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SYNTHESIS, CHARACTERIZATION AND SCREENING OF ANTIMICROBIAL ACTIVITY FOR SOME NEW SCHIFF BASES AND THIAZOLIDINONE DERIVATIVES DERIVED FROM AROMATIC CARBOXYLIC ACID
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In this study, the antimicrobial properties of newly synthesized Schiff bases (4a-4e) and thiazolidinone compounds (5a-5e) generated from 3,5-dinitrobenzoic acid were assessed. These compounds were obtained by reacting 3,5-dinitrobenzoic acid (1) with ethanol in a few drops of concentrated H2SO4 to produce the ester (2). The acid hydrazide (3), which was produced by treating the ester with hydrazine hydrate, reacted with the proper aldehydes, including 4-bromobenzaldehyde, 4-chlorobenzaldehyde, 4-hydroxybenzaldehyde, 4-methoxybenzaldehyde, and 4-hydroxy-3-methoxybenzaldehyde, respectively, to form Schiff bases (4a-4e). The thiazolidinone compounds (5a-5e) were produced by the cyclocondensation reaction of compounds (4a-4e) with thioglycolic acid. A variety of techniques, including mass spectroscopy, 1H NMR, 13C NMR, and FT-IR, were employed to find novel compounds, which exhibited mild antibacterial activity against four kinds of bacteria according to the biological results. The effectiveness of the thiazolidinone derivatives against Candida albicans was mediocre. The compounds showed stretching absorption bands at 1625-1639 cm-1, belonging to azomethine groups, and the amine-induced loss of absorption bands at 3392, 3311 cm-1. Schiff bases exhibited singlet signals at δ (8.33-8.87) ppm for azomethine groups and signals at 150.67-150.75 ppm for carbon by 1H NMR and 13C NMR. Thiazolidinone compounds showed stretching absorption bands at 1701-1708 cm-1 due to the lactam ring carbonyl group. The signals at (170.99-171.19) ppm are affording to the carbon carbonyl group of the lactam ring for thiazolidinone compounds. For citation: Abbas Z.M., Rumez R.M. Synthesis, Characterization and screening of antimicrobial activity for some new Schiff bases and thiazolidinone derivatives derived from aromatic carboxylic acid. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2025. V. 68. N 7. P. 27-34. DOI: 10.6060/ivkkt.20256807.7189.

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Analyzing big data sets by using different panelized regression methods with application: Surveys of multidimensional poverty in Iraq
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Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

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Wed Apr 06 2022
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Sat Sep 30 2023
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The effect of applying assurance engagements according to the international standard IASE (3402) in enhancing the auditing action
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