Traffic gap judgment in people with significant peripheral field loss.

PURPOSE: Subjects with significant peripheral field loss (PFL) self report difficulty in street crossing. In this study, we compared the traffic gap judgment ability of fully sighted and PFL subjects to determine whether accuracy in identifying crossable gaps was adversely affected because of field loss. Moreover, we explored the contribution of visual and nonvisual factors to traffic gap judgment ability. METHODS: Eight subjects with significant PFL as a result of advanced retinitis pigmentosa or glaucoma with binocular visual field <20 degrees and five age-matched normals (NV) were recruited. All subjects were required to judge when they perceived it was safe to cross at a 2-way 4-lane street while they stood on the curb. Eye movements were recorded by an eye tracker as the subjects performed the decision task. Movies of the eye-on-scene were made offline and fixation patterns were classified into either relevant or irrelevant. Subjects' street-crossing behavior, habitual approach to street crossing, and perceived difficulties were assessed. RESULTS: Compared with normal vision (NV) subjects, the PFL subjects identified 12% fewer crossable gaps while making 23% more errors by identifying a gap as crossable when it was too short (p < 0.05). The differences in traffic gap judgment ability of the PFL subjects might be explained by the significantly smaller fixation area (p = 0.006) and fewer fixations distributed to the relevant tasks (p = 0.001). The subjects' habitual approach to street crossing and perceived difficulties in street crossing (r > 0.60) were significantly correlated with traffic gap judgment performance. CONCLUSIONS: As a consequence of significant field loss, limited visual information about the traffic environment can be acquired, resulting in significantly reduced performance in judging safe crossable gaps. This poor traffic gap judgment ability in the PFL subjects raises important concerns for their safety when attempting to cross the street.

Explaining the relationship between ingroup identification and intergroup bias following recategorization: A self-regulation theory analysis

We tested the hypothesis that regulation of discrepancies between perceived actual and ideal differentiation between the ingroup and outgroup could help to explain the relationship between ingroup identification and intergroup bias when participants are recategorized into a superordinate group. Replicating previous findings, we found that following recategorization, identification was positively related to intergroup bias. No such differences emerged in a control condition. However, we also, in the recategorization condition only, observed a positive association between ingroup identification and the perceived discrepancy between actual and ideal degree of differentiation from the outgroup: at higher levels of identification, participants increasingly perceived the ingroup to be less differentiated from the outgroup than they would ideally like. This tendency mediated the relationship between identification and bias. We discuss the theoretical, methodological and practical implications of these findings.

Explaining Social Class Inequalities in Smoking: The Role of Education, Self-Efficacy, and Deprivation

Rates of smoking have decreased dramatically in most Northern European countries over the last 50 years or so, but manual working class groups are substantially more likely to smoke daily than are the professional and managerial classes. This article examines three hypotheses about the processes producing these inequalities. The first argues that social class inequalities reflect differences across education groups in knowledge of the risks of smoking. The second suggests that the living conditions of lower social class groups leads to the development of lower self-efficacy and a lower propensity to quit smoking. The third states that smoking has a functional use among poorer individuals. This article draws upon data from the Republic of Ireland to assess these hypotheses. Our analysis provides some support for the first hypothesis in that education independently reduces the odds of a manual class person smoking relative to a non-manual by 12 per cent. The second hypothesis is not supported by the data. The third hypothesis gains the most support: measures of disadvantage and deprivation account for almost one-third of the class differential in smoking. The results suggest that smoking cessation policy should reflect the importance of social and economic context in quitting behaviour.

Explaining binge drinking among adolescent males using the Theory of Planned Behaviour

Binge drinking among adolescents in Northern Ireland is prevalent and has detrimental eff ects on public health. Health education interventions, based on valid explanatory models of health behaviour, are required to reduce binge drinking behaviour among adolescents. " is paper examines the utility of the " eory of Planned Behaviour in explaining binge drinking behaviour among adolescent males. Using questionnaire responses from 94 adolescent boys attending secondary schools in the Belfast area, logistic regression modelling suggested that the " eory of Planned Behaviour explained 36% of the variance in self-reported binge drinking behaviour. Attitudes towards binge drinking were the strongest predictor of binge drinking behaviour. Tackling attitudes about binge drinking is a challenge to be considered when designing interventions to reduce binge drinking among this population

Indoor and Outdoor monitoring of photocatalytic activity using a mobile phone app. and a photocatalytic activity indicator ink (paii)

A resazurin (Rz) based photocatalyst activity indicator ink (paii) is used to test the activity of commercial self-cleaning materials. The semiconductor photocatalyst driven colour change of the ink is monitored indoors and outside using a simple mobile phone application that measures the RGB colour components of the digital image of the paii-covered, irradiated sample in real time. The results correlate directly with those generated using a traditional, lab-bound method of analysis (UV–vis spectrophotometry).

Towards a Mobile Assistive Technology for Monitoring and Assessing Cognitive Fatigue in Individuals with Acquired Brain Injury

Those living with an acquired brain injury often have issues with fatigue due to factors resulting from the injury. Cognitive impairments such as lack of memory, concentration and planning have a great impact on an individual’s ability to carry out general everyday tasks, which subsequently has the effect of inducing cognitive fatigue. Moreover, there is difficulty in assessing cognitive fatigue, as there are no real biological markers that can be measured. Rather, it is a very subjective effect that can only be diagnosed by the individual. Consequently, the traditional way of assessing cognitive fatigue is to use a self-assessment questionnaire that is able to determine contributing factors. State of the art methods to evaluate cognitive! fa tigue employ cognitive tests in order to analyse performance on predefined tasks. However, one primary issue with such tests is that they are typically carried out in a clinical environment, therefore do not have the ability to be utilized in situ within everyday life. This paper presents a smartphone application for the evaluation of fatigue, which can be used daily to track cognitive performance in order to assess the influence of fatigue.

Explaining the Coexistence of Large-scale and Small-scale Magnetic Fields in Fully Convective Stars

Despite the lack of a shear-rich tachocline region, low-mass fully convective (FC) stars are capable of generating strong magnetic fields, indicating that a dynamo mechanism fundamentally different from the solar dynamo is at work in these objects. We present a self-consistent three-dimensional model of magnetic field generation in low-mass FC stars. The model utilizes the anelastic magnetohydrodynamic equations to simulate compressible convection in a rotating sphere. A distributed dynamo working in the model spontaneously produces a dipole-dominated surface magnetic field of the observed strength. The interaction of this field with the turbulent convection in outer layers shreds it, producing small-scale fields that carry most of the magnetic flux. The Zeeman–Doppler-Imaging technique applied to synthetic spectropolarimetric data based on our model recovers most of the large-scale field. Our model simultaneously reproduces the morphology and magnitude of the large-scale field as well as the magnitude of the small-scale field observed on low-mass FC stars.