C.M. Triggs

Morphological distinction of molecular types in Ammonia – towards a taxonomic revision of the world’s most commonly misidentified foraminifera

Abstract In this study, morphometric analysis has been performed on 178 Ammonia specimens belonging to 12 different molecular types, plus non-sequenced type specimens of Ammonia beccarii and A. tepida. Molecular type distinction is based on phylogenetic analysis of 267 partial LSU rDNA sequences, obtained from 202 living Ammonia specimens, sampled in 30 localities from 17 countries bordering the Pacific Ocean, Atlantic Ocean, Mediterranean Sea, Caribbean Sea and North Sea. Restriction fragment length polymorphism (analysis was carried out for another seven specimens. Morphometric analysis was based on measurements or assessments of 37 external test characters in spiral, umbilical, profile and close-up Scanning Electron Microscopic views. Cluster analysis, canonical variates analysis, and detrended correspondence analysis, performed on the morphological data set, suggest that each molecular type can be distinguished morphologically and can be regarded as a separate species. Primary types of A. tepida and topotypes of A. beccarii are shown to be morphologically separate from any of the molecular types so far recognised. We are aware of at least 9 more distinctive morphotypes that have not yet been sequenced, and thus we infer that the total number of genetically distinct and morphologically separable living species of Ammonia worldwide is likely to exceed 25–30. At this stage not all molecular types can be unequivocally assigned to formally described species. Several genetically-based species can be distinguished by the presence of one distinct character, but most are discriminated on the basis of a combination of many different characters. Morphological characters (e.g. test shape, chamber shape, porosity, prolocular diameter, folium shape, radial furrow length, umbilical diameter) are shown to be slightly more valuable in separating the molecular types than surficial ornament (beads, pustules, bosses, secondary calcite). One highly distinctive group (2–3 species – beccarii, batava, ?inflata) is readily discriminated on the basis of its large test size, strongly beaded and grooved ornament, and the presence of fissures along the sutures on the spiral side. The results of this study imply that the widespread practice of recognising only one, two or three species of Recent Ammonia worldwide should be abandoned. The most commonly used name, Ammonia beccarii, should be restricted to a large, compressed, highly ornamented species, so far not recognised beyond its type locality in the Adriatic Sea. Other commonly used names, such as A. parkinsoniana and A. tepida, apply to species with far more restricted distributions than the literature would suggest.

A Comparative Study of Cost Estimation Models for Web Hypermedia Applications

Software cost models and effort estimates help project managers allocate resources, control costs and schedule and improve current practices, leading to projects finished on time and within budget. In the context of Web development, these issues are also crucial, and very challenging given that Web projects have short schedules and very fluidic scope. In the context of Web engineering, few studies have compared the accuracy of different types of cost estimation techniques with emphasis placed on linear and stepwise regressions, and case-based reasoning (CBR). To date only one type of CBR technique has been employed in Web engineering. We believe results obtained from that study may have been biased, given that other CBR techniques can also be used for effort prediction. Consequently, the first objective of this study is to compare the prediction accuracy of three CBR techniques to estimate the effort to develop Web hypermedia applications and to choose the one with the best estimates. The second objective is to compare the prediction accuracy of the best CBR technique against two commonly used prediction models, namely stepwise regression and regression trees. One dataset was used in the estimation process and the results showed that the best predictions were obtained for stepwise regression.

A comparison of development effort estimation techniques for Web hypermedia applications

Several studies have compared the prediction accuracy of different types of techniques with emphasis placed on linear and stepwise regressions, and case-based reasoning (CBR). We believe the use of only one type of CBR technique may bias the results, as there are others that can also be used for effort prediction. This paper has two objectives. The first is to compare the prediction accuracy of three CBR techniques to estimate the effort to develop Web hypermedia applications. The second objective is to compare the prediction accuracy of the best CBR technique, according to our findings, against three commonly used prediction models, namely multiple linear regression, stepwise regression and regression trees. One dataset was used in the estimation process and the results showed that different measures of prediction accuracy gave different results. MMRE and MdMRE showed better prediction accuracy for multiple regression models whereas box plots showed better accuracy for CBR.

The interpretation of elemental composition measurements from forensic glass evidence III.

