The nanostructured Manganese dioxide/Carbon fiber (CF) composite electrode was prepared galvanostatically using a facile method of anodic electrodeposition by varying the reaction time and MnSO4 concentration of the electrochemical solution. The effects of these parameters on the structures and properties of the prepared electrode were evaluated. For determining the crystal characteristics, morphologies, and topographies of the deposited MnO2 films onto the surfaces of carbon fibers, the X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and atomic force microscopy (AFM) techniques were used, respectively. It found that the carbon fibers were coated with γ-MnO2 with a density that increased with increasing the de

characteristic tissues and cells, exerting their pharmacological aspects and alleviating a lot of diseased processes. Accordingly, this research is about introducing some isatins to be nucleophilically attacked at C3 forming products of azomethine ylide functionality. These iminium compounds were made by allowing certain isatins to be reacted with the secondary amino acid, proline, at acetic acid and methanol medium and then collected after purification to be identified with total Leukocyte count (TLC) and melting point. The structural characterization was performed by fourier-transform infrared spectroscopy (FTIR), proton nuclear magnetic resonance (1H-NMR), and community health nursing (CHN) analysis. The microbiological evaluatio

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

          New nitrone and selenonitrone compounds were synthesized. The condensation method between N-(2-hydroxyethyl) hydroxylamine and substituted carbonyl compounds such as [benzil, 4, 4́-dichlorobenzil and  2,2́ -dinitrobenzil] afforded a variety of new nitrone compounds while the condensation between N-benzylhydroxylamine and substituted selenocarbonyl compounds such as [di(4-fluorobenzoyl) diselenide and (4-chlorobenzoyl selenonitrile] obtained selenonitrone compounds. The condensation of N-4-chlorophenylhydroxylamine with dibenzoyl diselenide obtained another type of selenonitrone compounds. The structures of the synthesized compounds were assigned based on spectroscopic data (FT-IR,

N-Benzylidene m-nitrobenzeneamines (Schiff bases) were prepared by condensation of m-nitroaniline with aromatic aldehydes. These Schiff bases were found to react with maleic anhydride to give 2-Aryl-3-(m-nitrophenyl)-2, 3-dihydro [1, 3] oxazepine–4, 7–diones and with phthalic anhydride to give 2-Aryl-3–(m-nitrophenyl)–2, 3–dihydrobenz|| 1, 2-e|||| 1, 3] oxazepine–4, 7-diones which were reacted with pyrrolidine to give the anilide–pyrrolidides of maleic acid and phthalic acid.

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF