Concordant cues in faces and voices: testing the backup signal hypothesis

Information from faces and voices combines to provide multimodal signals about a person. Faces and voices may offer redundant, overlapping (backup signals), or complementary information (multiple messages). This article reports two experiments which investigated the extent to which faces and voices deliver concordant information about dimensions of fitness and quality. In Experiment 1, participants rated faces and voices on scales for masculinity/femininity, age, health, height, and weight. The results showed that people make similar judgments from faces and voices, with particularly strong correlations for masculinity/femininity, health, and height. If, as these results suggest, faces and voices constitute backup signals for various dimensions, it is hypothetically possible that people would be able to accurately match novel faces and voices for identity. However, previous investigations into novel face–voice matching offer contradictory results. In Experiment 2, participants saw a face and heard a voice and were required to decide whether the face and voice belonged to the same person. Matching accuracy was significantly above chance level, suggesting that judgments made independently from faces and voices are sufficiently similar that people can match the two. Both sets of results were analyzed using multilevel modeling and are interpreted as being consistent with the backup signal hypothesis

Avoiding the avoidable: Towards a European heat waves risk governance

The death toll of recent heat waves in developed countries has been remarkably high, contradicting the common assumption that high levels of economic and technological development automatically lead to lower vulnerability to weather extremes. Future climate change may further increase this vulnerability. In this article we examine some recent evidence of heat wave-related mortality and we conclude that while economic wealth and technological capacity might be a necessary condition for adequately coping with adverse climate change effects, they are not sufficient. Questions of awareness, preparedness, organizational issues, and actor networks have to be addressed in a proactive and focused manner in order to avoid future heat wave damages. We propose some practical consequences for heat wave adaptation measures by adopting a risk governance framework that can be universally applied, as it is sufficiently flexible to deal with the multi-level and often fragmented reality of existing coping measures

Avoiding the avoidable: Towards a European heat waves risk governance

The death toll of recent heat waves in developed countries has been remarkably high, contradicting the common assumption that high levels of economic and technological development automatically lead to lower vulnerability to weather extremes. Future climate change may further increase this vulnerability. In this article we examine some recent evidence of heat wave-related mortality and we conclude that while economic wealth and technological capacity might be a necessary condition for adequately coping with adverse climate change effects, they are not sufficient. Questions of awareness, preparedness, organizational issues, and actor networks have to be addressed in a proactive and focused manner in order to avoid future heat wave damages. We propose some practical consequences for heat wave adaptation measures by adopting a risk governance framework that can be universally applied, as it is sufficiently flexible to deal with the multi-level and often fragmented reality of existing coping measures

Converging seasonal prevalence dynamics in experimental epidemics

Background Regular seasonal changes in prevalence of infectious diseases are often observed in nature, but the mechanisms are rarely understood. Empirical tests aiming at a better understanding of seasonal prevalence patterns are not feasible for most diseases and thus are widely lacking. Here, we set out to study experimentally the seasonal prevalence in an aquatic host-parasite system. The microsporidian parasite Hamiltosporidium tvärminnensis exhibits pronounced seasonality in natural rock pool populations of its host, Daphnia magna with a regular increase of prevalence during summer and a decrease during winter. An earlier study was, however, unable to test if different starting conditions (initial prevalence) influence the dynamics of the disease in the long term. Here, we aim at testing how the starting prevalence affects the regular prevalence changes over a 4-year period in experimental populations.Results In an outdoor experiment, populations were set up to include the extremes of the prevalence spectrum observed in natural populations: 5% initial prevalence mimicking a newly invading parasite, 100% mimicking a rock pool population founded by infected hosts only, and 50% prevalence which is commonly observed in natural populations in spring. The parasite exhibited similar prevalence changes in all treatments, but seasonal patterns in the 100% treatment differed significantly from those in the 5% and 50% treatments. Populations started with 5% and 50% prevalence exhibited strong and regular seasonality already in the first year. In contrast, the amplitude of changes in the 100% treatment was low throughout the experiment demonstrating the long-lasting effect of initial conditions on prevalence dynamics.Conclusions Our study shows that the time needed to approach the seasonal changes in prevalence depends strongly on the initial prevalence. Because individual D. magna populations in this rock pool metapopulation are mostly short lived, only few populations might ever reach a point where the initial conditions are not visible anymore

