Age and gender influences on sensory perceptions of novel low cost nutrient-rich food products developed using traditional Ghanaian food ingredients

Background: A number of factors are known to influence food preferences and acceptability of new products. These include their sensory characteristics and strong, innate neural influences. In designing foods for any target group, it is important to consider intrinsic and extrinsic characteristics which may contribute to palatability, and acceptability of foods. Objective: To assess age and gender influences on sensory perceptions of novel low cost nutrient-rich food products developed using traditional Ghanaian food ingredients. Materials and Methods: In this study, a range of food products were developed from Ghanaian traditional food sources using the Food Multimix (FMM) concept. These products were subjected to sensory evaluation to assess the role of sensory perception on their acceptability among different target age groups across the life cycle (aged 11-68 years olds) and to ascertain any possible influences of gender on preference and choice. Variables including taste, odour, texture, flavour and appearance were tested and the results captured on a Likert scale and scores of likeness and acceptability analysed. Multivariate analyses were used to develop prediction models for targeted recipe development for different target groups. Multiple factor analysis of variance (ANOVA) and logistic linear regression were employed to test the strength of acceptability and to ascertain age and gender influences on product preference. Results: The results showed a positive trend in acceptability (r = 0.602) which tended towards statistical significance (p = 0.065) with very high product favourability rating (91% acceptability; P=0.005). However, age [odds ratios=1.44 (11-15 years old) odds ratios=2.01 (18-68 years old) and gender (P=0.000)] were major influences on product preference with children and females (irrespective of age) showing clear preferences or dislike of products containing certain particular ingredients. Conclusion: These findings are potentially useful in planning recipes for feeding interventions involving different vulnerable and target groups.

Domain decomposition methods for welding problems

This paper, a 2-D non-linear electric arc-welding problem is considered. It is assumed that the moving arc generates an unknown quantity of energy which makes the problem an inverse problem with an unknown source. Robust algorithms to solve such problems e#ciently, and in certain circumstances in real-time, are of great technological and industrial interest. There are other types of inverse problems which involve inverse determination of heat conductivity or material properties [CDJ63][TE98], inverse problems in material cutting [ILPP98], and retrieval of parameters containing discontinuities [IK90]. As in the metal cutting problem, the temperature of a very hot surface is required and it relies on the use of thermocouples. Here, the solution scheme requires temperature measurements lied in the neighbourhood of the weld line in order to retrieve the unknown heat source. The size of this neighbourhood is not considered in this paper, but rather a domain decomposition concept is presented and an examination of the accuracy of the retrieved source are presented. This paper is organised as follows. The inverse problem is formulated and a method for the source retrieval is presented in the second section. The source retrieval method is based on an extension of the 1-D source retrieval method as proposed in [ILP].

Numerical solutions of certain nonlinear models in European options on a distributed computing environment

Financial modelling in the area of option pricing involves the understanding of the correlations between asset and movements of buy/sell in order to reduce risk in investment. Such activities depend on financial analysis tools being available to the trader with which he can make rapid and systematic evaluation of buy/sell contracts. In turn, analysis tools rely on fast numerical algorithms for the solution of financial mathematical models. There are many different financial activities apart from shares buy/sell activities. The main aim of this chapter is to discuss a distributed algorithm for the numerical solution of a European option. Both linear and non-linear cases are considered. The algorithm is based on the concept of the Laplace transform and its numerical inverse. The scalability of the algorithm is examined. Numerical tests are used to demonstrate the effectiveness of the algorithm for financial analysis. Time dependent functions for volatility and interest rates are also discussed. Applications of the algorithm to non-linear Black-Scholes equation where the volatility and the interest rate are functions of the option value are included. Some qualitative results of the convergence behaviour of the algorithm is examined. This chapter also examines the various computational issues of the Laplace transformation method in terms of distributed computing. The idea of using a two-level temporal mesh in order to achieve distributed computation along the temporal axis is introduced. Finally, the chapter ends with some conclusions.