Synthesis of alpha-galactooligosaccharides with alpha-galactosidase from Lactobacillus reuteri of canine origin

Crude cell-free extracts from Lactobacillus reuteri grown on cellobiose, maltose, lactose and raffinose were assayed for glycosidic activities. When raffinose was used as the carbon source, alpha-galactosidase was produced, showing the highest yield at the beginning of the stationary growth phase. A 64 kDa enzyme was purified by ultra- and gel filtration, and characterized for its hydrolytic and synthetic activity. Highest hydrolytic activity was found at pH 5.0 at 50 degreesC (K-M 0.55 mM, V-max 0.80 mumol min(-1) mg(-1) of protein). The crude cell-free extract was further used in glycosyl transfer reactions to synthesize oligosaccharides from melibiose and raffinose. At a substrate concentration of 23% (w/v) oligosaccharide mixtures were formed with main products being a trisaccharide at 26% (w/w) yield from melibiose after 8 h and a tetrasaccharide at 18% (w/w) yield from raffinose after 7 h. Methylation analysis revealed the trisaccharide to be 6' alpha-galactosyl melibiose and the tetrasaccharide to be stachyose. In both cases synthesis ceased when hydrolysis of the substrate reached 50%.

European Union: Shadow WTO agricultural domestic support notifications

The notification of the level of domestic support to the World Trade Organization (WTO) is intended to reflect compliance with obligations entered into at the time of the Uruguay Round. WTO members have often been slow to provide notification of domestic support levels. This makes the process of notification less useful as an indicator of the degree to which changes in policy have or have not benefited the trade system as a whole and exporting countries in particular. The notification of domestic support in the E.U. illustrates the value of a measure that reflects current policies and can therefore act as a basis for negotiation of further disciplines where these are necessary. The E.U. has made major changes in its Common Agricultural Policy (CAP) over the period since 1992 when the MacSharry reforms were implemented. Payments originally notified in the blue box (related to supply control) have over time been changed until in their present form they are unrelated to current production or price levels, and hence can satisfy the criteria for the green box. The E.U. has therefore much more latitude in trade talks to agree to reductions in the allowable trade-distorting support. This paper reproduced the E.U. notifications relating to 2003/04 and extends these with official statistics to the year 2006/07. It then projects forward the components of domestic support until the year 2013/14, based on forecasts of future production and estimates of policy parameters. The impact of a successful Doha Round is simulated, showing that the constraints envisaged in the WTO draft modalities document of May 19, 2008, would be binding by the year 2013, at about the time the next budget cycle in the E.U. starts. Without the Doha Round constraints, further reform might still happen for domestic reasons, but the framework provided by the WTO for domestic policy spending would be less relevant. In that case, much could hinge on the legitimacy of the Single Farm Payment system under the current rules governing the green box.

Neural network feature maps for Chinese phonemes

It has been shown through a number of experiments that neural networks can be used for a phonetic typewriter. Algorithms can be looked on as producing self-organizing feature maps which correspond to phonemes. In the Chinese language the utterance of a Chinese character consists of a very simple string of Chinese phonemes. With this as a starting point, a neural network feature map for Chinese phonemes can be built up. In this paper, feature map structures for Chinese phonemes are discussed and tested. This research on a Chinese phonetic feature map is important both for Chinese speech recognition and for building a Chinese phonetic typewriter.

Using self-organising feature maps for the control of artificial organisms

Variations on the standard Kohonen feature map can enable an ordering of the map state space by using only a limited subset of the complete input vector. Also it is possible to employ merely a local adaptation procedure to order the map, rather than having to rely on global variables and objectives. Such variations have been included as part of a hybrid learning system (HLS) which has arisen out of a genetic-based classifier system. In the paper a description of the modified feature map is given, which constitutes the HLSs long term memory, and results in the control of a simple maze running task are presented, thereby demonstrating the value of goal related feedback within the overall network.

Quantifying chaos: a tale of two maps

In many applications, there is a desire to determine if the dynamics of interest are chaotic or not. Since positive Lyapunov exponents are a signature for chaos, they are often used to determine this. Reliable estimates of Lyapunov exponents should demonstrate evidence of convergence; but literature abounds in which this evidence lacks. This paper presents two maps through which it highlights the importance of providing evidence of convergence of Lyapunov exponent estimates. The results suggest cautious conclusions when confronted with real data. Moreover, the maps are interesting in their own right.

An improved lesion detection approach based on similarity measurement between fuzzy intensity segmentation and spatial probability maps

The application of automatic segmentation methods in lesion detection is desirable. However, such methods are restricted by intensity similarities between lesioned and healthy brain tissue. Using multi-spectral magnetic resonance imaging (MRI) modalities may overcome this problem but it is not always practicable. In this article, a lesion detection approach requiring a single MRI modality is presented, which is an improved method based on a recent publication. This new method assumes that a low similarity should be found in the regions of lesions when the likeness between an intensity based fuzzy segmentation and a location based tissue probabilities is measured. The usage of a normalized similarity measurement enables the current method to fine-tune the threshold for lesion detection, thus maximizing the possibility of reaching high detection accuracy. Importantly, an extra cleaning step is included in the current approach which removes enlarged ventricles from detected lesions. The performance investigation using simulated lesions demonstrated that not only the majority of lesions were well detected but also normal tissues were identified effectively. Tests on images acquired in stroke patients further confirmed the strength of the method in lesion detection. When compared with the previous version, the current approach showed a higher sensitivity in detecting small lesions and had less false positives around the ventricle and the edge of the brain