Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Calcium is essential for the structural integrity of the cysteine-rich, ligand-binding repeat of the low-density lipoprotein receptor

Seven cysteine-rich repeats form the ligand-binding region of the low-density lipoprotein (LDL) receptor. Each of these repeats is assumed to bind a calcium ion, which is needed for association of the receptor with its ligands, LDL and beta-VLDL. The effects of metal ions on the folding of the reduced N-terminal cysteine-rich repeat have been examined by using reverse-phase high-performance liquid chromatography to follow the formation of fully oxidized isomers with different disulfide connectivities. in the absence of calcium many of the 15 possible isomers formed on oxidation, whereas in its presence the predominant product at equilibrium had the native disulfide bond connectivities. Other metals were far less effective at directing disulfide bond formation: Mn2+ partly mimicked the action of Ca2+, but Ba2+, Sr2+, and Mg2+ had little effect. This metal-ion specificity was also observed in two-dimensional H-1 NMR spectral studies: only Ca2+ induced the native three-dimensional fold. The two paramagnetic ions, Gd3+ and Mn2+, and Cd2+ did not promote adoption of a well-defined structure, and the two paramagnetic ions did not displace calcium ions. The location of calcium ion binding sites in the repeat was also explored by NMR spectroscopy. The absence of chemical shift changes for the side chain proton resonances of Asp26, Asp36, and Glu37 from pH 3.9 to 6.8 in the presence of calcium ions and their proximal location in the NMR structures implicated these side chains as calcium ligands. Deuterium exchange NMR experiments also revealed a network of hydrogen bonds that stabilizes the putative calcium-binding loop.

Inhibition of phenotype modulation, growth, and migration of vascular smooth muscle cells by a guanosine-rich 30-mer phosphorothioate oligodeoxynucleotide

The testing of a 30-mer dG-rich phosphorothioate oligodeoxynucleotide (LG4PS) for effects on the behaviour of vascular smooth muscle cells (VSMC) in vitro and in vivo is described. LG4PS at 0.3 mu M inhibited significantly the phenotype modulation of freshly isolated rabbit VSMC, and cell outgrowth from pig aortic explants was inhibited similar to 80% by 5 mu M LG4PS. The growth of proliferating rabbit and pig VSMC was inhibited similar to 70% by 0.3 mu M and 5 mu M LG4PS, respectively. Though less marked, the antiproliferative effects of LG4PS on human VSMC were comparable to those obtained with heparin. The cytotoxic effects of LG4PS on VSMC in vitro were low. Despite these promising results, adventitial application of 2-200 nmol LG4PS in pluronic gel failed to reduce vascular hyperplasia in balloon-injured rabbit carotid arteries, and the highest dose caused extensive mortality. (C) 1997 Academic Press Limited.

Purification and characterization of a plant antimicrobial peptide expressed in Escherichia coli

MiAMP1 is a low-molecular-weight, cysteine-rich, antimicrobial peptide isolated from the nut kernel of Macadamia integrifolia. A DNA sequence encoding MiAMP1 with an additional ATG: start codon was cloned into a modified pET vector under the control of the T7 RNA polymerase promoter. The pET vector was cotransformed together with the vector pSB161, which expresses a rare arginine tRNA. The peptide was readily isolated in high yield from the insoluble fraction of the Escherichia coil extract. The purified peptide was shown to have an identical molecular weight to the native peptide by mass spectroscopy indicating that the N-terminal methionine had been cleaved. Analysis by NMR spectroscopy indicated that the refolded recombinant peptide had a similar overall three-dimensional structure to that of the native peptide. The peptide inhibited the growth of phytopathogenic fungi in vitro in a similar manner to the native peptide. To our knowledge, MiAMP1 is the first antimicrobial peptide from plants to be functionally expressed in E. coil. This will permit a detailed structure-function analysis of the peptide and studies of its mode of action on phytopathogens. (C) 1999 Academic Press.

Theory of modulational instability in Bragg gratings with quadratic nonlinearity

Modulational instability in optical Bragg gratings with a quadratic nonlinearity is studied. The electric field in such structures consists of forward and backward propagating components at the fundamental frequency and its second harmonic. Analytic continuous wave (CW) solutions are obtained, and the intricate complexity of their stability, due to the large number of equations and number of free parameters, is revealed. The stability boundaries are rich in structures and often cannot be described by a simple relationship. In most cases, the CW solutions are unstable. However, stable regions are found in the nonlinear Schrodinger equation limit, and also when the grating strength for the second harmonic is stronger than that of the first harmonic. Stable CW solutions usually require a low intensity. The analysis is confirmed by directly simulating the governing equations. The stable regions found have possible applications in second-harmonic generation and dark solitons, while the unstable regions maybe useful in the generation of ultrafast pulse trains at relatively low intensities. [S1063-651X(99)03005-6].

Frequency stabilised grating feedback laser diode for atom cooling applications

The free running linewidth of an external cavity grating feedback diode laser is on the order of a few megahertz and is limited by the mechanical and acoustic vibrations of the external cavity. Such frequency fluctuations can be removed by electronic feedback. We present a hybrid stabilisation technique that uses both a Fabry-Perot confocal cavity and an atomic resonance to achieve excellent short and long term frequency stability. The system has been shown to reduce the laser linewidth of an external cavity diode laser by an order of magnitude to 140 kHz, while limiting frequency excursions to 60 kHz relative to an absolute reference over periods of several hours. The scheme also presents a simple way to frequency offset two lasers many gigahertz apart which should find a use in atom cooling experiments, where hyperfine ground-state frequency separations are often required.

Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software

In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector-parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. (C) 2000 Published by Elsevier Science B.V. All rights reserved.