Understanding the socio-economic distribution of multiple deprivation: An application of self-organising maps

In this paper we seek to contribute to recent efforts to develop and implement multi-dimensional approaches to social exclusion by applying self-organising maps (SOMs) to a set of material deprivation indicators from the Irish component of EU-SILC. The first stage of our analysis involves the identification of sixteen clusters that confirm the multi-dimensional nature of deprivation in contemporary Ireland and the limitations of focusing solely on income. In going beyond this mapping stage, we consider both patterns of socio-economic differentiation in relation to cluster membership and the extent to which such membership contributes to our understanding of economic stress. Our analysis makes clear the continuing importance of traditional forms of stratification relating to factors such as income, social class and housing tenure in accounting for patterns of multiple deprivation. However, it also confirms the role of acute life events and life cycle and location influences. Most importantly, it demonstrates that conclusions relating to the relative impact of different kinds of socio-economic influences are highly dependent on the form of deprivation being considered. Our analysis suggests that debates relating to the extent to which poverty and social exclusion have become individualized should take particular care to distinguish between different kinds of outcomes. Further analysis demonstrates that the SOM approach is considerably more successful than a comparable latent class analysis in identifying those exposed to subjective economic stress. (C) 2010 International Sociological Association Research Committee 28 on Social Stratification and Mobility. Published by Elsevier Ltd. All rights reserved.

Mapping patterns of multiple deprivation using self-organising maps: An application to EU-SILC data for Ireland

The development of conceptual frameworks for the analysis of social exclusion has somewhat out-stripped related methodological developments. This paper seeks to contribute to filling this gap through the application of self-organising maps (SOMs) to the analysis of a detailed set of material deprivation indicators relating to the Irish case. The SOM approach allows us to offer a differentiated and interpretable picture of the structure of multiple deprivation in contemporary Ireland. Employing this approach, we identify 16 clusters characterised by distinct profiles across 42 deprivation indicators. Exploratory analyses demonstrate that, controlling for equivalised household income, SOM cluster membership adds substantially to our ability to predict subjective economic stress. Moreover, in comparison with an analogous latent class approach, the SOM analysis offers considerable additional discriminatory power in relation to individuals' experience of their economic circumstances. The results suggest that the SOM approach could prove a valuable addition to a 'methodological platform' for analysing the shape and form of social exclusion. (c) 2009 Elsevier Inc. All rights reserved.

Economic vulnerability, multidimensional deprivation and social cohesion in an enlarged European community

In this article we have sought to combine regional and social exclusion perspectives on economic exclusion in the enlarged European Community. Our analysis, based on the European Quality of Life Survey, confirms that while the economically vulnerable, identified through latent class analysis, constitute substantially larger groups in the poorer economic clusters, they are much more sharply differentiated from others in the richer clusters. While the economically vulnerable are also disadvantaged in relation to measures of multidimensional deprivation and social cohesion, between economic clusters differences on these dimensions cannot be accounted for by corresponding variations in levels and intensity of economic vulnerability. In fact, the impact of such vulnerability on social cohesion is greater in the more affluent clusters. Copyright © 2005 SAGE Publications.

Rapid detection of health-care-associated bloodstream infection in critical care using multipathogen real-time polymerase chain reaction technology: a diagnostic accuracy study and systematic review

Background: There is growing interest in the potential utility of real-time polymerase chain reaction (PCR) in diagnosing bloodstream infection by detecting pathogen deoxyribonucleic acid (DNA) in blood samples within a few hours. SeptiFast (Roche Diagnostics GmBH, Mannheim, Germany) is a multipathogen probe-based system targeting ribosomal DNA sequences of bacteria and fungi. It detects and identifies the commonest pathogens causing bloodstream infection. As background to this study, we report a systematic review of Phase III diagnostic accuracy studies of SeptiFast, which reveals uncertainty about its likely clinical utility based on widespread evidence of deficiencies in study design and reporting with a high risk of bias. 

Objective: Determine the accuracy of SeptiFast real-time PCR for the detection of health-care-associated bloodstream infection, against standard microbiological culture. 

Design: Prospective multicentre Phase III clinical diagnostic accuracy study using the standards for the reporting of diagnostic accuracy studies criteria. 

Setting: Critical care departments within NHS hospitals in the north-west of England. 

Participants: Adult patients requiring blood culture (BC) when developing new signs of systemic inflammation. 

Main outcome measures: SeptiFast real-time PCR results at species/genus level compared with microbiological culture in association with independent adjudication of infection. Metrics of diagnostic accuracy were derived including sensitivity, specificity, likelihood ratios and predictive values, with their 95% confidence intervals (CIs). Latent class analysis was used to explore the diagnostic performance of culture as a reference standard. 

Results: Of 1006 new patient episodes of systemic inflammation in 853 patients, 922 (92%) met the inclusion criteria and provided sufficient information for analysis. Index test assay failure occurred on 69 (7%) occasions. Adult patients had been exposed to a median of 8 days (interquartile range 4–16 days) of hospital care, had high levels of organ support activities and recent antibiotic exposure. SeptiFast real-time PCR, when compared with culture-proven bloodstream infection at species/genus level, had better specificity (85.8%, 95% CI 83.3% to 88.1%) than sensitivity (50%, 95% CI 39.1% to 60.8%). When compared with pooled diagnostic metrics derived from our systematic review, our clinical study revealed lower test accuracy of SeptiFast real-time PCR, mainly as a result of low diagnostic sensitivity. There was a low prevalence of BC-proven pathogens in these patients (9.2%, 95% CI 7.4% to 11.2%) such that the post-test probabilities of both a positive (26.3%, 95% CI 19.8% to 33.7%) and a negative SeptiFast test (5.6%, 95% CI 4.1% to 7.4%) indicate the potential limitations of this technology in the diagnosis of bloodstream infection. However, latent class analysis indicates that BC has a low sensitivity, questioning its relevance as a reference test in this setting. Using this analysis approach, the sensitivity of the SeptiFast test was low but also appeared significantly better than BC. Blood samples identified as positive by either culture or SeptiFast real-time PCR were associated with a high probability (> 95%) of infection, indicating higher diagnostic rule-in utility than was apparent using conventional analyses of diagnostic accuracy. 

Conclusion: SeptiFast real-time PCR on blood samples may have rapid rule-in utility for the diagnosis of health-care-associated bloodstream infection but the lack of sensitivity is a significant limiting factor. Innovations aimed at improved diagnostic sensitivity of real-time PCR in this setting are urgently required. Future work recommendations include technology developments to improve the efficiency of pathogen DNA extraction and the capacity to detect a much broader range of pathogens and drug resistance genes and the application of new statistical approaches able to more reliably assess test performance in situation where the reference standard (e.g. blood culture in the setting of high antimicrobial use) is prone to error.

Multiloop robust H∞ control design based on the dynamic PLS approach to chemical processes

In this paper, a multiloop robust control strategy is proposed based on H∞ control and a partial least squares (PLS) model (H∞_PLS) for multivariable chemical processes. It is developed especially for multivariable systems in ill-conditioned plants and non-square systems. The advantage of PLS is to extract the strongest relationship between the input and the output variables in the reduced space of the latent variable model rather than in the original space of the highly dimensional variables. Without conventional decouplers, the dynamic PLS framework automatically decomposes the MIMO process into multiple single-loop systems in the PLS subspace so that the controller design can be simplified. Since plant/model mismatch is almost inevitable in practical applications, to enhance the robustness of this control system, the controllers based on the H∞ mixed sensitivity problem are designed in the PLS latent subspace. The feasibility and the effectiveness of the proposed approach are illustrated by the simulation results of a distillation column and a mixing tank process. Comparisons between H∞_PLS control and conventional individual control (either H∞ control or PLS control only) are also made

Differential effects of the CCKA receptor ligands PD-140, 548 and A-71623 on latent inhibition in the rat.

Latent inhibition (LI) is a behavioural paradigm in which repeated exposure to a stimulus without consequence inhibits the formation of any new associations with that stimulus. To the extent that LI reflects a process of learning to ignore irrelevant stimuli, disrupted LI has been suggested as an animal model for the attentional deficits observed in schizophrenia. The antipsychotic potential of cholecystokinin (CCK) stems from its colocalization with dopamine (DA) in the mesolimbic pathway, where it demonstrates both excitatory and inhibitory effects on dopaminergic activity. This may be explained by mediation through different receptor subtypes. A variety of hypotheses has emerged regarding the potential clinical application of subtype-selective CCK-based drugs. The present experiments examined the effects on LI of two selective CCKA ligands: PD-140,548 (a CCKA antagonist, Experiment 1: 0.001, 0.01, and 0.1 mg/kg) and A-71623 (a CCKA agonist, Experiment 2: 0.02, 0.05, and 0.1 mg/kg). In both experiments, the effects of haloperidol (0.1 mg/kg) were also investigated. Animals receiving 0.1 mg/kg of haloperidol or 0.001 or 0.1 mg/kg (but not 0.01 mg/kg) of PD-140,548 treated the preexposed stimulus as irrelevant after a low number of preexposures. In contrast, no facilitatory effect on LI was detectable at any of the A-71623 doses. The finding that A-71623 failed to enhance LI indicates that it is unlikely that this compound would have any antipsychotic effect within the clinical setting. Considering the facilitatory effect exerted by PD-140,548 on LI, it is probable that the inhibition of CCK activity might prove a more promising strategy for the pharmacological treatment of schizophrenia.

Effects of amisulpride, risperidone and chlorpromazine on auditory and visual latent inhibition, prepulse inhibition, executive function and eye movements in healthy volunteers.

In view of the evidence that cognitive deficits in schizophrenia are critically important for long-term outcome, it is essential to establish the effects that the various antipsychotic compounds have on cognition, particularly second-generation drugs. This parallel group, placebo-controlled study aimed to compare the effects in healthy volunteers (n = 128) of acute doses of the atypical antipsychotics amisulpride (300 mg) and risperidone (3 mg) to those of chlorpromazine (100 mg) on tests thought relevant to the schizophrenic process: auditory and visual latent inhibition, prepulse inhibition of the acoustic startle response, executive function and eye movements. The drugs tested were not found to affect auditory latent inhibition, prepulse inhibition or executive functioning as measured by the Cambridge Neuropsychological Test Battery and the FAS test of verbal fluency. However, risperidone disrupted and amisulpride showed a trend to disrupt visual latent inhibition. Although amisulpride did not affect eye movements, both risperidone and chlorpromazine decreased peak saccadic velocity and increased antisaccade error rates, which, in the risperidone group, correlated with drug-induced akathisia. It was concluded that single doses of these drugs appear to have little effect on cognition, but may affect eye movement parameters in accordance with the amount of sedation and akathisia they produce. The effect risperidone had on latent inhibition is likely to relate to its serotonergic properties. Furthermore, as the trend for disrupted visual latent inhibition following amisulpride was similar in nature to that which would be expected with amphetamine, it was concluded that its behaviour in this model is consistent with its preferential presynaptic dopamine antagonistic activity in low dose and its efficacy in the negative symptoms of schizophrenia.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Effect of pH, temperature, and moisture on the formation of volatile compounds in glycine/glucose model systems

Mixtures of glycine, glucose, and starch were extrusion cooked using sodium hydroxide at 0, 3, and 6 g/L of extruder water feed, 18% moisture, and 120, 150, and 180 degreesC target die temperatures, giving extrudates with pH values of 5.6, 6.8, and 7.4. Freeze-dried equimolar solutions of glucose and glycine were heated either dry or after equilibration to similar to 13% moisture at 180 degreesC in a reaction-tube system designed to mimic the heating profile in an extruder. Volatile compounds were isolated onto Tenax and analyzed by gas chromatography-mass spectrometry. For the extrudates, total yields of volatiles increased with decreasing pH at 180 degreesC, reached a maximum at pH 6.S at 150 degreesC, and increased with increasing pH at 120 degreesC. Amounts increased with temperature at all pH values. Pyrazines were the most abundant class for all sets of conditions (54-79% of total volatiles). Pyrroles, ketones, furans, oxazoles, and pyridines were also identified. Yields of volatiles from the reaction-tube samples increased by > 60% in the moist system. Levels of individual classes also increased in the presence of moisture, except pyrazines, which decreased similar to3.5-fold. Twenty-one of the compounds were common to the reaction-tube samples and the extrudates.