Fusion and breakup in the reactions of 6,7Li and 9Be

We develop a three body classical trajectory Monte Carlo (CTMC) method to dicsuss the effect of the breakup process on heavy-ion fusion reactions induced by weakly bound nuclei. This method follows the classical trajectories of breakup fragments after the breakup takes place, and thus provides an unambiguous separation between complete and incomplete fusion cross sections. Applying this method to the fusion reaction $^{6}$Li + $^{209}$Bi, we find that there is a significant contribution to the total complete fusion cross sections from the process where all the breakup fragments are captured by the target nucleus (i.e., the breakup followed by complete fusion).Comment: 4 pages, 3 eps figures. Uses espcrc1.sty. To be published in the proceedings of the 8th international conference on clustering aspects of nuclear structure and dynamics, November 24 - 29, 2003, Nara, Japan (Nucl. Phys. A

The Welding of Special and Alloy Steels

FOR applications in which the properties of mild steel are inadequate there are other steels which meet a wide range of specific requirements. These special and alloy steels are many and varied. Some are closely similar in composition to mild steel, but are made by special proc-esses to meet the needs of a special application; others contain considerable percentages of alloy additions, but still qualify to be called steels, as having an iron content of not less than 50 per cent

Naive Bayes vs. Decision Trees vs. Neural Networks in the Classification of Training Web Pages

Web classification has been attempted through many different technologies. In this study we concentrate on the comparison of Neural Networks (NN), Naïve Bayes (NB) and Decision Tree (DT) classifiers for the automatic analysis and classification of attribute data from training course web pages. We introduce an enhanced NB classifier and run the same data sample through the DT and NN classifiers to determine the success rate of our classifier in the training courses domain. This research shows that our enhanced NB classifier not only outperforms the traditional NB classifier, but also performs similarly as good, if not better, than some more popular, rival techniques. This paper also shows that, overall, our NB classifier is the best choice for the training courses domain, achieving an impressive F-Measure value of over 97%, despite it being trained with fewer samples than any of the classification systems we have encountered

Web-based Tools for the Analysis of DNA Microarrays

End of project reportDNA microarrays are widely used for gene expression profiling. Raw data resulting from microarray experiments, however, tends to be very noisy and there are many sources of technical variation and bias. This raw data needs to be quality assessed and interactively preprocessed to minimise variation before statistical analysis in order to achieve meaningful result. Therefore microarray analysis requires a combination of visualisation and statistical tools, which vary depending on what microarray platform or experimental design is used.Bioconductor is an existing open source software project that attempts to facilitate analysis of genomic data. It is a collection of packages for the statistical programming language R. Bioconductor is particularly useful in analyzing microarray experiments. The problem is that the R programming language’s command line interface is intimidating to many users who do not have a strong background in computing. This often leads to a situation where biologists will resort to using commercial software which often uses antiquated and much less effective statistical techniques, as well as being expensively priced. This project aims to bridge this gap by providing a user friendly web-based interface to the cutting edge statistical techniques of Bioconductor