Eighteen new cyclic imides (maleimides) conncted to benzothiazole moiety through sulfonamide group were synthesized via multistep synthesis.The first step involved preparation of two maleamic acids N-phenylmaleamic acid and N-benzylmaleamic acid via reaction of maleic anhydride with aniline or benzyl amine.Dehydration of the prepared amic acids by treatment with acetic anhydride and anhydrous sodium acetate in the second step afforded N-phenylmaleimide and N- benzyl maleimide which in turn were treated with chlorosulfonic acid in the third step to afford 4-(N-maleimidyl) phenyl sulfonyl chloride and 4-(N-maleimidyl) benzyl sulfonyl chloride respectively.In the Fourth step of this work each one of the two prepared maleimidyl sulfonyl chlorid

The new bidentate ligand 2-amino-5-phenyl-1,3,4-oxadiazole (Apods) was prepared by the reaction of benzaldehyde semicarbazone with bromine and sodium acetate in acetic acid gave. The prepared ligand was identified by Microelemental Analysis, FT.IR, UV-Vis and 1HNMR spectroscopic techniqes. Treatment of the prepared ligand with the following selected metal ions (MnII, CoII, NiII, CuII and ZnII) in aqueous ethanol with a 1:2 M:L ratio, yielded a series of complexes of the general formula [M(L)2Cl2].The prepared complexes were characterized using flame atomic absorption, (C.H.N)Analysis, FT.IR and UV-Vis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by Mohr metho

The study of biopolymers and their derivative materials had received a considerable degree of attention from researchers in the preparation of novel material. Biopolymers and their derivatives have a wide range of applications as a result of their bio-compatibility, bio-degradability and non-toxicity. In this paper, chitosan reacted with different aldehydes(2,4 –dichloro- benzaldehyde or 2-methyl benzaldehyde), different ketones (4-bromoacetophenone or 3-aminoacetophenone) to produce chitosan schiff base (1-4) . Chitosan schiff base (1-4) reacted with glutaric acid or adipic acid in acidic media in distilled water according to the steps of Fischer and Speier to produce compounds (5-12)

Crop diseases are usually caused by inoculum of pathogens which might exist on alternate hosts or weeds as endophytes. These endophytes, cum pathogens, usually confer some beneficial attributes to these weeds or alternate hosts from protection against herbivores, disease resistance, stress tolerance to secondary metabolites production. This study was therefore carried out to isolate potential crop pathogens which exist as endophytes on weed species in the University of Ilorin plantations. Green asymptomatic leaves were collected from 10 weed species across the plantations, and processed for their endophytic fungi isolation. Isolates were purified into pure cultures and used for molecular identification using the internal transcribed spac

Diazotization reaction between 1-(2,4,6-Trihydroxy-phenyl)-ethanone and diazonium salts was carried out resulting in ligand 4-(3-Acetyl-2,4,6-trihydroxy-phenylazo)-N-(5-methyl-isoxazol-3-yl)-benzenesulfonamide, this in turn reacted with the next metal ions (V4+ , Cr3+ , Mn2+ and Cu2+) forming stable complexes with unique geometries such as (Octahedral for both Cr3+ , Mn2+ and Cu2+ ,squar pyramidal for V4+). The creation of such complexes was detected by employing spectroscopic means involving ultraviolet-visible which proved the obtained geometries, fourier transfer proved the formation of azo group and and the coordination with metal ion through it. Pyrolysis (TGA & DSC) studies proved the coordination of water residues with me

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet