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 $\ell_1$ 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