Janet Chaseling

Repeat Burglary Victimisation: spatial and temporal patterns

To date there has been little Australian research on repeat victimisation. This is a study of repeat burglary in an area of Brisbane using police calls for service data. We demonstrate: (a) the prevalence of residential repeat victim addresses (‘hot dot’) is of a similar magnitude to that found in studies in the United Kingdom; (b) the time distributions of revictimisation are identical with those found in studies in the UK and elsewhere; (c) ‘hot spots’ (small areas with high crime density) can be identified by statistical analyses of spatial concentrations of incidents; (d) unstable hot spots tend to be temporary aggregations of hot dots, whereas stable hot spots seem to reflect more the social and physical characteristics of certain localities; and (e) the overall incidence of burglary could be reduced by at least 25 per cent if all repeat victimisation could be eliminated. There are a number of areas where concepts and techniques for repeat victim research could potentially be strengthened: (a) clarifying the connections between hot dots and hot spots, particularly through exploration of the concept of a ‘near repeat address’; (b) applying survival analysis to the data on the time periods between victimisations; and (c) using moving average techniques to examine changes in the spatial distributions of burglary over time.

Powers of discrete goodness-of-fit test statistics for a uniform null against a selection of alternative distributions

The comparative powers of six discrete goodness-of-fit test statistics for a uniform null distribution against a variety of fully specified alternative distributions are discussed. The results suggest that the test statistics based on the empirical distribution function for ordinal data (Kolmogorov–Smirnov, Cramér–von Mises, and Anderson–Darling) are generally more powerful for trend alternative distributions. The test statistics for nominal (Pearsons chi-square and the nominal Kolmogorov–Smirnov) and circular data (Watsons test statistic) are shown to be generally more powerful for the investigated triangular (∨), flat (or platykurtic type), sharp (or leptokurtic type), and bimodal alternative distributions.

A comparison of two methods for generating artificial multi-assemblage ecological datasets

Simulated ecological data sets have been widely used to assess the ability of ordination techniques to portray patterns in ecological assemblage data. Such data sets typically contain a single assemblage sampled over an environmental gradient or set of gradients. Little has been done on the generation of artificial data sets that contain a number of different species assemblages, to aid in the evaluation of multivariate techniques that test for differences between assemblages of species. This paper describes and compares two simulation methods that generate ecologically realistic artificial multi-assemblage data sets. Both methods provide multivariate data (e.g. species abundances) for replicate sites within discretely different assemblages. The first technique is a coenocline model based on species responses to variation modeled by a five-parameter β-function, where variation in species abundances both within and between assemblages is governed by differences in the positions of sites and assemblages along environmental gradients. The second technique, the resampling method, involves bootstrap resampling of real assemblage data sets, with the addition of selected types of controlled differences between assemblages. Here we use it to generate turnover in species composition. We calibrate both simulation methods based on a field assemblage of bird species. The two different simulation methods portray different levels and types of between-assemblage variation. The resampling method allows greater control over some aspects of assemblage difference (e.g. independently varying differences in species richness and compositional turnover) than the coenocline method. Both can generate usable replicated simulated data sets for assessing the ability of multivariate tests to detect ecological variation among assemblages.

An Evaluation of the Thai Tsunami Victim Identification DNA Operation

ABSTRACT The Thai Tsunami Victim Identification operation was the largest disaster victim identification operation in history, involving 3,679 unidentified victims from 41 countries, and police and forensic scientists from over 30 countries. This paper evaluates the DNA response to the 26 December 2004 South-East Asia Tsunami, measuring its impact at different stages of the operation. Only 15 identifications were established using DNA during the first 5 months, compared to 307 by fingerprints, 1,266 by dental, and 11 by physical analysis. Critical obstacles, such as available ante-mortem and post-mortem DNA profiles, data management challenges, and automated DNA matching issues were impeding the DNA response. Recognizing and resolving the key issues hindering DNA identification resulted in increased DNA identifications during the middle and late stages of the operation. Consideration of victim demographics was crucial to understanding the impact of different identification methods during the operation. DNA identifications were found to be primarily dependent on victim age and nationality. A large proportion of children from all nations were identified by DNA (33% of 10 to 16 year olds, 43% of 5 to 9 year olds, and 73% of 0 to 4 year olds), while only 13% of total adult identifications were supported though DNA analysis. Similarly, while DNA identified only 2% of adults from Finland, France, Germany, and Sweden combined, DNA was responsible for 30% of Thai adult identifications. By 16 July 2008, 3,308 victims were identified: 799 (24%) by DNA, 1,337 (40%) by dental, 1,142 (35%) by fingerprint, and 30 (1%) by physical characteristics.

Tissue preservation in extreme temperatures for rapid response to military deaths

Many deployable forensic capabilities, including those used by the Australian Defense Force (ADF), employ mobile battery-operated fridge/freezers for DNA sample preservation that are not suitable for rapid response application due to their size and weight. These fridge/freezers are expensive, require regular specialised maintenance, and have a set payload. A variety of transport media are successful preservatives for DNA samples, however, there is no research specifically targeted to their suitability for operational environments where temperatures exceed 50 °C. This research examined whether sodium chloride (NaCl), ethanol, and dimethyl sulfoxide (DMSO) could preserve muscle and bone samples (fresh and early decomposition) as effectively as refrigeration, when stored at 21 °C, 45 °C, 55 °C, and 65 °C for at least one week. A total of 78 muscle and 78 bone samples were collected from an unknown deceased individual. Half of each tissue type was stored at 30 °C for 48 h to induce early decomposition. Following this, samples were stored in the transport media for one week at the above temperatures, and a control set of samples were refrigerated (-4 °C) without any transport media. Preserved samples would need to provide DNA profiles comparable to the refrigerated samples for the transport media to be considered a successful replacement method. NaCl and 70% ethanol preserved muscle samples (fresh and decomposed) up to 65 °C, as well as 70% ethanol and 20% DMSO for fresh bone samples. These results were comparable with refrigeration and therefore, these preservatives could be used in rapid response operations by the military and for disaster victim identification. Conversely, under the conditions of this study, 20% DMSO and 70% ethanol failed to consistently produce full DNA profiles from decomposed bone, and NaCl performed poorly at preserving DNA from fresh and decomposed bone samples.