Newly 4-amino-1,2,4-triazole-3-thione ring 2 was formed at position six of 2-methylphenol from the reaction of 6-(5-thio1,3,4-oxadiazol-2-yl)-2-methylphenol 1 with hydrazine hydrochloride in the presence of anhydrase sodium acetate. Seven newly fused heterocyclic compounds were synthesized from compound 2. First fused heterocyclic was 6-(6-(3,5-di-tertbutyl-4-hydroxyphenyl)-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazol-3-yl)-2-methylphenol 3 synthesized from reaction compound 2 with 3,5-di-tert-butyl-4-hydroxybenzoic acid in POCl3. Reaction compound 2 with bromophencylbromide afford 6-(6-(4-bromophenyl)-5H-[1,2,4]triazolo[3,4-b][1,3,4]-thiadiazin-3-yl)-2-methylphenol 4. 6-(6-thio-1,7a-dihydro-[1,2,4] triazolo[3,4-b][1,3,4]-thiadiazol-3-yl)-2

Reducing of ethyl 4-((2-hydroxy-3-methoxybenzylidene)amino)benzoate (1) afford ethyl 4-((2-hydroxy-3-methoxybenzyl) amino)benzoate (2). Reaction of this compound with Vilsmeier reagent affords novel 2-chloro-[1,3] benzoxazine ring (3). The corresponding acid hydrazide of compound 3 was synthesized from reaction of compound (3) with hydrazine hydrate. Newly series of hydrazones(5a–i) were synthesized from reaction of acid hydrazide with various aryl aldehydes. Antibacterial activity of the hydrazones wassecerned utilizing gram-negative and gram-positive bacteria. Compound (5b) and (5c) exhibited significant antibacterial ability against both gram-negative and gram-positive bacteria, while the compounds(5a) showed mild antibacterial activit

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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

Groundwater can be assessed by studying water wells. This study was conducted in Al-Wafa District, Anbar Governorate, Iraq. The water samples were collected from 24 different wells in the study area, in January 2021. A laboratory examination of the samples was conducted. Geographical information systems technique was relied on to determine the values of polluting elements in the wells. The chemical elements that were measured were [cadmium, lead, cobalt and chromium]. The output of this research were planned to be spatial maps that show the distribution of the elements with respect to their concentrations. The results show a variation in the heavy elements concentrations at the studied area groundwater. The samples show different values