levels, namely (70 and 140 kPa), which represented the secondary blocks. Slippage percentage, field efficiency, leaf area, and 300 grain weight were studied. The experiment was carried out using a split-plot system under a Randomized complete block design, at three replications. The tillage depth of 13 cm exceeds/transcend by giving it the least slippage of (11.01%), the highest field efficiency of (50.

          The aim of this paper is to translate the basic properties of the classical complete normed algebra to the complete fuzzy normed algebra at this end a proof of multiplication fuzzy continuous is given. Also a proof of every fuzzy normed algebra  without identity can be embedded into fuzzy normed algebra  with identity  and  is an ideal in  is given. Moreover the proof of the resolvent set of a non zero element in complete fuzzy normed space is equal to the set of complex numbers is given. Finally basic properties of the resolvent space of a complete fuzzy normed algebra is given.

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H

A detailed study of adsorption from solution of amitriptyline-HCl, chlorpromazine-HCl and
chlordiazepoxide-HCl on bentonite clay surface has been performed at variable conditions of
temperature, pH and ionic strength. It is aimed in this work to explore the capability of this clay in
treatment of poisoning by the mentioned drugs if taken in quantities higher than the usual doses.
Quantities of drugs adsorbed have been determined by UV spectrophotometric technique. The
sequence of adsorption in neutral media at 37.5 CÙ’ followed the order:
Amitriptyline-HCl > chlorpromazine-HCl > chlordiazepoxide-HCl.
The results were discussed in the light of Langmuir and Freundich adsorption isotherms. The usual
basic th

Undoped and Co-doped zinc oxide (CZO) thin films have been prepared by spray pyrolysis technique using solution of zinc acetate and cobalt chloride. The effect of Co dopants on structural and optical properties has been investigated. The films were found to exhibit maximum transmittance (~90%) and low absorbance. The structural properties of the deposited films were examined by x-ray diffraction (XRD). These films, deposited on glass substrates at (400? C), have a polycrystalline texture with a wurtzite hexagonal structure, and the grain size was decreased with increasing Co concentration, and no change was observed in lattice constants while the optical band gap decreased from (3.18-3.02) eV for direct allowed transition. Other parameters

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and