Liquid transport in scale space

International audienceWhen a liquid stream is injected into a gaseous atmosphere, it destabilizes and continuously passes through different states characterized by different morphologies. Throughout this process, the flow dynamics may be different depending on the region of the flow and the scales of the involved liquid structures. Exploring this multi-scale, multi-dimensional phenomenon requires some new theoretical tools, some of which need yet to be elaborated. Here, a new analytical framework is proposed on the basis of two-point statistical equations of the liquid volume fraction. This tool, which originates from single phase turbulence, allows us notably to decompose the fluxes of liquid in flow–position space and scale space. Direct numerical simulations of liquid–gas turbulence decaying in a triply periodic domain are then used to characterize the time and scale evolution of the liquid volume fraction. It is emphasized that two-point statistics of the liquid volume fraction depend explicitly on the geometrical properties of the liquid–gas interface and in particular its surface density. The stretch rate of the liquid–gas interface is further shown to be the equivalent for the liquid volume fraction (a non-diffusive scalar) of the scalar dissipation rate. Finally, a decomposition of the transport of liquid in scale space highlights that non-local interactions between non-adjacent scales play a significant role

Stratified NH and ND emission in the prestellar core 16293E in L1689N

Context. High degrees of deuterium fractionation are commonly found in cold prestellar cores and in the envelopes around young protostars. As it brings strong constraints to chemical models, deuterium chemistry is often used to infer core history or molecule formation pathways. Whereas a large number of observations are available regarding interstellar deuterated stable molecules, relatively little is known about the deuteration of hydride radicals, as their fundamental rotational transitions are at high frequencies where the atmosphere is mostly opaque. Aims. Nitrogen hydride radicals are important species in nitrogen chemistry, as they are thought to be related to ammonia formation. Observations have shown that ammonia is strongly deuterated, with [NH_2D]/[NH_3] ~ 10%. Models predict similarly high [ND]/[NH] ratios, but so far only one observational determination of this ratio is available, towards the envelope of the protostar IRAS16293-2422. To test model predictions, we aim here to determine [ND]/[NH] in a dense, starless core. Methods. We observed NH and ND in 16293E with the HIFI spectrometer on board the Herschel Space Observatory as part of the CHESS guaranteed time key programme, and derived the abundances of these two species using a non local thermodynamic equilibrium radiative transfer model. Results. Both NH and ND are detected in the source, with ND in emission and NH in absorption against the continuum that arises from the cold dust emission. Our model shows, however, that the ND emission and the NH absorption originate from different layers in the cloud, as further evidenced by their different velocities. In the central region of the core, we can set a lower limit to the [ND]/[NH] ratio of ≳2%. This estimate is consistent with recent pure gas-phase models of nitrogen chemistry

BDNF Val66Met polymorphism is associated with self-reported empathy

Empathy is an important driver of human social behaviors and presents genetic roots that have been studied in neuroimaging using the intermediate phenotype approach. Notably, the Val66Met polymorphism of the Brain-derived neurotrophic factor (BDNF) gene has been identified as a potential target in neuroimaging studies based on its influence on emotion perception and social cognition, but its impact on self-reported empathy has never been documented. Using a neurogenetic approach, we investigated the association between the BDNF Val66Met polymorphism and self-reported empathy (Davis’ Interpersonal Reactivity Index; IRI) in a sample of 110 young adults. Our results indicate that the BDNF genotype is significantly associated with the linear combination of the four facets of the IRI, one of the most widely used self-reported empathy questionnaire. Crucially, the effect of BDNF Val66Met goes beyond the variance explained by two polymorphisms of the oxytocin transporter gene previously associated with empathy and its neural underpinnings (OXTR rs53576 and rs2254298). These results represent the first evidence suggesting a link between the BDNF gene and self-reported empathy and warrant further studies of this polymorphism due to its potential clinical significance

The influence of pre-radiation salivary flow rates and radiation dose on parotid salivary gland dysfunction in patients receiving radiotherapy for head and neck cancers

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72238/1/j.1754-4505.1998.tb00913.x.pd

Social networks and labour productivity in Europe: An empirical investigation

This paper uses firm-level data recorded in the AMADEUS database to investigate the distribution of labour productivity in different European countries. We find that the upper tail of the empirical productivity distributions follows a decaying power-law, whose exponent $\alpha$ is obtained by a semi-parametric estimation technique recently developed by Clementi et al. (2006). The emergence of "fat tails" in productivity distribution has already been detected in Di Matteo et al. (2005) and explained by means of a model of social network. Here we show that this model is tested on a broader sample of countries having different patterns of social network structure. These different social attitudes, measured using a social capital indicator, reflect in the power-law exponent estimates, verifying in this way the existence of linkages among firms' productivity performance and social network.Comment: LaTeX2e; 18 pages with 3 figures; Journal of Economic Interaction and Coordination, in pres

Molecular excitation in the Interstellar Medium: recent advances in collisional, radiative and chemical processes

We review the different excitation processes in the interstellar mediumComment: Accepted in Chem. Re

Mining multi-item drug adverse effect associations in spontaneous reporting systems

