A new ligand [N-(3-acetylphenylcarbamothioyl)-4-methoxybenzamide](MAA) was synthesized by reaction of 4-methoxybenzoylisothiocyanate with 3-aminoacetophenone,The ligand was characterized by elemental microanalysis C.H.N.S, FT-IR, UV-Vis and 1H,13CNMR spectra, some transition metals complexes of this ligand were prepared and characterized by FT-IR, UV-Vis spectra, conductivity measurements, magnetic susceptibility and atomic absorption, From obtained results the molecular formula of all prepared complexes were [M(MAA)2(H2O)2]Cl2 (M+2 =Mn, Co, Ni, Cu, Zn, Cd and Hg),the proposed geometrical structure for all complexes were octahedral

A new ligand [N-(4-chlorobenzoyl amino) -thioxomethyl] valine (cbv) is synthesized by reaction of 4- chloro benzoyl iso thio cyanate with valine acid. The ligand is Characterized by elemental analysis ,FT-IR, and 13C 1H NMR spectra, some transition metals complex of this ligand were prepared and Characterized by FTIR , UV-Visible spectra , conductivity measurement's ,magnetic susceptibility , atomic absorption and determination of molar ratio (M:L), from results obtained , the following formula [M(cbv)2] where M+2 =Mn, Fe ,Co , Ni , Cu,Zn,Cd, and Hg and the proposed molecular structure for these complexes as tetrahedral geometry, except copper complex is have square planer geometry

New vision of Mr. Abdul Mahdi Al-Muttafiqi in the light of unpublished documents

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.

Number of new polyester and polyamide are prepared as derivatives from 5,5`-(1,4-phenylene)-bis-(1,3,4-thiadiazole-2-amine) [C1], three series of heterocyclic compounds were synthesized.The first series includes the Schiff base [C2] prepared from the reaction between compound [C1] with p-hydroxy benzaldehyde in presence of acetic acid and absolute ethanol , then these derivatives have reaction with maleic anhydride , phthalic anhydride and sodium azide, respectively to obtain the compounds [C3-5] contaning (oxazepine and tetrazole) rings.The third series of compounds [C1-5] has transformed to their polymers [C6-15] by reaction with adipoyl chloride and glutroyl chloride , respectively. The reaction was followed by T.L.C and ident

This 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

Image 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