Reducing Disparities by way of a Cancer Disparities Research Training Program

Background: For minority populations, there is a continuing disparity in the burden of death and illness from cancer. Research to address this disparity should be conducted by investigators who can best understand and address the needs of culturally diverse communities. However, minorities are under-represented in health-related research. The goal of this project was to develop and evaluate an approach to motivating and preparing master’s degree students for careers dedicated to cancer disparities research. Method: A Cancer Disparities Research Training Program (CDRTP) was initiated in 2010. The program consists of coursework, practicum experiences, and research opportunities. Assessment of the curriculum is based on monitoring achievement of evaluation indicators and includes a quantitative assessment and qualitative approach. Results: In its first three years, the program graduated 20 trainees, all of whom were minorities (18 African Americans and two Asians). When asked about career goals, two-thirds of the trainees indicated interest in pursuing careers in research on cancer prevention and control. The trainees expressed high satisfaction with the courses, instructor, materials, and curriculum. Although trainees had suggestions about course details, evaluations overall were positive. Across focus groups, three recurrent themes emerged regarding activities to enhance the student experience: having a wider variety of topics, more guest speakers, and field trips. Conclusion: The CDRTP was intended to recruit students – primarily African Americans – into research on prevention and control of cancer disparities. Although final evaluation of the program’s overall outcome will not be available for several years, a preliminary evaluation indicates the program is being successful

Chewing gum and impasse-induced self-reported stress

An insoluble anagram task (Zellner et al., 2006) was used to investigate the proposition that chewing gum reduces self-rated stress (Scholey et al., 2009). Using a between-participants design, forty participants performed an insoluble anagram task followed by a soluble anagram task. These tasks were performed with or without chewing gum. Self-rated measures were taken at baseline, post-stressor, and post-recovery task. The insoluble anagram task was found to amplify stress in terms of increases in self-rated stress and reductions in both self-rated calmness and contentedness. However, chewing gum was found not to mediate the level of stress experienced. Furthermore, chewing gum did not result in superior performance on the soluble anagram task. The present study fails to generalise the findings of Scholey et al. to an impasse induced stress that has social components. The explanation for the discrepancy with Scholey et al. is unclear; however, it is suggested that the impossibility of the insoluble anagram task may negate any secondary stress reducing benefits arising from chewing gum-induced task improvement

Bayesian Analysis of Instrumental Variable Models: Acceptance-Rejection within Direct Monte Carlo

We discuss Bayesian inferential procedures within the family of instrumental variables regression models and focus on two issues: existence conditions for posterior moments of the parameters of interest under a flat prior and the potential of Direct Monte Carlo (DMC) approaches for efficient evaluation of such possibly highly non-elliptical posteriors. We show that, for the general case of m endogenous variables under a flat prior, posterior moments of order r exist for the coefficients reflecting the endogenous regressors' effect on the dependent variable, if the number of instruments is greater than m +r, even though there is an issue of local non-identification that causes non-elliptical shapes of the posterior. This stresses the need for efficient Monte Carlo integration methods. We introduce an extension of DMC that incorporates an acceptance-rejection sampling step within DMC. This Acceptance-Rejection within Direct Monte Carlo (ARDMC) method has the attractive property that the generated random drawings are independent, which greatly helps the fast convergence of simulation results, and which facilitates the evaluation of the numerical accuracy. The speed of ARDMC can be easily further improved by making use of parallelized computation using multiple core machines or computer clusters. We note that ARDMC is an analogue to the well-known "Metropolis-Hastings within Gibbs" sampling in the sense that one 'more difficult' step is used within an 'easier' simulation method. We compare the ARDMC approach with the Gibbs sampler using simulated data and two empirical data sets, involving the settler mortality instrument of Acemoglu et al. (2001) and father's education's instrument used by Hoogerheide et al. (2012a). Even without making use of parallelized computation, an efficiency gain is observed both under strong and weak instruments, where the gain can be enormous in the latter case

