The aim of the work is the synthesis and characterization of the tridentate Schiff base (HL) containing (N and O) as donor atoms type (ONO). The ligand is: (HL) phenyl 2-(2-hydroxybenzylidenamino)benzoate . This ligand was prepared by the reaction of (phenyl 2-aminobenzoate) with salicylaldehyde under reflux in ethanol and few drops of glacial acetic acid which gave the ligand (HL). The prepared ligand was characterized by (FT IR,UV–Vis) spectroscopy, Elemental analysis of carbon, hydrogen and nitrogen (C.H.N.) and melting point. The ligand was reacted with some metal ions under reflux in ethanol with (1 metal :2 ligand )mole ratio which gave complexes of the general formula: [M(L)2]Cl , M = Cr III La III and , Pr III Products were found

A new series of N-acyl hydrazones (4a-g) derived from indole-3-propionic acid (IPA) were synthesized. These N-acyl hydrazones were prepared by the reaction of 3-(1H-indol-3-yl) propane hydrazide and aldehyde in the existence of glacial acetic acid as a catalyst. ¹HNMR and FT-IR analyses were used to identify the synthesized compounds and they were in vitro evaluated as antibacterial agents against six different types of microorganisms by using well diffusion method. All the tested N-acyl hydrazones (4a-g) displayed moderate activity against the Gram-negative E.coli, comparable to that of Amoxicillin. Some of the tested N-acyl hydrazones also exhibited intermediate activity ag

In this research various of 2,5-disubstituted 1,3,4-oxadiazole (Schiff base, oxo-thiazolidine , and other compounds) were synthesized from 2,5-di(4,4?- amino-1,3,4-oxadiazole ) which use quently synthesized from mixture of 4-amino benzoic acid and hydrazine in the presence of polyphosphorus acid. The synthesized compounds were characterized by using some Spectral data (UV, FT-IR, and 1H-NMR).

Microbial fuel cell is a device that uses the microorganism metabolism for the production of electricity under specific operating conditions. Double chamber microbial fuel cell was tested for the use of two cheap electrode materials copper and aluminum for the production of electricity under different operating conditions. The investigated conditions were concentration of microorganism (yeast) (0.5- 2 g/l), solutions temperature (33-45 ^oC) and concentration of glucose as a substrate (1.5- 6 g/l). The results demonstrated that copper electrode exhibit good performance while the performance of aluminum is poor. The electricity is generated with and without the addition of substrate. Addition of glucose substrate

Introduction: Carrier-based gutta-percha is an effective method of root canal obturation creating a 3-dimensional filling; however, retrieval of the plastic carrier is relatively difficult, particularly with smaller sizes. The purpose of this study was to develop composite carriers consisting of polyethylene (PE), hydroxyapatite (HA), and strontium oxide (SrO) for carrier-based root canal obturation. Methods: Composite fibers of HA, PE, and SrO were fabricated in the shape of a carrier for delivering gutta-percha (GP) using a melt-extrusion process. The fibers were characterized using infrared spectroscopy and the thermal properties determined using differential scanning calorimetry. The elastic modulus and tensile strength tests were dete

Two compounds,[2-amino-4-(4-nitro phenyl) 1,3-thiazole],(4) and [2-amino-4-(4-bromo phenyl) 1,3-thiazole],(5), were synthesized by refluxing thiourea (1) with each of  para-ntiro and para-bomophanacyl bromides(2) and (3) respectively, in absolute methanol. Then, by reaction of [5] with 3,5-dinitrobenzoyl chloride in dimethylformamide (DMF) yielded  (6) .On the other hand, reaction of (4) with chloroacetyl chloride in dry benzene afforded (7), which is  upon treatment with thiourea in absolute methanol, af

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial