Model reductions for inference: generality of pairwise, binary, and planar factor graphs.

We offer a solution to the problem of efficiently translating algorithms between different types of discrete statistical model. We investigate the expressive power of three classes of model-those with binary variables, with pairwise factors, and with planar topology-as well as their four intersections. We formalize a notion of "simple reduction" for the problem of inferring marginal probabilities and consider whether it is possible to "simply reduce" marginal inference from general discrete factor graphs to factor graphs in each of these seven subclasses. We characterize the reducibility of each class, showing in particular that the class of binary pairwise factor graphs is able to simply reduce only positive models. We also exhibit a continuous "spectral reduction" based on polynomial interpolation, which overcomes this limitation. Experiments assess the performance of standard approximate inference algorithms on the outputs of our reductions.

Primary antibody deficiency and diagnostic delay.

AIMS: To assess the occurrence of diagnostic delay in primary antibody deficiency in the period 1989-2002, since a similar study in 1989, and to assess the impact of UK national guidelines communicated in 1995. METHODS: A retrospective case note review was performed of 89 consecutive patients with antibody deficiency referred to a regional referral centre for clinical immunology in north west England and north Wales. The delay in diagnosis and the estimated resulting morbidity in terms of infections were assessed. RESULTS: Fifty six of the 89 patients experienced delay in diagnosis. The overall median delay was 2 years (mean, 4.4), resulting in substantial morbidity (equivalent to two major infections and one minor infection). This shows a moderate improvement since the previous study in 1989 and since the introduction of UK national guidelines in 1995. Respiratory infections are the most frequent presenting infections, and respiratory physicians the most common source of referral. CONCLUSIONS: There is still considerable delay in the diagnosis of primary antibody deficiency, but the data suggest an improvement in practice since the previous study in 1989 and the distribution of national guidelines in 1995.

Measurement of filling-factor-dependent magnetophonon resonances in graphene using Raman spectroscopy

We perform polarization-resolved Raman spectroscopy on graphene in magnetic fields up to 45 T. This reveals a filling-factor-dependent, multicomponent anticrossing structure of the Raman G peak, resulting from magnetophonon resonances between magnetoexcitons and E2g phonons. This is explained with a model of Raman scattering taking into account the effects of spatially inhomogeneous carrier densities and strain. Random fluctuations of strain-induced pseudomagnetic fields lead to increased scattering intensity inside the anticrossing gap, consistent with the experiments. © 2013 American Physical Society.

2.1 GHz MOS mixer linearisation approach for IIP2 enhancement using multiple factor compensation

An integrated downconversion CMOS mixer incorporating a comprehensive compensation scheme is presented which aims to minimise second-order intermodulation distortion (IMD2). Unlike previously reported IMD2 calibration schemes which tune only one nonlinear factor at a time, the presented solution allows simultaneous adjustment of several different factors thus achieving a better compensation. The mixer has been implemented in UMC 0.18 μm CMOS to verify the proposed scheme and for comparison with alternative compensation methods. Measurements show that the solution described can improve the input intercept point (IIP2) by over 20 dB while maintaining good amplification and noise performance. IMD2 calibration results are presented and show useful advantages over other approaches. To the best of the authors' knowledge, this scheme for IMD2 calibration has not been previously reported. © The Institution of Engineering and Technology 2013.

Factor analysis and structural equation modelling of sustainable behaviour in contaminated land remediation

Contaminated land remediation has traditionally been viewed as sustainable practice because it reduces urban sprawl and mitigates risks to human being and the environment. However, in an emerging green and sustainable remediation (GSR) movement, remediation practitioners have increasingly recognized that remediation operations have their own environmental footprint. The GSR calls for sustainable behaviour in the remediation industry, for which a series of white papers and guidance documents have been published by various government agencies and professional organizations. However, the relationship between the adoption of such sustainable behaviour and its underlying driving forces has not been studied. This study aims to contribute to sustainability science by rendering a better understanding of what drives organizational behaviour in adopting sustainable practices. Factor analysis (FA) and structural equation modelling (SEM) were used to investigate the relationship between sustainable practices and key factors driving these behaviour changes in the remediation field. A conceptual model on sustainability in the environmental remediation industry was developed on the basis of stakeholder and institutional theories. The FA classified sustainability considerations, institutional promoting and impeding forces, and stakeholder's influence. Subsequently the SEM showed that institutional promoting forces had significant positive effects on adopting sustainability measures, and institutional impeding forces had significant negative effects. Stakeholder influences were found to have only marginal direct effect on the adoption of sustainability; however, they exert significant influence on institutional promoting forces, thus rendering high total effect (i.e. direct effect plus indirect effect) on the adoption of sustainability. This study suggests that sustainable remediation represents an advanced sustainable practice, which may only be fully endorsed by both internal and external stakeholders after its regulatory, normative and cognitive components are institutionalized. © 2014 Elsevier Ltd. All rights reserved.