L-Phenylalanine amino acid was condensed with 2-hydroxybezaldehyde to give the Schiff base sodium 2-(2-hydroxybenzylideneamino)-3-phenylpropanoate, which was used as a precursor [NaHL]. The precursor was reacted with 1,2-dichloroethane to give the Schiff base sodium 2,2'-(2,2'-(ethane-1,2diylbis(oxy))bis(2,1-phenylene))bis(methan-1-yl-1-ylidene)bis(azan1-yl-1-ylidene)bis(3-phenyl propanoate), which was used as a ligand [Na2L], in complexation with some metal (II) chloride MCl2, where [M= Co(II), Ni(II), Cu(II) and Zn(II)], to give [M(L)] complexes. The [Na2L] ligand and All complexes were characterized by spectroscopic methods, [FTIR, UV-Vis, atomic absorption], melting point, chloride content, conductivity and magnetic susceptibility measurements, as well as the Na2L ligand characterized by 1H NMR. The data, of these studies and measurements were important to suggest an octahedral geometry around Co(II), Ni(II), Cu(II) and Zn(II) ions. The synthesized ligand, along with its metal complexes, was screened for in vitro antibacterial activity against gram-positive bacteria like Staphylococcus aureus, and Acinetobacter baumannii. This study showed an effective inhibition of gram- positive bacteria.
Toxic substances have been released into water supplies in recent decades because of fast industrialization and population growth. Fenton electrochemical process has been addressed to treat wastewater which is very popular because of its high efficiency and straightforward design. One of the advanced oxidation processes (AOPs) is electro-Fenton (EF) process, and electrode material significantly affects its performance. Nickel foam was chosen as the source of electro-generated hydrogen peroxide (H2O2) due to its good characteristics. In the present study, the main goals were to explore the effects of operation parameters (FeSO4 concentration, current density, and electrolysis time) on the catalytic performance that was optimized by r
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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf
... Show MoreIn this paper we shall prepare an sacrificial solution for fuzzy differential algebraic equations of fractional order (FFDAEs) based on the Adomian decomposition method (ADM) which is proposed to solve (FFDAEs) . The blurriness will appear in the boundary conditions, to be fuzzy numbers. The solution of the proposed pattern of equations is studied in the form of a convergent series with readily computable components. Several examples are resolved as clarifications, the numerical outcomes are obvious that the followed approach is simple to perform and precise when utilized to (FFDAEs).
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This work deals with thermal cracking of three samples of extract lubricating oil produced as a by-product from furfural extraction process of lubricating oil base stock in AL-Dura refinery. The thermal cracking processes were carried out at a temperature range of 325-400 ºC and atmospheric pressure by batch laboratory reactor. The distillation of cracking liquid products was achieved by general ASTM distillation (ASTM D -86) for separation of gasoline fraction up to 220 ºC from light cycle oil fraction above 220 ºC. The comparison between the conversions at different operating conditions of thermal cracking processes indicates that a high conversion was obtained at 375°C, according to gasoline production. According to gasoline produ
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of
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This research (communicative values of the visual suggestion in TV advertising) presents a precise description for the process of conveying the communicative message through employing the visual suggestion in TV advertisements. This research consists of four chapters. The first chapter includes the research problem which is summarized by the following question: what are the communicative values accomplished in Tv advertisement which produce visual suggestions that raise strangeness and tension in the advertisement?
The research importance lies in benefiting the researchers and scholars in the field of TV advertisement direction and the visual suggestion is one the main ways for building the advertisement. It also benefits the relevan