42 resultados para Power to decide process
Resumo:
Female choice based on multiple male traits has been documented in many species but the functions of such multiple traits are still under debate. The satin bowerbird has a polygynous mating system in which males attract females to bowers for mating; females choose mates based on multiple aspects of males and their bowers. In this paper, we demonstrate that females use some cues to decide which males to examine closely and other cues to decide which males to mate with. Female visitation rates to bowers were significantly related to male size and the males' 'solitary' display rates, and, to a lesser extent, to the numbers of bower decorations. After controlling for female visitation rates, it was found that a male's mating success was significantly related to his size and the rate at which he 'painted' his bower with saliva and chewed up plant material.
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There is a general form of an argument which I call the 'argument from vagueness' which attempts to show that objects persist by perduring, via the claim that vagueness is never ontological in nature and thus that composition is unrestricted. I argue that even if we grant that vagueness is always the result of semantic indeterminacy rather than ontological vagueness, and thus also grant that composition is unrestricted, it does not follow that objects persist by perduring. Unrestricted mereological composition lacks the power to ensure that there exist instantaneous objects that wholly overlap persisting objects at times, and thus lacks the power to ensure that there exists anything that could be called a temporal part. Even if we grant that such instantaneous objects exist, however, I argue that it does not follow that objects perdure. To show this I briefly outline a coherent version of three dimensionalism that grants just such an assumption. Thus considerations pertaining to the nature of vagueness need not lead us inevitably to accept perdurantism.
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Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (
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Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (
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Presence-absence surveys are a commonly used method for monitoring broad-scale changes in wildlife distributions. However, the lack of power of these surveys for detecting population trends is problematic for their application in wildlife management. Options for improving power include increasing the sampling effort or arbitrarily relaxing the type I error rate. We present an alternative, whereby targeted sampling of particular habitats in the landscape using information from a habitat model increases power. The advantage of this approach is that it does not require a trade-off with either cost or the Pr(type I error) to achieve greater power. We use a demographic model of koala (Phascolarctos cinereus) population dynamics and simulations of the monitoring process to estimate the power to detect a trend in occupancy for a range of strategies, thereby demonstrating that targeting particular habitat qualities can improve power substantially. If the objective is to detect a decline in occupancy, the optimal strategy is to sample high-quality habitats. Alternatively, if the objective is to detect an increase in occupancy, the optimal strategy is to sample intermediate-quality habitats. The strategies with the highest power remained the same under a range of parameter assumptions, although observation error had a strong influence on the optimal strategy. Our approach specifically applies to monitoring for detecting long-term trends in occupancy or abundance. This is a common and important monitoring objective for wildlife managers, and we provide guidelines for more effectively achieving it.
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There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.
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A plethora of process modeling techniques has been proposed over the years. One way of evaluating and comparing the scope and completeness of techniques is by way of representational analysis. The purpose of this paper is to examine how process modeling techniques have developed over the last four decades. The basis of the comparison is the Bunge-Wand-Weber representation model, a benchmark used for the analysis of grammars that purport to model the real world and the interactions within it. This paper presents a comparison of representational analyses of several popular process modeling techniques and has two main outcomes. First, it provides insights, within the boundaries of a representational analysis, into the extent to which process modeling techniques have developed over time. Second, the findings also indicate areas in which the underlying theory seems to be over-engineered or lacking in specialization.
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Three main models of parameter setting have been proposed: the Variational model proposed by Yang (2002; 2004), the Structured Acquisition model endorsed by Baker (2001; 2005), and the Very Early Parameter Setting (VEPS) model advanced by Wexler (1998). The VEPS model contends that parameters are set early. The Variational model supposes that children employ statistical learning mechanisms to decide among competing parameter values, so this model anticipates delays in parameter setting when critical input is sparse, and gradual setting of parameters. On the Structured Acquisition model, delays occur because parameters form a hierarchy, with higher-level parameters set before lower-level parameters. Assuming that children freely choose the initial value, children sometimes will miss-set parameters. However when that happens, the input is expected to trigger a precipitous rise in one parameter value and a corresponding decline in the other value. We will point to the kind of child language data that is needed in order to adjudicate among these competing models.
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We show that quantum mechanics predicts a contradiction with local hidden variable theories for photon number measurements which have limited resolving power, to the point of imposing an uncertainty in the photon number result which is macroscopic in absolute terms. We show how this can be interpreted as a failure of a new premise, macroscopic local realism.
