Morbidity and pollution: model specification analysis for time-series data on hospital admissions

Time-series analysis of effects of pollutants on emergency hospital admissions indicates important synergistic interactions among pollutants and to a lesser degree nonlinearities in effects of single pollutants. Comparisons of alternative econometric specifications are made to determine the appropriateness of incorporating nonuniform pollution impacts. The data substantially support the existence of synergisms among pollutants with high levels of sulfur dioxide, SO, (particulates), increasing the impact of particulates (SO,) on emergency hospital admissions. Marginal effects of either pollutant are, however, small at current ambient air quality levels. These results indicate that damage estimates were likely to be understated during the 1960’s when pollution levels were high, while, at current levels of those pollutants considered here, marginal damages are lower than would be estimated in studies failing to incorporate synergistic and nonlinear impacts.time series; hospital admissions; pollution and human health; synergisms; nonlinearities; econometric model specification

Effects of Hydrology on the Growth and Recruitment of Stream Fish in the Eastern Broadleaf Province of Minnesota

Agricultural practices and urban development have altered streamflows within the Eastern Broadleaf Province of Minnesota. Stream-flow alteration can produce significant changes in native freshwater communities. Therefore, knowledge of streamflow effects on representative freshwater populations and communities within the province are needed to maintain ecological integrity. Fish community and population dynamics often display predictable responses to flow regimes, which can make fishes model organisms for examining flow-ecology relationships. In lotic systems, annual variation in streamflow can influence the annual growth and recruitment of fishes. Understanding the growth and recruitment of fish populations is essential for management and conservation efforts. Growth can affect population size structure and sexual maturation, while recruitment can affect the abundance, and genetic diversity of a population. Recruitment was quantified using studentized residuals from weighted catch-curve regressions as a measure of year-class strength. Relationships between annual streamflow magnitude and variability and the recruitment of the three species of interest were identified according to species-specific traits. I quantified the growth of Smallmouth Bass Micropterus dolomieu, Rock Bass Ambloplites rupestris, and Northern Hogsucker Hypentelium nigricans populations with mixed-effects growth models. Data from streams exhibiting growth-year effects were used to examine relationships between summer-high-flow duration and annual fish growth. Little evidence was found for either long-term or short-term flow effects on recruitment during the adult spawning or juvenile rearing periods. The recruitment of nest-building and benthic-lithophilous fishes was not significantly related to long-term-spawning-period flow magnitude for the majority (i.e., 10 of 14) of streams, and was not significantly related to short-term-spawning-period flow magnitude at any of the 14 streams. Recruitment of fishes exhibiting cruiser, maneuverer, and benthic-hugger locomotion morphologies was not significantly related to long-term-rearing-period flow variability for the majority (i.e., 12 of 14) of streams, and was not related to short-term-rearing-period flow variability for any of the 14 streams. Growth was attributed to age and individual fish effects for 11 of the 28 fish populations among species. Most populations that exhibited growth-year effects among streams did not show a significant relationship between growth and the duration of summer-high flows (i.e., 4 of 11 populations). Temperature regimes, as well as the timing, magnitude, and frequency of flows may have contributed to differences in the annual recruitment and growth of fishes among some of the streams in this study. However, minimal growth-year effects observed at the majority of my streams suggest that biotic factors (e.g., fish age, genetic differences) may play a large role in determining the growth rates of fishes within the streams studied

Optimal Geo-Indistinguishable Mechanisms for Location Privacy

We consider the geo-indistinguishability approach to location privacy, and the trade-off with respect to utility. We show that, given a desired degree of geo-indistinguishability, it is possible to construct a mechanism that minimizes the service quality loss, using linear programming techniques. In addition we show that, under certain conditions, such mechanism also provides optimal privacy in the sense of Shokri et al. Furthermore, we propose a method to reduce the number of constraints of the linear program from cubic to quadratic, maintaining the privacy guarantees and without affecting significantly the utility of the generated mechanism. This reduces considerably the time required to solve the linear program, thus enlarging significantly the location sets for which the optimal mechanisms can be computed.Comment: 13 page

Towards interpretable quantum machine learning via single-photon quantum walks

Variational quantum algorithms represent a promising approach to quantum machine learning where classical neural networks are replaced by parametrized quantum circuits. However, both approaches suffer from a clear limitation, that is a lack of interpretability. Here, we present a variational method to quantize projective simulation (PS), a reinforcement learning model aimed at interpretable artificial intelligence. Decision making in PS is modeled as a random walk on a graph describing the agent's memory. To implement the quantized model, we consider quantum walks of single photons in a lattice of tunable Mach-Zehnder interferometers trained via variational algorithms. Using an example from transfer learning, we show that the quantized PS model can exploit quantum interference to acquire capabilities beyond those of its classical counterpart. Finally, we discuss the role of quantum interference for training and tracing the decision making process, paving the way for realizations of interpretable quantum learning agents.Comment: 11+8 pages, 6+9 figures, 2 tables. F. Flamini and M. Krumm contributed equally to this wor