Bayesian classification criterion for forensic multivariate data

This study presents a classification criteria for two-class Cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland, law enforcement authorities regularly ask laboratories to determine cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. In this study, the classification analysis is based on data obtained from the relative proportion of three major leaf compounds measured by gas-chromatography interfaced with mass spectrometry (GC-MS). The aim is to discriminate between drug type (illegal) and fiber type (legal) cannabis at an early stage of the growth. A Bayesian procedure is proposed: a Bayes factor is computed and classification is performed on the basis of the decision maker specifications (i.e. prior probability distributions on cannabis type and consequences of classification measured by losses). Classification rates are computed with two statistical models and results are compared. Sensitivity analysis is then performed to analyze the robustness of classification criteria.

Detection of nandrolone metabolites in urine after a football game in professional and amateur players: a Bayesian comparison.

Nandrolone (19-nortestosterone) is a widely used anabolic steroid in sports where strength plays an essential role. Once nandrolone has been metabolised, two major metabolites are excreted in urine, 19-norandrosterone (NA) and 19-noretiocholanolone (NE). In 1997, in France, quite a few sportsmen had concentrations of 19-norandrosterone very close to the IOC cut off limit (2ng/ml). At that time, a debate took place about the capability of the human male body to produce by itself these metabolites without any intake of nandrolone or related compounds. The International Football Federation (FIFA) was very concerned with this problematic, especially because the World Cup was about to start in France. In this respect, a statistical study was held with all football players from the first and second divisions of the Swiss Football National League. All players gave a urine sample after effort and around 6% of them showed traces of 19-norandrosterone. These results were compared with amateur football players (control group) and around 6% of them had very small amounts of 19-norandrosterone and/or 19-noretiocholanolone in urine after effort, whereas none of them had detectable traces of one or the other metabolite before effort. The origin of these compounds in urine after a strenuous physical activity is still unknown, but three hypotheses can be put forward. First, an endogenous production of nandrolone metabolites takes place. Second, nandrolone metabolites are released from the fatty tissues after an intake of nandrolone, some related compounds or some contaminated nutritive supplements. Finally, the sportsmen may have taken something during or just before the football game.

Sedimentology, geochemistry and mineralogy of the Paleocene-Eocene thermal maximum (PETM) : sediment records from Egypt, India and Spain

