9,543 research outputs found
Exponential ergodicity of the jump-diffusion CIR process
In this paper we study the jump-diffusion CIR process (shorted as JCIR),
which is an extension of the classical CIR model. The jumps of the JCIR are
introduced with the help of a pure-jump L\'evy process . Under
some suitable conditions on the L\'evy measure of , we derive a
lower bound for the transition densities of the JCIR process. We also find some
sufficient condition guaranteeing the existence of a Forster-Lyapunov function
for the JCIR process, which allows us to prove its exponential ergodicity.Comment: 14 page
Preparatory cortical and spinal settings to counteract anticipated and non-anticipated perturbations
Little is known about how the central nervous system prepares postural responses differently in anticipated compared to non-anticipated perturbations. To investigate this, participants were exposed to translational and rotational perturbations presented in a blocked (anticipated) and a random (non-anticipated) design. The preparatory setting (âcentral setâ) was measured by H-reflexes, motor-evoked potentials (MEPs), and short-interval intracortical inhibition (SICI) shortly before perturbation onset in the soleus of 15 healthy adults. Additionally, the behavioral consequences of differential preparatory settings were analyzed by comparing the short- (SLR), medium- (MLR), and long-latency response (LLR) of the soleus after anticipated and non-anticipated rotations and translations. H-reflexes elicited before perturbation were different between conditions (p=0.023) with larger amplitudes in anticipated translations compared to anticipated rotations (37.0%; p=0.048). Reduced SICI was found in the three conditions containing perturbations compared to static standing (p0.001). Muscular responses assessed after perturbations remained unchanged for the SLR and MLR, whereas the LLR was decreased in anticipated rotations (â36.2%; p=0.002) and increased in anticipated translations (16.7%; p=0.046) compared to the corresponding non-anticipated perturbation. As the SLR and MLR are organized at the spinal and the LLR at the cortical level, the preparatory setting seems to mainly influence cortically mediated postural responses. However, the modulation of the H- reflex before anticipated perturbations indicates that supraspinal centers adjusted Ia- afferent transmission for the soleus in a perturbation-specific manner. Intracortical inhibition was also modulated but differentiates to a lesser extent only between perturbation conditions and unperturbed stance
Yield Curve Shapes and the Asymptotic Short Rate Distribution in Affine One-Factor Models
We consider a model for interest rates, where the short rate is given by a
time-homogenous, one-dimensional affine process in the sense of Duffie,
Filipovic and Schachermayer. We show that in such a model yield curves can only
be normal, inverse or humped (i.e. endowed with a single local maximum). Each
case can be characterized by simple conditions on the present short rate. We
give conditions under which the short rate process will converge to a limit
distribution and describe the limit distribution in terms of its cumulant
generating function. We apply our results to the Vasicek model, the CIR model,
a CIR model with added jumps and a model of Ornstein-Uhlenbeck type
Heavy Quark Production and PDF's Subgroup Report
We present a status report of a variety of projects related to heavy quark
production and parton distributions for the Tevatron Run II.Comment: Latex. 8 pages, 7 eps figures. Contribution to the Physics at Run II
Workshops: QCD and Weak Boson Physic
Magnetoelastic coupling in triangular lattice antiferromagnet CuCrS2
CuCrS2 is a triangular lattice Heisenberg antiferromagnet with a rhombohedral
crystal structure. We report on neutron and synchrotron powder diffraction
results which reveal a monoclinic lattice distortion at the magnetic transition
and verify a magnetoelastic coupling. CuCrS2 is therefore an interesting
material to study the influence of magnetism on the relief of geometrical
frustration.Comment: 6 pages, 6 figures, 1 tabl
Web Service Discovery in a Semantically Extended UDDI Registry: the Case of FUSION
Service-oriented computing is being adopted at an unprecedented rate, making the effectiveness of automated service discovery an increasingly important challenge. UDDI has emerged as a de facto industry standard and fundamental building block within SOA infrastructures. Nevertheless, conventional UDDI registries lack means to provide unambiguous, semantically rich representations of Web service capabilities, and the logic inference power required for facilitating automated service discovery. To overcome this important limitation, a number of approaches have been proposed towards augmenting Web service discovery with semantics. This paper discusses the benefits of semantically extending Web service descriptions and UDDI registries, and presents an overview of the approach put forward in project FUSION, towards semantically-enhanced publication and discovery of services based on SAWSDL
Guidance of sentinel lymph node biopsy decisions in patients with T1-T2 melanoma using gene expression profiling.
