Evolving Spatially Aggregated Features from Satellite Imagery for Regional Modeling

Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel method of inducing spatial aggregations as a component of the machine learning process, yielding regional model features whose construction is driven by model prediction performance rather than prior assumptions. Our results demonstrate that Genetic Programming is particularly well suited to this type of feature construction because it can automatically synthesize appropriate aggregations, as well as better incorporate them into predictive models compared to other regression methods we tested. In our experiments we consider a specific problem instance and real-world dataset relevant to predicting snow properties in high-mountain Asia

Ice-core evidence of earliest extensive copper metallurgy in the Andes 2700 years ago

The importance of metallurgy for social and economic development is indisputable. Although copper (Cu) was essential for the wealth of pre- and post-colonial societies in the Andes, the onset of extensive Cu metallurgy in South America is still debated. Comprehensive archaeological findings point to first sophisticated Cu metallurgy during the Moche culture ~200–800 AD, whereas peat-bog records from southern South America suggest earliest pollution potentially from Cu smelting as far back as ~2000 BC. Here we present a 6500-years Cu emission history for the Andean Altiplano, based on ice-core records from Illimani glacier in Bolivia, providing the first complete history of large-scale Cu smelting activities in South America. We find earliest anthropogenic Cu pollution during the Early Horizon period ~700–50 BC, and attribute the onset of intensified Cu smelting in South America to the activities of the central Andean Chiripa and Chavin cultures ~2700 years ago. This study provides for the first time substantial evidence for extensive Cu metallurgy already during these early cultures

Predator-induced changes of female mating preferences: innate and experiential effects

Background: In many species males face a higher predation risk than females because males display elaborate traits that evolved under sexual selection, which may attract not only females but also predators. Females are, therefore, predicted to avoid such conspicuous males under predation risk. The present study was designed to investigate predator-induced changes of female mating preferences in Atlantic mollies (Poecilia mexicana). Males of this species show a pronounced polymorphism in body size and coloration, and females prefer large, colorful males in the absence of predators. Results: In dichotomous choice tests predator-naïve (lab-reared) females altered their initial preference for larger males in the presence of the cichlid Cichlasoma salvini, a natural predator of P. mexicana, and preferred small males instead. This effect was considerably weaker when females were confronted visually with the non-piscivorous cichlid Vieja bifasciata or the introduced non-piscivorous Nile tilapia (Oreochromis niloticus). In contrast, predator experienced (wild-caught) females did not respond to the same extent to the presence of a predator, most likely due to a learned ability to evaluate their predators' motivation to prey. Conclusions: Our study highlights that (a) predatory fish can have a profound influence on the expression of mating preferences of their prey (thus potentially affecting the strength of sexual selection), and females may alter their mate choice behavior strategically to reduce their own exposure to predators. (b) Prey species can evolve visual predator recognition mechanisms and alter their mate choice only when a natural predator is present. (c) Finally, experiential effects can play an important role, and prey species may learn to evaluate the motivational state of their predators. Keywords: Sexual selection; female choice; non-independent mate choice; predator recognition; Poecilia mexican

Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006

<p>Abstract</p> <p>Background</p> <p>Spatial analytical techniques and models are often used in epidemiology to identify spatial anomalies (hotspots) in disease regions. These analytical approaches can be used to not only identify the location of such hotspots, but also their spatial patterns.</p> <p>Methods</p> <p>In this study, we utilize spatial autocorrelation methodologies, including Global Moran's I and Local Getis-Ord statistics, to describe and map spatial clusters, and areas in which these are situated, for the 20 leading causes of death in Taiwan. In addition, we use the fit to a logistic regression model to test the characteristics of similarity and dissimilarity by gender.</p> <p>Results</p> <p>Gender is compared in efforts to formulate the common spatial risk. The mean found by local spatial autocorrelation analysis is utilized to identify spatial cluster patterns. There is naturally great interest in discovering the relationship between the leading causes of death and well-documented spatial risk factors. For example, in Taiwan, we found the geographical distribution of clusters where there is a prevalence of tuberculosis to closely correspond to the location of aboriginal townships.</p> <p>Conclusions</p> <p>Cluster mapping helps to clarify issues such as the spatial aspects of both internal and external correlations for leading health care events. This is of great aid in assessing spatial risk factors, which in turn facilitates the planning of the most advantageous types of health care policies and implementation of effective health care services.</p

Growing old with the immune system: a study of immunosenescence in the zebra finch (Taeniopygia guttata)

Immunosenescence has not received much attention in birds and the few existing studies indicate that the occurrence of immunosenescence and/or its extent may differ between species. In addition, not much information is available on the immunosenescence patterns of different immune parameters assessed simultaneously in both sexes within a single species. The present study reports the results on immunosenescence in innate immunity and both cellular and humoral acquired immunity of both sexes in a captive population of zebra finch (Taeniopygia guttata) using three age groups (approximately 0.2, 2.5 and 5.1 years). Both male and female finches showed an inverse U-shaped pattern in cellular immune function with age, quantified by a PHA response. Males showed stronger responses than females at all ages. In contrast, an increase with age in humoral immunity, quantified through total plasma immunoglobulin Y levels, was found in both sexes. However, our measurements of innate immunity measured through the bacteria-killing ability against Escherichia coli gave inconclusive results. Still, we conclude that both cellular and humoral acquired immunity are susceptible to immunosenescence, and that the sexes differ in cellular immunity

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior