47 resultados para Bayesian approach


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The fight against doping is mainly focused on direct detection, using analytical methods for the detection of doping agents in biological samples. However, the World Anti-Doping Code also defines doping as possession, administration or attempted administration of prohibited substances or methods, trafficking or attempted trafficking in any prohibited substance or methods. As these issues correspond to criminal investigation, a forensic approach can help assessing potential violation of these rules.In the context of a rowing competition, genetic analyses were conducted on biological samples collected in infusion apparatus, bags and tubing in order to obtain DNA profiles. As no database of athletes' DNA profiles was available, the use of information from the location detection as well as contextual information were key to determine a population of suspected athletes and to obtain reference DNA profiles for comparison.Analysis of samples from infusion systems provided 8 different DNA profiles. The comparison between these profiles and 8 reference profiles from suspected athletes could not be distinguished.This case-study is one of the first where a forensic approach was applied for anti-doping purposes. Based on this investigation, the International Rowing Federation authorities decided to ban not only the incriminated athletes, but also the coaches and officials for 2 years.

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To provide a quantitative support to the handwriting evidence evaluation, a new method was developed through the computation of a likelihood ratio based on a Bayesian approach. In the present paper, the methodology is briefly described and applied to data collected within a simulated case of a threatening letter. Fourier descriptors are used to characterise the shape of loops of handwritten characters "a" of the true writer of the threatening letter, and: 1) with reference characters "a" of the true writer of the threatening letter, and then 2) with characters "a" of a writer who did not write the threatening letter. The findings support that the probabilistic methodology correctly supports either the hypothesis of authorship or the alternative hypothesis. Further developments will enable the handwriting examiner to use this methodology as a helpful assistance to assess the strength of evidence in handwriting casework.

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We present a Bayesian approach for estimating the relative frequencies of multi-single nucleotide polymorphism (SNP) haplotypes in populations of the malaria parasite Plasmodium falciparum by using microarray SNP data from human blood samples. Each sample comes from a malaria patient and contains one or several parasite clones that may genetically differ. Samples containing multiple parasite clones with different genetic markers pose a special challenge. The situation is comparable with a polyploid organism. The data from each blood sample indicates whether the parasites in the blood carry a mutant or a wildtype allele at various selected genomic positions. If both mutant and wildtype alleles are detected at a given position in a multiply infected sample, the data indicates the presence of both alleles, but the ratio is unknown. Thus, the data only partially reveals which specific combinations of genetic markers (i.e. haplotypes across the examined SNPs) occur in distinct parasite clones. In addition, SNP data may contain errors at non-negligible rates. We use a multinomial mixture model with partially missing observations to represent this data and a Markov chain Monte Carlo method to estimate the haplotype frequencies in a population. Our approach addresses both challenges, multiple infections and data errors.

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This paper extends previous research [1] on the use of multivariate continuous data in comparative handwriting examinations, notably for gender classification. A database has been constructed by analyzing the contour shape of loop characters of type a and d by means of Fourier analysis, which allows characters to be described in a global way by a set of variables (e.g., Fourier descriptors). Sample handwritings were collected from right- and left-handed female and male writers. The results reported in this paper provide further arguments in support of the view that investigative settings in forensic science represent an area of application for which the Bayesian approach offers a logical framework. In particular, the Bayes factor is computed for settings that focus on inference of gender and handedness of the author of an incriminated handwritten text. An emphasis is placed on comparing the efficiency for investigative purposes of characters a and d.

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Recognition and identification processes for deceased persons. Determining the identity of deceased persons is a routine task performed essentially by police departments and forensic experts. This thesis highlights the processes necessary for the proper and transparent determination of the civil identities of deceased persons. The identity of a person is defined as the establishment of a link between that person ("the source") and information pertaining to the same individual ("identifiers"). Various identity forms could emerge, depending on the nature of the identifiers. There are two distinct types of identity, namely civil identity and biological identity. The paper examines four processes: identification by witnesses (the recognition process) and comparisons of fingerprints, dental data and DNA profiles (the identification processes). During the recognition process, the memory function is examined and helps to clarify circumstances that may give rise to errors. To make the process more rigorous, a body presentation procedure is proposed to investigators. Before examining the other processes, three general concepts specific to forensic science are considered with regard to the identification of a deceased person, namely, matter divisibility (Inman and Rudin), transfer (Locard) and uniqueness (Kirk). These concepts can be applied to the task at hand, although some require a slightly broader scope of application. A cross comparison of common forensic fields and the identification of deceased persons reveals certain differences, including 1 - reverse positioning of the source (i.e. the source is not sought from traces, but rather the identifiers are obtained from the source); 2 - the need for civil identity determination in addition to the individualisation stage; and 3 - a more restricted population (closed set), rather than an open one. For fingerprints, dental and DNA data, intravariability and intervariability are examined, as well as changes in these post mortem (PM) identifiers. Ante-mortem identifiers (AM) are located and AM-PM comparisons made. For DNA, it has been shown that direct identifiers (taken from a person whose civil identity has been alleged) tend to lead to determining civil identity whereas indirect identifiers (obtained from a close relative) direct towards a determination of biological identity. For each process, a Bayesian model is presented which includes sources of uncertainty deemed to be relevant. The results of the different processes combine to structure and summarise an overall outcome and a methodology. The modelling of dental data presents a specific difficulty with respect to intravariability, which in itself is not quantifiable. The concept of "validity" is, therefore, suggested as a possible solution to the problem. Validity uses various parameters that have an acknowledged impact on teeth intravariability. In cases where identifying deceased persons proves to be extremely difficult due to the limited discrimination of certain procedures, the use of a Bayesian approach is of great value in bringing a transparent and synthetic value. RESUME : Titre: Processus de reconnaissance et d'identification de personnes décédées. L'individualisation de personnes décédées est une tâche courante partagée principalement par des services de police, des odontologues et des laboratoires de génétique. L'objectif de cette recherche est de présenter des processus pour déterminer valablement, avec une incertitude maîtrisée, les identités civiles de personnes décédées. La notion d'identité est examinée en premier lieu. L'identité d'une personne est définie comme l'établissement d'un lien entre cette personne et des informations la concernant. Les informations en question sont désignées par le terme d'identifiants. Deux formes distinctes d'identité sont retenues: l'identité civile et l'identité biologique. Quatre processus principaux sont examinés: celui du témoignage et ceux impliquant les comparaisons d'empreintes digitales, de données dentaires et de profils d'ADN. Concernant le processus de reconnaissance, le mode de fonctionnement de la mémoire est examiné, démarche qui permet de désigner les paramètres pouvant conduire à des erreurs. Dans le but d'apporter un cadre rigoureux à ce processus, une procédure de présentation d'un corps est proposée à l'intention des enquêteurs. Avant d'entreprendre l'examen des autres processus, les concepts généraux propres aux domaines forensiques sont examinés sous l'angle particulier de l'identification de personnes décédées: la divisibilité de la matière (Inman et Rudin), le transfert (Locard) et l'unicité (Kirk). Il est constaté que ces concepts peuvent être appliqués, certains nécessitant toutefois un léger élargissement de leurs principes. Une comparaison croisée entre les domaines forensiques habituels et l'identification de personnes décédées montre des différences telles qu'un positionnement inversé de la source (la source n'est plus à rechercher en partant de traces, mais ce sont des identifiants qui sont recherchés en partant de la source), la nécessité de devoir déterminer une identité civile en plus de procéder à une individualisation ou encore une population d'intérêt limitée plutôt qu'ouverte. Pour les empreintes digitales, les dents et l'ADN, l'intra puis l'inter-variabilité sont examinées, de même que leurs modifications post-mortem (PM), la localisation des identifiants ante-mortem (AM) et les comparaisons AM-PM. Pour l'ADN, il est démontré que les identifiants directs (provenant de la personne dont l'identité civile est supposée) tendent à déterminer une identité civile alors que les identifiants indirects (provenant d'un proche parent) tendent à déterminer une identité biologique. Puis une synthèse des résultats provenant des différents processus est réalisée grâce à des modélisations bayesiennes. Pour chaque processus, une modélisation est présentée, modélisation intégrant les paramètres reconnus comme pertinents. À ce stade, une difficulté apparaît: celle de quantifier l'intra-variabilité dentaire pour laquelle il n'existe pas de règle précise. La solution préconisée est celle d'intégrer un concept de validité qui intègre divers paramètres ayant un impact connu sur l'intra-variabilité. La possibilité de formuler une valeur de synthèse par l'approche bayesienne s'avère d'une aide précieuse dans des cas très difficiles pour lesquels chacun des processus est limité en termes de potentiel discriminant.

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We investigate the population genetic structure of the Maghrebian bat, Myotis punicus, between the mainland and islands to assess the island colonization pattern and current gene flow between nearby islands and within the mainland. Location North Africa and the Mediterranean islands of Corsica and Sardinia. Methods We sequenced part of the control region (HVII) of 79 bats across 11 colonies. The phylogeographical pattern was assessed by analysing molecular diversity indices, examining differentiation among populations and estimating divergence time. In addition, we genotyped 182 bats across 10 colonies at seven microsatellite loci. We used analysis of molecular variance and a Bayesian approach to infer nuclear population structure. Finally, we estimated sex-specific dispersal between Corsica and Sardinia. Results Mitochondrial analyses indicated that colonies between Corsica, Sardinia and North Africa are highly differentiated. Within islands there was no difference between colonies, while at the continental level Moroccan and Tunisian populations were highly differentiated. Analyses with seven microsatellite loci showed a similar pattern. The sole difference was the lack of nuclear differentiation between populations in North Africa, suggesting a male-biased dispersal over the continental area. The divergence time of Sardinian and Corsican populations was estimated to date back to the early and mid-Pleistocene. Main conclusions Island colonization by the Maghrebian bats seems to have occurred in a stepping-stone manner and certainly pre-dated human colonization. Currently, open water seems to prevent exchange of bats between the two islands, despite their ability to fly and the narrowness of the strait of Bonifacio. Corsican and Sardinian populations are thus currently isolated from any continental gene pool and must therefore be considered as different evolutionarily significant units (ESU).

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The research reported in this series of article aimed at (1) automating the search of questioned ink specimens in ink reference collections and (2) at evaluating the strength of ink evidence in a transparent and balanced manner. These aims require that ink samples are analysed in an accurate and reproducible way and that they are compared in an objective and automated way. This latter requirement is due to the large number of comparisons that are necessary in both scenarios. A research programme was designed to (a) develop a standard methodology for analysing ink samples in a reproducible way, (b) comparing automatically and objectively ink samples and (c) evaluate the proposed methodology in forensic contexts. This report focuses on the last of the three stages of the research programme. The calibration and acquisition process and the mathematical comparison algorithms were described in previous papers [C. Neumann, P. Margot, New perspectives in the use of ink evidence in forensic science-Part I: Development of a quality assurance process for forensic ink analysis by HPTLC, Forensic Sci. Int. 185 (2009) 29-37; C. Neumann, P. Margot, New perspectives in the use of ink evidence in forensic science-Part II: Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC, Forensic Sci. Int. 185 (2009) 38-50]. In this paper, the benefits and challenges of the proposed concepts are tested in two forensic contexts: (1) ink identification and (2) ink evidential value assessment. The results show that different algorithms are better suited for different tasks. This research shows that it is possible to build digital ink libraries using the most commonly used ink analytical technique, i.e. high-performance thin layer chromatography, despite its reputation of lacking reproducibility. More importantly, it is possible to assign evidential value to ink evidence in a transparent way using a probabilistic model. It is therefore possible to move away from the traditional subjective approach, which is entirely based on experts' opinion, and which is usually not very informative. While there is room for the improvement, this report demonstrates the significant gains obtained over the traditional subjective approach for the search of ink specimens in ink databases, and the interpretation of their evidential value.

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Lineages arriving on islands may undergo explosive evolutionary radiations owing to the wealth of ecological opportunities. Although studies on insular taxa have improved our understanding of macroevolutionary phenomena, we know little about the macroevolutionary dynamics of continental exchanges. Here we study the evolution of eight Carnivora families that have migrated across the Northern Hemisphere to investigate if continental invasions also result in explosive diversification dynamics. We used a Bayesian approach to estimate speciation and extinction rates from a substantial dataset of fossil occurrences while accounting for the incompleteness of the fossil record. Our analyses revealed a strongly asymmetrical pattern in which North American lineages invading Eurasia underwent explosive radiations, whereas lineages invading North America maintained uniform diversification dynamics. These invasions into Eurasia were characterized by high rates of speciation and extinction. The radiation of the arriving lineages in Eurasia coincide with the decline of established lineages or phases of climate change, suggesting differences in the ecological settings between the continents may be responsible for the disparity in diversification dynamics. These results reveal long-term outcomes of biological invasions and show that the importance of explosive radiations in shaping diversity extends beyond insular systems and have significant impact at continental scales.

