Harnstoffhydrolyse für die selektive katalytische Reduktion von NOx: Vergleich der Flüssig‐ und Gasphasenzersetzung

In order to reduce the NO_x concentration in car exhausts usually the selective catalytic reduction with ammonia is used. However, to avoid the transport of ammonia in vehicles urea is applied as NH₃ precursor. Controlled urea decomposition before the injection into the exhaust gas system itself may be accomplished by the use of a separate reactor. Urea decomposition to ammonia in the liquid phase under pressure in a heated reactor was compared to its decomposition in the gas phase. In the liquid phase, higher conversion rates relative to the reactor volume were realized than in the gas phase. Catalysts which showed high activity in the gas phase influenced the decomposition in the liquid phase only slightly.     

Ern?hrungslehre

Ohne Zusammenfassung     

Allgemeine Bestandteile der Nahrungs- und Genu?mittel

Ohne Zusammenfassung     

Lexical and nonlexical phonological priming in reading aloud.

Five homophone priming experiments were reported in which the lexicality of primes and targets were varied, so that primes and targets were either nonword homophones (keff-keph), word homophones (brake-break), pseudohomophones (brayk-braik), or of mixed lexicality (brake-brayk and brayk-break). Results showed that naming of targets was facilitated by a phonologically identical prime only when a word was in the prime-target pairing. Simulations of these data using the dual-route cascaded model of reading (e.g., M. Coltheart, B. Curtis, P. Atkins, & M. Haller, 1993) were also reported. These results are evidence against the view that there is a critical early stage in the process of visual word recognition in which words are represented in purely phonological form, and they are evidence for the view that knowledge of orthography and phonology is represented locally in the reading system. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ern?hrungslehre

Ohne Zusammenfassung     

Allgemeine Bestandteile der Nahrungs- und Genu?mittel

Ohne Zusammenfassung     

A stochastic method for Bayesian estimation of hidden Markov random field models with application to a color model.

We propose a new stochastic algorithm for computing useful Bayesian estimators of hidden Markov random field (HMRF) models that we call exploration/selection/estimation (ESE) procedure. The algorithm is based on an optimization algorithm of O. Fran?ois, called the exploration/selection (E/S) algorithm. The novelty consists of using the a posteriori distribution of the HMRF, as exploration distribution in the E/S algorithm. The ESE procedure computes the estimation of the likelihood parameters and the optimal number of region classes, according to global constraints, as well as the segmentation of the image. In our formulation, the total number of region classes is fixed, but classes are allowed or disallowed dynamically. This framework replaces the mechanism of the split-and-merge of regions that can be used in the context of image segmentation. The procedure is applied to the estimation of a HMRF color model for images, whose likelihood is based on multivariate distributions, with each component following a Beta distribution. Meanwhile, a method for computing the maximum likelihood estimators of Beta distributions is presented. Experimental results performed on 100 natural images are reported. We also include a proof of convergence of the E/S algorithm in the case of nonsymmetric exploration graphs.