The search involve the synthesis of some new 1,3-oxazepine and 1,3-diazepine derivatives were synthesized from Schiff base. The Schiff base (VIII) prepared from reaction of aldehyde (IV) derived from L-ascorbic acid with aromatic amine ([2-(4- nitrophenyl)-5-(4-aminophenyl)-1,3,4-oxadiazole] (VII). Oxazepine compounds (IX-XI) were synthesized from the cyclic condensation of Schiff base (VIII) with (maleic, phthalic and 3-nitrophthalic) anhydride, compounds (IX-XI) that were reacted with p-methoxyaniline to give diazepine derivatives (XII-XIV). The structures of the new synthesized compounds have been confirmed by physical properties and spectroscopy measurements such as FTIR, and some of them by 1 H-NMR, 13 CNMR, Mass, and evaluated

SYNTHESIS AND CHARACTERISATION OF NEWCo(II), Zn(II) AND Cd(II) COMPLEXES DERIVED FROM OXADIAZOLE LIGAND AND 1,10-PHENANTHROLINE AS Co-LIGAND

synthesis, Composition, Spectral, Geometry and Antibacterial Applications ofMn(||),Ni(||),Co(||),Cu(||) and Hg(||) schiff Base complexes of N2O2 mixed donor with 1,10-phenanthroline

In this work, prepared new ligand namely 5-(2,4-dichloro-phenyl)-1,3,4-oxadiazole-2-(3H)-thion, was obtained from the 2,4-dichlorobenzoyl chloride with hydrazine, after that reaxtion with CS2/KOH in methanol.

Background: Recent advancements in molecular techniques have identified over 450 genotypes of Human Papillomavirus (HPV), classified into low- and high-oncogenic risk categories. The rise in high-oncogenic risk HPV genotypes has been linked to various cancers, including those affecting the oral, oropharyngeal, and nasopharyngeal regions in both pediatric and adult populations. Methods: In this study, a cohort of 102 tonsillar tissue samples was included. This comprised 40 specimens from pediatric patients aged 4 to 9 years with nasopharyngeal adenoid hypertrophies, and 42 specimens from pediatric patients aged 5 to 12 years with palatine tonsillar hypertrophies. Among the 82 tonsillar tissue samples analyzed, 38 were from pediatric patients

The present work reports an approach of hydrothermal growth of ZnO nanorods, which simplifies the production of low cost films with controlled morphology for H₂S gas sensor application. The prepared ZnO nanorods exhibit a hexagonal wurtzite phase analyzed by the X-ray diffraction analysis. The FTIR spectra provide information that the band located between 465-570 cm^-1 corresponds to the stretching bond of Zn-O, which confirms the creation of ZnO. PL spectroscopic studies showed that the doping of Ag NPs and f-MWCNT in the ZnO matrix leads to the tuning of the bandgap. The SEM analysis showed the morphology of ZnO was the nanorods. The nanocomposites Ag/ZnO and F-MWCNT/ZnO which prepared, sep

The ligand [Potassium (E)-(4-(((2-((1-(3-aminophenyl) ethylidene) amino)-4-oxo-1, 4-dihydropteridin-6-yl) methyl) amino) benzoyl)-L-glutamate] was prepared from the condensation reaction of folic acid with (3-aminoacetophenone) through Schiff reaction to give a new Schiff base ligand [H2L]. The ligand [H2L] was characterized by elemental analysis CHN, atomic absorption (AA),(FT-IR),(UV-Vis), TLC, ES mass (for spectroscopes), molar conductance, and melting point. The new Schiff base ligand [H2L], reacts with Mn (II), Co (II), Ni (II), Cu (II), Cr (III) and Cd (II) metal ions and (2-aminophenol),(metal: derivative ligand: 2-aminophenol) to give a series of new mixed complexes in the general formula:-K3 [M2 (HL)(HA) 2],(where M= Mn (II) and Cd

<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation