Steering in computational science: Mesoscale modelling and simulation

This paper outlines the benefits of computational steering for high performance computing applications. Lattice-Boltzmann mesoscale fluid simulations of binary and ternary amphiphilic fluids in two and three dimensions are used to illustrate the substantial improvements which computational steering offers in terms of resource efficiency and time to discover new physics. We discuss details of our current steering implementations and describe their future outlook with the advent of computational grids.     

Simple statistically based alternatives to MAF for ToF‐SIMS spectral image analysis

The maximum autocorrelation factors technique (MAF) is becoming increasingly popular for the multivariate analysis of spectral images acquired with time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) instruments. In this article, we review the conditions under which the underlying chemical information can be separated from the large‐scale, non‐uniform noise characteristic of ToF‐SIMS data. Central to this pursuit is the ability to assess the covariance structure of the noise. Given a set of replicate images, the noise covariance matrix can be estimated in a straightforward way using standard statistical tools. Acquiring replicate images, however, is not always possible, and MAF solves a subtly different problem, namely, how to approximate the noise covariance matrix from a single image when replicates are not available. This distinction is important; the MAF approximation is not an unbiased statistical estimate of the noise covariance matrix, and it differs in a highly significant way from a true estimate for ToF‐SIMS data. Here, we draw attention to the fact that replicate measurements are made during the normal course of acquiring a ToF‐SIMS spectral image, rendering the MAF procedure unnecessary. Furthermore, in the common case that detector dead‐time effects permit no more than one ion of any specific species to be detected on a single primary ion shot, the noise covariance matrix can be estimated in a particularly simple way, which will be reported. Copyright © 2011 John Wiley & Sons, Ltd.     

空气中激光烧蚀Cu产生等离子体发射光谱的研究

利用Q-开关Nd:YAG激光器产生的1.06 μm、10 ns的脉冲激光聚焦在空气中的Cu靶上,观测了激光诱导的Cu等离子体发射光谱.采用不同的激光能量,分析了波长范围为440 nm到540 nm的空间分辨发射光谱.在局部热力学平衡(LTE)条件近似下,根据谱线的相对强度,得到了等离子体电子温度约在104 K以上,给出了靶面附近电子温度的空间演化规律,并探讨了N(Ⅱ)500.52 nm谱线的谱线强度和半高全宽随激光能量的变化规律.     

In-beam γ-ray spectroscopy of <Superscript>190</Superscript>Po: First observation of a low-lying prolate band in Po isotopes

Gamma rays from excited states of ¹⁹⁰Po have been observed using the Jurosphere Ge-detector array coupled to the RITU gas-filled separator. They were associated with a collective band which from spin 4 onwards resembles the prolate rotational bands known in the isotones ¹⁸⁸Pb and ¹⁸⁶Hg. This indicates that in ¹⁹⁰Po the prolate configuration becomes yrast above I = 2. The experimental results are interpreted in a two-band mixing calculation and are in agreement with α-decay data and potential energy surface calculations. Received: 10 January 2003 / Accepted: 19 February 2003 / Published online: 7 May 2003     

A hybrid genetic model for the prediction of corporate failure

This study examines the potential of a neural network (NN) model, whose inputs and structure are automatically selected by means of a genetic algorithm (GA), for the prediction of corporate failure using information drawn from financial statements. The results of this model are compared with those of a linear discriminant analysis (LDA) model. Data from a matched sample of 178 publicly quoted, failed and non-failed, US firms, drawn from the period 1991 to 2000 is used to train and test the models. The best evolved neural network correctly classified 86.7 (76.6)% of the firms in the training set, one (three) year(s) prior to failure, and 80.7 (66.0)% in the out-of-sample validation set. The LDA model correctly categorised 81.7 (75.0)% and 76.0 (64.7)% respectively. The results provide support for a hypothesis that corporate failure can be anticipated, and that a hybrid GA/NN model can outperform an LDA model in this domain.MSC codes: 62M45, 68W10, 90B50, 91C20     

Electron impact excitation collision strengths for neon-like Ni XIX calculated using the relativistic R-matrix method

In a recent paper [Pramana — J. Phys. 64, 129 (2005)] results have been presented for electron impact excitation collision strengths for transitions among the fine-structure levels of the 2s²2p⁶ and 2s²2p⁵3s configurations of Ni XIX. In this paper we demonstrate through an independent calculation with the relativistic R-matrix code that those results are unreliable and the conclusions drawn are invalid.     

The rotational spectrum,nuclear spin—spin coupling,nuclear quadrupole coupling,and molecular structure of KrHF

Rotational spectra have been assigned for the ⁸²Kr, ⁸³Kr, ⁸⁴Kr, and ⁸⁶Kr isotopic species of the KrHF and KrDF van der Waals molecules by using pulsed microwave Fourier transform spectroscopy in a Fabry—Perot cavity with a pulsed supersonic nozzle molecular source. The rotational, centrifugal distortion, nuclear spin—spin, and nuclear quadrupole coupling constants are used to determine the structure and obtain intramolecular potential binding information. The ⁸³Kr nuclear quadrupole coupling constants are 10.28 ± 0.08 MHz and 13.83 ± 0.13 MHz for KrHF and KrDF respectively. The electric field gradient at the krypton nucleus is calculated from the coupling constant and the known nuclear quadrupole moment and explained by Sternheimer shielding and formation of the van der Waals bond. There is a negligible charge transfer in the KrHF bond.     

Contra-Friedel-Crafts tert-butylation of substituted aromatic rings via directed metallation and sulfinylation

Directed metallation and sulfinylation yields sulfoxides which undergo ipso nucleophilic aromatic substitution with tertiary and secondary alkyllithiums, giving aromatic rings bearing alkyl groups generally incompatible with directed metallation methods and with regioselectivity complementary with classical Friedel-Crafts substitution.     

Tucker1 model algorithms for fast solutions to large PARAFAC problems

We describe a method of performing trilinear analysis on large data sets using a modification of the PARAFAC‐ALS algorithm. Our method iteratively decomposes the data matrix into a core matrix and three loading matrices based on the Tucker1 model. The algorithm is particularly useful for data sets that are too large to upload into a computer's main memory. While the performance advantage in utilizing our algorithm is dependent on the number of data elements and dimensions of the data array, we have seen a significant performance improvement over operating PARAFAC‐ALS on the full data set. In one case of data comprising hyperspectral images from a confocal microscope, our method of analysis was approximately 60 times faster than operating on the full data set, while obtaining essentially equivalent results. Copyright © 2008 by John Wiley & Sons, Ltd.