On decomposition of sub-linearised polynomials

We give a detailed exposition of the theory of decompositions of linearised polynomials, using a well-known connection with skew-polynomial rings with zero derivative. It is known that there is a one-to-one correspondence between decompositions of linearised polynomials and sub-linearised polynomials. This correspondence leads to a formula for the number of indecomposable sub-linearised polynomials of given degree over a finite field. We also show how to extend existing factorisation algorithms over skew-polynomial rings to decompose sub-linearised polynomials without asymptotic cost.

Charlatan philosopher and wise enchantress: Seduction and authority in eighteenth-century French discourses on happiness

In late 1757 Rousseau wrote a series of moral letters on happiness to Mme Sophie d'Houdetot. He distinguished himself and his teaching from the empty babble and hypocrisy prevalent in 'the century of philosophy and reason'. Philosophers were charlatans peddling happiness. This paper shows how Rousseau's critique of philosophy reworks the standard image of charlatans in the public square. It highlights a questioning and a gendering of reason implicit in the issue of credentials for teaching happiness. Against the dubious authority of the philosopher, Rousseau casts Sophie as the wise enchantress whose gentle influence inspires her tutor. He places moral authority outside the public square in a private, feminine domain. Rousseau's ideal woman cannot be a tainted charlatan like him. Yet the very opposition puts her in her place. (Author abstract)

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Towards evidence-based guidelines for wise use of computers by children

This paper argues for the systematic development and presentation of evidence-based guidelines for appropriate use of computers by children. The currently available guidelines are characterised and a proposed conceptual model presented. Five principles are presented as a foundation to the guidelines. The paper concludes with a framework for the guidelines, key evidence for and against guidelines, and gaps in the available evidence, with the aim of facilitating further discussion. Relevance to industry The current generation of children in affluent countries will typically have over 10 years of computer experience before they enter the workforce. Consequently, the primary prevention of computer-related health disorders and the development of good productivity skills for the next generation of workers needs to occur during childhood. (c) 2006 Elsevier B.V. All rights reserved.