Open to closed system transition traced through the TDIC isotopic signature at the aquifer recharge stage, implications for groundwater 14C dating

14C dating models are limited when considering recent groundwater for which the carbon isotopic signature of the total dissolved inorganic carbon (TDIC) is mainly acquired in the unsaturated zone. Reducing the uncertainties of dating thus implies a better identification of the processes controlling the carbon isotopic composition of the TDIC during groundwater recharge. Geochemical interactions between gas, water and carbonates in the unsaturated zone were investigated for two aquifers (the carbonate-free Fontainebleau sands and carbonate-bearing Astian sands, France) in order to identify the respective roles of CO2 and carbonates on the carbon isotopic signatures of the TDIC; this analysis is usually approached using open or closed system terms. Under fully open system conditions, the seasonality of the 13C values in the soil CO2 can lead to important uncertainties regarding the so-called "initial 14C activity" used in 14C correction models. In a carbonate-bearing unsaturated zone such as in the Astian aquifer, we show that an approach based on fully open or closed system conditions is not appropriate. Although the chemical saturation between water and calcite occurs rapidly within the first metre of the unsaturated zone, the carbon isotopic contents (δ13C) of the CO2 and the TDIC evolve downward, impacted by the dissolution-precipitation of the carbonates. In this study, we propose a numerical approach to describe this evolution. The δ13C and the A 14C (radiocarbon activity) of the TDIC at the base of the carbonate-hearing unsaturated zone depends on (i) the δ13C and the A 14C of the TDIC in the soil determined by the soil CO2, (ii) the water's residence time in the unsaturated zone and (iii) the carbonate precipitation-dissolution fluxes. In this type of situation, the carbonate δ13C-A 14C evolutions indicate the presence of secondary calcite and permit the calculation of its accretion flux, equal to ~ 4.5 ± 0.5 x 10-9 mol grock-1 yr-1. More generally, for other sites under temperate climate and with similar properties to the Astian sands site, this approach allows for a reliable determination of the carbon isotopic composition at the base of the unsaturated zone as the indispensable "input function" data of the carbon cycle into the aquifer.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

