Two new ligands Na2[ H3B (BDIA)].0.05H2O (L1)(BDIA = 1-Boranyl-2,3-
Dihydro-1H-Indol-3-yl)]Acetic Acid and Na3[H2B(BDIA)2].0.3H2O.0.3CH3Ph (L2)
were synthesized by reaction of NaBH4 with indole -3- acetic acid (IAA) . The
coordination properties of ligands were studied with Co(II) , Ni(II) , Cu(II) and
Pt(IV) ions. Characterization and structural aspects of the prepared compounds were
elucidated by 1HNMR, FTIR electronic spectra, magnetic susceptibility, elemental
and metal analysis, thermal analysis (TG & DTG) and conductivity measurements.
The obtained data for metal complexes suggested square planar geometry for
copper complexes, octahedral geometry for nickel and platinium complexes and
tetrahedral geom

This work deals with preparation of Sulfated Zirconia catalyst (SZ) for isomerization of n-hexane model and refinery light naphtha, as well as enhanced the role of promoters to get the target with the mild condition, stability, and to prevent formation of coke precursors on strong acidic sites of the catalyst. The prepared SZ catalysts were characterization by fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Brunauer –Emmett-Teller (BET) surface area analysis, Thermogravimetric Analysis (TGA), Scanning Electron Microscope (SEM) and atomic force microscopy (AFM) Analyzer. The results illustrate that the maximum conversion and selectivity for n-hexane isomerization with Ni-WSZ and operating temperature of 150 °C

Some metal ions (Mn+2, Co+2, Ni+2, Cu+2, Zn+2, Cd+2 and Hg+2) complexes of quinaldic acid (QuinH) and α-picoline (α-Pic) have been synthesized and characterized on the basis of their , FTIR, (U.V-Vis) spectroscopy, conductivity measurements, magnetic susceptibility and atomic absorption. From the results obtained the following general formula has suggested for the prepared complexes [M(Quin)2( α-Pic)2].XH2O where M+2 = (Mn, Co, Ni, Cu, Zn, Cd and Hg), X = 2, X = zero for (Co+2 and Hg+2) complexes, (Quin-) = quinaldate ion, (α-Pic) = α-picoline. The results showed that the deprotonated ligand (QuinH) by using (KOH) coordinated to metal ions as bidentate ligand through the oxygen atom of the carboxylate group (-COO-) and the nitrogen ato

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

In this paper, simulation study of the frequency shift of photonic bandgaps due to refractive index scaling using liquids filled hollow-core photonic crystal fibers is presented. Different liquids (distilled water, n-hexane, methanol, ethanol and acetone) are used to fill the cladding of 2 types of hollow core photonic crystal fibers (HC19-1060, HC7-1060). These liquids are used to change the effective index scaling and index contrast of the cladding. The effect of increasing temperature of the liquid (20-100 0C for water and 20-70 0C for other liquids ) infiltrated hollow core fiber on the bandgap width and transmission properties has been computed. The maximum photonic bandgap width at 0.0243 has appeared with filling HC7-1060 PCF with

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and