In this work, excess properties (eg excess molar volume (VE), excess viscosity (ȠE), excess Gibbs free energy of activation of viscos flow (ΔG* E) and molar refraction changes (ΔnD) of binary solvent mixtures of tetrahydrofurfuryl alcohol (THFA) with aromatic hydrocarbons (benzene, toluene and p-xylene) have been calculated. This was achieved by determining the physical properties including density ρ, viscosity Ƞ and refraction index nD of liquid mixtures at 298.15 K. Results of the excess parameters and deviation functions for the binary solvent mixtures at 298.15 K have been discussed by molecular interactions that occur in these mixtures. Generally, parameters showed negative values and have been found to fit well to Redlich-Kister

     Magnetized iron oxide nanoparticles (NPs) were prepared using Eucalyptus leaf extract and then coated with CTAB (Cetrimonium bromide) to increase efficiency. The prepared and modified (NPs) were characterized using AFM, FTIR, and X-ray techniques. The adsorption of the dye reactive blue RB 238 on coated (NPs) was investigated. The effect of various experimental factors, such as the initial concentration of the dye, the amount of adsorbent, pH and temperature on the removal of RB238 was studied. The best conditions for dye removal were found to be 298 K in an acidic medium of pH = 3 and an appropriate dose of the adsorbent of 0.15 g per 25 mg/L to achieve the best color removal of 90% within 60 minutes. The pseudo-second-order re

The present work involved four steps: First step include reaction of acrylamide ,N-?-Methylen-bis(acryl amide) and N-tert Butyl acryl amide with poly acryloyl chloride in the presence of triethyl amine (Et3N) as catalyst, the second step include homopolymerization of all products of the first step by using benzoyl peroxide(BPO) as initiator in (80-90)Co in the presence of Nitrogen gas(N2). In the third step the poly acrylimide which prepare in second step was convert into potassium salt by using alcoholic potassium hydroxide solution. Fourth step include Alkylation of the prepared polymeric salts in third step by react it with different alkyl halides(benzyl chloride, allylbromide , methyl iodide) by using DMF as solvent for(10-12) hours.

The aim of this paper is to analyzed unsteady heat transfer for magnetohydrodynamic (MHD) flow of a second grade fluid in a channel with porous medium. The equations which was used to describe the flow are the momentum and energy, these equations were written to get thier non dimentional form. Homotopy analysis method (HAM) is employed to obtain a semi-analytical solutions for velocity and heat transfer fields. The effect of each dimensionless parameter upon the velocity and temperature distributions is analyzed and shown graphically by using MATHEMATICA package.

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

oupling reaction of 4-aminoantipyrene with the (L-Histidine) gave the new bidentate azo ligand.The prepared ligand was identified by FT.IR, UV-Vis and HNMR spectroscopics technique. Treatment of the prepared ligand was done with the following metal ions (Ag+ ,Pb+2 ,Fe+3 ,Cr+3  ) in aqueous ethanol with a1:1 and 1:2  M:L ratio . The prepared complexes were characterized by using FT. IR and UV- VIS spectroscopic method as well as conductivity measurements. Their structures were suggested according to the results obtained.

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je