Bioinformatics tools in predictive ecology: Applications to fisheries

This article is made available throught the Brunel Open Access Publishing Fund - Copygith @ 2012 Tucker et al.There has been a huge effort in the advancement of analytical techniques for molecular biological data over the past decade. This has led to many novel algorithms that are specialized to deal with data associated with biological phenomena, such as gene expression and protein interactions. In contrast, ecological data analysis has remained focused to some degree on off-the-shelf statistical techniques though this is starting to change with the adoption of state-of-the-art methods, where few assumptions can be made about the data and a more explorative approach is required, for example, through the use of Bayesian networks. In this paper, some novel bioinformatics tools for microarray data are discussed along with their ‘crossover potential’ with an application to fisheries data. In particular, a focus is made on the development of models that identify functionally equivalent species in different fish communities with the aim of predicting functional collapse

Change of a Weibel-type to an Alfv\'enic shock in pair plasma by upstream waves

We examine with particle-in-cell (PIC) simulations how a parallel shock in pair plasma reacts to upstream waves, which are driven by escaping downstream particles. Initially, the shock is sustained in the two-dimensional simulation by a magnetic filamentation (beam-Weibel) instability. Escaping particles drive an electrostatic beam instability upstream. Modifications of the upstream plasma by these waves hardly affect the shock. In time, a decreasing density and increasing temperature of the escaping particles quench the beam instability. A larger thermal energy along than perpendicular to the magnetic field destabilizes the pair-Alfv\'en mode. In the rest frame of the upstream plasma, the group velocity of the growing pair-Alfv\'en waves is below that of the shock and the latter catches up with the waves. Accumulating pair-Alfv\'en waves gradually change the shock in the two-dimensional simulation from a Weibel-type shock into an Alfv\'enic shock with a Mach number that is about 6 for our initial conditions.Comment: 11 pages, 10 figures, accepted for publication in Physics of Plasma

GRB 070714B - Discovery of the Highest Spectroscopically Confirmed Short Burst Redshift

Gemini Nod & Shuffle spectroscopy on the host of the short GRB 070714B shows a single emission line at 7167 angstroms which, based on a grizJHK photometric redshift, we conclude is the 3727 angstrom [O II] line. This places the host at a redshift of z=.923 exceeding the previous record for the highest spectroscopically confirmed short burst redshift of z=.546 held by GRB 051221. This dramatically moves back the time at which we know short bursts were being formed, and suggests that the present evidence for an old progenitor population may be observationally biased.Comment: Conference procedings for Gamma Ray Bursts 2007 November 5-9, 2007 Santa Fe, New Mexico (4 pages, 2 figures

Evolution of Global Relativistic Jets: Collimations and Expansion with kKHI and the Weibel Instability

One of the key open questions in the study of relativistic jets is their interaction with the environment. Here, we study the initial evolution of both electron-proton and electron-positron relativistic jets, focusing on their lateral interaction with the ambient plasma. We trace the generation and evolution of the toroidal magnetic field generated by both kinetic Kelvin-Helmholtz (kKH) and Mushroom instabilities (MI). This magnetic field collimates the jet. We show that in electron-proton jet, electrons are perpendicularly accelerated with jet collimation. The magnetic polarity switches from the clockwise to anti-clockwise in the middle of jet, as the instabilities weaken. For the electron-positron jet, we find strong mixture of electron-positron with the ambient plasma, that results in the creation of a bow shock. Merger of magnetic field current filaments generate density bumps which initiate a forward shock. The strong mixing between jet and ambient particles prevents full development of the jet on the studied scale. Our results therefore provide a direct evidence for both jet collimation and particle acceleration in the created bow shock. Differences in the magnetic field structures generated by electron-proton and electron-positron jets may contribute to observable differences in the polarized properties of emission by electrons.Comment: 25 pages, 12 figures, ApJ, accepte

Gamma Ray Bursts: recent results and connections to very high energy Cosmic Rays and Neutrinos

Gamma-ray bursts are the most concentrated explosions in the Universe. They have been detected electromagnetically at energies up to tens of GeV, and it is suspected that they could be active at least up to TeV energies. It is also speculated that they could emit cosmic rays and neutrinos at energies reaching up to the $10^{18}-10^{20}$ eV range. Here we review the recent developments in the photon phenomenology in the light of \swift and \fermi satellite observations, as well as recent IceCube upper limits on their neutrino luminosity. We discuss some of the theoretical models developed to explain these observations and their possible contribution to a very high energy cosmic ray and neutrino background.Comment: 12 pages, 7 figures. Text of a plenary lecture at the PASCOS 12 conference, Merida, Yucatan, Mexico, June 2012; to appear in J.Phys. (Conf. Series

The Centaurus A Ultrahigh-Energy Cosmic Ray Excess and the Local Extragalactic Magnetic Field

The ultrahigh-energy cosmic-ray anisotropies discovered by the Pierre Auger Observatory give the potential to finally address both the particles' origins and properties of the nearby extragalactic magnetic field (EGMF). We examine the implications of the excess of ~ 10^20 eV events around the nearby radio galaxy Centaurus A. We find that, if Cen A is the source of these cosmic rays, the angular distribution of events constrains the EGMF strength within several Mpc of the Milky Way to > 20 nG for an assumed primary proton composition. Our conclusions suggest that either the observed excess is a statistical anomaly or the local EGMF is stronger then conventionally thought. We discuss the implications of this field, including UHECR scattering from more distant sources, time delays from transient sources, and the possibility of using magnetic lensing signatures to attain tighter constraints.Comment: 8 pages, 8 figures; Matches published version in AP

The Gamma Ray Burst section of the White Paper on the Status and Future of Very High Energy Gamma Ray Astronomy: A Brief Preliminary Report

Original paper can be found at: http://proceedings.aip.org/proceedings/ Copyright American Institute of Physics DOI: 10.1063/1.2943545otherPeer reviewe

Validating module network learning algorithms using simulated data

In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance. Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators.Comment: 13 pages, 6 figures + 2 pages, 2 figures supplementary informatio