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We consider the quantum field theory of two bosonic fields interacting via both parametric (cubic) and quartic couplings. In the case of photonic fields in a nonlinear optical medium, this corresponds to the process of second-harmonic generation (via chi((2)) nonlinearity) modified by the chi((3)) nonlinearity. The quantum solitons or energy eigenstates (bound-state solutions) are obtained exactly in the simplest case of two-particle binding, in one, two, and three space dimensions. We also investigate three-particle binding in one space dimension. The results indicate that the exact quantum solitons of this field theory have a singular, pointlike structure in two and three dimensions-even though the corresponding classical theory is nonsingular. To estimate the physically accessible radii and binding energies of the bound states, we impose a momentum cutoff on the nonlinear couplings. In the case of nonlinear optical interactions, the resulting radii and binding energies of these photonic particlelike excitations in highly nonlinear parametric media appear to be close to physically observable values.
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This study explores the role of nurturing communication in distinguishing interpersonal and intergroup interactions between health professionals and patients, from the perspective of communication accommodation theory (CAT). Participants (47 men and 87 women) rated videotapes of actual hospital consultations on 12 goal and 16 strategy items derived from CAT. Health professionals in interpersonal interactions were perceived to pay more attention to relationship and emotional needs and to use more nurturant discourse management and emotional expression. These results point the way toward elucidating the perceived optimal balance in accommodative behavior, both group based and interpersonal, in these contexts, and they highlight the importance of nurturant communication to this process.
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We review recent developments in quantum and classical soliton theory, leading to the possibility of observing both classical and quantum parametric solitons in higher-dimensional environments. In particular, we consider the theory of three bosonic fields interacting via both parametric (cubic) and quartic couplings. In the case of photonic fields in a nonlinear optical medium this corresponds to the process of sum frequency generation (via chi((2)) nonlinearity) modified by the chi((3)) nonlinearity. Potential applications include an ultrafast photonic AND-gate. The simplest quantum solitons or energy eigenstates (bound-state solutions) of the interacting field Hamiltonian are obtained exactly in three space dimensions. They have a point-like structure-even though the corresponding classical theory is nonsingular. We show that the solutions can be regularized with the imposition of a momentum cut-off on the nonlinear couplings. The case of three-dimensional matter-wave solitons in coupled atomic/molecular Bose-Einstein condensates is discussed.
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Neonate Lepidoptera are confronted with the daunting task of establishing themselves on a food plant. The factors relevant to this process need to be considered at spatial and temporal scales relevant to the larva and not the investigator. Neonates have to cope with an array of plant surface characters as well as internal characters once the integument is ruptured. These characters, as well as microclimatic conditions, vary within and between plant modules and interact with larval feeding requirements, strongly affecting movement behavior, which may be extensive even for such small organisms. In addition to these factors, there is an array of predators, pathogens, and parasitoids with which first instars must contend. Not surprisingly, mortality in neonates is high but can vary widely. Experimental and manipulative studies, as well as detailed observations of the animal, are vital if the subtle interaction of factors responsible for this high and variable mortality are to be understood. These studies are essential for an understanding of theories linking female oviposition behavior with larval survival, plant defense theory, and population dynamics, as well as modern crop resistance breeding programs.
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Background. A sample of 1089 Australian adults was selected for the longitudinal component of the Quake Impact Study, a 2-year, four-phase investigation of the psychosocial effects of the 1989 Newcastle earthquake. Of these, 845 (78%) completed a survey 6 months post-disaster as well as one or more of the three follow-up surveys. Methods. The phase I survey was used to construct dimensional indices of self-reported exposure to threat the disruption and also to classify subjects by their membership of five 'at risk' groups (the injured; the displaced; owners of damaged small businesses; helpers in threat and non-threat situations). Psychological morbidity was assessed at each phase using the 12-item General Health Questionnaire (GHQ-12) and the Impact of Event Scale (IES). Results. Psychological morbidity declined over time but tended to stabilize at about 12 months post-disaster for general morbidity (GHQ-12) and at about 18 months for trauma-related (IES) morbidity. Initial exposure to threat and/or disruption were significant predictors of psychological morbidity throughout the study and had superior predictive power to membership of the targeted 'at risk' groups. The degree of ongoing disruption and other life events since the earthquake were also significant predictors of morbidity. The injured reported the highest levels of distress, but there was a relative absence of morbidity among the helpers. Conclusions. Future disaster research should carefully assess the threat and disruption experiences of the survivors at the time of the event and monitor ongoing disruptions in the aftermath in order to target interventions more effectively.
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A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.