Modelling data from single-photon emission computerized tomography

The completely random character of radioactive disintegration provides the basis of a strong justification for a Poisson linear model for single-photon emission computed tomography data, which can be used to produce reconstructions of isotope densities, whether by maximum likelihood or Bayesian methods. However, such a model requires the construction of a matrix of weights, which represent the mean rates of arrival at each detector of photons originating from each point within the body space. Two methods of constructing these weights are discussed, and reconstructions resulting from phantom and real data are presented.     

Dose‐Response Models Incorporating Aerosol Size Dependency for Francisella tularensis

The effect of bioaerosol size was incorporated into predictive dose‐response models for the effects of inhaled aerosols of Francisella tularensis (the causative agent of tularemia) on rhesus monkeys and guinea pigs with bioaerosol diameters ranging between 1.0 and 24 μm. Aerosol‐size‐dependent models were formulated as modification of the exponential and β‐Poisson dose‐response models and model parameters were estimated using maximum likelihood methods and multiple data sets of quantal dose‐response data for which aerosol sizes of inhaled doses were known. Analysis of F. tularensis dose‐response data was best fit by an exponential dose‐response model with a power function including the particle diameter size substituting for the rate parameter k scaling the applied dose. There were differences in the pathogen's aerosol‐size‐dependence equation and models that better represent the observed dose‐response results than the estimate derived from applying the model developed by the International Commission on Radiological Protection (ICRP, 1994) that relies on differential regional lung deposition for human particle exposure.     

Binary probability maps using a hidden conditional autoregressive Gaussian process with an application to Finnish common toad data

The Finnish common toad data of Heikkinen and Hogmander are reanalysed using an alternative fully Bayesian model that does not require a pseudolikelihood approximation and an alternative prior distribution for the true presence or absence status of toads in each 10 km×10 km square. Markov chain Monte Carlo methods are used to obtain posterior probability estimates of the square-specific presences of the common toad and these are presented as a map. The results are different from those of Heikkinen and Hogmander and we offer an explanation in terms of the prior used for square-specific presence of the toads. We suggest that our approach is more faithful to the data and avoids unnecessary confounding of effects. We demonstrate how to extend our model efficiently with square-specific covariates and illustrate this by introducing deterministic spatial changes.     

Infant Contingency/Extinction Performance After Observing Partial Reinforcement

Social information gathering by infants 6 and 12 months old was examined as a foundation for later social learning that may be uniquely human. Infant performance on a contingency/extinction task was studied following a caregiver demonstration of the contingency on varied reinforcement schedules. Infants who observed caregivers receive any reinforcing stimulation in pretraining decreased responding over their own acquisition period, possibly because they began to habituate to the reinforcer. In extinction, infants who observed caregivers receive partial reinforcement in pretraining were more persistent in responding than others. This suggested that direct experience with partial reinforcement is not needed for greater persistence in extinction. These studies revealed details of social learning in the 1st year.     

Development of a Dose‐Response Model for SARS Coronavirus

In order to develop a dose‐response model for SARS coronavirus (SARS‐CoV), the pooled data sets for infection of transgenic mice susceptible to SARS‐CoV and infection of mice with murine hepatitis virus strain 1, which may be a clinically relevant model of SARS, were fit to beta‐Poisson and exponential models with the maximum likelihood method. The exponential model (k= 4.1 × l0²) could describe the dose‐response relationship of the pooled data sets. The beta‐Poisson model did not provide a statistically significant improvement in fit. With the exponential model, the infectivity of SARS‐CoV was calculated and compared with those of other coronaviruses. The does of SARS‐CoV corresponding to 10% and 50% responses (illness) were estimated at 43 and 280 PFU, respectively. Its estimated infectivity was comparable to that of HCoV‐229E, known as an agent of human common cold, and also similar to those of some animal coronaviruses belonging to the same genetic group. Moreover, the exponential model was applied to the analysis of the epidemiological data of SARS outbreak that occurred at an apartment complex in Hong Kong in 2003. The estimated dose of SARS‐CoV for apartment residents during the outbreak, which was back‐calculated from the reported number of cases, ranged from 16 to 160 PFU/person, depending on the floor. The exponential model developed here is the sole dose‐response model for SARS‐CoV at the present and would enable us to understand the possibility for reemergence of SARS.     

A Test of Symbolic Interactionist Predictions About Emotions in Imagined Situations

From the perspective of symbolic interactionism, inner experiences—including emotions—are shaped culturally as individuals formulate events in words, and individual experiences are shaped socially as others contribute to the verbal formulation of one's experiences. Understanding cultural shaping and social negotiation of emotions requires understanding how emotion attributions arise from linguistic framings of events, and Affect Control Theory (ACT) offers a model of emotions that addresses this issue. We report tests of ACT predictions of emotions in 128 events against self-reported emotions of respondents imagining themselves in such situations. ACT predictions are found to correlate with self-reported emotions. Thus, empirical results validate ACT's postulate that emotions emerge from the personal impression that is generated in an event, along with the difference between that impression and the person's identity. In the conclusion, we discuss how the ACT formulation can enlighten interpretations of social negotiations regarding emotions.     

CEO Age and Top Executive Pay: A UK Empirical Study

This study examines the implications that CEO age has onexecutive pay regarding data collected in a UK setting. Whereprior research has typically focused on total pay (salary plusbonus), this study offers a more complete conceptual model bysplitting pay into salary, annual bonus, and share options. Indoing so, we found that the relationship between CEO salaries andage are significantly related with this association weakeningover time. Another interesting finding not captured by priorresearch was that the relationship between CEO age and bonusappears to be non-linear in nature. Figures 2 which depicts thisnon-linear function suggest at about age 53, the proportion ofbonus as a percentage of salary begins to decrease at anincreasing rate. As a whole, these findings suggest corporate paycommittees should consider family and the financial circumstancesof the executive when designing remuneration schemes.     

Modelling data from single-photon emission computerized tomography

The completely random character of radioactive disintegration provides the basis of a strong justification for a Poisson linear model for single-photon emission computed tomography data, which can be used to produce reconstructions of isotope densities, whether by maximum likelihood or Bayesian methods. However, such a model requires the construction of a matrix of weights, which represent the mean rates of arrival at each detector of photons originating from each point within the body space. Two methods of constructing these weights are discussed, and reconstructions resulting from phantom and real data are presented.