Phytochemical and biological investigation of <Emphasis Type="Italic">Stevia rebaudiana</Emphasis> Bertoni; 1-labdane-type diterpene

Five labdane diterpenoids, austroinulin, iso-austroinulin, sterebin E, sterebin E acetate, and sterebin A acetate, along with hydrocarbons, aliphatic alcohols, β-amyrin, β-sitosterol and stigmasterol were isolated from the chloroform soluble fraction of the methanol extract of Stevia rebaudiana leaves. Chlorogenic and caffeic acids were isolated from the EtOAc fraction. All the isolated compounds were identified using spectral tools. The chloroform and methanol extracts proved significant anti-inflammatory effect and caused marked inhibition of carrageenan-induced paw oedema in rats.     

Uncertainty Matters: Computer Models at the Science–Policy Interface

The use of computer models offers a general and flexible framework that can help to deal with some of the complexities and difficulties associated with the development of water management plans as prescribed by the Water Framework Directive. However, despite the advantages modelling presents, the integration of information derived from models into policy is far away from being trivial or the norm. Part of the difficulties of this integration is rooted in the lack of confidence policy makers have on the incorporation of modelling information into policy formulation. In this paper we examine the reasons for this apparent lack of confidence and explore how some tools, presently in use, address this problem. We conclude that public confidence in models is highly dependent on the way uncertainties are addressed and suggest possible directions of action to improve the current situation. Four real case studies illustrate how computer models have been used in The Netherlands for carrying out management plans at regional and national scale. We suggest that the solution to integrate modelling information into policy formulation lies on both the modelling and the policy-making communities.     

Two-tier architecture for unconstrained handwritten character recognition

In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.     

Development of nano indium tin oxide (ITO) grains by alkaline hydrolysis of In(III) and Sn(IV) salts

Indium tin oxide (ITO) nano powders of different compositions (In: Sn = 90: 10, 70: 30 and 50: 50) were prepared by heat treatment (300-450°C) of mixed hydroxides of In(III) and Sn(IV). The hydroxides were obtained by the reaction of aq. NH₃ with mixed aq. solutions of In(NO₃)₃ and SnCl₄. FTIR and TG/DTA studies revealed that powders existed as In(OH)₃H₂O—SnO₃H₂H₂O in the solid state and then they transformed to In₂O₃—SnO₂ via some metastable intermediates after 300°C. Cubic phase of In₂O₃ was identified by XRD for the oxides up to 30% of Sn. Particle size measurements of the solid dispersed in acetone and SEM study for microstructure showed that the oxides were in the nano range (55-75 nm) whereas the size range determined from Debye-Scherrer equation were 11–24 nm.     

A computational study of LP-based heuristic algorithms for two-dimensional guillotine cutting stock problems

In this paper we develop and compare several heuristic methods for solving the general two-dimensional cutting stock problem. We follow the Gilmore-Gomory column generation scheme in which at each iteration a new cutting pattern is obtained as the solution of a subproblem on one stock sheet. For solving this subproblem, in addition to classical dynamic programming, we have developed three heuristic procedures of increasing complexity, based on GRASP and Tabu Search techniques, producing solutions differing in quality and in time requirements. In order to obtain integer solutions from the fractional solutions of the Gilmore-Gomory process, we compare three rounding procedures, rounding up, truncated branch and bound and the solution of a residual problem. We have coded and tested all the combinations of algorithms and rounding procedures. The computational results obtained on a set of randomly generated test problems show their relative efficiency and allow the potential user to choose from among them, according to the available computing time. Rceived: January 9, 2001 / Accepted: December 10, 2001     

Using artificial intelligence to model heavy plate mill rolling

This research summary discusses the application of neural networks, evolutionary strategies, and other artificial intelligence techniques in the modeling and optimization of the models used for temperature, rolling force, and torque calculation in heavy plate milling.     

Mathematical analysis of viscometric (polymer) flow fields in capillaries: Taylor dispersion revisited

A general formulation for capillary flow of two miscible fluids – one a dilute plug of polymer fluid inserted into a fully developed Poiseuille flow of the other, a Newtonian stream – is examined for its long time behavior. Phenomenologically, the system evolves from an initial state, that of a plug within the boundaries of sharp, well defined fronts inside a Newtonian stream, to a more homogenized state in the very long time scale. This problem was addressed by G.I. Taylor but with regard to a system of two Newtonian fluids, leading to the well-known results commonly described as `Taylor axial dispersion'. In this paper, a general and systematic perturbation analysis is presented from which Taylor's result is recovered as a special case of a more general solution which applies to fluids incorporating elastic properties. In particular, the influence of viscoelasticity and (polymer) diffusivity on the observed pressure profile in the capillary conduit is examined. This effect is clearly separated out for small Peclet number flows using asymptotic and numerical analysis. The results identify the influence of fluid viscosity, elasticity, and diffusivity on the observed pressure profile and form the basis for the improved characterization of polymeric elasticity using capillaries – a finding that is of significant scientific and commercial interest. These results were obtained by the authors as a class of observations resulting from the perturbation analysis of forced-flow capillary devices in viscoelastic fluid property investigation.