In the present study, new five polymers of acryloyl chloride have been synthesized by reaction 4-aminoantipyrine with many substituted acid chloride (A-E). Then condensation of polyacryloyl chloride with the product in one step (A-E), in a suitable solvent in the presence amount of (Et3N) to obtain new polyimides(A1-E5). The prepared compounds were characterized by UV. FT-IR, 1H-NMR and 13C-NMR spectroscopy and measuring of other physical properties such as softening point, melting point and solublities.

A new series of ?-D-glucose as Schiff bases derivatives is synthesized and characterized with studying their bioactivity. Hydroxyl groups at C (1,2&5,6) sugar moiety are converted into acetal form through a reaction with dry acetone using phosphoric acid and anhydrous zinc chloride as catalysts producing 1,2:5,6-di-O-isopropyledine ?-D-glucofuranose(I). The five memberd ring acetal of C(5,6) is hydrolyzed with acetic acid (65%)and a reaction of the new product with sodium periodate is carried on to get an aldehyde moiety which is used to produce a new series of Schiff bases through reacting with different amino compounds such as 4-amino antipyrene . The suggested chemical structures of the prepared compounds are confirmed by u

A new series of ?-D-glucose as Schiff bases derivatives is synthesized and characterized with studying their bioactivity. Hydroxyl groups at C (1,2&5,6) sugar moiety are converted into acetal form through a reaction with dry acetone using phosphoric acid and anhydrous zinc chloride as catalysts producing 1,2:5,6-di-O-isopropyledine ?-D-glucofuranose(I). The five memberd ring acetal of C(5,6) is hydrolyzed with acetic acid (65%)and a reaction of the new product with sodium periodate is carried on to get an aldehyde moiety which is used to produce a new series of Schiff bases through reacting with different amino compounds such as 4-amino antipyrene . The suggested chemical structures of the prepared compounds are confirmed by using UV., FT

Series of new complexes of the type [M2 (L)Cl4 ] are prepared from the new ligand[N1 ,N4 -bis(benzo[d]thiazol-2- yl)succinamide (L) derived from ethan-1,2-dicarbonyl chloride and 2-aminobenzothiozole,where, M= Ni(ii), Cu(ii) and Zn(ii) alsocomplexes of mix-ligands, the type [M(L)(8-HQ)]Cl, where, M = Ni(ii), Cu(ii) and Zn(ii),8-HQ= 8-Hydroxyquinoline. Chemical forms are obtained from their 1 H, 13CNMR, Mass spectra (for (L)), FT-IR and U.V spectrum, melting point, molar conduct.Using flame (AA), % M is determined in the complexes.The content of C, H, N and S in the (L) and its complexes was specified. Magnetic susceptibility and thermal analysis (TGA) of prepared compounds were measured.The propose geometry for all complexes[M2 (L)Cl4 ] wa

This study describes the preparation of a new bidentate Schiff base derived from the condensation of Isatin-3-hydrazone with 2-acetylthiophene and the preparation of new series of complexes with a good yield. The prepared ligand was characterized by IR, UV-Vis, C.H.N.S elemental analysis, 1H and 13C NMR, LC-Mass spectroscopy, and physical measurements. Its complexes were analyzed by C.H.N.S elemental analyses, UV-Vis., FTIR, NMR, LC-Mass Spectra, atomic absorption spectroscopy, magnetic susceptibility, and conductivity measurements The results from spectroscopy and measurement studies showed that the ligand coordinated to the metal ion as a bidentate ligand via oxygen and nitrogen, forming an octahedral geometry around it. In vitro antimicr

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