Profile of Triacylglycerols,Phenols, and Vitamin E of Manjari Medika Grape Seed Oil and Cake: Introducing a Novel Indian Variety

The aim of the study is to investigate the biochemical composition of grapeseed oil and cake from an unexplored Indian grape‐juice cultivar, Manjari Medika (MM). The composition of oil and residual seed cake is evaluated using various chromatographic and spectroscopic techniques. The findings demonstrate that the vitamin E content of MM‐seed oil (1.15–1.35 g kg^?1) is distinctively higher than the Codex standard, suggesting its superior quality as an edible oil. The predominant triacylglycerols include trilinolein (LLL, 43%), dilinoleoyl‐stearylglycerol (LSL, 19%), and dilinoleoyl‐palmitoylglycerol (LLP, 11%), which are earlier recognized as natural antioxidants. The seed‐cake is rich in polyphenols including acylated anthocyanins (e.g., pelargonidin‐3‐O‐coumaroyl glucoside) and certain other flavonoids (e.g., catechin). The profile of phytonutrients in MM seed‐oil and cake is significantly superior to its seeded female parent and two other widely cultivated wine‐grape varieties. In brief, the studied by‐products of this new grape‐juice cultivar can be an important source of high‐value ingredients for use in food supplements, nutraceuticals, and functional foods. Practical applications: This study reports the phytochemical profile of the seed‐oil and seed cake derived from a newly developed grape variety, Manjari Medika. High contents of selective antioxidants: lipids, vitamin E, and phenols in the seed‐oil and cake with health benefits suggest their potential for use in nutraceutical and functional foods. These byproducts can be utilised as ingredients of functional foods and nutraceuticals (e.g., grape seed oil capsule) and also as raw materials in food supply chains (e.g., for production of grape cookies or cake). MM can also be utilized as a colorant in the food industry.     

Cashing in on Caching: An Architecture for Time-Bounded Knowledge-Based Problem Solving

Knowledge-based computing, in general, suffers from an inherent open-endedness that precludes its application in time-bounded domains where an answer must be computed within a stipulated time limit. We examine a two-way improvement of the shortcomings: a knowledge representation scheme that provides easy access to relevant knowledge and thereby reduces search time, and a reasoning scheme that is algorithmic in nature and thus makes computational requirements meaningfully estimable.In this work, we offer a cache-based architecture that is capable of both storing knowledge in different formats (e.g. rules, cases), and invoking an appropriate reasoning scheme to fit the available computing time. The cache helps in retrieving the most relevant pieces of knowledge (not only exact matches) required for solving a given problem. This cache relies on a reasoning tactic, knowledge interpolation, that can generate a solution from two near-matches in an algorithmic way, to generate time-bounded solutions. We illustrate the design of such a cache for solving resource allocation problems in the domain of shortwave radio transmission and evaluate its performance in observing imposed temporal bounds.     

Efficient financial time series prediction with evolutionary virtual data position exploration

Prediction of stock index remains a challenging task of the financial time series prediction process. Random fluctuations in the stock index make it difficult to predict. Usually the time series prediction is based on the observations of past trend over a period of time. In general, the curve the time series data follows has a linear part and a non-linear part. Prediction of the linear part with past history is not a difficult task, but the prediction of non linear segments is difficult. Though different non-linear prediction models are in use, but their prediction accuracy does not improve beyond a certain level. It is observed that close enough data positions are more informative where as far away data positions mislead prediction of such non linear segments. Apart from the existing data positions, exploration of few more close enough data positions enhance the prediction accuracy of the non-linear segments significantly. In this study, an evolutionary virtual data position (EVDP) exploration method for financial time series is proposed. It uses multilayer perceptron and genetic algorithm to build this model. Performance of the proposed model is compared with three deterministic methods such as linear, Lagrange and Taylor interpolation as well as two stochastic methods such as Uniform and Gaussian method. Ten different stock indices from across the globe are used for this experiment and it is observed that in majority of the cases performance of the proposed EVDP exploration method is better. Some stylized facts exhibited by the financial time series are also documented.

     

On Policy/Standard Development…

An information security policy is a most vital and therefore essential part of any organisation’s set of controls. Yet most organisations have poorly written policies. This paper examines the possible shortfalls of policy writings. Starting from the meaning and etymological roots of the word, the theory behind particular structures is discussed. The case is made for a single policy, many standards hierarchy. Structural and linguistic considerations including a sample statement hierarchy provide 2 practical suggestions on how to build such a hierarchy. Authorship considerations and some fine details on how to convey the will and purpose of the signatories complete the paper.     

Face expression recognition system based on ripplet transform type II and least square SVM

Multimedia Tools and Applications - This paper discusses the development of an efficient and automated system for the recognition of facial expressions, which is essentially an application...     

Cardanol grafted natural rubber: A green substitute to natural rubber for enhancing silica filler dispersion

Natural rubber (NR) usage is wide‐spread from pencil erasers to aero tyres. Carbon black and silica are the most common reinforcing fillers in the rubber industries. Carbon black enhances the mechanical properties, while silica reduces the rolling resistance and enhances the wet grip characteristics. However, the dispersion of polar silica fillers in the nonpolar hydrocarbon rubbers like natural rubber is a serious issue to be resolved. In recent years, cardanol, an agricultural by‐product of the cashew industry is already established as a multifunctional additive in the rubber. The present study focuses on dispersion of silica filler in natural rubber grafted with cardanol (CGNR) and determination of its technical properties. The optimum cure time reduces and the cure rate increases for the CGNR vulcanizates as compared to that of the NR vulcanizates at all loadings of silica varying from 30 to 60 phr. The interaction between the phenolic moiety of cardanol and the siloxane as well as silanol functional groups present on the silica surface enhances the rubber–filler interaction which leads to better reinforcement. The crosslink density and bound rubber content are found to be higher for the silica reinforced CGNR vulcanizates. The physico‐mechanical properties of the silica reinforced CGNR vulcanizates are superior to those of the NR vulcanizates. The CGNR vulcanizates show lower compression set and lower abrasion loss. The dynamic‐mechanical properties exhibit less Payne effect for silica reinforced CGNR vulcanizates as compared to the NR vulcanizates. The transmission electron photomicrographs show uniform dispersion of silica filler in the CGNR matrix. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43057.     

Modelling of a downdraft biomass gasifier with finite rate kinetics in the reduction zone

A model of a downdraft gasifier has been developed based on chemical equilibrium in the pyro‐oxidation zone and finite rate kinetic‐controlled chemical reactions in the reduction zone. The char reactivity factor (C_RF) in the reduction zone, representing the number of active sites on the char and its degree of burn out, has been optimized by comparing the model predictions against the experimental results from the literature. The model predictions agree well with the temperature distribution and exit gas composition obtained from the experiments at C_RF=100. A detailed parametric study has been performed at different equivalence ratios (between 2 and 3.4) and moisture content (in the range of 0–40%) in the fuel to obtain the composition of the producer gas as well as its heating value. It is observed that the heating value of the producer gas increases with the increase in the equivalence ratio and decrease in the biomass moisture content. The effect of divergence angle of the reduction zone geometry (in the range of 30–150°) on the temperature and species concentration distributions in the gasifier has been studied. An optimum divergence angle, giving the best quality of the producer gas, has been identified for a particular height of the reduction zone. Copyright © 2009 John Wiley & Sons, Ltd.