Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating

Do incoming residents vary in measures of emotional status even prior to residency training?

Objectives: To determine whether Empathy, Emotional Intelligence, and Burnout scores differ by specialty in incoming residents. Methods: This is a single-site, prospective, cross-sectional study. Three validated survey instruments, the Jefferson Scale of Physician Empathy, Maslach Burnout Inventory, and Emotional and Social Competency Inventory, were written into a survey platform as a single 125-question Qualtrics survey. Over three academic years, 2015-2017, 229 incoming residents across all specialties were emailed the survey link during orientation. Residents were grouped by incoming specialty with anonymity assured. A total of 229 responses were included, with 121 (52.8%) identifying as female. Statistical analysis was performed using the Analysis of Variance or Kruskal-Wallis test, Chi-Square or Fisher\u27s Exact test, and Independent Samples t-test or Mann Whitney U test. A Bonferroni correction was applied for pairwise comparisons. Results: Family Medicine had a higher median Jefferson Scale of Physician Empathy score (127) compared to Emergency Medicine (115), (U=767.7, p=0.0330). Maslach Burnout Inventory depersonalization and personal accomplishment subcategory scores showed a significant difference between specialties when omnibus tests were performed, but pairwise comparisons with emergency medicine residents showed no differences. Differences were found in the Maslach Burnout Inventory categories of Depersonalization (χ Conclusions: Differences in measures of well-being exist across specialties, even prior to the start of residency training. The implication for educators of residency training is that some incoming residents, regardless of specialty, already exhibit troublesome features of burnout, and resources to effectively deal with these residents should be developed and utilized

Stochastic population growth in spatially heterogeneous environments

Classical ecological theory predicts that environmental stochasticity increases extinction risk by reducing the average per-capita growth rate of populations. To understand the interactive effects of environmental stochasticity, spatial heterogeneity, and dispersal on population growth, we study the following model for population abundances in $n$ patches: the conditional law of $X_{t+dt}$ given $X_t=x$ is such that when $dt$ is small the conditional mean of $X_{t+dt}^i-X_t^i$ is approximately $[x^i\mu_i+\sum_j(x^j D_{ji}-x^i D_{ij})]dt$, where $X_t^i$ and $\mu_i$ are the abundance and per capita growth rate in the $i$-th patch respectivly, and $D_{ij}$ is the dispersal rate from the $i$-th to the $j$-th patch, and the conditional covariance of $X_{t+dt}^i-X_t^i$ and $X_{t+dt}^j-X_t^j$ is approximately $x^i x^j \sigma_{ij}dt$. We show for such a spatially extended population that if $S_t=(X_t^1+...+X_t^n)$ is the total population abundance, then $Y_t=X_t/S_t$, the vector of patch proportions, converges in law to a random vector $Y_\infty$ as $t\to\infty$, and the stochastic growth rate $\lim_{t\to\infty}t^{-1}\log S_t$ equals the space-time average per-capita growth rate \sum_i\mu_i\E[Y_\infty^i] experienced by the population minus half of the space-time average temporal variation \E[\sum_{i,j}\sigma_{ij}Y_\infty^i Y_\infty^j] experienced by the population. We derive analytic results for the law of $Y_\infty$, find which choice of the dispersal mechanism $D$ produces an optimal stochastic growth rate for a freely dispersing population, and investigate the effect on the stochastic growth rate of constraints on dispersal rates. Our results provide fundamental insights into "ideal free" movement in the face of uncertainty, the persistence of coupled sink populations, the evolution of dispersal rates, and the single large or several small (SLOSS) debate in conservation biology.Comment: 47 pages, 4 figure

The MACHO Project Large Magellanic Cloud Variable Star Inventory. VIII. The Recent Star Formation History of the LMC from the Cepheid Period Distribution

We present an analysis of the period distribution of $\sim 1800$ Cepheids in the Large Magellanic Cloud, based on data obtained by the MACHO microlensing experiment and on a previous catalogue by Payne-Gaposchkin. Using stellar evolution and pulsation models, we construct theoretical period-frequency distributions that are compared to the observations. These models reveal that a significant burst of star formation has occurred recently in the LMC ($\sim 1.15\times 10^8$ years). We also show that during the last $\sim 10^8$ years, the main center of star formation has been propagating from SE to NW along the bar. We find that the evolutionary masses of Cepheids are still smaller than pulsation masses by $\sim 7$ % and that the red edge of the Cepheid instability strip could be slightly bluer than indicated by theory. There are $\sim 600$ Cepheids with periods below $\sim 2.5$ days cannot be explained by evolution theory. We suggest that they are anomalous Cepheids; a number of these stars are double-mode Cepheids

Primordial Black Holes: sirens of the early Universe

Primordial Black Holes (PBHs) are, typically light, black holes which can form in the early Universe. There are a number of formation mechanisms, including the collapse of large density perturbations, cosmic string loops and bubble collisions. The number of PBHs formed is tightly constrained by the consequences of their evaporation and their lensing and dynamical effects. Therefore PBHs are a powerful probe of the physics of the early Universe, in particular models of inflation. They are also a potential cold dark matter candidate.Comment: 21 pages. To be published in "Quantum Aspects of Black Holes", ed. X. Calmet (Springer, 2014

Spatial regularity of InAs-GaAs quantum dots: quantifying the dependence of lateral ordering on growth rate.