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Due to the rise of criminal, civil and administrative judicial situations involving people lacking valid identity documents, age estimation of living persons has become an important operational procedure for numerous forensic and medicolegal services worldwide. The chronological age of a given person is generally estimated from the observed degree of maturity of some selected physical attributes by means of statistical methods. However, their application in the forensic framework suffers from some conceptual and practical drawbacks, as recently claimed in the specialised literature. The aim of this paper is therefore to offer an alternative solution for overcoming these limits, by reiterating the utility of a probabilistic Bayesian approach for age estimation. This approach allows one to deal in a transparent way with the uncertainty surrounding the age estimation process and to produce all the relevant information in the form of posterior probability distribution about the chronological age of the person under investigation. Furthermore, this probability distribution can also be used for evaluating in a coherent way the possibility that the examined individual is younger or older than a given legal age threshold having a particular legal interest. The main novelty introduced by this work is the development of a probabilistic graphical model, i.e. a Bayesian network, for dealing with the problem at hand. The use of this kind of probabilistic tool can significantly facilitate the application of the proposed methodology: examples are presented based on data related to the ossification status of the medial clavicular epiphysis. The reliability and the advantages of this probabilistic tool are presented and discussed.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying ?true? hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distances.

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In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

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Testosterone abuse is conventionally assessed by the urinary testosterone/epitestosterone (T/E) ratio, levels above 4.0 being considered suspicious. A deletion polymorphism in the gene coding for UGT2B17 is strongly associated with reduced testosterone glucuronide (TG) levels in urine. Many of the individuals devoid of the gene would not reach a T/E ratio of 4.0 after testosterone intake. Future test programs will most likely shift from population based- to individual-based T/E cut-off ratios using Bayesian inference. A longitudinal analysis is dependent on an individual's true negative baseline T/E ratio. The aim was to investigate whether it is possible to increase the sensitivity and specificity of the T/E test by addition of UGT2B17 genotype information in a Bayesian framework. A single intramuscular dose of 500mg testosterone enanthate was given to 55 healthy male volunteers with either two, one or no allele (ins/ins, ins/del or del/del) of the UGT2B17 gene. Urinary excretion of TG and the T/E ratio was measured during 15 days. The Bayesian analysis was conducted to calculate the individual T/E cut-off ratio. When adding the genotype information, the program returned lower individual cut-off ratios in all del/del subjects increasing the sensitivity of the test considerably. It will be difficult, if not impossible, to discriminate between a true negative baseline T/E value and a false negative one without knowledge of the UGT2B17 genotype. UGT2B17 genotype information is crucial, both to decide which initial cut-off ratio to use for an individual, and for increasing the sensitivity of the Bayesian analysis.

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This article extends existing discussion in literature on probabilistic inference and decision making with respect to continuous hypotheses that are prevalent in forensic toxicology. As a main aim, this research investigates the properties of a widely followed approach for quantifying the level of toxic substances in blood samples, and to compare this procedure with a Bayesian probabilistic approach. As an example, attention is confined to the presence of toxic substances, such as THC, in blood from car drivers. In this context, the interpretation of results from laboratory analyses needs to take into account legal requirements for establishing the 'presence' of target substances in blood. In a first part, the performance of the proposed Bayesian model for the estimation of an unknown parameter (here, the amount of a toxic substance) is illustrated and compared with the currently used method. The model is then used in a second part to approach-in a rational way-the decision component of the problem, that is judicial questions of the kind 'Is the quantity of THC measured in the blood over the legal threshold of 1.5 μg/l?'. This is pointed out through a practical example.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

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Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (Bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker - typically a client of a forensic examination or a scientist acting on behalf of a client - ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and Bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and Bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked here also serve the purpose of supporting the discussion of the similarities, differences and complementary aspects of existing Bayesian probabilistic sampling criteria and the decision-theoretic approach proposed throughout this paper.