406 research outputs found

    Reconstruction of Hydraulic Data by Machine Learning

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    Numerical simulation models associated with hydraulic engineering take a wide array of data into account to produce predictions: rainfall contribution to the drainage basin (characterized by soil nature, infiltration capacity and moisture), current water height in the river, topography, nature and geometry of the river bed, etc. This data is tainted with uncertainties related to an imperfect knowledge of the field, measurement errors on the physical parameters calibrating the equations of physics, an approximation of the latter, etc. These uncertainties can lead the model to overestimate or underestimate the flow and height of the river. Moreover, complex assimilation models often require numerous evaluations of physical solvers to evaluate these uncertainties, limiting their use for some real-time operational applications. In this study, we explore the possibility of building a predictor for river height at an observation point based on drainage basin time series data. An array of data-driven techniques is assessed for this task, including statistical models, machine learning techniques and deep neural network approaches. These are assessed on several metrics, offering an overview of the possibilities related to hydraulic time-series. An important finding is that for the same hydraulic quantity, the best predictors vary depending on whether the data is produced using a physical model or real observations.Comment: Submitted to SimHydro 201

    Seeing Tree Structure from Vibration

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    Humans recognize object structure from both their appearance and motion; often, motion helps to resolve ambiguities in object structure that arise when we observe object appearance only. There are particular scenarios, however, where neither appearance nor spatial-temporal motion signals are informative: occluding twigs may look connected and have almost identical movements, though they belong to different, possibly disconnected branches. We propose to tackle this problem through spectrum analysis of motion signals, because vibrations of disconnected branches, though visually similar, often have distinctive natural frequencies. We propose a novel formulation of tree structure based on a physics-based link model, and validate its effectiveness by theoretical analysis, numerical simulation, and empirical experiments. With this formulation, we use nonparametric Bayesian inference to reconstruct tree structure from both spectral vibration signals and appearance cues. Our model performs well in recognizing hierarchical tree structure from real-world videos of trees and vessels.Comment: ECCV 2018. The first two authors contributed equally to this work. Project page: http://tree.csail.mit.edu

    Phenotypic covariance of longevity, immunity and stress resistance in the Caenorhabditis nematodes

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    Background \ud Ageing, immunity and stresstolerance are inherent characteristics of all organisms. In animals, these traits are regulated, at least in part, by forkhead transcription factors in response to upstream signals from the Insulin/Insulin– like growth factor signalling (IIS) pathway. In the nematode Caenorhabditis elegans, these phenotypes are molecularly linked such that activation of the forkhead transcription factor DAF-16 both extends lifespan and simultaneously increases immunity and stress resistance. It is known that lifespan varies significantly among the Caenorhabditis species but, although DAF-16 signalling is highly conserved, it is unclear whether this phenotypic linkage occurs in other species. Here we investigate this phenotypic covariance by comparing longevity, stress resistance and immunity in four \ud Caenorhabditis species. \ud \ud Methodology/Principal Findings \ud We show using phenotypic analysis of DAF-16 influenced phenotypes that among four closely related Caenorhabditis nematodes, the gonochoristic species (Caenorhabditis remanei and Caenorhabditis brenneri) have diverged \ud significantly with a longer lifespan, improved stress resistance and higher immunity than the hermaphroditic species (C. elegans and Caenorhabditis briggsae). Interestingly, we also observe significant differences in expression levels between the daf-16 homologues in these species using Real-Time PCR, which positively correlate with the observed phenotypes. Finally, we provide additional evidence in support of a role for DAF-16 in regulating phenotypic coupling by using a combination of wildtype isolates, constitutively active daf-16 mutants and bioinformatic analysis. \ud \ud Conclusions \ud The gonochoristic species display a significantly longer lifespan (p < 0.0001)and more robust immune and stress response (p<0.0001, thermal stress; p<0.01, heavy metal stress; p<0.0001, pathogenic stress) than the hermaphroditic species. Our data suggests that divergence in DAF-16 mediated phenotypes may underlie many of the differences observed between these four species of Caenorhabditis nematodes. These findings are further supported by the correlative higher daf-16 expression levels among the gonochoristic species and significantly higher lifespan, immunity and stress tolerance in the constitutively active daf-16 hermaphroditic mutants

    Phenotypic covariance of Longevity, Immunity and Stress Resistance in the Caenorhabditis Nematodes

