Is there a direct relationship between oral astringency and human salivary protein binding?

For decades, it is believed that astringency is due to the polyphenol-induced complexation of proline-rich salivary proteins in the oral cavity. In order to compare for the first time the human sensory threshold concentrations and the salivary protein binding activity of a series of astringent stimuli, human saliva protein was incubated for 5 min at 37 °C in the presence of astringent food-derived compounds and, after micro-centrifugation, the amount of the target molecules in the supernatant was quantitatively determined by HPLC-UV/Vis. Significant protein binding was observed for (−)-epigallocatechin-3-gallate, (−)-gallocatechin-3-gallate, (+)-gallocatechin, and (−)-catechin-3-gallate, all of which containing at least one galloyl moiety in the molecule and exhibiting rather high sensory thresholds of more than 200 μmol/L. In comparison, (+)-catechin and procyanidin B2, both lacking in any galloyl function, showed only comparatively low binding activity and, most interestingly, quercetin-3-O-α-l-rhamnopyranosyl-(1 → 6)-β-d-glucopyranoside and 3-carboxymethyl-indole-1-N-β-d-glucopyranoside did not show any protein binding at all, although the later N- and O-glycosides exhibited extraordinarily low sensory threshold concentrations of less than 0.001 and 0.0003 μmol/L, respectively. The data give some first evidence that the quantity of the non-bound, “free” astringent stimulus in the saliva liquid might be more closely related to the sensory perception of astringency than the amount complexed or precipitated by proteins. It is therefore questionable as to whether oral perception of astringency is related to the complexation and/or precipitation of salivary proteins.     

Effective modelling of percolation at the landscape scale using data-based approaches

Process-based models have been extensively applied to assess the impact of landuse change on water quantity and quality at landscape scales. However, the routine application of those models suffers from large computational efforts, lack of transparency and the requirement of many input parameters. Data-based models such as Feed-Forward Multilayer Perceptrons (MLP) and Classification and Regression Trees (CART) may be used as effective models, i.e. simple approximations of complex process-based models. These data-based approaches can subsequently be applied for scenario analysis and as a transparent management tool provided climatic boundary conditions and the basic model assumptions of the process-based models do not change dramatically. In this study, we apply MLP, CART and Multiple Linear Regression (LR) to model the spatially distributed and spatially aggregated percolation in soils using weather, groundwater and soil data. The percolation data is obtained via numerical experiments with Hydrus1D. Thus, the complex process-based model is approximated using simpler data-based approaches. The MLP model explains most of the percolation variance in time and space without using any soil information. This reflects the effective dimensionality of the process-based model and suggests that percolation in the study area may be modelled much simpler than using Hydrus1D. The CART model shows that soil properties play a negligible role for percolation under wet climatic conditions. However, they become more important if the conditions turn drier. The LR method does not yield satisfactory predictions for the spatially distributed percolation however the spatially aggregated percolation is well approximated. This may indicate that the soils behave simpler (i.e. more linear) when percolation dynamics are upscaled.     

Quasi-optical measurement of complex dielectric constant at 300 GHz

A two beam interferometer in the Martin-Puplett configuration is used to determine the complex dielectric constant at 300 GHz of teflon, TPX-plastics, SPECTRALON and paraffin waxes with melting temperatures of 48° C and 72° C, respectively. The design of the quasi-optical system leads to a constant beam diameter at the power detector independent of path delay and frequency. The power detector signal is recorded not only along one period but over about 50 periods. A spectrum estimation routine allows to determine more exactly amplitude and phase angle of the signal. A basic problem is noticed: imperfect detector and source match cause harmonic distortion of the power detector signal. The effects on processing the loss tangent and the invalidation are shown. Finally loss tangent and dielectric constant are determined indirectly by optimizing an equivalent microwave circuit using a commercial available microwave design system to take multiple reflections and losses in consideration.     

Dreidimensionale,turbulente Strömungs-und Mischungsgradberechnung mit dem PISO-Algorithmus

Zusammenfassung Die numerische Berechnung von turbulenten Str?mungen, sei es isotherm oder mit chemischer Reaktion und W?rmefreisetzung, kann infolge der st?ndigen Fortschritte auf Seiten der Hardware-Entwicklung, auf immer weiteren Anwendungsgebieten eingesetzt werden. Im vorliegenden Fall handelt es sich um ein Programmpaket (COMPAC-3D), welches für die dreidimensionale Simulation der Str?mung und W?rmefreisetzung in Dampferzeugerfeuerungen konzipiert wurde. Hierbei kommt ein neuer Gleichungsl?sungs-und Bilanzierungsalgorithmus zum Einsatz, welcher es gestattet, Parameterstudient mit wesentlich geringerem Rechenzeitaufwand durchzuführen. Dieser Algorithmus wird im folgenden beschrieben. Anhand eines klassischen Testbeispiels, n?mlich der horizontalen Eindüsung in eine vertikale Hauptstr?mung, werden die Simulationsergebnisse mit Me?werten und Ergebnissen aus Rechenl?ufen mit dem Programmpaket PHOENICS verglichen.     

Adaptive isogeometric analysis by local h-refinement with T-splines

Isogeometric analysis based on non-uniform rational B-splines (NURBS) as basis functions preserves the exact geometry but suffers from the drawback of a rectangular grid of control points in the parameter space, which renders a purely local refinement impossible. This paper demonstrates how this difficulty can be overcome by using T-splines instead. T-splines allow the introduction of so-called T-junctions, which are related to hanging nodes in the standard FEM. Obeying a few straightforward rules, rectangular patches in the parameter space of the T-splines can be subdivided and thus a local refinement becomes feasible while still preserving the exact geometry. Furthermore, it is shown how state-of-the-art a posteriori error estimation techniques can be combined with refinement by T-splines. Numerical examples underline the potential of isogeometric analysis with T-splines and give hints for further developments.     

Learning with "relevance": using a third factor to stabilize Hebbian learning

It is a well-known fact that Hebbian learning is inherently unstable because of its self-amplifying terms: the more a synapse grows, the stronger the postsynaptic activity, and therefore the faster the synaptic growth. This unwanted weight growth is driven by the autocorrelation term of Hebbian learning where the same synapse drives its own growth. On the other hand, the cross-correlation term performs actual learning where different inputs are correlated with each other. Consequently, we would like to minimize the autocorrelation and maximize the cross-correlation. Here we show that we can achieve this with a third factor that switches on learning when the autocorrelation is minimal or zero and the cross-correlation is maximal. The biological counterpart of such a third factor is a neuromodulator that switches on learning at a certain moment in time. We show in a behavioral experiment that our three-factor learning clearly outperforms classical Hebbian learning.     

Efficient computation of Morse-Smale complexes for three-dimensional scalar functions

The Morse-Smale complex is an efficient representation of the gradient behavior of a scalar function, and critical points paired by the complex identify topological features and their importance. We present an algorithm that constructs the Morse-Smale complex in a series of sweeps through the data, identifying various components of the complex in a consistent manner. All components of the complex, both geometric and topological, are computed, providing a complete decomposition of the domain. Efficiency is maintained by representing the geometry of the complex in terms of point sets.