1,646 research outputs found
Thermoresponsive Gels based on ABC Triblock Copolymers: Effect of the Length of the PEG Side Group
A Formal Treatment of Sequential Ignorability
Taking a rigorous formal approach, we consider sequential decision problems
involving observable variables, unobservable variables, and action variables.
We can typically assume the property of extended stability, which allows
identification (by means of G-computation) of the consequence of a specified
treatment strategy if the unobserved variables are, in fact, observed - but not
generally otherwise. However, under certain additional special conditions we
can infer simple stability (or sequential ignorability), which supports
G-computation based on the observed variables alone. One such additional
condition is sequential randomization, where the unobserved variables
essentially behave as random noise in their effects on the actions. Another is
sequential irrelevance, where the unobserved variables do not influence future
observed variables. In the latter case, to deduce sequential ignorability in
full generality requires additional positivity conditions. We show here that
these positivity conditions are not required when all variables are discrete.Comment: 25 pages, 5 figures, 1 tabl
Network protocol scalability via a topological Kadanoff transformation
A natural hierarchical framework for network topology abstraction is
presented based on an analogy with the Kadanoff transformation and
renormalisation group in theoretical physics. Some properties of the
renormalisation group bear similarities to the scalability properties of
network routing protocols (interactions). Central to our abstraction are two
intimately connected and complementary path diversity units: simple cycles, and
cycle adjacencies. A recursive network abstraction procedure is presented,
together with an associated generic recursive routing protocol family that
offers many desirable features.Comment: 4 pages, 5 figures, PhysComNet 2008 workshop submissio
Do CDS spreads reflect default risks? Evidence from UK bank bailouts
CDS spreads are generally considered to reflect the credit risks of their reference entities. However, CDS spreads of the major UK banks remained relatively stable in response to the recent credit crisis. We suggest that this can be explained by changes in loss given default (LGD). To obtain the result we first derive the probabilities of default from stock option prices and then determine the LGD consistent with actual CDS spreads. Our results reveal a significant decrease in the LGD of bailed out banks over the observed period in contrast to banks which were not bailed out and non-financial companies
Learning Bayesian Networks with the Saiyan algorithm
Some structure learning algorithms have proven to be effective in reconstructing hypothetical Bayesian Network (BN) graphs from synthetic data. However, in their mission to maximise a scoring function, many become conservative and minimise edges discovered. While simplicity is desired, the output is often a graph that consists of multiple independent graphical fragments or variables that do not enable full propagation of evidence. While this is not a problem in theory, it can be a problem in practice. This paper presents a novel unconventional heuristic local-search structure learning algorithm, called Saiyan, which returns a directed acyclic graph that enables full propagation of evidence. Forcing the algorithm to connect all data variables and to direct all of the edges discovered implies that the additional forced arcs are not expected to be correct at the rate of those identified unrestrictedly, and this evidently has a negative impact on the evaluation score of the discovered graph. Still, based on both synthetic and real-world experiments, the Saiyan algorithm demonstrates competitive performance relative to other state-of-the-art constraint-based, score-based, and hybrid structure learning algorithms
Dense matter equation of state for neutron star mergers
In simulations of binary neutron star mergers, the dense matter equation of
state (EOS) is required over wide ranges of density and temperature as well as
under conditions in which neutrinos are trapped, and the effects of magnetic
fields and rotation prevail. Here we assess the status of dense matter theory
and point out the successes and limitations of approaches currently in use. A
comparative study of the excluded volume (EV) and virial approaches for the
system using the equation of state of Akmal, Pandharipande and
Ravenhall for interacting nucleons is presented in the sub-nuclear density
regime. Owing to the excluded volume of the -particles, their mass
fraction vanishes in the EV approach below the baryon density 0.1 fm,
whereas it continues to rise due to the predominantly attractive interactions
in the virial approach. The EV approach of Lattimer et al. is extended here to
include clusters of light nuclei such as d, H and He in addition to
-particles. Results of the relevant state variables from this
development are presented and enable comparisons with related but slightly
different approaches in the literature. We also comment on some of the sweet
and sour aspects of the supra-nuclear EOS. The extent to which the neutron star
gravitational and baryon masses vary due to thermal effects, neutrino trapping,
magnetic fields and rotation are summarized from earlier studies in which the
effects from each of these sources were considered separately. Increases of
about occur for rigid (differential) rotation with
comparable increases occurring in the presence of magnetic fields only for
fields in excess of Gauss. Comparatively smaller changes occur due to
thermal effects and neutrino trapping. Some future studies to gain further
insight into the outcome of dynamical simulations are suggested.Comment: Revised manuscript with one additional figure and previous Fig. 4
replaced, 19 additional references and new tex
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