167 resultados para ecological feature


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Aims To investigate secular trends in the incidence of Type 1 diabetes in Northern Ireland over the period 1989-2003. To highlight geographical variations in the incidence of Type 1 diabetes by producing disease maps and to compare incidence rates by relevant area characteristics.

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This study investigates face recognition with partial occlusion, illumination variation and their combination, assuming no prior information about the mismatch, and limited training data for each person. The authors extend their previous posterior union model (PUM) to give a new method capable of dealing with all these problems. PUM is an approach for selecting the optimal local image features for recognition to improve robustness to partial occlusion. The extension is in two stages. First, authors extend PUM from a probability-based formulation to a similarity-based formulation, so that it operates with as little as one single training sample to offer robustness to partial occlusion. Second, they extend this new formulation to make it robust to illumination variation, and to combined illumination variation and partial occlusion, by a novel combination of multicondition relighting and optimal feature selection. To evaluate the new methods, a number of databases with various simulated and realistic occlusion/illumination mismatches have been used. The results have demonstrated the improved robustness of the new methods.

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The essay discusses the actions and motivations of various groups that tried to end the practice of double feature film exhibition in the United States during the 1930s and 1940s. Used as a price-cutting strategy, double features were embraced by marginal exhibitors and low-budget producers, but attacked by most major studios and established theatre chains. Methods employed to control the double feature included voluntary bans, governmental legislation, and legal action. During the depression, Franklin D. Roosevelt's New Deal opposed the double feature as a strategy likely to undermine established admission price levels. But the double feature proved resilient and survived all these efforts, as well as an additional series of assaults, based on conservation of energy and materiel, mounted during the Second World War.

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An abstract version of the comprehensive aquatic simulation model (CASM) is found to exhibit bistability under intermediate loading of nutrient input, supporting the alternative-stable-states theory and field observations for shallow lakes. Our simulations of biomanipulations under the bistable conditions reveal that a reduction in the abundance of zooplanktivorous fish cannot switch the system from a turbid to a clear state. Rather, a direct reduction of phytoplankton and detritus was found to be most effective to make this switch in the present model. These results imply that multiple manipulations may be effective for practical restorations of lakes. We discuss the present results of biomanipulations in terms of ecological resilience in multivariable systems or natural systems.

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Goldstone's idea of slow dynamics resulting from spontaneously broken symmetries is applied to Hubbell's neutral hypothesis of community dynamics, to efficiently simplify stage-structured multi-species models-introducing the quasi-neutral approximation (QNA). Rather than assuming population-dynamical neutrality in the QNA, deviations from ideal neutrality, thought to be small, drive dynamics. The QNA is systematically derived to first and second order in a two-scale singular perturbation expansion. The total reproductive value of species, as computed from the effective life-history parameters resulting from the non-linear interactions with the surrounding community, emerges as the new dynamic variables in this aggregated description. Using a simple stage-structured community-assembly model, the QNA is demonstrated to accurately reproduce population dynamics in large, complex communities. Further, the utility of the QNA in building intuition for management problems is illustrated by estimating the responses of a fish stock to harvesting and variations in fecundity.

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Protracted or intense rainfall may affect the reproductive success of reptilian species on a number of levels ranging from the availability of prey, the integrity of the nesting site and the subsequent survivability of offspring. For sea turtles (a species displaying temperature sex determination) nesting throughout the tropics and subtropics, rainfall has previously been shown to influence the development environment of clutches; in its extreme resulting in high levels of egg or hatchling mortality. Yet when compared to other abiotic variables affecting clutch success, rainfall has received relatively little attention. We therefore examined how fluctuations in local rainfall at a tropical nesting site for leatherback turtles (Dermochelys coriacea) affected the nest environment. Temperature data loggers placed within clutches (n = 8) revealed that protracted rainfall had a marked cooling effect on nests, so that seasonally improbable male-producing temperatures (

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This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.