A gradual increase in Earth's surface temperatures marking the transition from the late Paleocene to early Eocene (55.8±0.2Ma), represents an extraordinary warming event known as Paleocene-Eocene Thermal Maximum (PETM). Both marine and continental sedimentary records during this period reveal evidences for the massive injection of isotopically light carbon. The carbon dioxide injection from multiple potential sources may have triggered the global warming. The importance of the PETM studies is due to the fact that the PETM bears some striking resemblances to the human-caused climate change unfolding today. Most notably, the culprit behind it was a massive injection of heat-trapping greenhouse gases into the atmosphere and oceans, comparable in volume to what our persistent burning of fossil fuels could deliver in coming centuries. The exact knowledge of what went on during the PETM could help us to foresee the future climate change. The response of the oceanic and continental environments to the PETM is different. Many factors might control the response of the environments to the PETM such as paleogeography, paleotopography, paleoenvironment, and paleodepth. To better understand the mechanisms triggering PETM events, two different environments were studied: 1) shallow marine to inner shelf environment (Wadi Nukhul, Sinai; and the Dababiya GSSP, Luxor, Egypt), and 2) terrestrial environments (northwestern India lignite mines) representing wetland, and fluvial environments (Esplugafreda, Spain) both highlighting the climatic changes observed in continental conditions. In the marine realm, the PETM is characterized by negative ö13Ccar and ô13Corg excursions and shifts in Ô15N to ~0%o values above the P/E boundary and persisting along the interval suggesting a bloom and high production of atmospheric N2-fixers. Decrease in carbonate contents could be due to dissolution and/or dilution by increasing detrital input. High Ti, K and Zr and decreased Si contents at the P/E boundary indicate high weathering index (CIA), which coincides with significant kaolinite input and suggests intense chemical weathering under humid conditions at the beginning of the PETM. Two anoxic intervals are observed along the PETM. The lower one may be linked to methane released from the continental shelf with no change in the redox proxies, where the upper anoxic to euxinic conditions are revealed by increasing U, Mo, V, Fe and the presence of small size pyrite framboids (2-5fim). Productivity sensitive elements (Cu, Ni, and Cd) show their maximum concentrated within the upper anoxic interval suggesting high productivity in surface water. The obtained data highlight that intense weathering and subsequent nutrient inputs are crucial parameters in the chain of the PETM events, triggering productivity during the recovery phase. In the terrestrial environments, the establishment of wetland conditions and consequence continental climatic shift towards more humid conditions led to migration of modern mammals northward following the extension of the tropical belts. Relative ages of this mammal event based on bio-chemo- and paleomagnetic stratigraphy support a migration path originating from Asia into Europe and North America, followed by later migration from Asia into India and suggests a barrier to migration that is likely linked to the timing of the India-Asia collision. In contrast, at Esplugafereda, northeastern Spain, the terrestrial environment reacted differently. Two significant S13C shifts with the lower one linked to the PETM and the upper corresponding to the Early Eocene Thermal Maximum (ETM2); 180/160 paleothermometry performed on two different soil carbonate nodule reveal a temperature increase of around 8°C during the PETM. The prominent increase in kaolinite content within the PETM is linked to increased runoff and/or weathering of adjacent and coeval soils. These results demonstrate that the PETM coincides globally with extreme climatic fluctuations and that terrestrial environments are very likely to record such climatic changes. - La transition Paléocène-Eocène (55,8±0,2 Ma) est marquée par un réchauffement extraordinaire communément appelé « Paleocene-Eocene Thermal Maximum » (PETM). Les données géochimiques caractérisant les sédiments marins et continentaux de cette période indiquent que ce réchauffement a été déclenché par une augmentation massive de CO2 lié à la déstabilisation des hydrates de méthane stockés le long des marges océaniques. L'étude des événements PETM constitue donc un bon analogue avec le réchauffement actuel. Le volume de CO2 émis durant le PETM est comparable avec le CO2 lié à l'activité actuelle humaine. La compréhension des causes du réchauffement du PETM peut être cruciale pour prévoir et évaluer les conséquences du réchauffement anthropogénique, en particulier les répercussions d'un tel réchauffement sur les domaines continentaux et océaniques. De nombreux facteurs entrent en ligne de compte dans le cas du PETM, tels que la paléogéographie, la paléotopographie et les paléoenvironnement. Pour mieux comprendre les réponses environnementales aux événements du PETM, 2 types d'environnements ont été choisis : (1) le domaine marin ouvert mais relativement peu profond (Wadi Nukhul. Sinai, Dababiya, Luxor, Egypte), (2) le milieu continental marécageux humide (mines de lignite, Inde) et fluviatile, semi-aride (Esplugafreda, Pyrénées espagnoles). Dans le domaine marin, le PETM est caractérisé par des excursions négatives du ô13Ccar et ô13Corg et un shift persistant des valeurs de 815N à ~ 0 %o indiquant une forte activité des organismes (bactéries) fixant l'azote. La diminution des carbonates observée durant le PETM peut-être due à des phénomènes de dissolution ou une augmentation des apports terrigènes. Des taux élevés en Ti, K et Zr et une diminution des montants de Si, reflétés par des valeurs des indices d'altération (CIA) qui coïncident avec une augmentation significative des apports de kaolinite impliquent une altération chimique accrue, du fait de conditions plus humides au début du PETM. Deux événements anoxiques globaux ont été mis en évidence durant le PETM. Le premier, situé dans la partie inférieur du PETM, serait lié à la libération des hydrates de méthane stockés le long des talus continentaux et ne correspond pas à des variations significatives des éléments sensibles aux changements de conditions redox. Le second est caractérisé par une augmentation des éléments U, Mo, V et Fe et la présence de petit framboids de pyrite dont la taille varie entre 2 et 5pm. Le second épisode anoxique est caractérisé par une forte augmentation des éléments sensibles aux changements de la productivité (Cu, Ni et Co), indiquant une augmentation de la productivité dans les eaux de surface. Les données obtenues mettent en évidence le rôle crucial joué par l'altération et les apports en nutriments qui en découlent. Ces paramètres sont cruciaux pour la succession des événements qui ont conduit au PETM, et plus particulièrement l'augmentation de la productivité dans la phase de récupération. Durant le PETM, le milieu continental est caractérisé par l'établissement de conditions humides qui ont facilité voir provoqué la migration des mammifères modernes qui ont suivi le déplacement de ces ceintures climatiques. L'âge de cette migration est basé sur des arguments chimiostratigraphiques (isotopes stables), biostratigraphiques et paléomagnétiques. Les données bibliographiques ainsi que celles que nous avons récoltées en Inde, montrent que les mammifères modernes ont d'abord migré depuis l'Asie vers l'Europe, puis dans le continent Nord américain. Ces derniers ne sont arrivés en Inde que plus tardivement, suggérant que le temps de leur migration est lié à la collision Inde-Asie. Dans le Nord-Est de l'Espagne (Esplugafreda), la réponse du milieu continental aux événements PETM est assez différente. Comme en Inde, deux excursions signicatives en ô13C ont été observées. La première correspond au PETM et la seconde est corrélée avec l'optimum thermique de l'Eocène précoce (ETM2). Les isotopes stables de l'oxygène mesurés 2 différents types de nodules calcaires provenant de paléosols suggère une augmentation de 10°C pendant le PETM. Une augmentation simultanée des taux de kaolinite indique une intensification de l'altération chimique et/ou de l'érosion de sols adjacents. Ces résultats démontrent que le PETM coïncide globalement avec des variations climatiques extrêmes qui sont très aisément reconnaissables dans les dépôts continentaux.

