Learning to Use Illumination Gradients as an Unambiguous Cue to Three Dimensional Shape

The luminance and colour gradients across an image are the result of complex interactions between object shape, material and illumination. Using such variations to infer object shape or surface colour is therefore a difficult problem for the visual system. We know that changes to the shape of an object can affect its perceived colour, and that shading gradients confer a sense of shape. Here we investigate if the visual system is able to effectively utilise these gradients as a cue to shape perception, even when additional cues are not available. We tested shape perception of a folded card object that contained illumination gradients in the form of shading and more subtle effects such as inter-reflections. Our results suggest that observers are able to use the gradients to make consistent shape judgements. In order to do this, observers must be given the opportunity to learn suitable assumptions about the lighting and scene. Using a variety of different training conditions, we demonstrate that learning can occur quickly and requires only coarse information. We also establish that learning does not deliver a trivial mapping between gradient and shape; rather learning leads to the acquisition of assumptions about lighting and scene parameters that subsequently allow for gradients to be used as a shape cue. The perceived shape is shown to be consistent for convex and concave versions of the object that exhibit very different shading, and also similar to that delivered by outline, a largely unrelated cue to shape. Overall our results indicate that, although gradients are less reliable than some other cues, the relationship between gradients and shape can be quickly assessed and the gradients therefore used effectively as a visual shape cue

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

BACKGROUND: In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO) or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. METHODS: Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC) between predictions and mean observations, and the root mean squared error of predictions at the individual level. RESULTS: Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99). Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. CONCLUSIONS: Modeling health-state valuations based on ordinal ranks can provide results that are similar to those obtained from more widely analyzed valuation techniques such as the TTO. The information content in aggregate ranking data is not currently exploited to full advantage. The possibility of estimating cardinal valuations from ordinal ranks could also simplify future data collection dramatically and facilitate wider empirical study of health-state valuations in diverse settings and population groups

The association of socio-economic position across the life course and age at menopause: the British Women's Heart and Health Study.

OBJECTIVE: To assess the association of indicators of adverse socio-economic position from across the life course with age at menopause. DESIGN: Cross sectional study as part of the British Women's Heart and Health Study. SETTING: 23 British towns. POPULATION: Three thousand and five hundred and thirteen women aged 60-79 years from a total cohort of 4286. Women who underwent a hysterectomy or oophorectomy prior to their 'natural' menopause or who were taking hormone replacement therapy around the perimenopausal period and for whom a biological age at menopause could not be calculated were excluded from this study. MAIN OUTCOME MEASURES: Age at menopause. RESULTS: Most of the 10 indicators of adverse socio-economic position from childhood through to adulthood were linearly associated with a younger age at menopause. In age adjusted analyses, women from manual social classes in childhood began their menopause on average 0.68 years (95% confidence interval [CI] 0.11, 1.3) earlier than those from non-manual social classes. Those who lived in a house as a child without a bathroom began their menopause 0.47 years (95% CI 0.12, 0.82) earlier than those with a bathroom. Those who shared a bedroom began 0.36 years (95% CI 0.03, 0.70) earlier than those who had their own bedroom and finally those who lived in a household with no access to a car as a child began their menopause 0.47 years (95% CI 0.02, 0.95) earlier than those with access to a car. Adult indicators of adverse socio-economic position were similarly associated with earlier age at menopause. Age at completing full time education was not substantively associated with age at menopause. The inverse associations between each of the indicators of both childhood and adult socio-economic position and age at menopause were not importantly affected by adjustment for other reproductive factors but they attenuated by between 6% and 21% with adjustment for adult smoking and body mass index. The inverse associations between each of the childhood indicators of socio-economic position only and age at menopause attenuated markedly (between 12% and 70%) with adjustment for adult leg length. There was a cumulative effect of disadvantage across the life course demonstrated by a strong linear trend between a composite score of the 10 socio-economic indicators and young age at menopause. The age at onset of menopause for women who had 9 or 10 adverse socio-economic indicators was on average 1.70 years (95% CI 0.36, 3.0) younger than that of women with none or only one indicator. CONCLUSIONS: Adverse socio-economic circumstances in childhood, as well as in adulthood, are associated with an earlier age at menopause. The association between childhood deprivation and early menopause may at least in part be mediated via exposures, such as childhood diet, which affect both linear growth and age at menopause