Natural polymers are often non-toxic, biodegradable, biocompatible, and safe. A novel ligand was synthesized as a natural polymer using chitosan and oleander plant extract [(2R,3S,4R,5S)-5-(acetoxyamino)-4-hydroxy-3,6-dimethoxytetrahydro-2H-pyran-2-yl) methyl (16R)-3-(((2S,4S,5R)-4-methoxy-2,5-dimethyltetrahydro-2H-pyran-2-yl)oxy-10,13,16-trimethyl-17-(5-oxo-2,5-dihydrofuran-3-yl) hexadecahydro-14H-cyclopenta [a] phenanthren-14-yl) phthalate] (Chitosan-Ph-Oleander). This ligand and its complexes with several metals (Cr+3, Mn+2, Fe+3, Ni+2, Cu+2, Zn+2) were characterized using FTIR, UV-visible and 1H-NMR spectroscopy, as well as by molar conductivity, magnetic moment, and TGA analysis. The biological activity for the prepared polymer

A series of Schiff bases linked to phthalimidyl phenyl sulfonate moiety have been synthesized via multistep synthesis. The first step involved reaction of phthalic anhydride with aniline producing N-phenyl phthalamic acid which was subsequently dehydrated to the corresponding N-phenyl phthalimide via treatment with acetic anhydride and anhydrous sodium acetate. The synthesized imide was treated with chlorosulfonic acid in the third step producing 4-(N-phthalimidyl) phenyl sulfonyl chloride which was introduced in reaction with 4-hydroxy acetophenone in the fourth step producing 4-[4-(N-phthalimidyl) phenyl sulfonate] acetophenone and this in turn was introduced successfully in condensation reaction with various aromatic primary amines affor

A new Azo‐Schiff base ligand L was prepared by reaction of m‐hydroxy benzoic acid with (Schiff base B) of 3‐[2‐(1H–indol‐3‐yl)‐ethylimino]‐1.5‐dimethyl‐2‐phenyl‐2,3‐dihydro‐1H‐pyrazol‐4‐ylamine. This synthesized ligand was used for complexation with different metal ions like Ni(II), Co(II), Pd(II) and Pt(IV) by using a molar ratio of ligand: metal as 1:1. Resulted compounds were characterized by NMR (¹H and ¹³C), UV–vis spectroscopy, TGA, FT‐IR, MS, elemental analysis, magnetic moment and molar conductivity studies. The activation thermodynamic parameters, such as ΔE*, ΔH^*, ΔS^*, ΔG^*and

THE Schiff base reaction played an important role of the condensation reaction between 2-aminophenol and Glyoxylic acid in the presence of calculated amounts of KOH as a catalyst. The reaction has been carried out in ethanol under reflux and stirring condition for 3.5 hrs. All syntheses were carried out under hydrogen gas forming a new potassium (E)-1-hydroxy-2-(2-hydroxyphenylimino)ethanolate ligand type [NO2]. The ligand of the general formula K2[Mn(L2)] type and its Mnп complex K2[Mn(N2O4)] type, has been characterized by spectroscopic methods (F.T-I.R. and U.V-Vis.), elemental analysis (C.H.N) metal content, magnetic susceptibility measurement, Thin-layer chromatography (T.L.C), X-RD powder diffraction, 1H-NMR, 13C-NMR molar conductanc

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

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

In this work, two graphene oxide (GO) samples were prepared using the Hummers method with graphite (g) and KMnO4 (g) ratios of 1:3 (GO3) and 1:6 (GO6). The effect of oxidation degree on the structural, electrical, and dielectric properties of the GO samples was investigated. The structures of the GO samples were studied using various techniques, including X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDXS). XRD analysis revealed an increase in the interlayer spacing and a decrease in the number of layers of the samples with increasing oxidant content. The two GO samples have giant permittivity values of ~105 in the low-frequency

Fire is the most sever environmental condition affecting on concrete structures, thus investigating for fire safet, IJSR, Call for Papers, Online Journal