Indirect likelihood inference

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect likelihood (MIL) estimator. We also propose a computationally tractable Bayesian version of the estimator which we refer to as a Bayesian Indirect Likelihood (BIL) estimator. In most cases, the density of the statistic will be of unknown form, and we develop simulated versions of the MIL and BIL estimators. We show that the indirect likelihood estimators are consistent and asymptotically normally distributed, with the same asymptotic variance as that of the corresponding efficient two-step GMM estimator based on the same statistic. However, our likelihood-based estimators, by taking into account the full finite-sample distribution of the statistic, are higher order efficient relative to GMM-type estimators. Furthermore, in many cases they enjoy a bias reduction property similar to that of the indirect inference estimator. Monte Carlo results for a number of applications including dynamic and nonlinear panel data models, a structural auction model and two DSGE models show that the proposed estimators indeed have attractive finite sample properties.

Multiple-scale hydrological and geophysical data integration through non-linear Bayesian sequential simulation

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 scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main 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 logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Segmentació d'imatge de ressonància magnètica de pit utilitzant atlas probabilístic

La localització d'òrgans és un tòpic important en l'àmbit de la imatge mèdica per l'ajuda del tractament i diagnosi del càncer. Un exemple es pot trobar en la cal•libració de models farmacoquinètics. Aquesta pot ésser realitzada utilitzant un teixit de referència, on, per exemple en imatges de ressonància magnètica de pit, una correcta segmentació del múscul pectoral és necessària per a la detecció de signes de malignitat. Els mètodes de segmentació basat en atlas han estat altament avaluats en imatge de ressonància magnètica de cervell, obtenint resultats satisfactoris. En aquest projecte, en col•laboració amb el el Diagnostic Image Analysis Group de la Radboud University Nijmegen Medical Centre i la supervisió del Dr. N.Karssemeijer, es presenta la primera aproximació d'un mètode de segmentació basat en atlas per segmentar els diferents teixits visibles en imatges de ressonància magnètica (T1) del pit femení. L'atlas consisteix en 5 estructures (teixit greixòs, teixit dens, cor, pulmons i múscul pectoral) i ha estat utilitzat en un algorisme de segmentació Bayesià per tal de delinear les esmentades estructures. A més a més, s'ha dut a terme una comparació entre un mètode de registre global i un de local, utilitzats tant en la construcció de l'atlas com en la fase de segmentació, essent el primer el que ha presentat millors resultats en termes d'eficiència i precisió. Per a l'avaluació, s'ha dut a terme una comparació visual i numèrica entre les segmentacions obtingudes i les realitzades manualment pels experts col•laboradors. Pel que fa a la numèrica, s'ha emprat el coeficient de similitud de Dice ( mesura que dóna valors entre 0 i 1, on 0 significa no similitud i 1 similitud màxima) i s'ha obtingut una mitjana general de 0.8. Aquest resultat confirma la validesa del mètode presentat per a la segmentació d'imatges de ressonància magnètica del pit.

An empirical hierarchical Bayesian unification of occupational exposure assessment methods.

In occupational exposure assessment of airborne contaminants, exposure levels can either be estimated through repeated measurements of the pollutant concentration in air, expert judgment or through exposure models that use information on the conditions of exposure as input. In this report, we propose an empirical hierarchical Bayesian model to unify these approaches. Prior to any measurement, the hygienist conducts an assessment to generate prior distributions of exposure determinants. Monte-Carlo samples from these distributions feed two level-2 models: a physical, two-compartment model, and a non-parametric, neural network model trained with existing exposure data. The outputs of these two models are weighted according to the expert's assessment of their relevance to yield predictive distributions of the long-term geometric mean and geometric standard deviation of the worker's exposure profile (level-1 model). Bayesian inferences are then drawn iteratively from subsequent measurements of worker exposure. Any traditional decision strategy based on a comparison with occupational exposure limits (e.g. mean exposure, exceedance strategies) can then be applied. Data on 82 workers exposed to 18 contaminants in 14 companies were used to validate the model with cross-validation techniques. A user-friendly program running the model is available upon request.

Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach

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.

Genetic characterization of St. Louis encephalitis virus isolated from human in São Paulo, Brazil

The molecular characterization of SPH253157, a new strain of St. Louis encephalitis virus (SLEV), isolated in 2004 from the first case of human infection recognized in the state of São Paulo, Brazil, is reported. The patient, presenting a febrile illness without neurological involvement, was hospitalized as a probable case of dengue fever. Genomic RNA was isolated from the supernatant of C6/36 cells infected with acute phase-serum specimen of the patient and the envelope gene was amplified by reverse-transcription-polymerase chain reaction. The complete nucleotide sequence of the envelope gene of this isolate was directly sequenced from the amplified products and compared with other Brazilian and American SLEV strains. Phylogenetic analyses were carried out under maximum likelihood criterion with outgroups both included and excluded. Outgroups comprised four flavivirus of the Japanese encephalitis group. Phylogeny also included Bayesian analysis. The results indicated that the new SLEV isolate belongs to lineage III, being closely related to an Argentinean strain recovered from Culex sp. in 1979. It is concluded that there are at least 3 lineages of SLEV in Brazil.

Cancer mortality inequalities in urban areas: a Bayesian small area analysis in Spanish cities

Background Intra-urban inequalities in mortality have been infrequently analysed in European contexts. The aim of the present study was to analyse patterns of cancer mortality and their relationship with socioeconomic deprivation in small areas in 11 Spanish cities. Methods It is a cross-sectional ecological design using mortality data (years 1996-2003). Units of analysis were the census tracts. A deprivation index was calculated for each census tract. In order to control the variability in estimating the risk of dying we used Bayesian models. We present the RR of the census tract with the highest deprivation vs. the census tract with the lowest deprivation. Results In the case of men, socioeconomic inequalities are observed in total cancer mortality in all cities, except in Castellon, Cordoba and Vigo, while Barcelona (RR = 1.53 95%CI 1.42-1.67), Madrid (RR = 1.57 95%CI 1.49-1.65) and Seville (RR = 1.53 95%CI 1.36-1.74) present the greatest inequalities. In general Barcelona and Madrid, present inequalities for most types of cancer. Among women for total cancer mortality, inequalities have only been found in Barcelona and Zaragoza. The excess number of cancer deaths due to socioeconomic deprivation was 16,413 for men and 1,142 for women. Conclusion This study has analysed inequalities in cancer mortality in small areas of cities in Spain, not only relating this mortality with socioeconomic deprivation, but also calculating the excess mortality which may be attributed to such deprivation. This knowledge is particularly useful to determine which geographical areas in each city need intersectorial policies in order to promote a healthy environment.

A Bayesian network approach to the database serch problem in criminal proceedings

Background The 'database search problem', that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method's graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication.

Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials

Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data.Many of the issues that are discussed with reference to the statistical analysis of compositionaldata have a natural counterpart in the construction of a Bayesian statistical model for categoricaldata.This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986)in his seminal book on compositional data. Particular emphasis is put on the problem of whatparameterization to use

Histopathological examination of nerve samples from pure neural leprosy patients: obtaining maximum information to improve diagnostic efficiency

Nerve biopsy examination is an important auxiliary procedure for diagnosing pure neural leprosy (PNL). When acid-fast bacilli (AFB) are not detected in the nerve sample, the value of other nonspecific histological alterations should be considered along with pertinent clinical, electroneuromyographical and laboratory data (the detection of Mycobacterium leprae DNA with polymerase chain reaction and the detection of serum anti-phenolic glycolipid 1 antibodies) to support a possible or probable PNL diagnosis. Three hundred forty nerve samples [144 from PNL patients and 196 from patients with non-leprosy peripheral neuropathies (NLN)] were examined. Both AFB-negative and AFB-positive PNL samples had more frequent histopathological alterations (epithelioid granulomas, mononuclear infiltrates, fibrosis, perineurial and subperineurial oedema and decreased numbers of myelinated fibres) than the NLN group. Multivariate analysis revealed that independently, mononuclear infiltrate and perineurial fibrosis were more common in the PNL group and were able to correctly classify AFB-negative PNL samples. These results indicate that even in the absence of AFB, these histopathological nerve alterations may justify a PNL diagnosis when observed in conjunction with pertinent clinical, epidemiological and laboratory data.

A Bayesian approach for pervasive estimation of breaststroke velocity using a wearable IMU

A ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1 ± 9.6% and high correlation with the tethered reference system (rX,Y=0.91 ) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.