Distributed Gaussian processes

To scale Gaussian processes (GPs) to large data sets we introduce the robust Bayesian Committee Machine (rBCM), a practical and scalable product-of-experts model for large-scale distributed GP regression. Unlike state-of-theart sparse GP approximations, the rBCM is conceptually simple and does not rely on inducing or variational parameters. The key idea is to recursively distribute computations to independent computational units and, subsequently, recombine them to form an overall result. Efficient closed-form inference allows for straightforward parallelisation and distributed computations with a small memory footprint. The rBCM is independent of the computational graph and can be used on heterogeneous computing infrastructures, ranging from laptops to clusters. With sufficient computing resources our distributed GP model can handle arbitrarily large data sets

A practical measurement of thoracic sarcopenia: Correlation with clinical parameters and outcomes in advanced lung cancer

Thoracic sarcopenia can feasibly be measured from routine CT scans but does not correlate to patient-centred outcomes http://ow.ly/102UkQ

Counterflow dielectrophoresis for trypanosome enrichment and detection in blood

Human African trypanosomiasis or sleeping sickness is a deadly disease endemic in sub-Saharan Africa, caused by single-celled protozoan parasites. Although it has been targeted for elimination by 2020, this will only be realized if diagnosis can be improved to enable identification and treatment of afflicted patients. Existing techniques of detection are restricted by their limited field-applicability, sensitivity and capacity for automation. Microfluidic-based technologies offer the potential for highly sensitive automated devices that could achieve detection at the lowest levels of parasitemia and consequently help in the elimination programme. In this work we implement an electrokinetic technique for the separation of trypanosomes from both mouse and human blood. This technique utilises differences in polarisability between the blood cells and trypanosomes to achieve separation through opposed bi-directional movement (cell counterflow). We combine this enrichment technique with an automated image analysis detection algorithm, negating the need for a human operator

Session-ocaml: a session-based library with polarities and lenses

We propose session-ocaml, a novel library for session-typed concurrent/distributed programming in OCaml. Our technique solely relies on parametric polymorphism, which can encode core session type structures with strong static guarantees. Our key ideas are: ( ) polarised session types, which give an alternative formulation of duality enabling OCaml to automatically infer an appropriate session type in a session with a reasonable notational overhead; and ( ) a parameterised monad with a data structure called ‘slots’ manipulated with lenses, which can statically enforce session linearity and delegations. We show applications of session-ocaml including a travel agency usecase and an SMTP protocol

Near-Complete Genome Sequences of Several New Norovirus Genogroup II Genotypes.

We report here the near-complete genome sequences of 13 norovirus strains detected in stool samples from patients with acute gastroenteritis from Bangladesh, Ecuador, Guatemala, Peru, Nicaragua, and the United States that are classified into one existing (genotype II.22 [GII.22]), 3 novel (GII.23, GII.24 and GII.25), and 3 tentative novel (GII.NA1, GII.NA2, and GII.NA3) genotypes

Evaluation of stability of directly standardized rates for sparse data using simulation methods.

Background Directly standardized rates (DSRs) adjust for different age distributions in different populations and enable, say, the rates of disease between the populations to be directly compared. They are routinely published but there is concern that a DSR is not valid when it is based on a “small” number of events. The aim of this study was to determine the value at which a DSR should not be published when analyzing real data in England. Methods Standard Monte Carlo simulation techniques were used assuming the number of events in 19 age groups (i.e., 0–4, 5–9, ... 90+ years) follow independent Poisson distributions. The total number of events, age specific risks, and the population sizes in each age group were varied. For each of 10,000 simulations the DSR (using the 2013 European Standard Population weights), together with the coverage of three different methods (normal approximation, Dobson, and Tiwari modified gamma) of estimating the 95% confidence intervals (CIs), were calculated. Results The normal approximation was, as expected, not suitable for use when fewer than 100 events occurred. The Tiwari method and the Dobson method of calculating confidence intervals produced similar estimates and either was suitable when the expected or observed numbers of events were 10 or greater. The accuracy of the CIs was not influenced by the distribution of the events across categories (i.e., the degree of clustering, the age distributions of the sampling populations, and the number of categories with no events occurring in them). Conclusions DSRs should not be given when the total observed number of events is less than 10. The Dobson method might be considered the preferred method due to the formulae being simpler than that of the Tiwari method and the coverage being slightly more accurate

The globalisation of breast cancer

Boyle, Peter Howell, Antony eng England 2011/01/05 06:00 Breast Cancer Res. 2010 Dec 20;12 Suppl 4:S7. doi: 10.1186/bcr2736.International audienceno abstrac