Nanocrystalline aluminophosphate AlPO₄-5 molecular sieves were synthesized by hydrothermal method (HTS). Synthesis parameters like time and temperature of crystallization were investigated. Type of template (R) and ratio of R/P₂O₅ were studied also. Characterization of the synthesized AlPO₄-5 were done by powder X-ray diffraction (XRD), scanning electron microscopy (SEM/EDX), Fourier transform infrared (FTIR), differential scanning calorimetry-thermogravimetry analysis (DSC-TGA), and N₂ adsorption-desorption BET analysis. XRD patterns results showed excellent crystallinity for two types of templates, di-n-propylamine (DPA) and tetrapropyl ammonium hydroxide (TPAOH) f

Phenol oxidation by Fenton's reagent (H2O2 + Fe+2) in aqueous solution has been studied for the purpose of learning
more about the reactions involved and the extent of the oxidation process, under various operating conditions. An initial
phenol concentration of 100 mg/L was used as representative of a phenolic industrial wastewater. Working temperature
of 25C was tested, and initial pH was set at 5.6 . The H2O2 and the Fe+2 doses were varied in the range of
(H2O2/Fe+2/phenol = 3/0.25/1 to 5/0.5/1). Keeping the stirring speed of 200 rpm.
The results exhibit that the highest phenol conversion (100%) was obtained under (H2O/Fe+2/phenol ratio of 5/0.5/1)
at about 180 min. The study has indicated that Fenton's oxidation i

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

The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

The present study envisaged utilizing 4-aminoantipyrine as key intermediate for the synthesis of some new derivatives bearing anti-bacterial and anti-cancer activities moieties viz., antipyrine diazenyl benzaldehydes 2(ad) which were obtained by coupling of diazotized 4-aminoantipyrine (1) with substituted benzaldehydes at 0◦C (iced) temperature. The other antipyrine derivatives where containing bis heterocycles like bis thiazolidinone-antipyrine (4), bis imidazolidinone -antipyrine (5) and bis azetidinone -antipyrine (6).These compounds were prepared through the reaction between 4- aminoantipyrine and terephthaldicarboxaldehyde to get (3) which were reacted with mercaptoacetic acid , glycine or chloroacetyl chloride separately to get com

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

The free Schiff base ligand (HL1) is prepared by being mixed with the co-ligand 1, 10-phenanthroline (L2). The product then is reacted with metal ions: (Cr+3, Fe+3, Co+2, Ni+2, Cu+2 and Cd+2) to get new metal ion complexes. The ligand is prepared and its metal ion complexes are characterized by physic-chemical spectroscopic techniques such as: FT-IR, UV-Vis, spectra, mass spectrometer, molar conductivity, magnetic moment, metal content, chloride content and microanalysis (C.H.N) techniques. The results show the formation of the free Schiff base ligand (HL1). The fragments of the prepared free Schiff base ligand are identified by the mass spectrometer technique. All the analysis of ligand and its metal complexes are in good agreement with th

FH Ghanim, Journal of Global Pharma Technology, 2018