The clock paradox in a static homogeneous gravitational field

The gedanken experiment of the clock paradox is solved exactly using the general relativistic equations for a static homogeneous gravitational field. We demonstrate that the general and special relativistic clock paradox solutions are identical and in particular that they are identical for finite acceleration. Practical expressions are obtained for proper time and coordinate time by using the destination distance as the key observable parameter. This solution provides a formal demonstration of the identity between the special and general relativistic clock paradox with finite acceleration and where proper time is assumed to be the same in both formalisms. By solving the equations of motion for a freely falling clock in a static homogeneous field elapsed times are calculated for realistic journeys to the stars.Comment: Revision: Posted with the caption included with the figure

ASSESSING VARIABILITY OF AGREEMENT MEASURES IN REMOTE SENSING USING A BAYESIAN APPROACH

Remote sensing imagery is a popular accessment tool in agriculture, forestry, and rangeland management. Spectral classification of imagery provides a means of estimating production and identifYing potential problems, such as weed, insect, and disease infestations. Accuracy of classification is traditionally based on ground truthing and summary statistics such as Cohen\u27s Kappa. Variability assessment and comparison of these quantities have been limited to asymptotic procedures relying on large sample sizes and gaussian distributions. However, asymptotic methods fail to take into account the underlying distribution of the classified data and may produce invalid inferential results. Bayesian methodology is introduced to develop probability distributions for Cohen\u27s Conditional Kappa that can subsequently be used for image assessment and comparison. Techniques are demonstrated on a set of images used in identifYing a species of weed, yellow starthistle, at various spatial resolutions and flying times

ESTIMATING THE LIKELIHOOD OF YELLOW STARTHISTLE OCCURRENCE USING AN EMPIRICALLY DERIVED NONLINEAR REGRESSION MODEL

Yellow starthistle is a noxious weed common in the semiarid climate of Central Idaho and other western states. Early detection of yellow starthistle and predicting its infestation potential have important scientific and managerial implications. Weed detection and delineation are often carried out by visual observation or survey techniques. However, such methods may be ineffective in detecting sparse infestations. The distribution of yellow starthistle over a large region may be affected by various exogenous variables such as elevation, slope and aspect. These landscape variables can be used to develop prediction models to estimate the potential invasion of yellow starthistle into new areas. A nonlinear prediction model has been developed based on a polar coordinate transformation to investigate the ability of landscape characteristics to predict the likelihood of yellow starthistle occurrence in North Central Idaho. The study region included the lower Snake river and parts of the Salmon and Clearwater basins encompassing various land use categories. The model provided accurate estimates of incidence of yellow starthistle within each specified land use category and performed well in subsequent statistical validations

MODELING DISPERSAL OF YELLOW STARTHISTLE IN THE CANYON GRASSLANDS OF NORTH CENTRAL IDAHO

Yellow starthistle is an invasive plant species that reduces productivity and plant diversity within the canyon grasslands of Idaho. Early detection of yellow starthistle and predicting its spread have important managerial implications that could greatly reduce the economic/environmental losses due to this weed. The spread of an invasive plant species depends on its ability to reproduce and disperse seed into new areas. Typically, information on the factors that directly affect a plant’s ability to reproduce and subsequently disperse seed is not available or difficult to obtain. Alternatively, topographic factors, such as slope and aspect as well as competitive correlates such as vegetation indices related to plant community biomass could be used to model plant survival and seed movement. In this research, several spatial network models incorporating these variables were considered for the prediction of yellow starthistle dispersal. Models will differed in their assessment of plant movement costs, which can be separated into two processes, survival to reproduction and seed dispersal. The candidate models were evaluated based on their predictive ability and biological relevance. Topographical variables, slope and aspect, were found to be significant contributors to yellow starthistle dispersal models, whereas vegetation indices did not improve the prediction process. The optimal model was applied to an area in central Idaho for predicting the dispersal of yellow starthistle in 1987 given a known 1981 infestation

Microscopic activity patterns in the Naming Game

The models of statistical physics used to study collective phenomena in some interdisciplinary contexts, such as social dynamics and opinion spreading, do not consider the effects of the memory on individual decision processes. On the contrary, in the Naming Game, a recently proposed model of Language formation, each agent chooses a particular state, or opinion, by means of a memory-based negotiation process, during which a variable number of states is collected and kept in memory. In this perspective, the statistical features of the number of states collected by the agents becomes a relevant quantity to understand the dynamics of the model, and the influence of topological properties on memory-based models. By means of a master equation approach, we analyze the internal agent dynamics of Naming Game in populations embedded on networks, finding that it strongly depends on very general topological properties of the system (e.g. average and fluctuations of the degree). However, the influence of topological properties on the microscopic individual dynamics is a general phenomenon that should characterize all those social interactions that can be modeled by memory-based negotiation processes.Comment: submitted to J. Phys.