Cover Picture: Protein Detecting Arrays Based on Cationic Polythiophene–DNA‐Aptamer Complexes (Adv. Mater. 20/2006)

The cover image depicts biochips based on responsive nanoaggregates made from stoichiometric complexes between a cationic polythiophene and an appropriate DNA aptamer. These structures undergo a conformational transition from an unfolded to a folded (G‐quadruplex) structure in the presence of a specific target protein that results in a significant increase of the fluorescence intensity, as reported on p. 2703 by Leclerc and co‐workers.     

Effect of Hot Band Annealing on Magnetic Properties in 3% Si Grain‐oriented Electrical Steels

Hot band annealing is known to be a prerequisite for good magnetic properties irrespective of manufacturing methods in grain‐oriented Fe‐3 wt.% Si electrical steels. In this study, the effects of hot band annealing on magnetic properties were investigated in 3% grain‐oriented electrical steels of low soluble AI contents and one‐stage cold rolling. Microstructure and precipitate distribution were compared with hot band annealing conditions. Secondary recrystallization behaviour with hot band annealing condition was also discussed.     

Odyssey: a high‐performance clustered video server

Video servers are essential in video‐on‐demand and other multimedia applications. In this paper, we present our high‐performance clustered CBR video server, Odyssey. Odyssey is a server connecting PCs with switched Ethernet. It provides efficient support for normal play and interactive browsing functions such as fast‐forward and fast‐backward. We designed a set of algorithms for scheduling, synchronization and admission control, which results in a high utilization of resources. Odyssey is able to deliver a large number of video streams. Copyright © 2003 John Wiley & Sons, Ltd.     

10th GAMM-IMACS International Symposium on Scientific Computing,Computer Arithmetic,and Validated Numerics SCAN'2002

Reliable Computing -     

A Neuro-fuzzy Coding for Processing Incomplete Data: Application to the Classification of Seismic Events

This letter presents a method for modelling and processing incomplete data in connectionist systems. The approach consists in applying a neuro-fuzzy coding to the input data of a neural network. After an introduction to the different kinds of imperfections, we propose a neuro-fuzzy coding in order to take incomplete data into account. We show the efficiency of this coding on the problem of the classification of seismic events. The results show that a neuro-fuzzy coding of the inputs of a neural network increases the performance and classifies incomplete data with little affect on the results.