<p>Abstract</p> <p>Background</p> <p>Multi-item adverse drug event (ADE) associations are associations relating multiple drugs to possibly multiple adverse events. The current standard in pharmacovigilance is bivariate association analysis, where each single drug-adverse effect combination is studied separately. The importance and difficulty in the detection of multi-item ADE associations was noted in several prominent pharmacovigilance studies. In this paper we examine the application of a well established data mining method known as association rule mining, which we tailored to the above problem, and demonstrate its value. The method was applied to the FDAs spontaneous adverse event reporting system (AERS) with minimal restrictions and expectations on its output, an experiment that has not been previously done on the scale and generality proposed in this work.</p> <p>Results</p> <p>Based on a set of 162,744 reports of suspected ADEs reported to AERS and published in the year 2008, our method identified 1167 multi-item ADE associations. A taxonomy that characterizes the associations was developed based on a representative sample. A significant number (67% of the total) of potential multi-item ADE associations identified were characterized and clinically validated by a domain expert as previously recognized ADE associations. Several potentially novel ADEs were also identified. A smaller proportion (4%) of associations were characterized and validated as known drug-drug interactions.</p> <p>Conclusions</p> <p>Our findings demonstrate that multi-item ADEs are present and can be extracted from the FDA’s adverse effect reporting system using our methodology, suggesting that our method is a valid approach for the initial identification of multi-item ADEs. The study also revealed several limitations and challenges that can be attributed to both the method and quality of data.</p

Design of Experiments for Screening

The aim of this paper is to review methods of designing screening experiments, ranging from designs originally developed for physical experiments to those especially tailored to experiments on numerical models. The strengths and weaknesses of the various designs for screening variables in numerical models are discussed. First, classes of factorial designs for experiments to estimate main effects and interactions through a linear statistical model are described, specifically regular and nonregular fractional factorial designs, supersaturated designs and systematic fractional replicate designs. Generic issues of aliasing, bias and cancellation of factorial effects are discussed. Second, group screening experiments are considered including factorial group screening and sequential bifurcation. Third, random sampling plans are discussed including Latin hypercube sampling and sampling plans to estimate elementary effects. Fourth, a variety of modelling methods commonly employed with screening designs are briefly described. Finally, a novel study demonstrates six screening methods on two frequently-used exemplars, and their performances are compared

Hydrogen cyanide and isocyanide in prestellar cores

We studied the abundance of HCN, H13CN, and HN13C in a sample of prestellar cores, in order to search for species associated with high density gas. We used the IRAM 30m radiotelescope to observe along the major and the minor axes of L1498, L1521E, and TMC 2, three cores chosen on the basis of their CO depletion properties. We mapped the J=1-0 transition of HCN, H13CN, and HN13C towards the source sample plus the J=1-0 transition of N2H+ and the J=2-1 transition of C18O in TMC 2. We used two different radiative transfer codes, making use of recent collisional rate calculations, in order to determine more accurately the excitation temperature, leading to a more exact evaluation of the column densities and abundances. We find that the optical depths of both H13CN(1-0) and HN13C(1-0) are non-negligible, allowing us to estimate excitation temperatures for these transitions in many positions in the three sources. The observed excitation temperatures are consistent with recent computations of the collisional rates for these species and they correlate with hydrogen column density inferred from dust emission. We conclude that HCN and HNC are relatively abundant in the high density zone, n(H2) about 10^5 cm-3, where CO is depleted. The relative abundance [HNC]/[HCN] differs from unity by at most 30 per cent consistent with chemical expectations. The three hyperfine satellites of HCN(1-0) are optically thick in the regions mapped, but the profiles become increasingly skewed to the blue (L1498 and TMC 2) or red (L1521E) with increasing optical depth suggesting absorption by foreground layers.Comment: 13 pages, 19 figures, to be published in Astronomy and Astrophysic

Challenges in Estimating Insecticide Selection Pressures from Mosquito Field Data

Insecticide resistance has the potential to compromise the enormous effort put into the control of dengue and malaria vector populations. It is therefore important to quantify the amount of selection acting on resistance alleles, their contributions to fitness in heterozygotes (dominance) and their initial frequencies, as a means to predict the rate of spread of resistance in natural populations. We investigate practical problems of obtaining such estimates, with particular emphasis on Mexican populations of the dengue vector Aedes aegypti. Selection and dominance coefficients can be estimated by fitting genetic models to field data using maximum likelihood (ML) methodology. This methodology, although widely used, makes many assumptions so we investigated how well such models perform when data are sparse or when spatial and temporal heterogeneity occur. As expected, ML methodologies reliably estimated selection and dominance coefficients under idealised conditions but it was difficult to recover the true values when datasets were sparse during the time that resistance alleles increased in frequency, or when spatial and temporal heterogeneity occurred. We analysed published data on pyrethroid resistance in Mexico that consists of the frequency of a Ile1,016 mutation. The estimates for selection coefficient and initial allele frequency on the field dataset were in the expected range, dominance coefficient points to incomplete dominance as observed in the laboratory, although these estimates are accompanied by strong caveats about possible impact of spatial and temporal heterogeneity in selection