284 research outputs found

    The effect of category variability in perceptual categorization

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    Exemplar and distributional accounts of categorization make differing predictions for the classification of a critical exemplar precisely halfway between the nearest exemplars of 2 categories differing in variability. Under standard conditions of sequential presentation, the critical exemplar was classified into the most similar, least variable category, consistent with an exemplar account. However, if the difference in variability is made more salient, then the same exemplar is classified into the more variable, most likely category, consistent with a distributional account. This suggests that participants may be strategic in their use of either strategy. However, when the relative variability of 2 categories was manipulated, participants showed changes in the classification of intermediate exemplars that neither approach could account for

    Teenager: Thirteen

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    pages 52-5

    Duets

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    pages 54-5

    Decision by sampling

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    We present a theory of decision by sampling (DbS) in which, in contrast with traditional models, there are no underlying psychoeconomic scales. Instead, we assume that an attribute’s subjective value is constructed from a series of binary, ordinal comparisons to a sample of attribute values drawn from memory and is its rank within the sample. We assume that the sample reflects both the immediate distribution of attribute values from the current decision’s context and also the background, real-world distribution of attribute values. DbS accounts for concave utility functions; losses looming larger than gains; hyperbolic temporal discounting; and the overestimation of small probabilities and the underestimation of large probabilities

    Estimating Dengue Transmission Intensity from Case-Notification Data from Multiple Countries

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    Despite being the most widely distributed mosquito-borne viral infection, estimates of dengue transmission intensity and associated burden remain ambiguous. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing the burden of disease and the likely impact of interventions.We estimated the force of infection (λ) and corresponding basic reproduction numbers (R0) by fitting catalytic models to age-stratified incidence data identified from the literature. We compared estimates derived from incidence and seroprevalence data and assessed the level of under-reporting of dengue disease. In addition, we estimated the relative contribution of primary to quaternary infections to the observed burden of dengue disease incidence. The majority of R0 estimates ranged from one to five and the force of infection estimates from incidence data were consistent with those previously estimated from seroprevalence data. The baseline reporting rate (or the probability of detecting a secondary infection) was generally low (<25%) and varied within and between countries.As expected, estimates varied widely across and within countries, highlighting the spatio-temporally heterogeneous nature of dengue transmission. Although seroprevalence data provide the maximum information, the incidence models presented in this paper provide a method for estimating dengue transmission intensity from age-stratified incidence data, which will be an important consideration in areas where seroprevalence data are not available

    Estimating Dengue Transmission Intensity from Sero-Prevalence Surveys in Multiple Countries

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    BACKGROUND:Estimates of dengue transmission intensity remain ambiguous. Since the majority of infections are asymptomatic, surveillance systems substantially underestimate true rates of infection. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing both the burden of disease from dengue and the likely impact of interventions. METHODOLOGY/PRINCIPAL FINDINGS:The force of infection (λ) and corresponding basic reproduction numbers (R0) for dengue were estimated from non-serotype (IgG) and serotype-specific (PRNT) age-stratified seroprevalence surveys identified from the literature. The majority of R0 estimates ranged from 1-4. Assuming that two heterologous infections result in complete immunity produced up to two-fold higher estimates of R0 than when tertiary and quaternary infections were included. λ estimated from IgG data were comparable to the sum of serotype-specific forces of infection derived from PRNT data, particularly when inter-serotype interactions were allowed for. CONCLUSIONS/SIGNIFICANCE:Our analysis highlights the highly heterogeneous nature of dengue transmission. How underlying assumptions about serotype interactions and immunity affect the relationship between the force of infection and R0 will have implications for control planning. While PRNT data provides the maximum information, our study shows that even the much cheaper ELISA-based assays would provide comparable baseline estimates of overall transmission intensity which will be an important consideration in resource-constrained settings

    Communications Biophysics

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    Contains research objectives and summary of research on thirteen research projects split into four section.National Institutes of Health (Grant 1 RO1 NS10737-01)National Institutes of Health (Grant 1 ROI NS10916-01)National Institutes of Health (Grant 5 RO1 NS11000-02)National Institutes of Health (Grant 1 RO1 NS11153-01)Harvard M.I.T. Rehabilitation Engineering CenterU. S. Department of Health, Education, and Welfare, Grant 23-P-55854National Institutes of Health (Grant 1 RO1 NS11680-01)Norlin Music, Inc.Clarence J. LeBel FundNational Institutes of Health (Grant 1 RO1 NS11080-01A1)National Institutes of Health (Grant 5 TO1 GM01555-08)M.I.T. Health Sciences FundBoston City Hospital Purchase Order 1176-05-21335-C

    Communications Biophysics

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    Contains research objectives, summary of research and reports on three research projects.National Institutes of Health (Grant 5 PO1 GM14940-06)National Institutes of Health (Grant 2 TOl GM01555-06)National Institutes of Health (Grant 1 ROl NS10737-01)National Aeronautics and Space Administration (Grant NGL 22-009-304)Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U. S. Air Force) under Contract DAAB07-71-C-0300B-D Electrodyne Division, Becton Dickinson and Company (Grant)Boston City Hospital Purchase Order 1176-21-33
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