Unstable coronal loops : numerical simulations with predicted observational signatures

We present numerical studies of the nonlinear, resistive magnetohydrodynamic (MHD) evolution of coronal loops. For these simulations we assume that the loops carry no net current, as might be expected if the loop had evolved due to vortex flows. Furthermore the initial equilibrium is taken to be a cylindrical flux tube with line-tied ends. For a given amount of twist in the magnetic field it is well known that once such a loop exceeds a critical length it becomes unstableto ideal MHD instabilities. The early evolution of these instabilities generates large current concentrations. Firstly we show that these current concentrations are consistent with the formation of a current sheet. Magnetic reconnection can only occur in the vicinity of these current concentrations and we therefore couple the resistivity to the local current density. This has the advantage of avoiding resistive diffusion in regions where it should be negligible. We demonstrate the importance of this procedure by comparison with simulations based on a uniform resistivity. From our numerical experiments we are able to estimate some observational signatures for unstable coronal loops. These signatures include: the timescale of the loop brightening; the temperature increase; the energy released and the predicted observable flow speeds. Finally we discuss to what extent these observational signatures are consistent with the properties of transient brightening loops.Comment: 13 pages, 9 figure

Motion of flux transfer events: a test of the Cooling model

The simple model of reconnected field line motion developed by Cooling et al. (2001) has been used in several recent case studies to explain the motion of flux transfer events across the magnetopause. We examine 213 FTEs observed by all four Cluster spacecraft under a variety of IMF conditions between November 2002 and June 2003, when the spacecraft tetrahedron separation was ~5000 km. Observed velocities were calculated from multi-spacecraft timing analysis, and compared with the velocities predicted by the Cooling model in order to check the validity of the model. After excluding three categories of FTEs (events with poorly defined velocities, a significant velocity component out of the magnetopause surface, or a scale size of less than 5000 km), we were left with a sample of 118 events. 78% of these events were consistent in both direction of motion and speed with one of the two model de Hoffmann-Teller (dHT) velocities calculated from the Cooling model (to within 30° and a factor of two in the speed). We also examined the plasma signatures of several magnetosheath FTEs; the electron signatures confirm the hemisphere of connection indicated by the model in most cases. This indicates that although the model is a simple one, it is a useful tool for identifying the source regions of FTEs

Little evidence for a selective advantage of armour-reduced threespined stickleback individuals in an invertebrate predation experiment

The repeated colonization of freshwater habitats by the ancestrally marine threespined stickleback Gasterosteus aculeatus has been associated with many instances of parallel reduction in armour traits, most notably number of lateral plates. The change in predation regime from marine systems, dominated by gape-limited predators such as piscivorous fishes, to freshwater habitats where grappling invertebrate predators such as insect larvae can dominate the predation regime, has been hypothesized as a driving force. Here we experimentally test the hypothesis that stickleback with reduced armour possess a selective advantage in the face of predation by invertebrates, using a natural population of stickleback that is highly polymorphic for armour traits and a common invertebrate predator from the same location. Our results provide no compelling evidence for selection in this particular predator–prey interaction. We suggest that the postulated selective advantage of low armour in the face of invertebrate predation may not be universal

Study of reconnection-associated multi-scale fluctuations with Cluster and Double Star

The objective of the paper is to asses the specific spectral scaling properties of magnetic reconnection associated fluctuations/turbulence at the Earthward and tailward outflow regions observed simultaneously by the Cluster and Double Star (TC-2) spacecraft on September 26, 2005. Systematic comparisons of spectral characteristics, including variance anisotropy and scale-dependent spectral anisotropy features in wave vector space were possible due to the well-documented reconnection events, occurring between the positions of Cluster (X = -14--16 $R_e$) and TC-2 (X = -6.6 $R_e$). Another factor of key importance is that the magnetometers on the spacecraft are similar. The comparisons provide further evidence for asymmetry of physical processes in Earthward/tailward reconnection outflow regions. Variance anisotropy and spectral anisotropy angles estimated from the multi-scale magnetic fluctuations in the tailward outflow region show features which are characteristic for magnetohydrodynamic cascading turbulence in the presence of a local mean magnetic field. The multi-scale magnetic fluctuations in the Earthward outflow region are exhibiting more power, lack of variance and scale dependent anisotropies, but also having larger anisotropy angles. In this region the magnetic field is more dipolar, the main processes driving turbulence are flow breaking/mixing, perhaps combined with turbulence ageing and non-cascade related multi-scale energy sources.Comment: 30 pages, 6 figure

