Birla Institute of Technology, Mesra

About: Birla Institute of Technology, Mesra is a education organization based out in Ranchi, India. It is known for research contribution in the topics: Computer science & Dielectric. The organization has 2801 authors who have published 4789 publications receiving 52426 citations. The organization is also known as: BIT.

Preparation and evaluation of gels from gum of Moringa oleifera

Abstract: The present study was undertaken with an objective to find out the gelling potentials of a natural gum obtained from plant Moringa oleifera . The gum was extracted by using water as solvent and precipitated using acetone as non-solvent. Physical characteristics such as, solubility, swelling index, loss on drying, and pH were studied. Diclofenac sodium was used as model drug for the formulation of gels. Seven batches of drug loaded gels with concentration of mucilage ranging from 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, and 8.5 were formulated by using glycerin as plasticizer and methyl paraben as preservative. The pH, viscosity, and in vitro diffusion profiles were studied. The gels prepared with 8.0% of mucilage were found to be ideal and comparable with a commercial preparation.

Formulation and optimization of nanoemulsion using antifungal lipid and surfactant for accentuated topical delivery of Amphotericin B

Abstract: The objective of the study was to develop, optimize and evaluate a nanoemulsion (NE) of Amphotericin B (AmB) using excipients with inherent antifungal activities (Candida albicans and Aspergillus niger) for topical delivery. AmB-loaded NE was prepared using Capmul PG8 (CPG8), labrasol and polyethylene glycol-400 by spontaneous titration method and evaluated for mean particle size, polydispersity index, zeta potential and zone of inhibition (ZOI). NE6 composed of CPG8 (15%w/w), Smix (24%w/w) and water (61%w/w) was finally selected as optimized NE. AmB-NE6 was studied for improved in vitro release, ex vivo skin permeation and deposition using the Franz diffusion cell across the rat skin followed with drug penetration using confocal laser scanning microscopy (CLSM) as compared to drug solution (DS) and commercial Fungisome®. The results of in vitro studies exhibited the maximum ZOI value of NE6 as 19.1 ± 1.4 and 22.8 ± 2.0 mm against A. niger and C. albicans, respectively, along with desired globular...

Identification of nonlinear systems using particle swarm optimization technique

Abstract: System identification in noisy environment has been a matter of concern for researchers in many disciplines of science and engineering. In the past the least mean square algorithm (LMS), genetic algorithm (GA) etc. have been employed for developing a parallel model. During training by LMS algorithm the weights rattle around and does not converge to optimal solution. This gives rise to poor performance of the model. Although GA always ensures the convergence of the weights to the global optimum but it suffers from slower convergence rate. To alleviate the problem we propose a novel Particle Swarm Optimization (PSO) technique for identifying nonlinear systems. The PSO is also a population based derivative free optimization technique like GA, and hence ascertains the convergence of the model parameters to the global optimum, there by yielding the same performance as provided by GA but with a faster speed. Comprehensive computer simulations validate that the PSO based identification is a better candidate even under noisy condition both in terms of convergence speed as well as number of input samples used.