Decentralised Clinical Guidelines Modelling with Lightweight Coordination Calculus

Background: Clinical protocols and guidelines have been considered as a major means to ensure that cost-effective services are provided at the point of care. Recently, the computerisation of clinical guidelines has attracted extensive research interest. Many languages and frameworks have been developed. Thus far, however,an enactment mechanism to facilitate decentralised guideline execution has been a largely neglected line of research. It is our contention that decentralisation is essential to maintain a high-performance system in pervasive health care scenarios. In this paper, we propose the use of Lightweight Coordination Calculus (LCC) as a feasible solution. LCC is a light-weight and executable process calculus that has been used successfully in multi-agent systems, peer-to-peer (p2p) computer networks, etc. In light of an envisaged pervasive health care scenario, LCC, which represents clinical protocols and guidelines as message-based interaction models, allows information exchange among software agents distributed across different departments and/or hospitals. Results: We outlined the syntax and semantics of LCC; proposed a list of refined criteria against which the appropriateness of candidate clinical guideline modelling languages are evaluated; and presented two LCC interaction models of real life clinical guidelines. Conclusions: We demonstrated that LCC is particularly useful in modelling clinical guidelines. It specifies the exact partition of a workflow of events or tasks that should be observed by multiple "players" as well as the interactions among these "players". LCC presents the strength of both process calculi and Horn clauses pair of which can provide a close resemblance of logic programming and the flexibility of practical implementation

Spatially Adaptive Stochastic Methods for Fluid-Structure Interactions Subject to Thermal Fluctuations in Domains with Complex Geometries

We develop stochastic mixed finite element methods for spatially adaptive simulations of fluid-structure interactions when subject to thermal fluctuations. To account for thermal fluctuations, we introduce a discrete fluctuation-dissipation balance condition to develop compatible stochastic driving fields for our discretization. We perform analysis that shows our condition is sufficient to ensure results consistent with statistical mechanics. We show the Gibbs-Boltzmann distribution is invariant under the stochastic dynamics of the semi-discretization. To generate efficiently the required stochastic driving fields, we develop a Gibbs sampler based on iterative methods and multigrid to generate fields with $O(N)$ computational complexity. Our stochastic methods provide an alternative to uniform discretizations on periodic domains that rely on Fast Fourier Transforms. To demonstrate in practice our stochastic computational methods, we investigate within channel geometries having internal obstacles and no-slip walls how the mobility/diffusivity of particles depends on location. Our methods extend the applicability of fluctuating hydrodynamic approaches by allowing for spatially adaptive resolution of the mechanics and for domains that have complex geometries relevant in many applications

Statistical analysis of variability properties of the Kepler blazar W2R 1926+42

We analyzed Kepler light curves of the blazar W2R 1926+42 that provided nearly continuous coverage from quarter 11 through quarter 17 (589 days between 2011 and 2013) and examined some of their flux variability properties. We investigate the possibility that the light curve is dominated by a large number of individual flares and adopt exponential rise and decay models to investigate the symmetry properties of flares. We found that those variations of W2R 1926+42 are predominantly asymmetric with weak tendencies toward positive asymmetry (rapid rise and slow decay). The durations (D) and the amplitudes (F0) of flares can be fit with log-normal distributions. The energy (E) of each flare is also estimated for the first time. There are positive correlations between logD and logE with a slope of 1.36, and between logF0 and logE with a slope of 1.12. Lomb-Scargle periodograms are used to estimate the power spectral density (PSD) shape. It is well described by a power law with an index ranging between -1.1 and -1.5. The sizes of the emission regions, R, are estimated to be in the range of 1.1*10^15 cm - 6.6*10^16 cm. The flare asymmetry is difficult to explain by a light travel time effect but may be caused by differences between the timescales for acceleration and dissipation of high-energy particles in the relativistic jet. A jet-in-jet model also could produce the observed log-normal distributions