536 research outputs found

    Locomotion in Response to Shifting Climate Zones: Not So Fast

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    Although a species’ locomotor capacity is suggestive of its ability to escape global climate change, such a suggestion is not necessarily straightforward. Species vary substantially in locomotor capacity, both ontogenetically and within/among populations, and much of this variation has a genetic basis. Accordingly, locomotor capacity can and does evolve rapidly, as selection experiments demonstrate. Importantly, even though this evolution of locomotor capacity may be rapid enough to escape changing climate, genetic correlations among traits (often due to pleiotropy) are such that successful or rapid dispersers are often limited in colonization or reproductive ability, which may be viewed as a trade-off. The nuanced assessment of this variation and evolution is reviewed for well-studied models: salmon, flying versus flightless insects, rodents undergoing experimental evolution, and metapopulations of butterflies. This work reveals how integration of physiology with population biology and functional genomics can be especially informative

    Weight-volume relationships of Aspen and winter-cut Black Spruce pulpwood in northern Minnesota

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    Maps of zeroes of the grand canonical partition function in a statistical model of high energy collisions

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    Theorems on zeroes of the truncated generating function in the complex plane are reviewed. When examined in the framework of a statistical model of high energy collisions based on the negative binomial (Pascal) multiplicity distribution, these results lead to maps of zeroes of the grand canonical partition function which allow to interpret in a novel way different classes of events in pp collisions at LHC c.m. energies.Comment: 17 pages, figures (ps included); added references, some figures enlarged. To appear in J. Phys.

    Locomotion in Response to Shifting Climate Zones: Not So Fast

    Get PDF
    Although a species’ locomotor capacity is suggestive of its ability to escape global climate change, such a suggestion is not necessarily straightforward. Species vary substantially in locomotor capacity, both ontogenetically and within/among populations, and much of this variation has a genetic basis. Accordingly, locomotor capacity can and does evolve rapidly, as selection experiments demonstrate. Importantly, even though this evolution of locomotor capacity may be rapid enough to escape changing climate, genetic correlations among traits (often due to pleiotropy) are such that successful or rapid dispersers are often limited in colonization or reproductive ability, which may be viewed as a trade-off. The nuanced assessment of this variation and evolution is reviewed for well-studied models: salmon, flying versus flightless insects, rodents undergoing experimental evolution, and metapopulations of butterflies. This work reveals how integration of physiology with population biology and functional genomics can be especially informative

    Quantum Chaotic Dynamics and Random Polynomials

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    We investigate the distribution of roots of polynomials of high degree with random coefficients which, among others, appear naturally in the context of "quantum chaotic dynamics". It is shown that under quite general conditions their roots tend to concentrate near the unit circle in the complex plane. In order to further increase this tendency, we study in detail the particular case of self-inversive random polynomials and show that for them a finite portion of all roots lies exactly on the unit circle. Correlation functions of these roots are also computed analytically, and compared to the correlations of eigenvalues of random matrices. The problem of ergodicity of chaotic wave-functions is also considered. For that purpose we introduce a family of random polynomials whose roots spread uniformly over phase space. While these results are consistent with random matrix theory predictions, they provide a new and different insight into the problem of quantum ergodicity. Special attention is devoted all over the paper to the role of symmetries in the distribution of roots of random polynomials.Comment: 33 pages, Latex, 6 Figures not included (a copy of them can be requested at [email protected]); to appear in Journal of Statistical Physic

    Chaotic maps and flows: Exact Riemann-Siegel lookalike for spectral fluctuations

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    To treat the spectral statistics of quantum maps and flows that are fully chaotic classically, we use the rigorous Riemann-Siegel lookalike available for the spectral determinant of unitary time evolution operators FF. Concentrating on dynamics without time reversal invariance we get the exact two-point correlator of the spectral density for finite dimension NN of the matrix representative of FF, as phenomenologically given by random matrix theory. In the limit NN\to\infty the correlator of the Gaussian unitary ensemble is recovered. Previously conjectured cancellations of contributions of pseudo-orbits with periods beyond half the Heisenberg time are shown to be implied by the Riemann-Siegel lookalike

    Spectral Analysis of the Supreme Court

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    The focus of this paper is the linear algebraic framework in which the spectral analysis of voting data like that above is carried out. As we will show, this framework can be used to pinpoint voting coalitions in small voting bodies like the United States Supreme Court. Our goal is to show how simple ideas from linear algebra can come together to say something interesting about voting. And what could be more simple than where our story begins— with counting

    I2N: image to nutrients, a sensor guided semi-automated tool for annotation of images for nutrition analysis of eating episodes

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    INTRODUCTION: Dietary assessment is important for understanding nutritional status. Traditional methods of monitoring food intake through self-report such as diet diaries, 24-hour dietary recall, and food frequency questionnaires may be subject to errors and can be time-consuming for the user. METHODS: This paper presents a semi-automatic dietary assessment tool we developed - a desktop application called Image to Nutrients (I2N) - to process sensor-detected eating events and images captured during these eating events by a wearable sensor. I2N has the capacity to offer multiple food and nutrient databases (e.g., USDA-SR, FNDDS, USDA Global Branded Food Products Database) for annotating eating episodes and food items. I2N estimates energy intake, nutritional content, and the amount consumed. The components of I2N are three-fold: 1) sensor-guided image review, 2) annotation of food images for nutritional analysis, and 3) access to multiple food databases. Two studies were used to evaluate the feasibility and usefulness of I2N: 1) a US-based study with 30 participants and a total of 60 days of data and 2) a Ghana-based study with 41 participants and a total of 41 days of data). RESULTS: In both studies, a total of 314 eating episodes were annotated using at least three food databases. Using I2N's sensor-guided image review, the number of images that needed to be reviewed was reduced by 93% and 85% for the two studies, respectively, compared to reviewing all the images. DISCUSSION: I2N is a unique tool that allows for simultaneous viewing of food images, sensor-guided image review, and access to multiple databases in one tool, making nutritional analysis of food images efficient. The tool is flexible, allowing for nutritional analysis of images if sensor signals aren't available
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