986 research outputs found
Testing a Simplified Version of Einstein's Equations for Numerical Relativity
Solving dynamical problems in general relativity requires the full machinery
of numerical relativity. Wilson has proposed a simpler but approximate scheme
for systems near equilibrium, like binary neutron stars. We test the scheme on
isolated, rapidly rotating, relativistic stars. Since these objects are in
equilibrium, it is crucial that the approximation work well if we are to
believe its predictions for more complicated systems like binaries. Our results
are very encouraging.Comment: 9 pages (RevTeX 3.0 with 6 uuencoded figures), CRSR-107
Bioethanol Production from Brewers Spent Grains Using a Fungal Consolidated Bioprocessing (CBP) Approach.
Production of bioethanol from brewers spent grains (BSG) using consolidated bioprocessing (CBP) is reported. Each CBP system consists of a primary filamentous fungal species, which secretes the enzymes required to deconstruct biomass, paired with a secondary yeast species to ferment liberated sugars to ethanol. Interestingly, although several pairings of fungi were investigated, the sake fermentation system (A. oryzae and S. cerevisiae NCYC479) was found to yield the highest concentrations of ethanol (37Â g/L of ethanol within 10Â days). On this basis, 1Â t of BSG (dry weight) would yield 94Â kg of ethanol using 36Â hL of water in the process. QRT-PCR analysis of selected carbohydrate degrading (CAZy) genes expressed by A. oryzae in the BSG sake system showed that hemicellulose was deconstructed first, followed by cellulose. One drawback of the CBP approach is lower ethanol productivity rates; however, it requires low energy and water inputs, and hence is worthy of further investigation and optimisation
Quasiequilibrium sequences of black-hole--neutron-star binaries in general relativity
We construct quasiequilibrium sequences of black hole-neutron star binaries
for arbitrary mass ratios by solving the constraint equations of general
relativity in the conformal thin-sandwich decomposition. We model the neutron
star as a stationary polytrope satisfying the relativistic equations of
hydrodynamics, and account for the black hole by imposing equilibrium boundary
conditions on the surface of an excised sphere (the apparent horizon). In this
paper we focus on irrotational configurations, meaning that both the neutron
star and the black hole are approximately nonspinning in an inertial frame. We
present results for a binary with polytropic index n=1, mass ratio
M_{irr}^{BH}/M_{B}^{NS}=5 and neutron star compaction
M_{ADM,0}^{NS}/R_0=0.0879, where M_{irr}^{BH} is the irreducible mass of the
black hole, M_{B}^{NS} the neutron star baryon rest-mass, and M_{ADM,0}^{NS}
and R_0 the neutron star Arnowitt-Deser-Misner mass and areal radius in
isolation, respectively. Our models represent valid solutions to Einstein's
constraint equations and may therefore be employed as initial data for
dynamical simulations of black hole-neutron star binaries.Comment: 5 pages, 1 figure, revtex4, published in Phys.Rev.
Quasiequilibrium black hole-neutron star binaries in general relativity
We construct quasiequilibrium sequences of black hole-neutron star binaries
in general relativity. We solve Einstein's constraint equations in the
conformal thin-sandwich formalism, subject to black hole boundary conditions
imposed on the surface of an excised sphere, together with the relativistic
equations of hydrostatic equilibrium. In contrast to our previous calculations
we adopt a flat spatial background geometry and do not assume extreme mass
ratios. We adopt a Gamma=2 polytropic equation of state and focus on
irrotational neutron star configurations as well as approximately nonspinning
black holes. We present numerical results for ratios of the black hole's
irreducible mass to the neutron star's ADM mass in isolation of
M_{irr}^{BH}/M_{ADM,0}^{NS} = 1, 2, 3, 5, and 10. We consider neutron stars of
baryon rest mass M_B^{NS}/M_B^{max} = 83% and 56%, where M_B^{max} is the
maximum allowed rest mass of a spherical star in isolation for our equation of
state. For these sequences, we locate the onset of tidal disruption and, in
cases with sufficiently large mass ratios and neutron star compactions, the
innermost stable circular orbit. We compare with previous results for black
hole-neutron star binaries and find excellent agreement with third-order
post-Newtonian results, especially for large binary separations. We also use
our results to estimate the energy spectrum of the outgoing gravitational
radiation emitted during the inspiral phase for these binaries.Comment: 17 pages, 15 figures, published in Phys. Rev.
Solving Einstein's equations for rotating spacetimes: Evolution of relativistic star clusters
A numerical relativity code designed to evolve rotating axisymmetric spacetimes is constructed. Both polarization states of gravitational radiation can be tracked. The source of the gravitational field is chosen to be a configuration of collisionless particles. The code is used to evaluate the stability of polytropic and toroidal star clusters. The formation of Kerr black holes by the collapse of unstable clusters is demonstrated. Unstable clusters with J/(M^2) 1 collapse to new equilibrium configurations
Implementing an apparent-horizon finder in three dimensions
Locating apparent horizons is not only important for a complete understanding
of numerically generated spacetimes, but it may also be a crucial component of
the technique for evolving black-hole spacetimes accurately. A scheme proposed
by Libson et al., based on expanding the location of the apparent horizon in
terms of symmetric trace-free tensors, seems very promising for use with
three-dimensional numerical data sets. In this paper, we generalize this scheme
and perform a number of code tests to fully calibrate its behavior in
black-hole spacetimes similar to those we expect to encounter in solving the
binary black-hole coalescence problem. An important aspect of the
generalization is that we can compute the symmetric trace-free tensor expansion
to any order. This enables us to determine how far we must carry the expansion
to achieve results of a desired accuracy. To accomplish this generalization, we
describe a new and very convenient set of recurrence relations which apply to
symmetric trace-free tensors.Comment: 14 pages (RevTeX 3.0 with 3 figures
Rapid analysis of formic acid, acetic acid, and furfural in pretreated wheat straw hydrolysates and ethanol in a bioethanol fermentation using atmospheric pressure chemical ionisation mass spectrometry.
Atmospheric pressure chemical ionisation mass spectrometry (APCI-MS) offers advantages as a rapid analytical technique for the quantification of three biomass degradation products (acetic acid, formic acid and furfural) within pretreated wheat straw hydrolysates and the analysis of ethanol during fermentation. The data we obtained using APCI-MS correlated significantly with high-performance liquid chromatography analysis whilst offering the analyst minimal sample preparation and faster sample throughput
Deep learning cardiac motion analysis for human survival prediction
Motion analysis is used in computer vision to understand the behaviour of
moving objects in sequences of images. Optimising the interpretation of dynamic
biological systems requires accurate and precise motion tracking as well as
efficient representations of high-dimensional motion trajectories so that these
can be used for prediction tasks. Here we use image sequences of the heart,
acquired using cardiac magnetic resonance imaging, to create time-resolved
three-dimensional segmentations using a fully convolutional network trained on
anatomical shape priors. This dense motion model formed the input to a
supervised denoising autoencoder (4Dsurvival), which is a hybrid network
consisting of an autoencoder that learns a task-specific latent code
representation trained on observed outcome data, yielding a latent
representation optimised for survival prediction. To handle right-censored
survival outcomes, our network used a Cox partial likelihood loss function. In
a study of 302 patients the predictive accuracy (quantified by Harrell's
C-index) was significantly higher (p < .0001) for our model C=0.73 (95 CI:
0.68 - 0.78) than the human benchmark of C=0.59 (95 CI: 0.53 - 0.65). This
work demonstrates how a complex computer vision task using high-dimensional
medical image data can efficiently predict human survival
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