468 research outputs found
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 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
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