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The present study aimed at evaluating and comparing the in vitro antimicrobial activity of 10 medicinal plants used in traditional and homemade medicines: Curcuma longa, Azadiracta indica, Ocimum sanctum, Adathoda vasica, Polygala grineris, Cynodon dactylon, Solanum nigrum, Cardiospermum halicacabum, Phylanthus niruri, and Acalypa indica. Gram-positive and gram-negative bacteria Serratia marcesens, Escherichia coli, Bacillus subtilis, Klebshiella pneumoniae, Streptococcus pyrogens, and Staphylococcus aureus and two pathogenic fungi—Candida albicans and Aspergillus niger—were tested on the leaf extracts. The methanolic extracts were tested at two concentrations for microbial susceptibility. Assays were done using agar well diffusion method and minimal inhibitory concentration for samples showing growth inhibition. All extracts inhibited the growth of S. pyrogens. Among the plant extracts tested, P. niruri showed the greatest inhibitory action.

The present work reports on the development of modeling and optimization for micro-electric discharge machining (μ-EDM) process. Artificial neural network (ANN) is used for analyzing the material removal of µ-EDM to establish the parameter optimization model. A feed forward neural network with back propagation algorithm is trained to optimize the number of neurons and number of hidden layers to predict a better material removal rate. A neural network model is developed using MATLAB programming, and the trained neural network is simulated. When experimental and network model results are compared for the performance considered, it is observed that the developed model is within the limits of the agreeable error. Then, genetic algorithms (GAs) have been employed to determine optimum process parameters for any desired output value of machining characteristics. This well-trained neural network model is shown to be effective in estimating the MRR and is improved using optimized machining parameters.

The Buddhist Kingdom of Bhutan is in sharp focus now. This is due to two critical factors: Bhutan's assertion of its identity and Beijing's tactics in the Himalayan region. Both factors have had an...

A two-dimensional mathematical model is presented to describe the solidification and cooling of liquid steel. The liquid steel is poured into a mold to obtain a solid mass of desired shape, called an ingot. After cooling of the steel in the mold for some time, the mold is removed. Then the leftover ingot mass is cooled in air. This article is concerned with the above process. Nevertheless, the technique can be very applicable to other processes such as continuous casting. Partial differential equations describing the process have been discretized using control-volume (or finite-volume) technique. The discretization equations obtained are of tridiagonal matrix form, which have been solved using the well-known tridiagonal matrix algorithm (TDMA) and the alternate direction implicit (ADI) solver. The model has been validated by measuring surface temperatures of molds and ingots using an infrared thermo-Vision scanner. This is then used to compute temperature distribution and solidification status of the ingo...

Two-dimensional solidification in a rectangular enclosure has been analyzed, taking into account the effects of natural convection and considering the convective and radiative boundary conditions at the surface of the mold and at the top of the enclosure. The bottom is taken as insulated. The dimensionless equations governing the unsteady velocity profiles in the melt and the unsteady temperature profiles in the melt, the solid, and the mold are solved by finite-difference methods, using the alternating direction implicit technique for the vorticity and the stream function. The effect of natural convection on the heat transfer at the interface and on the movement and shape of the interface is found to be significant compared to the results obtained by neglecting natural convection in the melt.