Using Bayesian networks to represent parameterised risk models for the UK railways

PhDThe techniques currently used to model risk and manage the safety of the UK railway network are not aligned to the mechanism by which catastrophic accidents occur in this industry. In this thesis, a new risk modelling method is proposed to resolve this problem. Catastrophic accidents can occur as the result of multiple failures occurring to all of the various defences put in place to prevent them. The UK railway industry is prone to this mechanism of accident occurrence, as many different technical, operational and organizational defences are used to prevent accidents. The railway network exists over a wide geographic area, with similar accidents possible at many different locations. The risk from these accidents is extremely variable and depends on the underlying conditions at each particular location, such as the state of assets or the speed of trains. When unfavourable conditions coincide the probability of multiple failures of planned defences increases and a 'risk hotspot' arises. Ideal requirements for modelling risk are proposed, taking account of the need to manage multiple defences of conceptually different type and the existence of risk hotspots. The requirements are not met by current risk modelling techniques although some of the requirements have been addressed experimentally, and in other industries and countries. It is proposed to meet these requirements using Bayesian Networks to supplement and extend fault and event tree analysis, the traditional techniques used for risk modelling in the UK railway industry. Application of the method is demonstrated using a case study: the building of a model of derailment risk on the UK railway network. The proposed method provides a means of better integrating industry wide analysis and risk modelling with the safety management tasks and safety related decisions that are undertaken by safety managers in the industry

Genome Sequence of Fusobacterium nucleatum Subspecies Polymorphum — a Genetically Tractable Fusobacterium

Fusobacterium nucleatum is a prominent member of the oral microbiota and is a common cause of human infection. F. nucleatum includes five subspecies: polymorphum, nucleatum, vincentii, fusiforme, and animalis. F. nucleatum subsp. polymorphum ATCC 10953 has been well characterized phenotypically and, in contrast to previously sequenced strains, is amenable to gene transfer. We sequenced and annotated the 2,429,698 bp genome of F. nucleatum subsp. polymorphum ATCC 10953. Plasmid pFN3 from the strain was also sequenced and analyzed. When compared to the other two available fusobacterial genomes (F. nucleatum subsp. nucleatum, and F. nucleatum subsp. vincentii) 627 open reading frames unique to F. nucleatum subsp. polymorphum ATCC 10953 were identified. A large percentage of these mapped within one of 28 regions or islands containing five or more genes. Seventeen percent of the clustered proteins that demonstrated similarity were most similar to proteins from the clostridia, with others being most similar to proteins from other gram-positive organisms such as Bacillus and Streptococcus. A ten kilobase region homologous to the Salmonella typhimurium propanediol utilization locus was identified, as was a prophage and integrated conjugal plasmid. The genome contains five composite ribozyme/transposons, similar to the CdISt IStrons described in Clostridium difficile. IStrons are not present in the other fusobacterial genomes. These findings indicate that F. nucleatum subsp. polymorphum is proficient at horizontal gene transfer and that exchange with the Firmicutes, particularly the Clostridia, is common