Proton nuclear magnetic resonance (1H NMR) spectroscopic analysis of mixtures has been used extensively for a variety of applications ranging from the analysis of plant extracts, wine, and food to the evaluation of toxicity in animals. For example, NMR analysis of urine samples has been used extensively for biomarker discovery and, more simply, for the construction of classification models of toxicity, disease, and biochemical phenotype. However, NMR spectra of complex mixtures typically show unwanted local peak shifts caused by matrix and instrument variability, which must be compensated for prior to statistical analysis and interpretation of the data. One approach is to align the spectral peaks across the data set. An efficient and fast warping algorithm is required as the signals typically contain ca. 32,000-64,000 data points and there can be several thousand spectra in a data set. As demonstrated in our study, the iterative fuzzy warping algorithm fulfills these requirements and can be used on-line for an alignment of the NMR spectra. Correlation coefficients between the aligned and target spectra are used as the evaluation function for the algorithm, and its performance is compared with those of other published warping methods.

An increasing emphasis is being placed on more effective ways of identifying and developing future managers, administrators and executives. The in‐tray (in‐basket) exercise, which simulates or samples the typical contents of an executive's in‐tray and is dealt with by assessees under standardized conditions, may have a significant contribution to make. The major research findings with the technique are reviewed in relation to the assumptions on which its utility depends. These concern face validity, content validity, concurrent and predictive validity, procedures for assessment of in‐tray performance and the empirical determination of assessment criteria. Experimental data suggesting high relative face validity in graduate recruitment and adequate inter‐rater reliability in senior executive promotion procedures are reported. Its utility in relation to the concept of achievement‐versus‐aptitude, to trainability testing and to equal opportunity at work is suggested, and avenues for future research are indicated. Finally a brief review is given of the extent of the use of the technique by organizations and its strengths, advantages and possible further applications.

Employer of choice (EOC) is an evolving interest for Australian business, as organizations look to attract and retain desirable staff and maintain a positive reputation in the marketplace. EOC reflects the value and importance organizations place on their key stakeholders—their staff. This article defines EOC in a context reflecting Australian business conditions and demonstrates how to use an existing information and communication technology (ICT) platform, typically available to office‐based staff in large institutions, to educate and engage with employees about their organization's EOC program.Characteristics common to “good employers” as presented by global research houses and consultancy groups are matched against standard characteristics evident from a review of Australian documentation on EOC, in order to provide the most appropriate EOC characteristics for Australian organizations.This article conceptualizes a model curriculum to educate large office‐based staff on their organization's EOC program using computer‐assisted learning (CAL). The model embraces constructivists' principles and adult learning pedagogy that enables individually tailored education. The belief is that an engaged and satisfied staff will enhance an organization's reputation and decrease the risk of staff loss. © 2010 Wiley Periodicals, Inc.

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