A new Schiff base [I] was prepared by refluxing Amoxicillin trihydrate and 4-Hydroxy- 3,5-dimethoxybenzaldehyde in aqueous methanol solution using glacial acetic acid as a catalyst. The new 1,3-oxazepine derivative [II] was obtained by Diels- Alder reaction of Schiff base [I] with phthalic anhydride in dry benzene. The reaction of Schiff base [I] with thioglycolic acid in dry benzene led to the formation of thiazolidin-4-one derivative [III]. While the imidazolidin-4-one [IV] derivative was produced by reacting the mentioned Schiff base [I] with glycine and triethylamine in ethanol for 9 hrs. Tetrazole derivative [V] was synthesized by refluxing Schiff base [I] with sodium azide in dimethylformamid DMF. The structure of synthesized compound

A new Schiff base [I] was prepared by refluxing Amoxicillin trihydrate and 4-Hydroxy- 3,5-dimethoxybenzaldehyde in aqueous methanol solution using glacial acetic acid as a catalyst. The new 1,3-oxazepine derivative [II] was obtained by Diels- Alder reaction of Schiff base [I] with phthalic anhydride in dry benzene. The reaction of Schiff base [I] with thioglycolic acid in dry benzene led to the formation of thiazolidin-4-one derivative [III]. While the imidazolidin-4-one [IV] derivative was produced by reacting the mentioned Schiff base [I] with glycine and triethylamine in ethanol for 9 hrs. Tetrazole derivative [V] was synthesized by refluxing Schiff base [I] with sodium azide in dimethylformamid DMF. The structure of synthesized compound

الوصف New complexes of Cu (ll), Ni (II)„Co (II), and Zn (ll) with 2-amino-5-p-Flouro Phenyl 1, 3, 4-Thiadiazole have been synthesized. The products were isolated, studied and characterized by physical measurements, ie,(FT-IR)„UV-Vis and the melting points were determined. The new Schiff base (L) has been used to prepare some complexes. The prepared complexes were identified and their structural geometry were suggested

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

الهدف من الدراسه تحضير فئه جديده من بوليمرات السليكون P1-P4  والتي تمت على اساس استحدام ثنائي مثيل ثنائي كلورو سيلان((DCDMS مع بعض المركبات العضويه التي تحتوي مجاميع الهيدروكسيل  الطرفيه والتي حضرت لاول مره M1-M4،  بأستخدم البلمره التكثيفيه .كما تم تحضير متراكباتها النانويهP′1-P′4  بوجود جسيمات الفضه النانويه (Ag-NPs)  باستخدام طريقة صب المحاليل. شخصت جميع التراكيب للمونمرات والبوليمرات المحضره باستخدام  مطيافية

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