Thermal Radiation and Heat Source Effects on a MHD Nanofluid Past a Vertical Plate in a Rotating System with Porous Medium

This article studies the effect of thermal radiation on a MHD free convection flow of a nanofluid bounded by a semi‐infinite vertical plate with a constant heat source in a rotating frame of reference. The plate is assumed to oscillate in time with constant frequency so that the solutions of the boundary layer are the same oscillatory type. The dimensionless governing equations for this investigation are solved analytically using the regular perturbation method. The effect of various important parameters entering into the problem on velocity and temperature fields within the boundary layer are discussed for three different water‐based nanofluids such as Cu, Al₂O₃, and TiO₂ with the help of graphs. The predicted results clearly indicate that the presence of nanoparticles in the base fluid enhances the heat transfer process significantly. The present work shows the need for immediate attention in next‐generation solar film collectors, heat‐exchanger technology, material processing exploiting vertical surface, geothermal energy storage, and all those processes which are greatly exaggerated by heat‐enhancement concepts. © 2013 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.21101     

Large margin mixture of AR models for time series classification

In this paper, we propose the large margin autoregressive (LMAR) model for classification of time series patterns. The parameters of the generative AR models for different classes are estimated using the margin of the boundaries of AR models as the optimization criterion. Models that use a mixture of AR (MAR) models are considered for representing the data that cannot be adequately represented using a single AR model for a class. Based on a mixture model representing each class, we propose the large margin mixture of AR (LMMAR) models. The proposed methods are applied on the simulated time series data, electrocardiogram data, speech data for E-set in English alphabet and electroencephalogram time series data. Performance of the proposed methods is compared with that of support vector machine (SVM) based classifier that uses AR coefficients based features. The proposed methods give a better classification performance compared to the SVM based classifier. Being generative models, the LMAR and LMMAR models provide a generative interpretation that enables utilization of the rejection option in the high risk classification tasks. The proposed methods can also be used for detection of novel time series data.     

Antifungal activity of some essential oil components

Fifteen essential oil components were evaluated for antifungal activity towards five spoilage-causing fungi. In liquid shake cultures, unsaturated aldehydes (citral, cinnamic aldehyde and cittronellal) followed by geraniol, an unsaturated alcohol were most inhibitory to Aspergillus niger, Fusarium oxysporum and Penicillium digitatum; their minimal inhibitory concentrations (MIC) was 100 μg ml⁻¹. Menthol, a terpene alcohol was most inhibitory to Rhizopus stolonifer and Mucor sp. with a MIC of 200 μg ml⁻¹. Hydrocarbons like camphene, limonene and α-terpinene were least inhibitory. When incorporated in agar medium different patterns of activity were found. Thus citral, cinnamic aldehyde, citronellal, geraniol and menthol not only failed to completely inhibit A. niger, F. oxysporum and P. digitatum but were more active against R. stolonifer and Mucor sp. than in liquid medium. The differences were due to the vapour of the volatile test compounds which accumulated over the agar medium. The growth inhibition due to the vapours alone was measured by using structurally modified petri-plates. The vapours were more active against R. stolonifer and Mucor sp. than against A. niger, F. Oxysporum and P. digitatum. Fungal growth inhibition by volatile compounds in agar medium reflects the combined activity of the vapour and the compound incorporated in the medium and the inhibition is different from that obtained in liquid medium. Regarding the structure-activity relationship of citral, the-CHO group in conjugation with a carbon to carbon double bond (C=C) was found to be responsible for the antifungal activity of the molecule.     

Photofermentation of malate for biohydrogen production— A modeling approach

A kinetic model for photofermentative biohydrogen production is developed in this study to predict the dynamics of the process. The proposed model contains 17 parameters to describe cell growth, substrate consumption, and hydrogen evolution as well as inhibition of the process by biomass, light intensity, and substrate. Batch experimental results from the literature were used to calibrate and validate the model with malic acid as a model substrate, using Rhodobacter sphaeroides as a model biomass. Temporal hydrogen evolution and cell growth predicted by the proposed model agreed well with the experimentally measured data obtained from four literature reports, with statistically significant correlation coefficients exceeding 0.9. Based on sensitivity analysis performed with the validated model, only six of the 17 parameters were found to be significant. Model simulations indicated that the range of optimal light intensity for maximum hydrogen yield from malate by R. sphaeroides was 150–250 W/m².