Aleppo bentonite was investigated to remove ciprofloxacin hydrochloride from aqueous solution. Batch adsorption experiments were conducted to study the several factors affecting the removal process, including contact time, pH of solution, bentonite dosage, ion strength, and temperature. The optimum contact time, pH of solution and bentonite dosage were determined to be 60 minutes, 6 and 0.15 g/50 ml, respectively. The bentonite efficiency in removing CIP decreased from 89.9% to 53.21% with increasing Ionic strength from 0 to 500mM, and it increased from 89% to 96.9% when the temperature increased from 298 to 318 K. Kinetic studies showed that the pseudo second-order model was the best in describing  the adsorption sys

EM International

The [2-hydroxy-1, 2-diphynel-ethanone oxime] was reacted with 1, 2-dichloroethan to give the new ligand [H2L]. this ligand was reacted with some metal ions (Co (II), Ni (II), Cu (II), Zn (II) and Cd (II) in methanol as a solvent to give a series of new (1: 1) complexes of the general formula [M (HL)] Cl,(where: M= Co (II), Ni (II), Cu (II), Zn (II) and Cd (II)) are isolated All compounds have been characterized by spectroscopic methods [IR, UV-Vis] atomic absorption. Chloride content along with conductivity measurements. From the above data the proposed molecular structure for (Co, Cu, Ni, Zn and Cd) complexes adopting a tetrahedral structure

The [2-hydroxy -1,2-diphynel-ethanone oxime] was reacted with 1,2- dichloroethan to give the new ligand [H2L].this ligand was reacted with some metal ions (Co(II),Ni(II),Cu(II),Zn(II) and Cd(II) in methanol as a solvent to give a series of new (1:1)complexes of the general formula [ M(HL)]Cl ,( where : M= Co(II),Ni(II),Cu(II),Zn(II) and Cd(II)) are isolated All compounds have been characterized by spectroscopic methods [ I.R , U.V -Vis ] atomic absorption . Chloride content along with conductivity measurements. From the above data the proposed molecular structure for (Co, Cu, Ni, Zn and Cd) complexes adopting a tetrahedral structure.

New binuclear Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Hg(II) Complexes of N2S2 tetradentate or N4S2 hexadentate symmetric Schiff base were prepared by the condensation of butane-1,4-diylbis(2-amino ethylcarbamodithioate) with 3-acetyl pyridine. The complexes having the general formula [M2LCl4] (where L=butane-1,4-diyl bis (2-(z)-1-(pyridine-3-ylethylidene amino))ethyl carbamodithioate, M= Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Hg(II)), were prepared by the reaction of the mentioned metal salts and the ligand. The resulting binuclear complexes were characterized by molar conductance, magnetic susceptibility ,infrared and electronic spectral measurements. This study indicated that Mn(II), Ni(II) and Cu(II) complexes have octahedral g

Complexes of Co(II),Ni(II),Cu(II)and Zn(II) with mixed ligand of 4 tributylphosphine (PBu3) were prepared in aqueous ethanol with (1:2:2) (M:L:PBu3)The prepared

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi