Social Class Variation in Risk: A Comparative Analysis of the Dynamics of Economic Vulnerability

A joint concern with multidimensionality and dynamics is a defining feature of the pervasive use of the terminology of social exclusion in the European Union. The notion of social exclusion focuses attention on economic vulnerability in the sense of exposure to risk and uncertainty. Sociological concern with these issues has been associated with the thesis that risk and uncertainty have become more pervasive and extend substantially beyond the working class. This paper combines features of recent approaches to statistical modelling of poverty dynamics and multidimensional deprivation in order to develop our understanding of the dynamics of economic vulnerability. An analysis involving nine countries and covering the first five waves of the European Community Household Panel shows that, across nations and time, it is possible to identify an economically vulnerable class. This class is characterized by heightened risk of falling below a critical resource level, exposure to material deprivation and experience of subjective economic stress. Cross-national differentials in persistence of vulnerability are wider than in the case of income poverty and less affected by measurement error. Economic vulnerability profiles vary across welfare regimes in a manner broadly consistent with our expectations. Variation in the impact of social class within and across countries provides no support for the argument that its role in structuring such risk has become much less important. Our findings suggest that it is possible to accept the importance of the emergence of new forms of social risk and acknowledge the significance of efforts to develop welfare states policies involving a shift of opportunities and decision making on to individuals without accepting the 'death of social class' thesis.

Web Services and Incerta Spiriti: A Game Theoretic Approach to Uncertainty

A web-service is a remote computational facility which is made available for general use by means of the internet. An orchestration is a multi-threaded computation which invokes remote services. In this paper game theory is used to analyse the behaviour of orchestration evaluations when underlying web-services are unreliable. Uncertainty profiles are proposed as a means of defining bounds on the number of service failures that can be expected during an orchestration evaluation. An uncertainty profile describes a strategic situation that can be analyzed using a zero-sum angel-daemon game with two competing players: an angel a whose objective is to minimize damage to an orchestration and a daemon d who acts in a destructive fashion. An uncertainty profile is assessed using the value of its angel daemon game. It is shown that uncertainty profiles form a partial order which is monotonic with respect to assessment.

A Corpus-Based Approach to Speech Enhancement from Nonstationary Noise

Temporal dynamics and speaker characteristics are two important features of speech that distinguish speech from noise. In this paper, we propose a method to maximally extract these two features of speech for speech enhancement. We demonstrate that this can reduce the requirement for prior information about the noise, which can be difficult to estimate for fast-varying noise. Given noisy speech, the new approach estimates clean speech by recognizing long segments of the clean speech as whole units. In the recognition, clean speech sentences, taken from a speech corpus, are used as examples. Matching segments are identified between the noisy sentence and the corpus sentences. The estimate is formed by using the longest matching segments found in the corpus sentences. Longer speech segments as whole units contain more distinct dynamics and richer speaker characteristics, and can be identified more accurately from noise than shorter speech segments. Therefore, estimation based on the longest recognized segments increases the noise immunity and hence the estimation accuracy. The new approach consists of a statistical model to represent up to sentence-long temporal dynamics in the corpus speech, and an algorithm to identify the longest matching segments between the noisy sentence and the corpus sentences. The algorithm is made more robust to noise uncertainty by introducing missing-feature based noise compensation into the corpus sentences. Experiments have been conducted on the TIMIT database for speech enhancement from various types of nonstationary noise including song, music, and crosstalk speech. The new approach has shown improved performance over conventional enhancement algorithms in both objective and subjective evaluations.

Harnessing the power of personality assessment:Subjective assessment predicts behaviour in horses

Objective assessment of animal personality is typically time consuming, requiring the repeated measure of behavioural responses. By contrast, subjective assessment of personality allows information to be collected quickly by experienced caregivers. However, subjective assessment must predict behaviour to be valid. Comparisons of subjective assessments and behaviour have been made but often with methodological weaknesses and thus, limited success. Here we test the validity of a subjective assessment against a battery of behaviour tests in 146 horses (Equus caballus). Our first aim was to determine if subjective personality assessment could predict behaviour during behaviour testing. We made specific a priori predictions for how subjectively measured personality should relate to behaviour testing. We found that Extroversion predicted time to complete a handling test and refusal behaviour during this test. It also predicted minimum distance to a novel object. Neuroticism predicted how reactive an individual was to a sudden visual stimulus but not how quickly it recovered from this. Agreeableness did not predict any behaviour during testing. There were several unpredicted correlations between subjective measures and behaviour tests which we explore further. Our second aim was to combine data from the subjective assessment and behaviour tests to gain a more comprehensive understanding of personality. We found that the combination of methods provides new insights into horse behaviour. Furthermore, our data are consistent with the idea of horses showing different coping styles, a novel finding for this species. © 2013 Elsevier B.V.

Autoecological Approaches to Resolve Subjective Taxonomic Divisions within Arcellacea

Arcellacea (testate lobose amoebae) are important lacustrine environmental indicators that have been used in paleoclimatic reconstructions, assessing the effectiveness of mine tailings pond reclamation projects and for studying the effects of land use change in rural, industrial and urban settings. Recognition of ecophenotypically significant infra-specific ‘strains’ within arcellacean assemblages has the potential to enhance the utility of the group in characterizing contemporary and paleoenvironments. We present a novel approach which employs statistical tools to investigate the environmental and taxonomic significance of proposed strains. We test this approach on two identified strains: Difflugia protaeiformis Lamarck strain ‘acuminata’ (DPA), characterized by fine grained agglutination, and Difflugia protaeiformis Lamarck strain ‘claviformis’ (DPC), characterized by coarse grained agglutination. Redundancy analysis indicated that both organisms are associated with similar environmental variables. No relationship was observed between substrate particle size and abundance of DPC, indicating that DPC has a size preference for xenosomes during test construction. Thus DPC should not be designated as a distinct strain but rather form a species complex with DPA. This study elucidates the need to justify the designation of strains based on their autecology in addition to morphological stability.

Understanding of BRCA1/2 genetic tests results:the importance of objective and subjective numeracy

Background: The majority of women (71%) who undergo BRCA1/2 testing—designed to identify genetic mutations associated with increased risk of cancer—receive results that are termed ‘ambiguous’ or ‘uninformative negative’. How women interpret these results and the association with numerical ability was examined. Methods: In this study, 477 women at increased risk for breast and ovarian cancer were recruited via the Cancer Genetics Network. They were presented with information about the four different possible BRCA1/2 test results—positive, true negative, ambiguous and uninformative negative—and asked to indicate which of six options represents the best response. Participants were then asked which treatment options they thought a woman receiving the results should discuss with her doctor. Finally, participants completed measures of objective and subjective numeracy. Results: Almost all of the participants correctly interpreted the positive and negative BRCA1/2 genetic test results. However, they encountered difficulties interpreting the uninformative and ambiguous BRCA1/2 genetic test results. Participants were almost equally likely to think either that the woman had learned nothing from the test result or that she was as likely to develop cancer as the average woman. Highly numerate participants were more likely to correctly interpret inconclusive test results (ambiguous, OR = 1.62; 95% CI [1.28, 2.07]; p < 0.001; uninformative, OR = 1.40; 95% CI [1.10, 1.80]). Discussion: Given the medical and psychological ramifications of genetic testing, healthcare professionals should consider devoting extra effort to ensuring proper comprehension of ambiguous and uninformative negative test results by women. Copyright © 2014 John Wiley & Sons, Ltd.

Analysis of Transonic Limit Cycle Oscillations under Uncertainty

For the computation of limit cycle oscillations (LCO) at transonic speeds, CFD is required to capture the nonlinear flow features present. The Harmonic Balance method provides an effective means for the computation of LCOs and this paper exploits its efficiency to investigate the impact of variability (both structural a nd aerodynamic) on the aeroelastic behaviour of a 2 dof aerofoil. A Harmonic Balance inviscid CFD solver is coupled with the structural equations and is validated against time marching analyses. Polynomial chaos expansions are employed for the stochastic investiga tion as a faster alternative to Monte Carlo analysis. Adaptive sampling is employed when discontinuities are present. Uncertainties in aerodynamic parameters are looked at first followed by the inclusion of structural variability. Results show the nonlinear effect of Mach number and it’s interaction with the structural parameters on supercritical LCOs. The bifurcation boundaries are well captured by the polynomial chaos.

An Extended Event Reasoning Framework for Decision Support under Uncertainty

To provide in-time reactions to a large volume of surveil- lance data, uncertainty-enabled event reasoning frameworks for CCTV and sensor based intelligent surveillance system have been integrated to model and infer events of interest. However, most of the existing works do not consider decision making under uncertainty which is important for surveillance operators. In this paper, we extend an event reasoning framework for decision support, which enables our framework to predict, rank and alarm threats from multiple heterogeneous sources.