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    Background: Ageing, immunity and stresstolerance are inherent characteristics of all organisms. In animals, these traits are regulated, at least in part, by forkhead transcription factors in response to upstream signals from the Insulin/Insulin–like growth factor signalling (IIS) pathway. In the nematode Caenorhabditis elegans, these phenotypes are molecularly linked such that activation of the forkhead transcription factor DAF-16 both extends lifespan and simultaneously increases immunity and stress resistance. It is known that lifespan varies significantly among the Caenorhabditis species but, although DAF-16 signalling is highly conserved, it is unclear whether this phenotypic linkage occurs in other species. Here we investigate this phenotypic covariance by comparing longevity, stress resistance and immunity in four Caenorhabditis species. \ud \ud Methodology/Principal Findings: We show using phenotypic analysis of DAF-16 influenced phenotypes that among four closely related Caenorhabditis nematodes, the gonochoristic species (Caenorhabditis remanei and Caenorhabditis brenneri) have diverged significantly with a longer lifespan, improved stress resistance and higher immunity than the hermaphroditic species (C. elegans and Caenorhabditis briggsae). Interestingly, we also observe significant differences in expression levels between the daf-16 homologues in these species using Real-Time PCR, which positively correlate with the observed phenotypes. Finally, we provide additional evidence in support of a role for DAF-16 in regulating phenotypic coupling by using a combination of wildtype isolates, constitutively active daf-16 mutants and bioinformatic analysis. \ud \ud Conclusions: The gonochoristic species display a significantly longer lifespan (p<0.0001) and more robust immune and stress response (p<0.0001, thermal stress; p<0.01, heavy metal stress; p<0.0001, pathogenic stress) than the hermaphroditic species. Our data suggests that divergence in DAF-16 mediated phenotypes may underlie many of the differences observed between these four species of Caenorhabditis nematodes. These findings are further supported by the correlative higher daf-16 expression levels among the gonochoristic species and significantly higher lifespan, immunity and stress tolerance in the constitutively active daf-16 hermaphroditic mutants

    Defining Medical Futility and Improving Medical Care

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    It probably should not be surprising, in this time of soaring medical costs and proliferating technology, that an intense debate has arisen over the concept of medical futility. Should doctors be doing all the things they are doing? In particular, should they be attempting treatments that have little likelihood of achieving the goals of medicine? What are the goals of medicine? Can we agree when medical treatment fails to achieve such goals? What should the physician do and not do under such circumstances? Exploring these issues has forced us to revisit the doctor-patient relationship and the relationship of the medical profession to society in a most fundamental way. Medical futility has both a quantitative and qualitative component. I maintain that medical futility is the unacceptable likelihood of achieving an effect that the patient has the capacity to appreciate as a benefit. Both emphasized terms are important. A patient is neither a collection of organs nor merely an individual with desires. Rather, a patient (from the word “to suffer”) is a person who seeks the healing (meaning “to make whole”) powers of the physician. The relationship between the two is central to the healing process and the goals of medicine. Medicine today has the capacity to achieve a multitude of effects, raising and lowering blood pressure, speeding, slowing, and even removing and replacing the heart, to name but a minuscule few. But none of these effects is a benefit unless the patient has at the very least the capacity to appreciate it. Sadly, in the futility debate wherein some critics have failed or refused to define medical futility an important area of medicine has in large part been neglected, not only in treatment decisions at the bedside, but in public discussions—comfort care—the physician’s obligation to alleviate suffering, enhance well being and support the dignity of the patient in the last few days of life

    Bethe-hole polarization analyser for the magnetic vector of light

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    The nature of light as an electromagnetic wave with transverse components has been confirmed using optical polarizers, which are sensitive to the orientation of the electric field. Recent advances in nanoscale optical technologies demand their magnetic counterpart, which can sense the orientation of the optical magnetic field. Here we report that subwavelength metallic apertures on infinite plane predominantly sense the magnetic field of light, establishing the orientation of the magnetic component of light as a separate entity from its electric counterpart. A subwavelength aperture combined with a tapered optical fibre probe can also serve as a nanoscale polarization analyser for the optical magnetic field, analogous to a nanoparticle sensing the local electric polarization. As proof of its functionality, we demonstrate the measurement of a magnetic field orientation that is parallel to the electric field, as well as a circularly polarized magnetic field in the presence of a linearly polarized electric field
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