In this paper we introduce a permutation testing approach to the interpretation of evidence which consists of elemental composition measurements, with glass evidence as an example. This work extends previous work of Curran et al. [J.M. Curran, C.M. Triggs, J.R. Almirall, J.S. Buckleton and K.AJ. Walsh, The interpretation of elemental composition measurements from forensic glass evidence, Science and Justice 37 (1997) 241-244.] and shows how we may remove some of the constraints that limited the applicability of the previous results. We provide the reader with tools for evidence pre-screening that may aid in the direction of further analyses of the data, rather than for the presentation of evidence interpretation in a court case.

An extended likelihood ratio framework for interpreting evidence.

This paper reviews some current methods, the likelihood ratio-based approach and the full Bayesian approach for the interpretation of evidence and discusses previously identified shortcomings in them. It suggests an approach based on a compromise--based on an extended likelihood ratio--that may combine the merits of logic without overstepping acceptable bounds for the forensic scientist in the presentation of evidence. The approach is exposed formally and takes advantage of inferential networks called Bayesian networks.

ASSESSING TRANSFER PROBABILITIES IN A BAYESIAN INTERPRETATION OF FORENSIC GLASS EVIDENCE

When someone breaks glass a number of tiny fragments may be transferred to that person. If the glass is broken in the commission of a crime then these fragments may be used as evidence. A Bayesian interpretation of this evidence relies on the forensic scientists ability to assess the probability of transfer. This paper examines the problem of assessing this probability and suggests some solutions.

Glass on clothing and shoes of members of the general population and people suspected of breaking crimes

The outer clothing and footwear of 122 people attending a university gymnasium and a private gymnasium were searched for fragments of glass. Both the surfaces and the pockets of the clothing and the uppers and soles of the footwear were searched. New Zealand forensic glass cases have been reviewed to determine the amount of non-matching glass present on the clothing of people who are suspected of breaking crimes. Data from 114 suspects who had no matching glass on their clothing and shoes were accumulated. Statistical modelling techniques have been applied to the data collected.

The sensitivity of the Bayesian HPD method to the choice of prior

Statistical sampling error is present in every statistical calculations using DNA because all such statistics rely on a sample (database) of individuals, which is used to estimate the population frequencies of alleles. Curran et al.gave a method for estimating the sampling error of the statistics based on the region of the highest density of the Bayesian posterior (HPD). The Bayesian HPD method relies on the assumption of a prior distribution for the population allele frequencies as well as Monte Carlo simulation. In this paper we answer three pivotal questions. Firstly we address the question of how many Monte Carlo iterations are required to get sufficient accuracy in our estimates of sampling error. Secondly, we address the question of the appropriate choice of the prior distribution for the population allele frequencies. Thirdly, we demonstrate the flexibility of the Bayesian HPD over other methods.

SAMPLING IN FORENSIC COMPARISON PROBLEMS

When someone breaks glass a number of tiny fragments may be transferred to that person. If the glass is broken in the commission of a crime then these fragments may be used as evidence. If a large number of fragments are recovered from the suspect, then it may be more efficient for the forensic scientist to examine a subset of these fragments. Such sampling incurs information loss. This paper will derive an expression that allows a partial quantification of this loss. The loss of such information due to the examination of a subset of recovered material arises with many forms of evidence.

The robustness of a continuous likelihood approach to bayesian analysis of forensic glass evidence

Abstract In previous work [1] , [2] , [3] the authors [K.A.J. Walsh, J.S. Buckleton, C.M. Triggs, A practical example of glass interpretation, Sci. Justice 36 (1996) 213–218; J.M. Curran, Forensic application of Bayesian interference to glass evidence, Ph.D. Thesis, Department of Statistics, University of Auckland, 1997; J.M. Curran, C.M. Triggs, J.S. Buckleton, S. Coulson, Combining a continuous Bayesian approach with grouping information, Forensic Sci. Int. 91 (1998) 181–196] have presented various aspects of a Bayesian interpretation of forensic glass evidence. Such an interpretation relies on assumptions that may not hold. This paper demonstrates the robustness of the Bayesian approach to deviations from the statistically convenient notion of normality of the measurements.