Artificial neural networks: A novel approach to analysing the nutritional ecology of a blowfly species, Chrysomya megacephala

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Resolution and Absolute Configuration Assignment of a Natural Racemic Chromane from Peperomia obtusifolia (Piperaceae)

The resolution of the natural racemic chromane 3,4-dihydro-5-hydroxy-2,7-dimethyl-8-(3 ''-methyl-2 ''-butenyl)-2-(4'-methyl-1',3'-pentadienyl)-2H-1-benzopyran-6-carboxylic acid (1) isolated from the leaves of Peperomia obtusifolia has been accomplished using stereoselective HPLC. The absolute coil figuration of the resolved enantiomers was determined by the analysis of optical rotations and CD spectra. The finding of a racemic mixture instead of an enantiomerically pure metabolite raises questions about the final steps in the biosynthesis of this class of natural products, suggesting that the intramolecular chromane ring formation step may not be enzymatically controlled at all in P. obtusifolia. Chirality 21:799-801, 2009. (C) 2008 Wiley-Liss, Inc.

Entransy and its utilization in problems of thermodynamics and heat transfer

The concept of entransy was recently proposed in terms of the analogy to the electric energy stored in a capacitor. The entransy of a system describes its heat transfer ability, as the exergy of a system quantifies its work production potential. Hence, the concept of entransy can be useful in problems where the heat transfer is the main objective, as for example, in systems collecting solar energy. This concept is quite recent and there are only a few works related to this topic. It is expected, however, that this approach will soon be used more often in the analysis of problems in thermodynamics and heat transfer. The objective of this work is to present a review of the concept of entransy in a systematic way, beginning with its definition, balance equations and a few examples of simple applications. It is hoped that this concept of entransy becomes a useful tool in the analysis and design of more efficient thermal systems. © 2012 Praise Worthy Prize S.r.l.- All rights reserved.

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.