7,580 research outputs found
The Formation Mechanism of Brown Dwarfs
We present results from the first hydrodynamical star formation calculation
to demonstrate that brown dwarfs are a natural and frequent product of the
collapse and fragmentation of a turbulent molecular cloud. The brown dwarfs
form via the fragmentation of dense molecular gas in unstable multiple systems
and are ejected from the dense gas before they have been able to accrete to
stellar masses. Thus, they can be viewed as `failed stars'. Approximately three
quarters of the brown dwarfs form in gravitationally-unstable circumstellar
discs while the remainder form in collapsing filaments of molecular gas. These
formation mechanisms are very efficient, producing roughly the same number of
brown dwarfs as stars, in agreement with recent observations. However, because
close dynamical interactions are involved in their formation, we find a very
low frequency of binary brown dwarf systems (\lsim 5%) and that those binary
brown dwarf systems that do exist must be close \lsim 10 AU. Similarly, we
find that young brown dwarfs with large circumstellar discs (radii \gsim 10
AU) are rare (%).Comment: 5 pages, 2 GIF figures, postscript with figures available at
http://www.astro.ex.ac.uk/people/mbat
The Formation of Close Binary Systems by Dynamical Interactions and Orbital Decay
We present results from the first hydrodynamical star formation calculation
to demonstrate that close binary stellar systems (separations \lsim 10 AU)
need not be formed directly by fragmentation. Instead, a high frequency of
close binaries can be produced through a combination of dynamical interactions
in unstable multiple systems and the orbital decay of initially wider binaries.
Orbital decay may occur due to gas accretion and/or the interaction of a binary
with its circumbinary disc. These three mechanisms avoid the problems
associated with the fragmentation of optically-thick gas to form close systems
directly. They also result in a preference for close binaries to have roughly
equal-mass components because dynamical exchange interactions and the accretion
of gas with high specific angular momentum drive mass ratios towards unity.
Furthermore, due to the importance of dynamical interactions, we find that
stars with greater masses ought to have a higher frequency of close companions,
and that many close binaries ought to have wide companions. These properties
are in good agreement with the results of observational surveys.Comment: Published in MNRAS, 10 pages, 6 figures (5 degraded). Paper with
high-resolution figures and animations available from
http://www.astro.ex.ac.uk/people/mbat
The First Supernova Explosions in the Universe
We investigate the supernova explosions that end the lives of massive
Population III stars in low-mass minihalos (M~10^6 M_sun) at redshifts z~20.
Employing the smoothed particle hydrodynamics method, we carry out numerical
simulations in a cosmological set-up of pair-instability supernovae with
explosion energies of E_SN=10^51 and 10^53 ergs. We find that the more
energetic explosion leads to the complete disruption of the gas in the
minihalo, whereas the lower explosion energy leaves much of the halo intact.
The higher energy supernova expels > 90% of the stellar metals into a region ~1
kpc across over a timescale of 3-5 Myr. Due to this burst-like initial star
formation episode, a large fraction of the universe could have been endowed
with a metallicity floor, Z_min>10^-4 Z_sun, already at z>15.Comment: Published in ApJ Letter
Slow Excitation Trapping in Quantum Transport with Long-Range Interactions
Long-range interactions slow down the excitation trapping in quantum
transport processes on a one-dimensional chain with traps at both ends. This is
counter intuitive and in contrast to the corresponding classical processes with
long-range interactions, which lead to faster excitation trapping. We give a
pertubation theoretical explanation of this effect.Comment: 4 pages, 3 figure
Strong lensing by fermionic dark matter in galaxies
It has been shown that a self-gravitating system of massive keV fermions in
thermodynamic equilibrium correctly describes the dark matter (DM) distribution
in galactic halos and predicts a denser quantum core towards the center of the
configuration. Such a quantum core, for a fermion mass in the range of keV
keV, can be an alternative interpretation of the
central compact object in Sgr A*. We present in this work the gravitational
lensing properties of this novel DM model in Milky Way-like spiral galaxies. We
describe the lensing effects of the pure DM component both on halo scales,
where we compare them to the effects of the Navarro-Frenk-White and the
Non-Singular Isothermal Sphere DM models, and near the galaxy center, where we
compare them with the effects of a Schwarzschild BH. For the particle mass
leading to the most compact DM core, keV, we draw the
following conclusions. At distances pc from the center of the
lens the effect of the central object on the lensing properties is negligible.
