New Schiff-base ligands bearing tetrazole moiety and their polymeric metal complexes with Co(II), Ni(II) and Cd(II) ions are reported. Ligands were prepared in a multiple-step reaction. The reaction of sodium 2,6- diformylphenolate and cyclohexane-1,3-dione with 5-amino-2-fluorobenzonitrile resulted in the isolation of two precursors sodium 2,6-bis((E)-(3-cyano-4-fluorophenylimino)methyl)-4-methylphenolate 1 and 5,5'- (1E,1'E)-cyclohexane-1,3-diylidenebis- (azan-1-yl-1-ylidene)bis(2-fluorobenzonitrile) 2, respectively. The reaction of precursors with azide gave the required ligands; sodium 2,6-bis((E)-(4-fluoro-3-(1H-tetrazol-5- yl)phenylimino)methyl)-4-methylphenolate (NaL) and (N, N'E, N, N'E)-N, N'-(cyclohexane-1,3-diylidene)bis(4- fluoro-3-(1H-tetrazol-5-yl)aniline) (L1). The reaction of these ligands with the appropriate metal ions gave polymeric metal complexes of the formulae {[M2(L)]Cl}n and [M(L1)Cl2]n (where M = Co(II), Ni(II) and Cd(II)). A range of techniques were used to confirm the entity of ligands and their complexes. The formation of ligands and mode of complexation and geometrical structure of the title polymeric complexes were verified using FTIR, electronic spectra, NMR, ESMS, magnetic susceptibility, micro-elemental analysis, metal content, chloride content and conductance. The analytical and spectroscopic data indicated the formation of four-coordinate complexes, with a tetrahedral geometry for Co(II) and Cd(II), and square planer for Ni(II) in L- and L1 complexes. Biological evaluation of ligands and their polymeric complexes against gram-positive bacteria (G+), Bacillus stubtili, Staphylococcus aureus, and gram-negative bacteria (G-), Escherichia coli and Pseudomonas aeruginosa, showed ligands and their polymeric metal complexes have a good effect on the screened bacteria.
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
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Obesity is an escalating health problem in developing countries. One to ten children worldwide are overweight in a report showed by the International Obesity Task Force. Ghrelin, orexigenic peptide, has 28 amino acids, it is considered the greatest remarkable promotion in the last two decades for understanding the physiological changes of action regulating food intake and hunger. Obestatin is a 23-amino acid peptide nearly connected to ghrelin that secures from substitutio
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Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina
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Sumatriptan(ST) is a selective agonist at serotonin 5-HTI receptors, as well as 5-HT1B/1D subtypes. It is effective for acute migraine attacks, but has a short half life (about 2 hours) and low oral bioavailability (15%). The purpose of this study was to develop and optimize nasal mucoadhesive in-situ gel(IG) of ST to enhance nasal residence time for migraine management. Cold method was used to prepare different formulas of ST nasal IG, using thermosensitive polymers (poloxamer 407 alone or with poloxamer 188) with a mucoadhesive polymer hyaluronic acid (HA) which were examined for gelation temperature and gelation time, pH, drug content, gel strength, spreadability, muc
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