Search

It is well established that visual search becomes harder when the similarity between target and distractors is increased and the similarity between distractors is decreased. However, in models of visual search, similarity is typically treated as a static, time-invariant property of the relation between objects. Data from other perceptual tasks (e.g., categorization) demonstrate that similarity is dynamic and changes as perceptual information is accumulated (Lamberts, 1998). In three visual search experiments, the time course of target-distractor similarity effects and distractor-distractor similarity effects was examined. A version of the extended generalized context model (EGCM; Lamberts, 1998) provided a good account of the time course of the observed similarity effects, supporting the notion that similarity in search is dynamic. Modeling also indicated that increasing distractor homogeneity influences both perceptual and decision processes by (respectively) increasing the rate at which stimulus features are processed and enabling strategic weighting of stimulus information. (Contains 9 tables and 11 figures.)

The time course of perception and retrieval of object features was investigated. Participants completed a perceptual matching task and 2 recognition tasks under time pressure. The recognition tasks imposed different retention loads. A stochastic model of feature sampling with a Bayesian decision component was used to estimate the rate of feature perception and the rate of retrieval of feature information. The results demonstrated that retrieval rates did not differ among object features if only a single object was held in memory. If 2 objects were retained in memory, differences among retrieval rates of features emerged, indicating that features that were quickly perceived were also quickly retrieved. The results from the 2-object retention condition are compatible with process reinstatement models of retrieval. (Contains 3 figures, 1 footnote, and 2 tables.)

Due to air quality concerns and stricter carbon targets, surface transport electrification is quickly spreading, posing questions on the impact it will have on national and local electrical networks. This paper proposes an agent-based model to assess the per-minute weekday and weekend impact of the uptake of Electric Vehicles (EVs) over the next decade on local electrical and charging infrastructures, aimed at local decision-makers and stakeholders for transport electrification forecasting purposes. This study compares two scenarios, the first assessing the case where no restrictions are imposed on the daily charging events, and the second scenario where the peak electrical demand period between 5pm and 8.30pm is constrained for charging. Swindon Borough is selected as case study since it has one of UK's highest EV adoption rates and has ambitious aims for decarbonisation. The results show that, over time, scenario two consistently lessened the constraints imposed on the grid by lowering the weekday and weekend peak loads up to 7% and 20%, respectively, and through lowering the usage rate of the charging infrastructure by around 12%. This scenario postponed the 5pm to 8.30pm EV charging demand to later hours, resulting in delayed load waves in residential areas that, over time, took values of higher proportion of the daily peak, forecasted to match it by 2036. However, controlling the EV demand through this strategy became less effective over time, and so, constraining charging between 7am and 2.30pm is suggested for further control. To conclude, this scenario can be portrayed in reality by adding flexibility to the grid, through the use of time-of-use tariffs (TOUTs), hence, if well implemented, postponing the upgrade of the grid and the charging infrastructure, presenting savings to the network operator, charging network stakeholders and EV users. The paper thus highlights the advantages of using a model of a heterogeneous population with fine spatial and temporal detail to provide decision-support to key stakeholders in planning energy transitions. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this paper is to demonstrate the relationships between sustainable building design and occupant well-being. It starts with a definition of sustainable design and well-being, and focuses on the relationships between energy performance and occupant feedback. Methodologically it draws on detailed monitoring and surveys of 12 case study office buildings in the UK and India, and the paper uses the data to explore whether energy use and associated CO2 emissions are correlated to occupant satisfaction and comfort. The results demonstrate that increased energy use in the case study buildings is associated with increased mechanisation (e.g. centralised air conditioning) and reduced occupant control. This reduced control in turn is shown to relate to reduced occupant comfort and satisfaction. Finally, the paper reveals that the reported health conditions of occupants correlates strongly with their levels of satisfaction. The overall conclusion is that energy use in typical office buildings is inversely correlated with the well-being of the occupants: more energy use does not improve well-being. [Copyright &y& Elsevier]

Background: The eHealth Impact Questionnaire (eHIQ) provides a standardized method to measure attitudes of electronic health (eHealth) users toward eHealth. It has previously been validated in a population of eHealth users in the United Kingdom and consists of 2 parts and 5 subscales. Part 1 measures attitudes toward eHealth in general and consists of the subscales attitudes towards online health information (5 items) and attitudes towards sharing health experiences online (6 items). Part 2 measures the attitude toward a particular eHealth application and consists of the subscales confidence and identification (9 items), information and presentation (8 items), and understand and motivation (9 items).Objective: This study aimed to translate and validate the eHIQ in a Dutch population of eHealth users.Methods: The eHIQ was translated and validated in accordance with the COnsensus-based Standards for the selection of health status Measurement INstruments criteria. The validation comprised 3 study samples, with a total of 1287 participants. Structural validity was assessed using confirmatory factor analyses and exploratory factor analyses (EFAs; all 3 samples). Internal consistency was assessed using hierarchical omega (all 3 samples). Test-retest reliability was assessed after 2 weeks, using 2-way intraclass correlation coefficients (sample 1). Measurement error was assessed by calculating the smallest detectable change (sample 1). Convergent and divergent validity were assessed using correlations with the remaining measures (all 3 samples). A graded response model was fit, and item information curves were plotted to describe the information provided by items across item trait levels (all 3 samples).Results: The original factor structure showed a bad fit in all 3 study samples. EFAs showed a good fit for a modified factor structure in the first study sample. This factor structure was subsequently tested in samples 2 and 3 and showed acceptable to good fits. Internal consistency, test-retest reliability, convergent validity, and divergent validity were acceptable to good for both the original as the modified factor structure, except for test-retest reliability of one of the original subscales and the 2 derivative subscales in the modified factor structure. The graded response model showed that some items underperformed in both the original and modified factor structure.Conclusions: The Dutch version of the eHIQ (eHIQ-NL) shows a different factor structure compared with the original English version. Part 1 of the eHIQ-NL consists of 3 subscales: attitudes towards online health information (5 items), comfort with sharing health experiences online (3 items), and usefulness of sharing health experiences online (3 items). Part 2 of the eHIQ-NL consists of 3 subscales: motivation and confidence to act (10 items), information and presentation (13 items), and identification (3 items). [ABSTRACT FROM AUTHOR]

The debate on volunteering has paid insufficient attention to the relationship between public spending and volunteering. The importance of this relationship is highlighted by the British government's 'Big Society' plan, which asserts that an increase in volunteering will compensate for the withdrawal of public agencies and spending. This idea is based on the widely held belief that a high degree of government intervention decreases voluntary activities. This article uses a multidisciplinary approach to improve understanding of how public spending affects the decision to volunteer. A theoretical model conceptualizes this relationship in terms of time donation by employed individuals. The model is tested empirically through an econometric analysis of two survey data sets and interpretative analysis of narratives of local volunteers and public professionals. The results suggest that volunteering is likely to decline when government intervention decreases and that a collaborative approach to sustaining volunteering is needed. [ABSTRACT FROM AUTHOR]