This paper deals with the preparation and investigation studies of a number of new complexes of Cu(II) , Zn(II) , Hg(II) , Ag(I) , Pt(IV) and Pb(II).The complexes were formed by the reaction of the mentioned metal ions with the ligand which is derived from oxadiazole (OXB), 2- (2-butyl) thio-5- phenyl – 1,3,4 – oxadiazole in the mole ratio (1:1) , (1:2) and (1:3) (metal to ligand ).The result complexes having general formulae :M(OXB)Cl2] [M(OXB)X2]H2O [ M= Cu(II) , Zn(II) M= Hg(II) , Pb(II) [M(OXB)2 X2] X= Cl– M = Cu (II), Zn (II), Hg (II), Pb (II) X= Cl–, NO3-, CH3COO- [Pt(OXB)3]Cl4 [Ag(OXB)]NO32-(2-??????? ) ???? -5- ???? –4,3,1– ???????????? OXB = These complexes have been characterized by variety of chemical, physical and spectroscopic techniques , such as elemental analysis , molar conductance , Infrared absorption spectra , electronic spectra and magnetic susceptibility measurements . These studies indicate that the tetracoordinate complexes have either square planer or tetrahedral structures and the hexacoordinate complexes while that bidentate complexes for Ag(I) have been found to have non-linear (deviated) structure . Furthermore, the prepared complexes ability was tested as their bactericidal materials.
The present study introduces description of new species of leafhopper Cicadella latreilla nov. External morphological characters particularly female genitalia were discussed and illustrated, shape of male abdominal apodeme, chaetotaxy of genital style and genital plate of male genitalia, shape of Aedeagus and connective . The external morphological characters were: spotting patterns of vertex, face, pronotum of prothorax, and metothorax, and of lower and upper valves of ovipositors,shape of female seventh abdominasternum.
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
... Show MoreSome 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
... Show MoreThis work include synthesized and characterization the compound [I] by reaction 1,4-phenylenediamine with chloro acetic acid then this compound reaction with methanol in present sulfuric acid to synthesized ester compound [II] after that reaction with hydrazine hydrate to synthesized acide hydrazide [III] and the later compound reaction with substituted acetophenone[IV]n to synthesized substituted acetophenone hydrazones[V-XI]. In addition synthesized4-formylpyrazole derivatives [XIIXVIII] via cyclisation substituted acetophenone hydrazones [V-XI] with Vilsmeier-Haack reagent DMF/POCl3. The compounds characterized by melting points, FTIR, 1HNMR and mass spectroscopy. The mesomorphic behavior studied by using polarized optical microscopy and
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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