a connectionist architecture and learning algorithm for sequential decision learning are presented. The architecture provides representations for probabilities and utilities. The learning algorithm provides a mechanism to learn from longterm rewards/utilities while observing information available locally in time. The mechanism is based on gradient ascent on the current estimate of the long-term reward in the weight spju^e defined by a "policy" network. The learning principle can be seen as a generalization of previous methods proposed to implement "policy iteration" mechanisms with connectionist networks. The algorithm is simulated for an "agent" moving in an environment described as a simple one-dimensional random walk. Results show the agent discovers optimal moving strategies in simple caises and learns how to avoid short-term suboptimal rewards in order to maximize long-term rewards in more complex cases.

A connectionist architecture is proposed and provides representations for probabilities and utilities, the basic elements of formal decision making theories. The outputs of standard feed forward feature-extraction networks then become inputs to this decision making network. A formalism shows how the gradient of expected utility can be hack propagated through the decision making network "down" to the feature extraction network. The formalism can be adapted to algorithms which optimize total or minimum expected utility. Utilities can be either given or estimated during learning. When utility estimation and decision making behavior adapt simultaneously, learning dynamics show properties contrasted to "puzzhng" observations made in experimental situations with human subjects. The results illustrate the interest in computational properties emerging out of the integration of elements of decision making formalisms and connectionist learning modeb.

Abstract: Research Summary: We examine to what extent and when multiunit firms internally redeploy managers between units. While theory has emphasized how changes in demand conditions affect redeployment, we argue that optimal internal resource allocation involves consideration of both demand and each unit's resource supply. We formalize this argument, showing how redeployment arises from “supply‐side inducements”—return advantages in new over existing resource uses resulting from changes in resource supply. Empirical tests using manager deaths as an exogenous, supply‐side shock to firms' resource stocks support our arguments, showing that firms frequently redeploy resources away from better‐endowed and toward negatively affected units. Incorporating supply‐side inducements into redeployment theory implies additional value‐creation opportunities from redeployment and carries novel predictions for the direction of intra‐firm resource flows. Managerial Summary: Firms continuously decide how to allocate valuable resources—such as their most productive workers, unique inputs, or machinery—among different units. We argue that to optimally allocate such resources, managers must respond to changes in both the demand environment and in the resource stock of different units. When some units successfully accumulate resources while others suffer adverse shocks, opportunity exists to improve efficiency by internally redeploying resources. Counterintuitively, optimal redeployment frequently involves shifting resources away from successful, well‐endowed units. New business units, being resource‐poor, are often the most important recipients of resources. Empirical analyses studying how firms allocate managers in a large sample of Brazilian firms offer support for these arguments.

Background

Heat and air pollution are both associated with increases in mortality. However, the interactive effect of temperature and air pollution on mortality remains unsettled. Similarly, the relationship between air pollution, air temperature, and social deprivation has never been explored.

Methods

We used daily mortality data from 2004 to 2009, daily mean temperature variables and relative humidity, for Paris, France. Estimates of chronic exposure to air pollution and social deprivation at a small spatial scale were calculated and split into three strata. We developed a stratified Poisson regression models to assess daily temperature and mortality associations, and tested the heterogeneity of the regression coefficients of the different strata. Deaths due to ambient temperature were calculated from attributable fractions and mortality rates were estimated.

Results

We found that chronic air pollution exposure and social deprivation are effect modifiers of the association between daily temperature and mortality. We found a potential interactive effect between social deprivation and chronic exposure with regards to air pollution in the mortality-temperature relationship.

Conclusion

Our results may have implications in considering chronically polluted areas as vulnerable in heat action plans and in the long-term measures to reduce the burden of heat stress especially in the context of climate change.

We report on a novel fabrication approach of metal nanowires with complex surface. Taking advantage of nodular growth triggered by the presence of surface defects created intentionally on the substrate as well as the high tilt angle between the magnetron source axis and the normal to the substrate, metal nanowires containing hillocks emerging out of the surface can be created. The approach is demonstrated for several metals and alloys including gold, copper, silver, gold-copper and gold-silver. We demonstrate that applying an electrochemical dealloying process to the gold-copper alloy nanowire arrays allows for transforming the hillocks into ring-like shaped nanopores. The resulting porous gold nanowires exhibit a very high roughness and high specific surface making of them a promising candidate for the development of SERS-based sensors.

Background

While a great number of papers have been published on the short-term effects of air pollution on mortality, few have tried to assess whether this association varies according to the neighbourhood socioeconomic level and long-term ambient air concentrations measured at the place of residence. We explored the effect modification of 1) socioeconomic status, 2) long-term NO2 ambient air concentrations, and 3) both combined, on the association between short-term exposure to NO2 and all-cause mortality in Paris (France).

Methods

A time-stratified case-crossover analysis was performed to evaluate the effect of short-term NO2 variations on mortality, based on 79,107 deaths having occurred among subjects aged over 35 years, from 2004 to 2009, in the city of Paris. Simple and double interactions were statistically tested in order to analyse effect modification by neighbourhood characteristics on the association between mortality and short-term NO2 exposure. The data was estimated at the census block scale (n=866).

Results

The mean of the NO2 concentrations during the five days prior to deaths were associated with an increased risk of all-cause mortality: overall Excess Risk (ER) was 0.94% (95%CI=[0.08;1.80]. A higher risk was revealed for subjects living in the most deprived census blocks in comparison with higher socioeconomic level areas (ER=3.14% (95%CI=[1.41-4.90], p<0.001). Among these deprived census blocks, excess risk was even higher where long-term average NO2 concentrations were above 55.8 μg/m3 (the top tercile of distribution): ER=4.84% (95%CI=[1.56;8.24], p for interaction=0.02).

Conclusion

Our results show that people living in census blocks characterized by low socioeconomic status are more vulnerable to air pollution episodes. There is also an indication that people living in these disadvantaged census blocks might experience even higher risk following short-term air pollution episodes, when they are also chronically exposed to higher NO2 levels.

Future changes in tropical cyclone properties are an important component of climate change impacts and risk for many tropical and midlatitude countries. In this study we assess the performance of a multimodel ensemble of climate models, at resolutions ranging from 250 to 25 km. We use a common experimental design including both atmosphere-only and coupled simulations run over the period 1950-2050, with two tracking algorithms applied uniformly across the models. There are overall improvements in tropical cyclone frequency, spatial distribution, and intensity in models at 25 km resolution, with several of them able to represent very intense storms. Projected tropical cyclone activity by 2050 generally declines in the South Indian Ocean, while changes in other ocean basins are more uncertain and sensitive to both tracking algorithm and imposed forcings. Coupled models with smaller biases suggest a slight increase in average TC 10 m wind speeds by 2050.