La pertinence en science forensique. Une (en)quête épistémologique et empirique

A criminal investigation requires to search and to interpret vestiges of a criminal act that happened in a past time. The forensic investigator arises in this context as a critical reader of the investigation scene, in search of physical traces that should enable her to tell a story of the offence/crime which allegedly occurred. The challenge of any investigator is to detect and recognise relevant physical traces in order to provide forensic clues for investigation and intelligence purposes. Inspired by this obser- vation, the current research focuses on the following questions : What is a relevant physical trace? And, how does the forensic investigator know she is facing one ? The interest of such questions is to provide a definition of a dimension often used in forensic science but never studied in its implications and operations. This doctoral research investigates scientific paths that are not often explored in forensic science, by using semiotic and sociological tools combined with statistical data analysis. The results are shown following a semiotic path, strongly influenced by Peir- ce's studies, and a second track, called empirical, where investigations data were analysed and forensic investigators interviewed about their work practices in the field. By the semiotic track, a macroscopic view is given of a signification process running from the discove- red physical trace at the scene to what is evaluated as being relevant for the investigator. The physical trace is perceived in the form of several signs, whose meaning is culturally codified. The reasoning should consist of three main steps : 1- What kind of source does the discovered physical trace refer to ? 2- What cause/activity is at the origin of this source in the specific context of the case ? 3- What story can be told from these observations ? The stage 3 requires to reason in creating hypotheses that should explain the presence of the discovered trace coming from an activity ; the specific activity that is related to the investigated case. To validate this assumption, it would depend on their ability to respond to a rule of relevancy. The last step is the symbolisation of the relevancy. The rule would consist of two points : the recognition of the factual/circumstantial relevancy (Is the link between the trace and the case recognised with the formulated hypothesis ? ) and appropriate relevancy (What investment is required to collect and analyse the discovered trace considering the expected outcome at the investigation/intelligence level?). This process of meaning is based on observations and a conjectural reasoning subject to many influences. In this study, relevancy in forensic science is presented as a conventional dimension that is symbolised and conditioned by the context, the forensic investigator's practice and her workplace environment (culture of the place). In short, the current research states relevancy results of the interactions between parameters from situational, structural (or organisational) and individual orders. The detection, collection and analysis of relevant physical traces at scenes depends on the knowledge and culture mastered by the forensic investigator. In the study of the relation relevant trace-forensic investigator, this research introduces the KEE model as a conceptual map that illustrates three major areas of forensic knowledge and culture acquisition, involved in the research and evaluation of the relevant physical trace. Through the analysis of the investigation data and interviews, the relationship between those three parameters and the relevancy was highlighted. K, for knowing, embodies a rela- tionship to the immediate knowledge allowing to give an overview of the reality at a specific moment ; an important point since relevancy is signified in a context. E, for education, is considered through its relationship with relevancy via a culture that tends to become institutionalised ; it represents the theoretical knowledge. As for the parameter E, for experience, it exists in its relation to relevancy in the adjustments of the strategies of intervention (i.e a practical knowledge) of each practitioner having modulated her work in the light of success and setbacks case after case. The two E parameters constitute the library resources for the semiotic recognition process and the K parameter ensures the contextualisation required to set up the reasoning and to formulate explanatory hypotheses for the discovered physical traces, questioned in their relevancy. This research demonstrates that the relevancy is not absolute. It is temporal and contextual; it is a conventional and relative dimension that must be discussed. This is where the whole issue of the meaning of what is relevant to each stakeholder of the investigation process rests. By proposing a step by step approach to the meaning process from the physical trace to the forensic clue, this study aims to provide a more advanced understanding of the reasoning and its operation, in order to streng- then forensic investigators' training. This doctoral research presents a set of tools critical to both pedagogical and practical aspects for crime scene management while identifying key-influences with individual, structural and situational dimensions. - Une enquête criminelle consiste à rechercher et à faire parler les vestiges d'un acte incriminé passé. L'investigateur forensique se pose dans ce cadre comme un lecteur critique des lieux à la recherche de traces devant lui permettre de former son récit, soit l'histoire du délit/crime censé s'être produit. Le challenge de tout investigateur est de pouvoir détecter et reconnaître les traces dites pertinentes pour fournir des indices forensiques à buts d'enquête et de renseignement. Inspirée par un tel constat, la présente recherche pose au coeur de ses réflexions les questions suivantes : Qu'est-ce qu'une trace pertinente ? Et, comment fait le forensicien pour déterminer qu'il y fait face ? L'intérêt de tels questionnements se comprend dans la volonté de définir une dimension souvent utili- sée en science forensique, mais encore jamais étudiée dans ses implications et fonctionnements. Cette recherche se lance dans des voies d'étude encore peu explorées en usant d'outils sémiotiques et des pratiques d'enquêtes sociologiques combinés à des traitements statistiques de données. Les résultats sont représentés en suivant une piste sémiotique fortement influencée par les écrits de Peirce et une seconde piste dite empirique où des données d'interventions ont été analysées et des investigateurs forensiques interviewés sur leurs pratiques de travail sur le terrain. Par la piste sémiotique, une vision macroscopique du processus de signification de la trace en élément pertinent est représentée. La trace est perçue sous la forme de plusieurs signes dont la signification est codifiée culturellement. Le raisonnement se formaliserait en trois principales étapes : 1- Quel type de source évoque la trace détectée? 2- Quelle cause/activité est à l'origine de cette source dans le contexte précis du cas ? 3- Quelle histoire peut être racontée à partir de ces observations ? Cette dernière étape consiste à raisonner en créant des hypothèses devant expliquer la présence de la trace détectée suite à une activité posée comme étant en lien avec le cas investigué. Pour valider ces hypothèses, cela dépendrait de leur capacité à répondre à une règle, celle de la pertinence. Cette dernière étape consiste en la symbolisation de la pertinence. La règle se composerait de deux points : la reconnaissance de la pertinence factuelle (le lien entre la trace et le cas est-il reconnu dans l'hypothèse fournie?) et la pertinence appropriée (quel est l'investissement à fournir dans la collecte et l'exploitation de la trace pour le bénéfice attendu au niveau de l'investigation/renseignement?). Tout ce processus de signification se base sur des observations et un raisonnement conjectural soumis à de nombreuses influences. Dans cette étude, la pertinence en science forensique se formalise sous les traits d'une dimension conventionnelle, symbolisée, conditionnée par le contexte, la pratique de l'investigateur forensique et la culture du milieu ; en somme cette recherche avance que la pertinence est le fruit d'une interaction entre des paramètres d'ordre situationnel, structurel (ou organisationnel) et individuel. Garantir la détection, la collecte et l'exploitation des traces pertinentes sur les lieux dépend de la connaissance et d'une culture maîtrisées par le forensicien. Dans l'étude du rapport trace pertinente-investigateur forensique, la présente recherche pose le modèle SFE comme une carte conceptuelle illustrant trois grands axes d'acquisition de la connaissance et de la culture forensiques intervenant dans la recherche et l'évaluation de la trace pertinente. Par l'analyse des données d'in- terventions et des entretiens, le rapport entre ces trois paramètres et la pertinence a été mis en évidence. S, pour savoir, incarne un rapport à la connaissance immédiate pour se faire une représentation d'une réalité à un instant donné, un point important pour une pertinence qui se comprend dans un contexte. F, pour formation, se conçoit dans son rapport à la pertinence via cette culture qui tend à s'institutionnaliser (soit une connaissance théorique). Quant au paramètre E, pour expérience, il se comprend dans son rapport à la pertinence dans cet ajustement des stratégies d'intervention (soit une connaissance pratique) de chaque praticien ayant modulé leur travail au regard des succès et échecs enregistrés cas après cas. F et E formeraient la bibliothèque de ressources permettant le processus de reconnaissance sémiotique et S assurerait la contextualisation nécessaire pour poser le raisonnement et formuler les hypothèses explicatives pour les traces détectées et questionnées dans leur pertinence. Ce travail démontre que la pertinence n'est pas absolue. Elle est temporelle et contextuelle, c'est une dimension conventionnelle relative et interprétée qui se doit d'être discutée. C'est là que repose toute la problématique de la signification de ce qui est pertinent pour chaque participant du processus d'investigation. En proposant une lecture par étapes du processus de signification depuis la trace à l'indice, l'étude vise à offrir une compréhension plus poussée du raisonnement et de son fonctionnement pour renforcer la formation des intervenants forensiques. Cette recherche présente ainsi un ensemble d'outils critiques à portée tant pédagogiques que pratiques pour la gestion des lieux tout en identifiant des influences-clé jouées par des dimensions individuelles, structurelles et situationnelles.

