Bursting emission from B0611+22

Over the past decade it has become apparent that a class of `bursting pulsars' exist with the discovery of PSR J1752+2359 and PSR J1938+2213. In these pulsars, a sharp increase in the emission is observed that then tends to systematically drop-off from pulse-to-pulse. In this paper we describe the discovery of such a relationship in high-sensitivity observations of the young (characteristic age of 90,000 yrs) 0.33 s pulsar B0611+22 at both 327 MHz and 1400 MHz with the Arecibo radio telescope. While Nowakowski previously showed that B0611+22 has mode-switching properties, the data presented here show, for the first time, that this pulsar emits bursts with characteristic time-scales of several hundred seconds. At 327 MHz, the pulsar shows steady behaviour in one emission mode which is enhanced by bursting emission slightly offset in pulse phase from this steady emission. Contrastingly at 1400 MHz, the two modes appear to behave in a competing operation while still offset in phase. Using a fluctuation spectrum analysis, we also investigate each mode independently for sub-pulse drifting. Neither emission mode (i.e. during bursts or persistent emission) shows the presence of the drifting sub-pulse phenomenon. The bursting phenomena seen here appears to be a hybrid between bursting seen in other pulsars and the bistable profile illumination behaviour reported in two other pulsars by Rankin et al. Further examples of this cross-frequency behaviour are required, as this phenomenon may be quite common among the pulsar population.Comment: 12 pages, 11 figure

Institutionalising future geographies of financial inclusion: national legitimacy versus local autonomy in the British credit union movement.

This paper provides a critical overview of recent developments in British credit union development, and contributed to the broader analysis of alternative financial/economic spaces and (the geographies of) alterity. The paper was underpinned by a wide range of local, national and international conference presentations including the National Association of Credit Union Workers, Birmingham, 2001; Combating Financial Exclusion, Salford, 2001; Association of American Geographers, New York, 2001, New Orleans, 2003; Alternative Economic Spaces, Hull, 2005; and discussions with local user communities throughout the UK (including through non-academic publishing, such as SCCD news and New Start articles)

A Bayesian space–time model for clustering areal units based on their disease trends

Population-level disease risk across a set of non-overlapping areal units varies in space and time, and a large research literature has developed methodology for identifying clusters of areal units exhibiting elevated risks. However, almost no research has extended the clustering paradigm to identify groups of areal units exhibiting similar temporal disease trends. We present a novel Bayesian hierarchical mixture model for achieving this goal, with inference based on a Metropolis-coupled Markov chain Monte Carlo ((MC) 3 ) algorithm. The effectiveness of the (MC) 3 algorithm compared to a standard Markov chain Monte Carlo implementation is demonstrated in a simulation study, and the methodology is motivated by two important case studies in the United Kingdom. The first concerns the impact on measles susceptibility of the discredited paper linking the measles, mumps, and rubella vaccination to an increased risk of Autism and investigates whether all areas in the Scotland were equally affected. The second concerns respiratory hospitalizations and investigates over a 10 year period which parts of Glasgow have shown increased, decreased, and no change in risk

Capacity-building and community control of local economic assets

This paper explores the major changes and challenges confronting British credit unions, and highlights some of their implications in relation to notions of capacity-building. The paper’s key themes were presented at a wide range of local, national and international conference presentations including the National Association of Credit Union Workers, Birmingham, 2001; ESRC ‘Capacity building: learning for community economic development’ seminar series, ‘Seminar Three: Capacity-building and community control of local economic assets’, Salford University, 2001; Alternative Economic Spaces, Hull, 2005; and via discussions with local user communities throughout the UK (including through non-academic publishing, including SCCD news and New Start articles)

Cluster detection and risk estimation for spatio-temporal health data

In epidemiological disease mapping one aims to estimate the spatio-temporal pattern in disease risk and identify high-risk clusters, allowing health interventions to be appropriately targeted. Bayesian spatio-temporal models are used to estimate smoothed risk surfaces, but this is contrary to the aim of identifying groups of areal units that exhibit elevated risks compared with their neighbours. Therefore, in this paper we propose a new Bayesian hierarchical modelling approach for simultaneously estimating disease risk and identifying high-risk clusters in space and time. Inference for this model is based on Markov chain Monte Carlo simulation, using the freely available R package CARBayesST that has been developed in conjunction with this paper. Our methodology is motivated by two case studies, the first of which assesses if there is a relationship between Public health Districts and colon cancer clusters in Georgia, while the second looks at the impact of the smoking ban in public places in England on cardiovascular disease clusters