Neural networks for genetic epidemiology: past, present, and future

During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN) are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes

Magnetic Field Amplification in Galaxy Clusters and its Simulation

We review the present theoretical and numerical understanding of magnetic field amplification in cosmic large-scale structure, on length scales of galaxy clusters and beyond. Structure formation drives compression and turbulence, which amplify tiny magnetic seed fields to the microGauss values that are observed in the intracluster medium. This process is intimately connected to the properties of turbulence and the microphysics of the intra-cluster medium. Additional roles are played by merger induced shocks that sweep through the intra-cluster medium and motions induced by sloshing cool cores. The accurate simulation of magnetic field amplification in clusters still poses a serious challenge for simulations of cosmological structure formation. We review the current literature on cosmological simulations that include magnetic fields and outline theoretical as well as numerical challenges.Comment: 60 pages, 19 Figure

Neural networks for modeling gene-gene interactions in association studies

<p>Abstract</p> <p>Background</p> <p>Our aim is to investigate the ability of neural networks to model different two-locus disease models. We conduct a simulation study to compare neural networks with two standard methods, namely logistic regression models and multifactor dimensionality reduction. One hundred data sets are generated for each of six two-locus disease models, which are considered in a low and in a high risk scenario. Two models represent independence, one is a multiplicative model, and three models are epistatic. For each data set, six neural networks (with up to five hidden neurons) and five logistic regression models (the null model, three main effect models, and the full model) with two different codings for the genotype information are fitted. Additionally, the multifactor dimensionality reduction approach is applied.</p> <p>Results</p> <p>The results show that neural networks are more successful in modeling the structure of the underlying disease model than logistic regression models in most of the investigated situations. In our simulation study, neither logistic regression nor multifactor dimensionality reduction are able to correctly identify biological interaction.</p> <p>Conclusions</p> <p>Neural networks are a promising tool to handle complex data situations. However, further research is necessary concerning the interpretation of their parameters.</p

A detailed spectral and morphological study of the gamma-ray supernova remnant RX J1713.7-3946 with H.E.S.S

We present results from deep observations of the Galactic shell-type supernova remnant (SNR) RX J1713.7-3946 (also known as G347.3-0.5) conducted with the complete H.E.S.S. array in 2004. Detailed morphological and spatially resolved spectral studies reveal the very-high-energy (VHE -- Energies E > 100 GeV) gamma-ray aspects of this object with unprecedented precision. Since this is the first in-depth analysis of an extended VHE gamma-ray source, we present a thorough discussion of our methodology and investigations of possible sources of systematic errors. Gamma rays are detected throughout the whole SNR. The emission is found to resemble a shell structure with increased fluxes from the western and northwestern parts. The differential gamma-ray spectrum of the whole SNR is measured over more than two orders of magnitude, from 190 GeV to 40 TeV, and is rather hard with indications for a deviation from a pure power law at high energies. Spectra have also been determined for spatially separated regions of RX J1713.7-3946. The flux values vary by more than a factor of two, but no significant change in spectral shape is found. There is a striking correlation between the X-ray and the gamma-ray image. Radial profiles in both wavelength regimes reveal the same shape almost everywhere in the region of the SNR. The VHE gamma-ray emission of RX J1713.7-3946 is phenomenologically discussed for two scenarios, one where the gamma rays are produced by VHE electrons via Inverse Compton scattering and one where the gamma rays are due to neutral pion decay from proton-proton interactions. In conjunction with multi-wavelength considerations, the latter case is favoured. However, no decisive conclusions can yet be drawn regarding the parent particle population dominantly responsible for the gamma-ray emission from RX J1713.7-3946.Comment: 20 pages, 20 figures (low resolution), Accepted for publication in A&A - Revision 1: Added reference to Section 4.2. Added sentence to acknowledgement