Joule heating and high frequency nonlinear effects in the surface impedance of high Tc superconductors

Using the dielectric resonator method, we have investigated nonlinearities in the surface impedance Zs = Rs + jXs of YBa2Cu3O7 thin films at 10 GHz as function of the incident microwave power level and temperature. The use of a rutile dielectric resonator allows us to measure the precise temperature of the films. We conclusively show that the usually observed increase of the surface resistance of YBa2Cu3O7 thin film as function of microwave power is due to local heating

Épidémiologie et physiopathologie de la rétinopathie du prématuré [Epidemiology and pathophysiology of retinopathy of prematurity].

Retinopathy of prematurity (ROP) is a major cause of visual impairment in premature infants. It is characterized by an arrest in normal retinal vascular development associated with microvascular degeneration, followed by an abnormal hypoxiainduced neovascularization. Recent studies point out that ROP is a multifactorial disease, implicating both oxygen-dependent and oxygen-independent mechanisms. Oxygen-dependent factors leading to microvascular degeneration include generation of reactive oxygen species and suppression of specific oxygen-regulated vascular survival factors, such as vascular endothelial growth factor (VEGF) and erythropoietin. The other major mechanism for the initial capillary loss is oxygen-independent and implicates a deficit in growth factor IGF-1/IGFBP3. The proliferative, second phase of ROP is triggered by increases in vascular growth factors concentrations, in an attempt to compensate for the hypoxic retina. Novel signaling pathways for vascular repair, implicating both metabolite signaling and inflammatory lipids signaling, represent new therapeutic avenues for ROP

Listériose et grossesse. Protocole de prise en charge au sein de l’hôpital Necker-Enfants–Malades

International audienceListeriosis is a rare and severe food-borne infection. The clinical and biologica presentation is not specific. Complications such as fetal loss, prematurity < 32 WG (weeks of gestation) and neonatal infection are reported in 80 % of cases. Diagnosis is made by the isolation of Listeria monocytogenes in any sample of maternal, fetal or neonatal origin. Treatment relies on a combination of amoxicillin and gentamicin.La listériose est une infection rare et grave d’origine alimentaire. Sa présentation et biologique est non spécifique et l’infection se complique de perte fœtale, de grande prématurité ou d’infection néonatale dans 80 % des cas. Le diagnostic est porté sur l’identification de Listeria monocytogenes de tout prélèvement d’origine maternelle fœtale ou néonatale. Le traitement repose sur une combinaison d’amoxicilline et de gentamicine

Understanding links between water-quality variables and nitrate concentration in freshwater streams using high frequency sensor data.

Real-time monitoring using in-situ sensors is becoming a common approach for measuring water-quality within watersheds. High-frequency measurements produce big datasets that present opportunities to conduct new analyses for improved understanding of water-quality dynamics and more effective management of rivers and streams. Of primary importance is enhancing knowledge of the relationships between nitrate, one of the most reactive forms of inorganic nitrogen in the aquatic environment, and other water-quality variables. We analysed high-frequency water-quality data from in-situ sensors deployed in three sites from different watersheds and climate zones within the National Ecological Observatory Network, USA. We used generalised additive mixed models to explain the nonlinear relationships at each site between nitrate concentration and conductivity, turbidity, dissolved oxygen, water temperature, and elevation. Temporal auto-correlation was modelled with an auto-regressive-moving-average (ARIMA) model and we examined the relative importance of the explanatory variables. Total deviance explained by the models was high for all sites (99%). Although variable importance and the smooth regression parameters differed among sites, the models explaining the most variation in nitrate contained the same explanatory variables. This study demonstrates that building a model for nitrate using the same set of explanatory water-quality variables is achievable, even for sites with vastly different environmental and climatic characteristics. Applying such models will assist managers to select cost-effective water-quality variables to monitor when the goals are to gain a spatial and temporal in-depth understanding of nitrate dynamics and adapt management plans accordingly

Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters

In situ sensors that collect high-frequency data are used increasingly to monitor aquatic environments. These sensors are prone to technical errors, resulting in unrecorded observations and/or anomalous values that are subsequently removed and create gaps in time series data. We present a framework based on generalized additive and auto-regressive models to recover these missing data. To mimic sporadically missing (i) single observations and (ii) periods of contiguous observations, we randomly removed (i) point data and (ii) day- and week-long sequences of data from a two-year time series of nitrate concentration data collected from Arikaree River, USA, where synoptically collected water temperature, turbidity, conductance, elevation, and dissolved oxygen data were available. In 72% of cases with missing point data, predicted values were within the sensor precision interval of the original value, although predictive ability declined when sequences of missing data occurred. Precision also depended on the availability of other water quality covariates. When covariates were available, even a sudden, event-based peak in nitrate concentration was reconstructed well. By providing a promising method for accurate prediction of missing data, the utility and confidence in summary statistics and statistical trends will increase, thereby assisting the effective monitoring and management of fresh waters and other at-risk ecosystems

Learning Node Selecting Tree Transducer from Completely Annotated Examples

Abstract. A base problem in Web information extraction is to find appropriate queries for informative nodes in trees. We propose to learn queries for nodes in trees automatically from examples. We introduce node selecting tree transducer (NSTT) and show how to induce deterministic NSTTs in polynomial time from completely annotated examples. We have implemented learning algorithms for NSTTs, started applying them to Web information extraction, and present first experimental results