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A new series of bases of Schiff (H₂-H₄) derived from phthalic anhydrideweresynthesized. These Schiff bases were prepared by the reaction of different amines (tyrosine methyl ester, phenylalanine methyl ester, and isoniazid) with the phthalimide derived aldehyde with the aid of glacial acetic acid or triethylamine ascatalysts. All the synthesized compounds were characterized by (FT-IR and ¹HNMR) analyses and were in vitro evaluated for their antimicrobial activity against six various kinds of microorganisms. All the synthesized compounds had been screened for their antimicrobial activity against two Gram-positive bacteria “Staph. Aureus, and Bacillus subtilis

Investigation of mesomorphic properties of new 1,3,4-thiadiazolines (which are synthesised via many steps in Scheme 1) was carried out in this study. These compounds are designed to have a heterocyclic unit, a carboxylate linkage group and a polar ether chain at the end of the molecule adjacent to the benzene ring, which enhance the dipolar interactions forces (varied from one to eight carbons) to investigate the association properties of their phases. The structure of the target compounds and the intermediates were confirmed by 1H NMR, 13C NMR, mass and FTIR spectral techniques. Polarised microscopic studies revealed that all the compounds in the series exhibited enantiotropic liquid crystalline properties. This was further confirmed using

Atorvastatin (ATR) is a poorly water-soluble anti-hyperlipidemic drug. The drug belongs to the class II group according to the biopharmaceutical classification system (BCS) with low bioavailability due to its low solubility. Solid dispersion is an effective technique for enhancing the solubility and dissolution of drugs. Phospholipid solid dispersion (PSD) using phosphatidylcholine (PC) as a carrier with or without adsorbent (magnesium aluminum silicate, silicon dioxide 15nm, silicon dioxide 30nm, calcium silicate) was used to prepare ATR PSD using different drug: PC: adsorbent ratios by solvent evaporation method. The resulted PSD was evaluated for its percentage yield, drug content, solubility, dissolution rate, Fourier transforma

The purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of

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