A revised asteroid polarization-albedo relationship using WISE/NEOWISE data

We present a reanalysis of the relationship between asteroid albedo and polarization properties using the albedos derived from the Wide-field Infrared Survey Explorer. We find that the function that best describes this relation is a three-dimensional linear fit in the space of log(albedo)-log(polarization slope)-log(minimum polarization). When projected to two dimensions the parameters of the fit are consistent with those found in previous work. We also define p* as the quantity of maximal polarization variation when compared with albedo and present the best fitting albedo-p* relation. Some asteroid taxonomic types stand out in this three-dimensional space, notably the E, B, and M Tholen types, while others cluster in clumps coincident with the S- and C-complex bodies. We note that both low albedo and small (D<30 km) asteroids are under-represented in the polarimetric sample, and we encourage future polarimetric surveys to focus on these bodies.Comment: 16 pages, Accepted to Ap

Dynamic modeling of mean-reverting spreads for statistical arbitrage

Statistical arbitrage strategies, such as pairs trading and its generalizations, rely on the construction of mean-reverting spreads enjoying a certain degree of predictability. Gaussian linear state-space processes have recently been proposed as a model for such spreads under the assumption that the observed process is a noisy realization of some hidden states. Real-time estimation of the unobserved spread process can reveal temporary market inefficiencies which can then be exploited to generate excess returns. Building on previous work, we embrace the state-space framework for modeling spread processes and extend this methodology along three different directions. First, we introduce time-dependency in the model parameters, which allows for quick adaptation to changes in the data generating process. Second, we provide an on-line estimation algorithm that can be constantly run in real-time. Being computationally fast, the algorithm is particularly suitable for building aggressive trading strategies based on high-frequency data and may be used as a monitoring device for mean-reversion. Finally, our framework naturally provides informative uncertainty measures of all the estimated parameters. Experimental results based on Monte Carlo simulations and historical equity data are discussed, including a co-integration relationship involving two exchange-traded funds.Comment: 34 pages, 6 figures. Submitte

Main Belt Asteroids with WISE/NEOWISE I: Preliminary Albedos and Diameters

We present initial results from the Wide-field Infrared Survey Explorer (WISE), a four-band all-sky thermal infrared survey that produces data well suited to measuring the physical properties of asteroids, and the NEOWISE enhancement to the WISE mission allowing for detailed study of Solar system objects. Using a NEATM thermal model fitting routine we compute diameters for over 100,000 Main Belt asteroids from their IR thermal flux, with errors better than 10%. We then incorporate literature values of visible measurements (in the form of the H absolute magnitude) to determine albedos. Using these data we investigate the albedo and diameter distributions of the Main Belt. As observed previously, we find a change in the average albedo when comparing the inner, middle, and outer portions of the Main Belt. We also confirm that the albedo distribution of each region is strongly bimodal. We observe groupings of objects with similar albedos in regions of the Main Belt associated with dynamical breakup families. Asteroid families typically show a characteristic albedo for all members, but there are notable exceptions to this. This paper is the first look at the Main Belt asteroids in the WISE data, and only represents the preliminary, observed raw size and albedo distributions for the populations considered. These distributions are subject to survey biases inherent to the NEOWISE dataset and cannot yet be interpreted as describing the true populations; the debiased size and albedo distributions will be the subject of the next paper in this series.Comment: Accepted to ApJ. Online table to also appear on the publisher's websit

Assimilation of healthy and indulgent impressions from labelling influences fullness but not intake or sensory experience

Background: Recent evidence suggests that products believed to be healthy may be over-consumed relative to believed indulgent or highly caloric products. The extent to which these effects relate to expectations from labelling, oral experience or assimilation of expectations is unclear. Over two experiments, we tested the hypotheses that healthy and indulgent information could be assimilated by oral experience of beverages and influence sensory evaluation, expected satiety, satiation and subsequent appetite. Additionally, we explored how expectation-experience congruency influenced these factors. Results: Results supported some assimilation of healthiness and indulgent ratings—study 1 showed that indulgent ratings enhanced by the indulgent label persisted post-tasting, and this resulted in increased fullness ratings. In study 2, congruency of healthy labels and oral experience promoted enhanced healthiness ratings. These healthiness and indulgent beliefs did not influence sensory analysis or intake—these were dictated by the products themselves. Healthy labels, but not experience, were associated with decreased expected satiety. Conclusions: Overall labels generated expectations, and some assimilation where there were congruencies between expectation and experience, but oral experience tended to override initial expectations to determine ultimate sensory evaluations and intake. Familiarity with the sensory properties of the test beverages may have resulted in the use of prior knowledge, rather than the label information, to guide evaluations and behaviour