Who will become dominant? Investigating the roles of individual behaviour, body size, and environmental predictability in brown trout fry hierarchies

This paper presents a study investigating performance of brown trout fry, with different behavioural characteristics, in environments differing in food predictability. Based on previous experimental findings, we hypothesised that more active individuals would be favoured by a predictable environment, as compared to an unpredictable environment, as a consequence of being more aggressive and likely to dominate the best feeding stations. This hypothesis was not supported, as more active individuals instead tended to perform better, in terms of growth and survival, in unpredictable environments. However, this effect may stem from initial size differences, as more active fish also tended to be larger. In predictable environments, no trends between activity (or size) and performance were detected. Dominant individuals could be identified based on lighter body colouration in 9 out of 10 rearing tanks, but dominance appeared not to be related to activity score. The results highlight a potential advantage of more active and/or larger fry in unpredictable environments, while performance in predictable environments is likely depending on other phenotypic characteristics. Our general experimental approach can be useful for further developments in the investigation of performance of different ethotypes of brown trout fry

Thermal neutron image intensifier tube provides brightly visible radiographic pattern

Vacuum-type neutron image intensifier tube improves image detection in thermal neutron radiographic inspection. This system converts images to an electron image, and with electron acceleration and demagnification between the input target and output screen, produces a bright image viewed through a closed circuit television system

A Beaming-Independent Estimate of the Energy Distribution of Long Gamma-Ray Bursts: Initial Results and Future Prospects

We present single-epoch radio afterglow observations of 24 long-duration gamma-ray burst (GRB) on a timescale of >100 d after the burst. These observations trace the afterglow evolution when the blastwave has decelerated to mildly- or non-relativistic velocities and has roughly isotropized. We infer beaming-independent kinetic energies using the Sedov-Taylor self-similar solution, and find a median value for the sample of detected bursts of about 7x10^51 erg, with a 90% confidence range of 1.1x10^50-3.3x10^53 erg. Both the median and 90% confidence range are somewhat larger than the results of multi-wavelength, multi-epoch afterglow modeling (including large beaming corrections), and the distribution of beaming-corrected gamma-ray energies. This is due to bursts in our sample with only a single-frequency observation for which we can only determine an upper bound on the peak of the synchrotron spectrum. This limitation leads to a wider range of allowed energies than for bursts with a well-measured spectral peak. Our study indicates that single-epoch centimeter-band observations covering the spectral peak on a timescale of ~1 yr can provide a robust estimate of the total kinetic energy distribution with a small investment of telescope time. The substantial increase in bandwidth of the EVLA (up to 8 GHz simultaneously with full coverage at 1-40 GHz) will provide the opportunity to estimate the kinetic energy distribution of GRBs with only a few hours of data per burst.Comment: Submitted to ApJ; 11 pages, 5 figures, 2 table

Genes2Networks: Connecting Lists of Proteins by Using Background Literature-based Mammalian Networks

In recent years, in-silico literature-based mammalian protein-protein interaction network datasets have been developed. These datasets contain binary interactions extracted manually from legacy experimental biomedical research literature. Placing lists of genes or proteins identified as significantly changing in multivariate experiments, in the context of background knowledge about binary interactions, can be used to place these genes or proteins in the context of pathways and protein complexes.
Genes2Networks is a software system that integrates the content of ten mammalian literature-based interaction network datasets. Filtering to prune low-confidence interactions was implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from “seed” lists of human Entrez gene names. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is available at http://actin.pharm.mssm.edu/genes2networks.
Genes2Network is a powerful web-based software application tool that can help experimental biologists to interpret high-throughput experimental results used in genomics and proteomics studies where the output of these experiments is a list of significantly changing genes or proteins. The system can be used to find relationships between nodes from the seed list, and predict novel nodes that play a key role in a common function

Efficient spin control in high-quality-factor planar micro-cavities

A semiconductor microcavity embedding donor impurities and excited by a laser field is modelled. By including general decay and dephasing processes, and in particular cavity photon leakage, detailed simulations show that control over the spin dynamics is significally enhanced in high-quality-factor cavities, in which case picosecond laser pulses may produce spin-flip with high-fidelity final states.Comment: 6 pages, 4 figure

