Ein Beitrag zur Analytik der Fumars?ure und der Maleins?ure in Lebensmitteln

Zusammenfassung Zur Prüfung der Frage, in welchom Ausmaß Fumarsäure bei Backprozessen und bei indirekter Bestrahlung mit Ultraviolettlicht eine Umwandlung in Maleinsäure erfährt, wurde ein geeignetes analytisches Verfahren entwickelt. Die Isolierung der in Rede stehenden Säuren aus Gebäcken erfolgt aus einem wäßrigen Auszug durch Adsorption an Ionenaustauscherharz und anschließende Elution mit Ammonium-hydrogencarbonatlösung. Zur qualitativen und quantitativen Erfassung der Fumarund Maleinsäure wird eine dünnschichtchromatographische Methode beschrieben. Bei indirekter Bestrahlung mit ultraviolettem Licht erfolgt keine nachweisbare Isomerisierung wäßriger Fumarsäurelösungen. Im wäßrigen Medium beginnt oberhalb von 180° C eine Isomerisierung der Fumarsäure zu Maleinsäure. Überlagert wird dieser Prozeß durch Sublimation der Säuren sowie durch Isomerisierung der Maleinsäure zu Fumarsäure. Dadurch verringert sich der allein in der Brotkruste lokalisierte Anteil der Maleinsäure weiter. Für Brot und Keks wird auf Grund der Versuchsergebnisse das Verhalten der Fumarsäure beim Backprozeß diskutiert.     

POLYCHAR-10 World Forum on Polymer Applications &; Theory in 2002

A report from POLYCHAR-10 is provided. An introduction to the following papers presented at the POLYCHAR-10 Forum is given. A small selection of the authors and titles of the papers presented is listed. Prizes awarded are listed along with the composition of the Prize Committee. Some research groups of high activity which are represented at POLYCHAR every year are named. Electronic Publication     

Future trends in data mining

Over recent years data mining has been establishing itself as one of the major disciplines in computer science with growing industrial impact. Undoubtedly, research in data mining will continue and even increase over coming decades. In this article, we sketch our vision of the future of data mining. Starting from the classic definition of “data mining”, we elaborate on topics that — in our opinion — will set trends in data mining.     

Metallo‐Supramolecular Block Copolymers

Supramolecular copolymers have become of increasing interest in recent years for the search of new materials with tunable properties. In particular, metallo‐supramolecular block copolymers—copolymers in which the blocks are linked together by a metal–ligand complex—have seen important progresses, allowing better control over the synthetic strategies for various architectures, and providing a better understanding of the parameters governing their self‐assembly. We review here recent developments on the synthesis and self‐assembly of such materials achieved in this field.     

Cover Picture: Magnetorheological Fluids Based on Ionic Liquids (Adv. Mater. 13/2007)

The use of ionic liquids as carriers of magnetorheological fluids is described by Schubert and co‐workers on p. 1740. Combining the properties of ionic liquids with magnetorheological technology may lead to new, “smart” fluids for application in medical therapies, engineering devices, or multiphase biological and chemical systems. In the presence of a magnetic field the fluids behave as solids owing to a stronger interaction between their suspended magnetic particles. In the absence of the magnetic field, they become liquids again in a fully reversible process.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.     

A multidistrict audit on the management of Chlamydia trachomatis in genitourinary medicine clinics in Yorkshire

Although there have been recent molecular biological studies for evidence of possible changes in trypanosome biochemistry, such studies are not yet complemented by parallel clinical studies to determine the possible implications to the sleeping sickness patient. The study of the duration of symptoms and the case fatality of T. b. rhodesiense showed that the disease progressed to the stage of central nervous system involvement between three weeks to two months of infection. Most (> 80%) deaths occurred within six months of illness. The case fatality rate of treated sleeping sickness patients was 6% of which the rate in the late-stage of sleeping sickness was more than two and a half times that in the early stage. The incidence of melarsoprol encephalopathy was 2.5% and case fatality due to this condition was 1.0% and similar to previous findings. Thus it appears the virulence of T. b. rhodesiense circulating in south east Uganda has not changed during the past decades.     

Episodic Logic: A comprehensive,natural representation for language understanding

A new comprehensive framework for narrative understanding has been developed. Its centerpiece is a new situational logic calledEpisodic Logic (EL), a knowledge and semantic representation well-adapted to the interpretive and inferential needs of general NLU. The most distinctive features of EL is its natural language-like expressiveness. It allows for generalized quantifiers, lambda abstraction, sentence and predicate modifiers, sentence and predicate reification, intensional predicates (corresponding to wanting, believing, making, etc.), unreliable generalizations, and perhaps most importantly, explicit situational variables (denoting episodes, events, states of affairs, etc.) linked to arbitrary formulas that describe them. These allow episodes to be explicitly related in terms of part-whole, temporal and causal relations. Episodic logical form is easily computed from surface syntax and lends itself to effective inference.