AIM: Can gene expression profiling be used to identify patients with T1-T2 melanoma at low risk for sentinel lymph node (SLN) positivity?
PATIENTS & METHODS: Bioinformatics modeling determined a population in which a 31-gene expression profile test predicted \u3c5% SLN positivity. Multicenter, prospectively-tested (n = 1421) and retrospective (n = 690) cohorts were used for validation and outcomes, respectively.
RESULTS: Patients 55-64 years and â„65 years with a class 1A (low-risk) profile had SLN positivity rates of 4.9% and 1.6%. Class 2B (high-risk) patients had SLN positivity rates of 30.8% and 11.9%. Melanoma-specific survival was 99.3% for patients â„55 years with class 1A, T1-T2 tumors and 55.0% for class 2B, SLN-positive, T1-T2 tumors.
CONCLUSION: The 31-gene expression profile test identifies patients who could potentially avoid SLN biopsy
Generation and validation
Markov state models of molecular kinetics (MSMs), in which the long-time
statistical dynamics of a molecule is approximated by a Markov chain on a
discrete partition of configuration space, have seen widespread use in recent
years. This approach has many appealing characteristics compared to
straightforward molecular dynamics simulation and analysis, including the
potential to mitigate the sampling problem by extracting long-time kinetic
information from short trajectories and the ability to straightforwardly
calculate expectation values and statistical uncertainties of various
stationary and dynamical molecular observables. In this paper, we summarize
the current state of the art in generation and validation of MSMs and give
some important new results. We describe an upper bound for the approximation
error made by modelingmolecular dynamics with a MSM and we show that this
error can be made arbitrarily small with surprisingly little effort. In
contrast to previous practice, it becomes clear that the best MSM is not
obtained by the most metastable discretization, but the MSM can be much
improved if non-metastable states are introduced near the transition states.
Moreover, we show that it is not necessary to resolve all slow processes by
the state space partitioning, but individual dynamical processes of interest
can be resolved separately. We also present an efficient estimator for
reversible transition matrices and a robust test to validate that a MSM
reproduces the kinetics of the molecular dynamics data
On small-noise equations with degenerate limiting system arising from volatility models
The one-dimensional SDE with non Lipschitz diffusion coefficient is widely
studied in mathematical finance. Several works have proposed asymptotic
analysis of densities and implied volatilities in models involving instances of
this equation, based on a careful implementation of saddle-point methods and
(essentially) the explicit knowledge of Fourier transforms. Recent research on
tail asymptotics for heat kernels [J-D. Deuschel, P.~Friz, A.~Jacquier, and
S.~Violante. Marginal density expansions for diffusions and stochastic
volatility, part II: Applications. 2013, arxiv:1305.6765] suggests to work with
the rescaled variable : while
allowing to turn a space asymptotic problem into a small- problem
with fixed terminal point, the process satisfies a SDE in
Wentzell--Freidlin form (i.e. with driving noise ). We prove a
pathwise large deviation principle for the process as
. As it will become clear, the limiting ODE governing the
large deviations admits infinitely many solutions, a non-standard situation in
the Wentzell--Freidlin theory. As for applications, the -scaling
allows to derive exact log-asymptotics for path functionals of the process:
while on the one hand the resulting formulae are confirmed by the CIR-CEV
benchmarks, on the other hand the large deviation approach (i) applies to
equations with a more general drift term and (ii) potentially opens the way to
heat kernel analysis for higher-dimensional diffusions involving such an SDE as
a component.Comment: 21 pages, 1 figur
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