The Median Probability Model and Correlated Variables

The median probability model (MPM) Barbieri and Berger (2004) is defined as the model consisting of those variables whose marginal posterior probability of inclusion is at least 0.5. The MPM rule yields the best single model for prediction in orthogonal and nested correlated designs. This result was originally conceived under a specific class of priors, such as the point mass mixtures of non-informative and g-type priors. The MPM rule, however, has become so very popular that it is now being deployed for a wider variety of priors and under correlated designs, where the properties of MPM are not yet completely understood. The main thrust of this work is to shed light on properties of MPM in these contexts by (a) characterizing situations when MPM is still safe under correlated designs, (b) providing significant generalizations of MPM to a broader class of priors (such as continuous spike-and-slab priors). We also provide new supporting evidence for the suitability of g-priors, as opposed to independent product priors, using new predictive matching arguments. Furthermore, we emphasize the importance of prior model probabilities and highlight the merits of non-uniform prior probability assignments using the notion of model aggregates

Quantum transport in weakly coupled superlattices at low temperature

We report on the study of the electrical current flowing in weakly coupled superlattice (SL) structures under an applied electric field at very low temperature, i.e. in the tunneling regime. This low temperature transport is characterized by an extremely low tunneling probability between adjacent wells. Experimentally, I(V) curves at low temperature display a striking feature, i.e a plateau or null differential conductance. A theoretical model based on the evaluation of scattering rates is developed in order to understand this behaviour, exploring the different scattering mechanisms in AlGaAs alloys. The dominant interaction in usual experimental conditions such as ours is found to be the electron-ionized donors scattering. The existence of the plateau in the I(V) characteristics is physically explained by a competition between the electric field localization of the Wannier-Stark electron states in the weakly coupled quantum wells and the electric field assisted tunneling between adjacent wells. The influence of the doping concentration and profile as well as the presence of impurities inside the barrier are discussed

Numerical solution of the nonlinear evolution equation at small x with impact parameter and beyond the LL approximation

Nonlinear evolution equation at small x with impact parameter dependence is analyzed numerically. Saturation scales and the radius of expansion in impact parameter are extracted as functions of rapidity. Running coupling is included in this evolution, and it is found that the solution is sensitive to the infrared regularization. Kinematical effects beyond leading logarithmic approximation are taken partially into account by modifying the kernel which includes the rapidity dependent cuts. While the local nonlinear evolution is not very sensitive to these effects, the kinematical constraints cannot be neglected in the evolution with impact parameter.Comment: 22 pages, 37 figures, RevTe

Fringe tracking performance monitoring: FINITO at VLTI

Since April 2011, realtime fringe tracking data are recorded simultaneously with data from the VLTI/AMBER interferometric beam combiner. Not only this offers possibilities to post-process AMBER reduced data to obtain more accurate interferometric quantities, it also allows to estimate the performance of the fringe tracking a function of the conditions of seeing, coherence time, flux, etc. First we propose to define fringe tracking performance metrics in the AMBER context, in particular as a function of AMBER's integration time. The main idea is to determine the optimal exposure time for AMBER: short exposures are dominated by readout noise and fringes in long exposures are completely smeared out. Then we present this performance metrics correlated with Paranal local ASM (Ambient Site Monitor) measurements, such as seeing, coherence time or wind speed for example. Finally, we also present some preliminary results of attempts to model and predict fringe tracking performances, using Artificial Neural Networks.Comment: SPIE conference, Optical and Infrared Interferometry II

The Association between Vitamin D Receptor Expression and Prolonged Overall Survival in Breast Cancer.

Summary In this study, we analyzed vitamin D receptor (VDR) expression and survival in a breast cancer patient cohort of 82 breast cancer patients. Immunohistochemical analysis was possible in 91.5% of the patients (75/82). Staining was evaluated using the semi-quantitative assay according to Remmele and Stegner (immunoreactivity score [IRS]). IRS 0–1 was negative/very low, IRS 2–4 was moderate to high, and IRS 6–12 was high. Statistical analysis was performed by Spearman’s correlation test (p<0.05 significant). Overall survival was analyzed using Kaplan-Meier estimations. Only 6 patients had a negative IRS. Moderate IRS values were present in 20 patients. Most of the patients had a high IRS (49). For survival analysis, data were dichotomized (IRS 0–4: negative to moderate and IRS 6–12: high VDR expression). In univariate analysis, VDR expression showed significant differences in progression-free survival (PFS) and overall survival (OS). Patients with high IRS scores showed significantly better PFS and OS than patients with moderate/negative IRS scores for VDR expression. Tumor size was significantly correlated to PFS. When analyzed separately, the three different IRS groups showed significant differences in VDR expression. The present data suggest that VDR expression in breast cancer tissue may be of clinical significance, and the results provide evidence that VDR may be a factor with prognostic relevance. (J Histochem Cytochem 60:121–129, 2012). Keywords: breast cancer, vitamin D receptor, immunohistochemistry, prognosi