The collection and analysis of pre-evacuation times derived from evacuation trials and their application to evacuation modelling

This paper presents data relating to occupant pre-evacuation times from university and hospital outpatient facilities. Although the two occupancies are entirely different, they do employ relatively similar procedures: members of staff sweep areas to encourage individuals to evacuate.However the manner in which the dependent population reacts to these procedures is quite different. In the hospital case, the patients only evacuated once a member of the nursing staff had instructed them to do so, while in the university evacuation, the students were less dependent upon the actions of the staff, with over 50% of them evacuating with no prior prompting. In addition, the student pre-evacuation time was found to be dependent on their level of engagement in various activities.

A framework for state-based time-series analysis and prediction

Time-series analysis and prediction play an important role in state-based systems that involve dealing with varying situations in terms of states of the world evolving with time. Generally speaking, the world in the discourse persists in a given state until something occurs to it into another state. This paper introduces a framework for prediction and analysis based on time-series of states. It takes a time theory that addresses both points and intervals as primitive time elements as the temporal basis. A state of the world under consideration is defined as a set of time-varying propositions with Boolean truth-values that are dependent on time, including properties, facts, actions, events and processes, etc. A time-series of states is then formalized as a list of states that are temporally ordered one after another. The framework supports explicit expression of both absolute and relative temporal knowledge. A formal schema for expressing general time-series of states to be incomplete in various ways, while the concept of complete time-series of states is also formally defined. As applications of the formalism in time-series analysis and prediction, we present two illustrating examples.

Changes in the properties of Bacillus thuringiensis after prolonged culture in a rich medium

AIM: To investigate the effect of repeated culture in a rich medium on certain genetic, metabolic, pathogenic and structural characteristics of fresh isolates of Bacillus thuringiensis. METHODS AND RESULTS: Four strains of B. thuringiensis, which had been isolated in vegetative form from leaf surfaces, were grown for 500 generations in batch culture in a rich medium. One of the strains, S4g, differed from the parent in the following respects: greater cell width; changed plasmid profile; complete loss of ability to produce delta-endotoxins; loss of ability to produce beta-exotoxin and disruption of vip3 gene; radically different fatty acid composition; and altered metabolic activity. Two of the other evolved strains (S1g and S6g) showed differences in fatty acid profiles compared with the parents. Genetic finger-printing showed that there were also mutations in the cry genes of two of the evolved strains (S1g and S2g). The delta-endotoxins of strain S6g were significantly less toxic to the larvae of Pieris brassica compared with those of the parent and it also differed in the plasmid content. CONCLUSION: Radical and unpredictable changes can occur in fresh isolates of B. thuringiensis when subjected to growth in the laboratory. SIGNIFICANCE AND IMPACT OF THE STUDY: This is the first analysis of a Gram positive and biotechnologically significant bacterium after repeated laboratory culture. It is of great relevance to the biotechnological exploitation of B. thuringiensis that prolonged growth of environmental isolates on laboratory culture media can have profound effects on their structure, genome and virulence determinants.