This paper presents the synthesis and study of some new mixed-ligand complexes containing anthranilic acid and amino acid phenylalanine (phe) with some metals . The resulting products were found to be solid crystalline complexes which have been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity . The proposed structure of the complexes using program , chem office 3D(2000) . The general formula have been given for the prepared complexes : [M(A-H)(phe-H)] M(II): Hg(II) , Mn(II) ,Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) . A = Anthranilic acid = C7H7NO2 Phe = phenylalanine = C9H11NO2

Thispaperpresentsthesynthesisandstudyofsomenewmixed-liagnd complexescontainingtowaminoacids[Alanine(Ala)andphenylalanine(phe)]withsome metals .Theresultsproductswerefoundtobesolidcrystallinecomplexeswhichhave been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity and solubiltyThe proposed structure of the complexes using program , chem office 3D(2000) .The general formula have been given for the prepared complexes :[M(A-H)(phe-H)]M(II): Hg , Mn ,Co , Ni , Cu ) , Zn , Cd(II) .Ala = Alanine acid = C3H7NO2Phe = phenylalanine = C9H11NO2

This paper presents the synthesis and study of some new mixed-liagnd complexes containing tow amino acids[Alanine(Ala) and phenylalanine (phe)] with some metals . The results products were found to be solid crystalline complexes which have been characterized by using (FT-IR,UV-Vis) spectra , melting point, elemental analysis (C.H.N) , molar conductivity and solubilty The proposed structure of the complexes using program , chem office 3D(2000) . The general formula have been given for the prepared complexes : [M(A-H)(phe-H)] M(II): Hg , Mn ,Co , Ni , Cu ) , Zn , Cd(II) . Ala = Alanine acid = C3H7NO2 Phe = phenylalanine = C9H11NO2

The new bidentate ligand 2-amino-5-phenyl-1,3,4-oxadiazole (Apods) was prepared by the reaction of benzaldehyde semicarbazone with bromine and sodium acetate in acetic acid gave. The prepared ligand was identified by Microelemental Analysis, FT.IR, UV-Vis and 1HNMR spectroscopic techniqes. Treatment of the prepared ligand with the following selected metal ions (MnII, CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio, yielded a series of complexes of the general formula [M(L)2Cl2].The prepared complexes were characterized using flame atomic absorption, (C.H.N)Analysis, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by Mohr metho

In this research, an organobentonite (HDTMA-BT) was prepared by modifying a jordanian bentonite (BT) with hexadecyltrimethylammonium bromide. By means of in situ free radical polymerization in THF with AIBN as the initiator, this organobentonite is used to prepare the polymethylmethacrylate-bentonite (PMA-HDTMA-BT) nanocomposite. Scanning electron microscopy (SEM), x-ray diffraction (XRD), energy dispersive spectrometer (EDS) and Fourier transform infrared (FTIR) spectroscopy were used to characterize both HDTMA-BT and PMA-HDTMA-BT. Those adsorbents were used in a batch process to remove Pb(II), Cr(III) ions, and p-chlorophenol (PCP) from aqueous solution. Investigated factors included adsorbent dosage, initial pH solution, contact time, an

Aim of the present study is Identification of specific gene for GPCR using specific primers .and identification of difference in PCR analysis in patients with heart thrombosis and compared with healthy, Sequencing of PCR product regarding GPCR compared for all three subject, Identification the similarity of human GPCR with local strain of yeast fifty healthy control and fifty patients with thrombosis which diagnosed medically with cardiac specific troponin t, troponin 1 levels and electro myocardiogram ECG. The aged for all subjects ranged (39-75) years patients were lying in cardiac care unit at Ibn- al- Nafees teaching hospital and Sheikh Zayed teaching hospital. Genomic DNA of whole blood was extracted from buffy coat and cell cu

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.