The lateral ordering of arrays of self-assembled InAs-GaAs quantum dots (QDs) has been quantified as a function of growth rate, using the Hopkins-Skellam index (HSI). Coherent QD arrays have a spatial distribution which is neither random nor ordered, but intermediate. The lateral ordering improves as the growth rate is increased and can be explained by more spatially regular nucleation as the QD density increases. By contrast, large and irregular 3D islands are distributed randomly on the surface. This is consistent with a random selection of the mature QDs relaxing by dislocation nucleation at a later stage in the growth, independently of each QD's surroundings. In addition we explore the statistical variability of the HSI as a function of the number N of spatial points analysed, and we recommend N > 10(3) to reliably distinguish random from ordered arrays

Biotic resistance to invasion along an estuarine gradient

Biotic resistance is the ability of native communities to repel the establishment of invasive species. Predation by native species may confer biotic resistance to communities, but the environmental context under which this form of biotic resistance occurs is not well understood. We evaluated several factors that influence the distribution of invasive Asian mussels (Musculista senhousia) in Mission Bay, a southern California estuary containing an extensive eelgrass (Zostera marina) habitat. Asian mussels exhibit a distinct spatial pattern of invasion, with extremely high densities towards the back of Mission Bay (up to 4,000 m−2) in contrast with near-complete absence at sites towards the front of the bay. We established that recruits arrived at sites where adult mussels were absent and found that dense eelgrass does not appear to preclude Asian mussel growth and survival. Mussel survival and growth were high in predator-exclusion plots throughout the bay, but mussel survival was low in the front of the bay when plots were open to predators. Additional experiments revealed that consumption by spiny lobsters (Panulirus interruptus) and a gastropod (Pteropurpura festiva) likely are the primary factors responsible for resistance to Asian mussel invasion. However, biotic resistance was dependent on location within the estuary (for both species) and also on the availability of a hard substratum (for P. festiva). Our findings indicate that biotic resistance in the form of predation may be conferred by higher order predators, but that the strength of resistance may strongly vary across estuarine gradients and depend on the nature of the locally available habitat

Comparing angular and curved shapes in terms of implicit associations and approach/avoidance responses.

Most people prefer smoothly curved shapes over more angular shapes. We investigated the origin of this effect using abstract shapes and implicit measures of semantic association and preference. In Experiment 1 we used a multidimensional Implicit Association Test (IAT) to verify the strength of the association of curved and angular polygons with danger (safe vs. danger words), valence (positive vs. negative words) and gender (female vs. male names). Results showed that curved polygons were associated with safe and positive concepts and with female names, whereas angular polygons were associated with danger and negative concepts and with male names. Experiment 2 used a different implicit measure, which avoided any need to categorise the stimuli. Using a revised version of the Stimulus Response Compatibility (SRC) task we tested with a stick figure (i.e., the manikin) approach and avoidance reactions to curved and angular polygons. We found that RTs for approaching vs. avoiding angular polygons did not differ, even in the condition where the angles were more pronounced. By contrast participants were faster and more accurate when moving the manikin towards curved shapes. Experiment 2 suggests that preference for curvature cannot derive entirely from an association of angles with threat. We conclude that smoothly curved contours make these abstract shapes more pleasant. Further studies are needed to clarify the nature of such a preference

Hyperon Photoproduction in the Nucleon Resonance Region

Cross-sections and recoil polarizations for the reactions gamma + p --> K^+ + Lambda and gamma + p --> K^+ + Sigma^0 have been measured with high statistics and with good angular coverage for center-of-mass energies between 1.6 and 2.3 GeV. In the K^+Lambda channel we confirm a structure near W=1.9 GeV at backward kaon angles, but our data shows a more complex s- and u- channel resonance structure than previously seen. This structure is present at forward and backward angles but not central angles, and its position and width change with angle, indicating that more than one resonance is playing a role. Rising back-angle cross sections at higher energies and large positive polarization at backward angles are consistent with sizable s- or u-channel contributions. None of the model calculations we present can consistently explain these aspects of the data.Comment: 5 pages, 3 figures, submitted to Physical Review Letter