However, we show that measurements of the deflection angle produced by the DM
distribution in the outer region at a few kpc, together with rotation curve
data, could help to discriminate between different DM models. We show that at
distances pc strong lensing effects, such as multiple images and
Einstein rings, may occur. Large differences in the deflection angle produced
by a DM central core and a central BH appear at distances
pc; in this regime the weak-field formalism is no longer applicable and the
exact general-relativistic formula has to be used. We find that quantum DM
cores do not show a photon sphere what implies that they do not cast a shadow.
Similar conclusions apply to the other DM distributions for other fermion
masses in the above specified range and for other galaxy types.Comment: 10 pages, 8 figures. v2: Version published in PR
Application of chicken microarrays for gene expression analysis in other avian species
BACKGROUND: With the threat of emerging infectious diseases such as avian influenza, whose natural hosts are thought to be a variety of wild water birds including duck, we are armed with very few genomic resources to investigate large scale immunological gene expression studies in avian species. Multiple options exist for conducting large gene expression studies in chickens and in this study we explore the feasibility of using one of these tools to investigate gene expression in other avian species. RESULTS: In this study we utilised a whole genome long oligonucleotide chicken microarray to assess the utility of cross species hybridisation (CSH). We successfully hybridised a number of different avian species to this array, obtaining reliable signals. We were able to distinguish ducks that were infected with avian influenza from uninfected ducks using this microarray platform. In addition, we were able to detect known chicken immunological genes in all of the hybridised avian species. CONCLUSION: Cross species hybridisation using long oligonucleotide microarrays is a powerful tool to study the immune response in avian species with little available genomic information. The present study validated the use of the whole genome long oligonucleotide chicken microarray to investigate gene expression in a range of avian species
Group-theoretic models of the inversion process in bacterial genomes
The variation in genome arrangements among bacterial taxa is largely due to
the process of inversion. Recent studies indicate that not all inversions are
equally probable, suggesting, for instance, that shorter inversions are more
frequent than longer, and those that move the terminus of replication are less
probable than those that do not. Current methods for establishing the inversion
distance between two bacterial genomes are unable to incorporate such
information. In this paper we suggest a group-theoretic framework that in
principle can take these constraints into account. In particular, we show that
by lifting the problem from circular permutations to the affine symmetric
group, the inversion distance can be found in polynomial time for a model in
which inversions are restricted to acting on two regions. This requires the
proof of new results in group theory, and suggests a vein of new combinatorial
problems concerning permutation groups on which group theorists will be needed
to collaborate with biologists. We apply the new method to inferring distances
and phylogenies for published Yersinia pestis data.Comment: 19 pages, 7 figures, in Press, Journal of Mathematical Biolog
The Effect of Different Forms of Synaptic Plasticity on Pattern Recognition in the Cerebellar Cortex
âThe original publication is available at www.springerlink.comâ. Copyright Springer.Many cerebellar learning theories assume that long-term depression (LTD) of synapses between parallel fibres (PFs) and Purkinje cells (PCs) provides the basis for pattern recognition in the cerebellum. Previous work has suggested that PCs can use a novel neural code based on the duration of silent periods. These simulations have used a simplified learning rule, where the synaptic conductance was halved each time a pattern was learned. However, experimental studies in cerebellar slices show that the synaptic conductance saturates and is rarely reduced to less than 50% of its baseline value. Moreover, the previous simulations did not include plasticity of the synapses between inhibitory interneurons and PCs. Here we study the effect of LTD saturation and inhibitory synaptic plasticity on pattern recognition in a complex PC model. We find that the PC model is very sensitive to the value at which LTD saturates, but is unaffected by inhibitory synaptic plasticity.Peer reviewe
A Semi-parametric Technique for the Quantitative Analysis of Dynamic Contrast-enhanced MR Images Based on Bayesian P-splines
Dynamic Contrast-enhanced Magnetic Resonance Imaging (DCE-MRI) is an
important tool for detecting subtle kinetic changes in cancerous tissue.
Quantitative analysis of DCE-MRI typically involves the convolution of an
arterial input function (AIF) with a nonlinear pharmacokinetic model of the
contrast agent concentration. Parameters of the kinetic model are biologically
meaningful, but the optimization of the non-linear model has significant
computational issues. In practice, convergence of the optimization algorithm is
not guaranteed and the accuracy of the model fitting may be compromised. To
overcome this problems, this paper proposes a semi-parametric penalized spline
smoothing approach, with which the AIF is convolved with a set of B-splines to
produce a design matrix using locally adaptive smoothing parameters based on
Bayesian penalized spline models (P-splines). It has been shown that kinetic
parameter estimation can be obtained from the resulting deconvolved response
function, which also includes the onset of contrast enhancement. Detailed
validation of the method, both with simulated and in vivo data, is provided
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