Coupling reaction of 2-amino benzoic acid with the 8-hydroxy quinoline gave the azo ligand (H2L): 5-(2-benzoic acid azo )-8-hydroxy quinoline.Treatment of this ligand with some metal ions (CoII, NiII and CuII ) in ethanolic medium with a (1:2) (M:L) ratio yielded a series of neutral complexes with general Formula[M(HL)2],where: M=Co(II), Ni(II) and Cu(II), HL=anion azo ligand (-1).The prepared complexes were characterized using flame atomic absorption,FT-IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements.

Four complexes of Co(II),Ni(II),Cu(II) and Zn(II) with the azo ligand (4-chloro-N-(2-(dimethylamino)ethyl)-5-((2-hydroxy- 4,6-dimethylphenol)diazenyl)-2-methoxybenzamide) L. The structure of ligand and complexes were confirmed on the basis of their analytical and spectral data, these dyes were tested as dyeing in cotton fabric, and also testing in light and cleaner firmness. Also, antimicrobial and antifungal activities of ligand and their complexes were evaluated and the results showed that the ZnL compound showed the higher antibacterial activity with inhibition zone of 13mm against Staphyloco-ccus epidermidis, Steptococcus sp. and Escherichia coli compared with ligand and other metal complexes .In case of ZnL compound the antifungal acti

The ligand 4-(2-aminmo-5-nitro-phenylazo)-1,5-dimethyl-2-phenyl-1,2-dihydro-pyrazol-3-one derived from 4-aminoantipyrine and 4-nitroaniline was synthesized. The synthesized ligand was characterized by 1HNMR, FT-IR, UV-Vis spectra and (C.H.N) analysis. Complexes of (YIII and LaIII ) with the ligand were prepared in aqueous ethanol with a 1:2 M:L ratio and at optimum pH. The prepared complexes were characterized by using flame atomic absorption, FT-IR, UV-Vis spectra,(C.H.N) analysis and conductivity measurement. The stoichiometry of complexes was studied by the mole ratio and job methods. A concentration range (1×10-4 - 3×10-4 M) obeyed Beer's law, the complex solutions show high values of molar absorption. On the basis of physicochemical

   The formation of  Co(II), Ni(II), Cu(II), Zn(II), and Cd(II)-complexes (C1-C5) respectively was studied with new Schiff base ligand [benzyl(2-hydroxy-1-naphthalidene) hydrazine carbodithioate  derived from reaction of  2-hydroxy-1-naphthaldehyde and benzyl hydrazine carbodithioate. The suggested structures of the ligand and its complexes have been determined   by using C.H.N.S analyzer, thermal analysis, FT-IR, U.V-Visible, 1HNMR, 13CNMR , conductivity measurement , magnetic susceptibility and atomic absorption. According to these studies,  the ligand coordinates as  a tridentate with metal ions through nitrogen atom of azomethane , oxygen atom of  hydroxyl, and  sulfur atom of thione

Four complexes of Co(II),Ni(II),Cu(II) and Zn(II) with the azo ligand (4-chloro-N-(2-(dimethylamino)ethyl)-5-((2-hydroxy-4,6-dimethylphenol)diazenyl)-2-methoxybenzamide) L. The structure of ligand and complexes were confirmed on the basis of their analytical and spectral data, these dyes were tested as dyeing in cotton fabric, and also testing in light and cleaner firmness. Also, antimicrobial and antifungal activities of ligand and their complexes were evaluated and the results showed that the ZnL compound showed the higher antibacterial activity with inhibition zone of 13mm against Staphyloco-ccus epidermidis, Steptococcus sp. and Escherichia coli compared with ligand and other metal complexes .In case of ZnL compound the antifungal activ

The ligand 4-(2-aminmo-5-nitro-phenylazo)-1,5-dimethyl-2-phenyl-1,2-dihydro-pyrazol-3-one derived from 4-aminoantipyrine and 4-nitroaniline was synthesized. The synthesized ligand was characterized by 1HNMR, FT-IR, UV-Vis spectra and (C.H.N) analysis. Complexes of (YIII and LaIII ) with the ligand were prepared in aqueous ethanol with a 1:2 M:L ratio and at optimum pH. The prepared complexes were characterized by using flame atomic absorption, FT-IR, UV-Vis spectra,(C.H.N) analysis and conductivity measurement. The stoichiometry of complexes was studied by the mole ratio and job methods. A concentration range (1×10-4 - 3×10-4 M) obeyed Beer's law, the complex solutions show high values of molar absorption. On the basis of physicochemical

A new chelate complexes of Co(II),Ni(II),Zn(II) and Cd(II) were prepared by reacting these ions with the ligand 2-[4- Carboxy methyl phenyl azo]-4,5-diphenyl imidazole (4CMeI) The preparation were conducted after fixing the optimum conditions such as (pH) and concentration .UV- visible spectra of these complex solutions were studied for a range of (pH) and concentration which obey lampert-Beers Law.The structures of complexes were deduced according to mole ratio method which were obtained from the spectroscopic studies of the complex solutions .The ratios of metal: ligand obtained were (1:2) for all complexes..(UV-Vis) absorption spectra and The infrared spectra of the chelating complexes were studied ,this may indicate that coordination be

  The formation of  Co(II), Ni(II), Cu(II), Zn(II), and Cd(II)-complexes (C1-C5) respectively was studied with new Schiff base ligand [benzyl(2-hydroxy-1-naphthalidene) hydrazine carbodithioate  derived from reaction of  2-hydroxy-1-naphthaldehyde and benzyl hydrazine carbodithioate. The suggested structures of the ligand and its complexes have been determined   by using C.H.N.S analyzer, thermal analysis, FT-IR, U.V-Visible, 1HNMR, 13CNMR , conductivity measurement , magnetic susceptibility and atomic absorption. According to these studies,  the ligand coordinates as  a tridentate with metal ions through nitrogen atom of azomethane , oxygen atom of  hydroxyl, and  sulfur atom of thione  

Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w