Comment: Expert Elicitation for Reliable System Design

Comment: Expert Elicitation for Reliable System Design [arXiv:0708.0279]Comment: Published at http://dx.doi.org/10.1214/088342306000000529 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

A hybrid Bayesian network for medical device risk assessment and management

ISO 14971 is the primary standard used for medical device risk management. While it specifies the requirements for medical device risk management, it does not specify a particular method for performing risk management. Hence, medical device manufacturers are free to develop or use any appropriate methods for managing the risk of medical devices. The most commonly used methods, such as Fault Tree Analysis (FTA), are unable to provide a reasonable basis for computing risk estimates when there are limited or no historical data available or where there is second-order uncertainty about the data. In this paper, we present a novel method for medical device risk management using hybrid Bayesian networks (BNs) that resolves the limitations of classical methods such as FTA and incorporates relevant factors affecting the risk of medical devices. The proposed BN method is generic but can be instantiated on a system-by-system basis, and we apply it to a Defibrillator device to demonstrate the process involved for medical device risk management during production and post-production. The example is validated against real-world data

Representations of matroids

The concept of matroids was originally introduced by Whitney and Van der Waerden in the 1930's to generalise the notion of linear dependence in a vector space; certain axioms satisfied by this relation were observed to be satisfied by other types of ’ dependence’ relations, such as algebraic dependence and ’ cycle’ dependence in a graph. Consequently a matroid was defined to be a set with an abstract dependence relation satisfying these axioms. One of the most natural questions to ask is whether every such ’ matroid' is representable in the obvious sense in a vector space. The answer is of course no (otherwise matroid theory would be equivalent to linear algebra) although in the early years of the subject examples of non-representable matroids were not easily obtainable. In this thesis we continue the work of Inglcton (in [20]) and Vamos (in [35,36]) on the representation problem, buiding up to an algebraic treatment in the important last chapter

Re-assessing the infection strategies of the entomopathogenic nematode Steinernema feltiae (Rhabditidae; Steinernematidae)

Previous studies have indicated that between 60 and 80% of a population of entomopathogenic nematodes do not infect their insect hosts at any one period in time. Two hypotheses explain this behaviour: the first that there is a subpopulation of non-infectious nematodes and the second that the non-infectious group is created by inhibitory cues derived from infected insects. Through an experimental approach with the Galleria mellonella-Steinernema feltiae system we show that both mechanisms operate together. When conditions for infection were optimized, the sum of individual infection behaviours was similar to the number infecting as a population, implying observed infection rates are driven by intrinsic mechanisms. In addition, there was evidence that an infected host released a chemical cue into the environment which inhibited subsequent levels of infection. This degree of inhibition was independent of the number of infecting nematodes. Both these mechanisms are dynamic, so the observed proportion of infectious nematodes depended heavily on the time of exposure. The implications of these findings for both the design of laboratory trials and the use of entomopathogenic nematodes in biological control are discussed