ABCtoolbox: a versatile toolkit for approximate Bayesian computations.

BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.

The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods.

The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.

Meeting report of the European mouse complex genetics network SYSGENET.

The second scientific meeting of the European systems genetics network for the study of complex genetic human disease using genetic reference populations (SYSGENET) took place at the Center for Cooperative Research in Biosciences in Bilbao, Spain, December 10-12, 2012. SYSGENET is funded by the European Cooperation in the Field of Scientific and Technological Research (COST) and represents a network of scientists in Europe that use mouse genetic reference populations (GRPs) to identify complex genetic factors influencing disease phenotypes (Schughart, Mamm Genome 21:331-336, 2010). About 50 researchers working in the field of systems genetics attended the meeting, which consisted of 27 oral presentations, a poster session, and a management committee meeting. Participants exchanged results, set up future collaborations, and shared phenotyping and data analysis methodologies. This meeting was particularly instrumental for conveying the current status of the US, Israeli, and Australian Collaborative Cross (CC) mouse GRP. The CC is an open source project initiated nearly a decade ago by members of the Complex Trait Consortium to aid the mapping of multigenetic traits (Threadgill, Mamm Genome 13:175-178, 2002). In addition, representatives of the International Mouse Phenotyping Consortium were invited to exchange ongoing activities between the knockout and complex genetics communities and to discuss and explore potential fields for future interactions.

A statistical shape model of the human second cervical vertebra.

PURPOSE: Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. METHODS: The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. RESULTS: The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. CONCLUSION: The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.

An interactive web-GIS tool for risk analysis: a case study in the Fella River basin, Italy

This paper presents a prototype of an interactive web-GIS tool for risk analysis of natural hazards, in particular for floods and landslides, based on open-source geospatial software and technologies. The aim of the presented tool is to assist the experts (risk managers) in analysing the impacts and consequences of a certain hazard event in a considered region, providing an essential input to the decision-making process in the selection of risk management strategies by responsible authorities and decision makers. This tool is based on the Boundless (OpenGeo Suite) framework and its client-side environment for prototype development, and it is one of the main modules of a web-based collaborative decision support platform in risk management. Within this platform, the users can import necessary maps and information to analyse areas at risk. Based on provided information and parameters, loss scenarios (amount of damages and number of fatalities) of a hazard event are generated on the fly and visualized interactively within the web-GIS interface of the platform. The annualized risk is calculated based on the combination of resultant loss scenarios with different return periods of the hazard event. The application of this developed prototype is demonstrated using a regional data set from one of the case study sites, Fella River of northeastern Italy, of the Marie Curie ITN CHANGES project.