174,794 research outputs found
Bayesian Nonparametric Hidden Semi-Markov Models
There is much interest in the Hierarchical Dirichlet Process Hidden Markov
Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous
Hidden Markov Model for learning from sequential and time-series data. However,
in many settings the HDP-HMM's strict Markovian constraints are undesirable,
particularly if we wish to learn or encode non-geometric state durations. We
can extend the HDP-HMM to capture such structure by drawing upon
explicit-duration semi-Markovianity, which has been developed mainly in the
parametric frequentist setting, to allow construction of highly interpretable
models that admit natural prior information on state durations.
In this paper we introduce the explicit-duration Hierarchical Dirichlet
Process Hidden semi-Markov Model (HDP-HSMM) and develop sampling algorithms for
efficient posterior inference. The methods we introduce also provide new
methods for sampling inference in the finite Bayesian HSMM. Our modular Gibbs
sampling methods can be embedded in samplers for larger hierarchical Bayesian
models, adding semi-Markov chain modeling as another tool in the Bayesian
inference toolbox. We demonstrate the utility of the HDP-HSMM and our inference
methods on both synthetic and real experiments
TumorML: Concept and requirements of an in silico cancer modelling markup language
This paper describes the initial groundwork carried out as part of the European Commission funded Transatlantic Tumor Model Repositories project, to develop a new markup language for computational cancer modelling, TumorML. In this paper we describe the motivations for such a language, arguing that current state-of-the-art biomodelling languages are not suited to the cancer modelling domain. We go on to describe the work that needs to be done to develop TumorML, the conceptual design, and a description of what existing markup languages will be used to compose the language specification
Limiting operations for sequences of quantum random variables and a convergence theorem for quantum martingales
We study quantum random variables and generalize several classical limit
results to the quantum setting. We prove a quantum analogue of Lebesgue's
dominated convergence theorem and use it to prove a quantum martingale
convergence theorem. This quantum martingale convergence theorem is of
particular interest since it exhibits non-classical behaviour; even though the
limit of the martingale exists and is unique, it is not explicitly
identifiable. However, we provide a partial classification of the limit through
a study of the space of all quantum random variables having quantum expectation
zero.Comment: 11 pages, 0 figure
Enhanced superconductivity and lattice instability in Nb-Rh alloys
Superconductivity with transition temperature above 10 °K has been observed in a new Nb-Rh intermediate phase. The new metastable phase is obtained by liquid quenching the binary alloy or by the addition of a small percentage of carbon to form a stable ternary alloy
Underwater optical wireless communications : depth dependent variations in attenuation
Depth variations in the attenuation coefficient for light in the ocean were calculated using a one-parameter model based on the chlorophyll-a concentration Cc and experimentally-determined Gaussian chlorophyll-depth profiles. The depth profiles were related to surface chlorophyll levels for the range 0–4 mg/m2, representing clear, open ocean. The depth where Cc became negligible was calculated to be shallower for places of high surface chlorophyll; 111.5 m for surface chlorophyll 0.8<Cc<2.2 mg/m3 compared with 415.5 m for surface Cc<0.04 mg/m3. Below this depth is the absolute minimum attenuation for underwater ocean communication links, calculated to be 0.0092 m−1 at a wavelength of 430 nm. By combining this with satellite surface-chlorophyll data, it is possible to quantify the attenuation between any two locations in the ocean, with applications for low-noise or secure underwater communications and vertical links from the ocean surface
Geometry of Banach spaces and biorthogonal systems
A separable Banach space X contains isomorphically if and only if X
has a bounded wc_0^*-stable biorthogonal system. The dual of a separable Banach
space X fails the Schur property if and only if X has a bounded
wc_0^*-biorthogonal system
Radio emission from the massive stars in the Galactic Super Star Cluster Westerlund 1
Current mass-loss rate estimates imply that main sequence winds are not
sufficient to strip away the H-rich envelope to yield Wolf-Rayet (WR) stars.
The rich transitional population of Westerlund 1 (Wd 1) provides an ideal
laboratory to observe mass-loss processes throughout the transitional phase of
stellar evolution. An analysis of deep radio continuum observations of Wd 1 is
presented. We detect 18 cluster members. The radio properties of the sample are
diverse, with thermal, non-thermal and composite thermal/non-thermal sources
present. Mass-loss rates are ~10^{-5} solar mass/year across all spectral
types, insufficient to form WRs during a massive star lifetime, and the stars
must undergo a period of enhanced mass loss. The sgB[e] star W9 may provide an
example, with a mass-loss rate an order of magnitude higher than the other
cluster members, and an extended nebula of density ~3 times the current wind.
This structure is reminiscent of luminous blue variables, and one with evidence
of two eras of high, possibly eruptive, mass loss. Three OB supergiants are
detected, implying unusually dense winds. They also may have composite spectra,
suggesting binarity. Spatially resolved nebulae are associated with three of
the four RSGs and three of the six YHGs in the cluster, which are due to
quiescent mass loss rather than outbursts. For some of the cool star winds, the
ionizing source may be a companion star though the cluster radiation density is
sufficiently high to provide the necessary ionizing radiation. Five WR stars
are detected with composite spectra, interpreted as arising in colliding-wind
binaries.Comment: 15 pages, 6 figures. Accepted for publication in Astronomy and
Astrophysic
Induced magnetosphere of Venus
Solar wind and ionospheric conductivity studied for role in inducing Venus or Mars magnetosphere
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