Dispersion and uncertainty in multislit matter wave diffraction

We show that single and multislit experiments involving matter waves may be constructed to assess dispersively generated correlations between the position and momentum of a single free particle. These correlations give rise to position dependent phases which develop dynamically as a result of dispersion and may play an important role in the interference patterns. To the extent that initial transverse coherence is preserved throughout the proposed diffraction setup, such interference patterns are noticeably different from those of a classical dispersion free wave. (c) 2007 Published by Elsevier B.V.

Purity and entanglement of two-photon polarization states generated by spontaneous parametric down-conversion

We elucidate the dependence of purity and entanglement of two-photon states generated by spontaneous parametric down-conversion on the parameters of the source, such as crystal length, pump beam divergence, frequency bandwidth, and detectors angular aperture. The effect of crystal anisotropy is taken into account. Numerical simulations are presented for two types of commonly used source configurations. (C) 2009 Elsevier B.V. All rights reserved.

A non-parametric vessel detection method for complex vascular structures

Modern medical imaging techniques enable the acquisition of in vivo high resolution images of the vascular system. Most common methods for the detection of vessels in these images, such as multiscale Hessian-based operators and matched filters, rely on the assumption that at each voxel there is a single cylinder. Such an assumption is clearly violated at the multitude of branching points that are easily observed in all, but the Most focused vascular image studies. In this paper, we propose a novel method for detecting vessels in medical images that relaxes this single cylinder assumption. We directly exploit local neighborhood intensities and extract characteristics of the local intensity profile (in a spherical polar coordinate system) which we term as the polar neighborhood intensity profile. We present a new method to capture the common properties shared by polar neighborhood intensity profiles for all the types of vascular points belonging to the vascular system. The new method enables us to detect vessels even near complex extreme points, including branching points. Our method demonstrates improved performance over standard methods on both 2D synthetic images and 3D animal and clinical vascular images, particularly close to vessel branching regions. (C) 2008 Elsevier B.V. All rights reserved.

Estimation of Parameters in Random Effect Models with Incidence Matrix Uncertainty

Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.

Likelihood prediction for generalized linear mixed models under covariate uncertainty

This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

Linking environmental uncertainty to non-financial performance measures and performance : a research note

Several previous research studies have reported mixed results concerning the direct association between non-financial performance measures and  performance. The presence of environmental uncertainty on this relationship has not been established. This paper makes a contribution to this area by proposing that it is in conditions of environmental uncertainty that non-financial measures are most useful in improving organizational performance. It analyses empirical data from a sample of New Zealand manufacturing organizations to test the hypothesis that non-financial measures of performance would lead to improved organizational performance under conditions of increased environmental uncertainty. Multiple regression analysis of the data suggests that performance should be a declining function of the size of the ‘mismatch’ between an organization's environment and use of the different combinations of non-financial performance measures. Further, the paper concludes that prior mixed results may be attributed to the omission of environmental uncertainty.

The knowledge economy and innovation: certain uncertainty and the risk economy

The knowledge economy is a dominant force in today's world, and innovation policy and national systems of innovation are central to it. In this article, we draw on different sociological and economic theories of risk to engage critically with innovation policy and national systems of innovation. Beck's understanding of a risk society, Schumpeter's innovation thesis, and Perez's techno-economic paradigm are used to consider the risk economy, and the broader risk implications of knowledge economy policies and their associated innovation systems. Derrida's theory of haunting provides the methodological framework for our discussion. We use his notion of “hauntology” to conceptualize the risk economy as a ghost that haunts knowledge economy policies and systems. The spectral risk economy draws attention to the inherent instability of the knowledge economy, and challenges the certainty of its economic dogma by offering an alternative perspective. The risk economy problematizes knowledge economy policies and systems by revealing the uncertain and “undecidable” future of social, political and cultural hazards ignored in the interest of commercial gain.

An effective non-parametric method for globally clustering genes from expression profiles

Clustering is widely used in bioinformatics to find gene correlation patterns. Although many algorithms have been proposed, these are usually confronted with difficulties in meeting the requirements of both automation and high quality. In this paper, we propose a novel algorithm for clustering genes from their expression profiles. The unique features of the proposed algorithm are twofold: it takes into consideration global, rather than local, gene correlation information in clustering processes; and it incorporates clustering quality measurement into the clustering processes to implement non-parametric, automatic and global optimal gene clustering. The evaluation on simulated and real gene data sets demonstrates the effectiveness of the algorithm.

Interrogating the discourse of 'social literacies' in an era of uncertainty

Originally, the term 'social literacies' was used to suggest the skills, knowledge and processes for addressing multicultural teaching and learning (Kalantzis and Cope, 1983). The meaning of the phrase has since evolved to encompass widely different concepts, including for example, social 'competencies', and/or citizenship education (eg., Arthur & Davison, 2000). Clearly the discourse around 'social literacies' is shifting in response to changing educational policies, both nationally and internationally.

