747 research outputs found

    Experiments on wind-perturbed rogue wave hydrodynamics using the Peregrine breather model

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    Being considered as a prototype for description of oceanic rogue waves, the Peregrine breather solution of the nonlinear Schrödinger equation has been recently observed and intensely investigated experimentally in particular within the context of water

    Spectral up- and downshifting of Akhmediev breathers under wind forcing

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    We experimentally and numerically investigate the effect of wind forcing on the spectral dynamics of Akhmediev breathers, a wave-type known to model the modulation instability. We develop the wind model to the same order in steepness as the higher order modifcation of the nonlinear Schroedinger equation, also referred to as the Dysthe equation. This results in an asymmetric wind term in the higher order, in addition to the leading order wind forcing term. The derived model is in good agreement with laboratory experiments within the range of the facility's length. We show that the leading order forcing term amplifies all frequencies equally and therefore induces only a broadening of the spectrum while the asymmetric higher order term in the model enhances higher frequencies more than lower ones. Thus, the latter term induces a permanent upshift of the spectral mean. On the other hand, in contrast to the direct effect of wind forcing, wind can indirectly lead to frequency downshifts, due to dissipative effects such as wave breaking, or through amplification of the intrinsic spectral asymmetry of the Dysthe equation. Furthermore, the definitions of the up- and downshift in terms of peak- and mean frequencies, that are critical to relate our work to previous results, are highlighted and discussed.Comment: 30 pages, 11 figure

    Modelling of impaired cerebral blood flow due to gaseous emboli

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    Bubbles introduced to the arterial circulation during invasive medical procedures can have devastating consequences for brain function but their effects are currently difficult to quantify. Here we present a Monte-Carlo simulation investigating the impact of gas bubbles on cerebral blood flow. For the first time, this model includes realistic adhesion forces, bubble deformation, fluid dynamical considerations, and bubble dissolution. This allows investigation of the effects of buoyancy, solubility, and blood pressure on embolus clearance. Our results illustrate that blockages depend on several factors, including the number and size distribution of incident emboli, dissolution time and blood pressure. We found it essential to model the deformation of bubbles to avoid overestimation of arterial obstruction. Incorporation of buoyancy effects within our model slightly reduced the overall level of obstruction but did not decrease embolus clearance times. We found that higher blood pressures generate lower levels of obstruction and improve embolus clearance. Finally, we demonstrate the effects of gas solubility and discuss potential clinical applications of the model

    Investigating the impact of two decades of urbanization on the water balance of the Yzeron peri-urban catchment, France

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    International audienceThis paper addresses the impact of 18 years of urbanization (1990-2008) on the Yzeron meso-scale peri-urban catchment (150 km²), located close to Lyon, France. A simplified version of the distributed hydrological model J2000 was used to perform long term simulations at a daily time step for several land use scenarios. These scenarios were derived from satellite SPOT images from years 1990, 1999 and 2008. The corresponding land use maps were classified into 5 classes depending on the percentage of impervious surfaces and the dominant non-impervious land use (agriculture or forest). The paper presents the methodology for the model setup and the simulation results for the main water balance components of the catchment: total runoff, runoff components, evapotranspiration and soil moisture. The results highlight the change of the catchment seasonal response from 1990 to 2008, mainly due to a change of the respective contributions of groundwater flow / surface runoff (+ 92% / - 28%, respectively). Monthly mean summer discharge unexpectedly appears to be higher in summer. It is provided by intermittent surface runoff generated by summer storm events. As surface runoff generated on urban surfaces is likely to carry a wide range of contaminants, this has a potential large impact on water quality

    Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model

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    Rivers are rich in biodiversity and act as ecological corridors for plant and animal species. With climate change and increasing anthropogenic water demand, more frequent and prolonged periods of drying in river systems are expected, endangering biodiversity and river ecosystems. However, understanding and predicting the hydrological mechanisms that control periodic drying and rewetting in rivers is challenging due to a lack of studies and hydrological observations, particularly in non-perennial rivers. Within the framework of the Horizon 2020 DRYvER (Drying River Networks and Climate Change) project, a hydrological modelling study of flow intermittence in rivers is being carried out in three European catchments (Spain, Finland, France) characterised by different climate, geology, and anthropogenic use. The objective of this study is to represent the spatio-temporal dynamics of flow intermittence at the reach level in mesoscale river networks (between 120 and 350 km2). The daily and spatially distributed flow condition (flowing or dry) is predicted using the J2000 distributed hydrological model coupled with a random forest classification model. Observed flow condition data from different sources (water level measurements, photo traps, citizen science applications) are used to build the predictive model. This study aims to evaluate the impact of the observed flow condition dataset (sample size, spatial and temporal representativity) on the performance of the predictive model. Results show that the hybrid modelling approach developed in this study allows the spatio-temporal patterns of drying to be accurately predicted in the three catchments, with a sensitivity criterion above 0.9 for the prediction of dry events in the Finnish and French case studies and 0.65 in the Spanish case study. This study shows the value of combining different data sources of observed flow condition to reduce the uncertainty in predicting flow intermittence.</p

    The Global School Adaptation score: a new neurodevelopmental assessment tool for very preterm children at five years of age

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    Objective To determine the usefulness of a neurodevelopmental assessment tool consisting of a questionnaire administered to teachers to measure the Global School Adaptation (GSA) scores of very preterm children at the age of 5 years. Study design A sample of 445 very preterm children (&lt;35 weeks of gestation) was assessed at 5 years of age using GSA and IQ scores. According to the consistency between the scores, children were determined to be well classified, intermediately classified, or misclassified. The differences between groups were assessed through univariate and multivariate logistic regression. Results The GSA score was highly or intermediately consistent with the IQ score for 89.2% of the children, and 10.8% were considered misclassified. Children with a higher GSA than IQ score had more autonomy and self-confidence (P &lt; .01), and those with a lower GSA than IQ score had more behavioral problems (P &lt; .01). Analysis by logistic regression showed that sex and gestational age significantly affected the consistency between the 2 scores. Thus, girls were less likely to have a lower GSA than IQ score (aOR = 0.45; 95% CI: 0.24-0.84; P = .01), and a lower gestational age significantly increased the likelihood of having a higher GSA than IQ score (for children born between 24 and 28 weeks of gestation: aOR = 2.70; 95% CI: 1.23-5.92; P = .01). Conclusions The GSA score is a simple, inexpensive, and reliable screening tool for assessing neurodevelopment in very preterm children at 5 years of age
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