In this paper, we examine how constructs of 'social literacies' have been and might be deployed. Building from a review of the policy, program and theoretical literature, we pose questions concerning how 'social literacies' might be used to interrogate and rework relations, especially those of gender and culture. Questions to be considered include: will the concept of 'social literacies' enable us to better understand the processes of identity and community formations in this era of uncertainty? Which knowledges and skills are identified in the literature and positioned as critical in establishing 'productive' social relations/literacies? Additionally, we begin to theorise the degree to which such constructions of 'social literacies' might enhance and/or limit quality learning at the tertiary levels of teacher education.

Parametric conditional frailty models for recurrent cardiovascular events in the lipid study

Background Analysis of recurrent event data is frequently needed in clinical and epidemiological studies. An important issue in such analysis is how to account for the dependence of the events in an individual and any unobserved heterogeneity of the event propensity across individuals.Methods We applied a number of conditional frailty and nonfrailty models in an analysis involving recurrent myocardial infarction events in the Long-Term Intervention with Pravastatin in Ischaemic Disease study. A multiple variable risk prediction model was developed for both males and females. Results A Weibull model with a gamma frailty term fitted the data better than other frailty models for each gender. Among nonfrailty models the stratified survival model fitted the data best for each gender. The relative risk estimated by the elapsed time model was close to that estimated by the gap time model. We found that a cholesterol-lowering drug, pravastatin (the intervention being tested in the trial) had significant protective effect against the occurrence of myocardial infarction in men (HR¼0.71, 95% CI0.60–0.83). However, the treatment effect was not significant in women due to smaller sample size (HR¼0.75, 95% CI 0.51–1.10). There were no significant interactions between the treatment effect and each recurrent MI event (p¼0.24 for men and p¼0.55 for women). The risk of developing an MI event for a male who had an MI event during follow-up was about 3.4 (95% CI 2.6–4.4) times the risk compared with those who did not have an MI event. The corresponding relative risk for a female was about 7.8 (95% CI 4.4–13.6). Limitations The number of female patients was relatively small compared with their male counterparts, which may result in low statistical power to find real differences in the effect of treatment and other potential risk factors.Conclusions The conditional frailty model suggested that after accounting for all the risk factors in the model, there was still unmeasured heterogeneity of the risk for myocardial infarction, indicating the effect of subject-specific risk factors. These risk prediction models can be used to classify cardiovascular disease patients into different risk categories and may be useful for the most effective targeting of preventive therapies for cardiovascular disease.

Parametric modelling and the tessellation of architectural surfaces

Parametric modelling is gaining in popularity as both a fabrication and design tool, but its application in the architectural design industry has not been widely explored. This form of modelling has the ability to generate complex forms with intuitively reactive components, allowing designers to express and
fabricate structures previously too laborious and geometrically complex to realise. The key aim of the paper is to address the increasing need for seamless and bi-directional connectivity between the design, modelling and
fabrication ambit.

Educational organizations and gender in times of uncertainty

In this chapter I identify and elaborate, from a feminist perspective, upon the theoretical shifts and key concepts that inform sociological analyses of gender and educational organizations. Gender inequalities are embedded in the multi-dimensional structure of relationships between women and men, which, as the modern sociology of gender shows, operates at every level of experience, from economic arrangements, culture and the state to interpersonal relationships and individual emotions. (Connell, 2005: 1801) Even naming this a sociology of gender and organizations is problematic. Many sociologists consider gender as a key sociological concept, but not necessarily from a feminist perspective. Feminism is a multidisciplinary, transnational movement that 'focuses on the relationship between social movements, political action and social inequalities' (Arnot, 2002: 3) and on the everyday experiences of women and girls and how they translate into social and structural 'ruling relations' (Smith, 1988). Feminism takes on multiple trajectories and imperatives in different cultural contexts, although with familial resemblances, most particularly the shared objective of equality for women and girls. Education as a primary institution of individual and collective mobility and social change, but also social and economic reproduction, has long been a focus of feminist theory and activism. So a feminist sociology needs to address this complexity of feminist sociological 'encounters' with gender and organizations.

A simple parametric method for reducing sample sizes in gut passage time trials

Seed dispersal is now regularly analyzed using spatially explicit models, relying in part on frugivore gut passage times to produce model outputs. In determining species-specific gut passage times, there is a trade-off in sample size between minimizing collection effort and maintaining statistical reliability. Here we demonstrate that a two-parameter lognormal parametric distribution reliably fits empirical gut passage time distributions and is easily parameterized using relatively small data sets of approximately 30 defecations. We suggest this approach as a statistically reliable substitute for larger empirical gut passage data sets in seed dispersal modeling, and also as a way of using published gut passage data sets to parameterize new models.