This project aims at studying the "digital turn", that is, the transition of a cultural realm defined by the presence of physically available media content to a world where digitized media, that is likely to deeply reconfigure our ways of being in the world. In order to analyze this "digital revolution", we will focus on artistic contexts, and, more specifically, on music in everyday life, and its socio-technical reconfiguration. We have chosen this relatively narrow subject to conduct our investigations for a series of reasons. Firstly, music consumption is a widely shared social experience in which technological innovation - Acetate to Mp3 - is a key element in the transformation. Second, illegal downloading and peer to peer file sharing have become major issues of public debate, legislation and intervention. Finally, our everyday experience of music is not limited to listening, but engages our identities, our conception of time, our emotions and attachments, our ways of understanding and articulating public and private space, etc., in short, it constitutes a very complete social experience.Furthermore, we are seeing since the early 2000s a turning point where the model of the music business goes through an almost uninterrupted market recession, while simultaneously, the digital music sales expand significantly. Indeed, digitization of content - what Fabien Granjon and Clément Combes have named the "digitamorphosis," succeeding Antoine Hennion’s "discomorphosis", drives a shift in the way amateurs relate to musical content. The rules of listening and interpretation are not immutable. An entire century of music recordings and experiments has already transformed what we expect from music, its creative processes, and the soundscapes and formats that make our everyday musical experience. However, these changes depend on discrete value alterations accumulating over time, and, among other things, on a standardization of traditional codes and more recent practices. In short, as digital schemes develop, the limits of what is acceptable are modified: listening, possessing, sharing or archiving are experiences that are evolving due to streaming technologies, the co-existence of multiple listening devices (personal computer, home stereos, portable music players), and the presence of musical content in social networks. Thus, digitization of music subverts the dominant paradigm of media and medium as a merged whole (tape, acetate, CD), suggesting then the possibility of a new paradigm: that of music as a service and not just a data. We could be going from a product-based society to a society of experience. In order to carry out this project in which cultural sociologists, ethnomusicologists and computer science specialists participate from three partner laboratories (Atlantic Centre of Philosophy at the University of Nantes, Nantes Computing Laboratory ; Arts and Language Research Center at EHESS), we will set three goals: first, to establish a chronological sequence of the "digital turn", bringing about simultaneously a reflective analysis on what it means to take a socio-historical approach on this type of transformation. Second, we seek to understand how the shift from an analog culture to a digital one, as well as the appearance of a “native-digital” generation, may transform our every day musical experience. Finally, we will consider the hypothesis of digital technology (and especially social networks) as a lever of transformation of the traditional paradigms that shape our present understanding of musical taste, legal frameworks for musical consumption and political ideals of democracy through the Internet.

Verifying correctness and robustness of programs and systems is a major challenge in a society which relies more and more on safety-critical systems controlled by embedded software. This issue is even more critical when the computations involve floating-point number arithmetic, an arithmetic known for its quite unusual behaviors, and which is increasingly used in embedded software. Note for example the "catastrophic cancellation" phenomenon where most of the significant digits of a result are cancelled or, numerical sequences whose limit is very different over the real numbers and over the floating-point numbers. A more important problem arises when we want to analyse the relationship between floating-point computations and an "idealized" computation that would be carried out with real numbers, the reference in the design of the program. The point is that for some input values, the control flow over the real numbers can go through one conditional branch while it goes through another one over the floating-point numbers. Certifying that a program, despite some control flow divergences, computes what it is actually expected to compute with a minimum error is the subject of the robustness or continuity analysis. Providing a set of techniques and tools for verifying the accuracy, correctness and robustness for critical embedded software is a major challenge. The aim of this project is to address this challenge by exploring new methods based on a tight collaboration between abstract interpretation (IA) and constraint programming (CP). In other words, the goal is to push the limits of these two techniques for improving accuracy analysis, to enable a more complete verification of programs using floating point computations, and thus, to make critical decisions more robust. The cornerstone of this project is the combination of the two approaches to increase the accuracy of the proof of robustness by using PPC techniques, and, where appropriate, to generate non-robust test cases. The goal is to benefit from the strengths of both techniques: PPC provides powerful but computationally expensive algorithms to reduce domains with an arbitrary given precision whereas AI does not provide fine control over domain precision, but has developed many abstract domains that quickly capture program invariants of various forms. Incorporating some PPC mechanisms (search tree, heuristics) in abstract domains would enable, in the presence of false alarms, to refine the abstract domain by using a better accuracy. The first problem to solve is to set the theoretical foundations of an analyser based on two substantially different paradigms. Once the interactions between PPC and IA are well formalized, the next issue is to handle constraints of general forms and potentially non-linear abstract domains. Last but not least, an important issue concerns the robustness analysis of more general systems than programs, like hybrid systems which are modeling control command programs. Research results will be evaluated on realistic benchmarks coming from industrial companies, in order to determine their benefits and relevance. For the explored approaches, using realistic examples is a key point since the proposed techniques often only behave in an acceptable manner on a given sub classes of problems (if we consider the worst-case computational complexity all these problems are intractable). That's why many solutions are closely connected to the target problems.

ANTIMOINE is a project focused on the tools needed to conduct an anthropological analysis of territories from cultural heritage data. On the application point of view areas are education, tourism, land, territories project management ... From a scientific point of view the aim of the project is the introduction of meaning in legacy information systems so as to provide, in response to a user inquiry, a favorable environment cultural heritage interpretation. This context consists of a set of cultural heritage objects linked by associations with a semantic feature heritage. This context, not defined a priori is obtained in the course of a database heritage. To achieve this goal ANTIMOINE adopts an interdisciplinary approach involving linguistics, data mining and virtual reality. If each partner brings its own lock, fifth lock, transverse emerges: the cooperation between processes specific to each discipline. Cooperation allowing on one hand the introduction of the second direction to reduce the complexity. To solve these locks we rely on three theories: Possible Argmentatifs Semantics (linguistics), the analysis of frequent patterns (data mining) and enaction (virtual reality). This work will be illustrated and evaluated through a prototype operating a real database. This prototype will be developed incrementally and will allow the implementation of three scenarios: education, tourism and museum .. With each scenario a different hardware platform: desktop, digital tablet, immersive device. To get to overcome these obstacles ANTIMOINE relies on a consortium of four partners: the laboratory Lab-STICC - ENIB (Virtual Reality), LINA-COD (data mining) and CoDIRe (linguistic) and society Topic-Topos (database administration and software integration). The work to be performed is divided into five tasks: Task 1 : coordination Task 2 : semantic analysis of cultural heritage . analysis of the semantics of inheritance. It is to propose and use the tools from texts and other data used to create semantic models of heritage, ie The semantic features (concepts) and associations between these rules. Task 3 : data mining . It is to study and develop tools to discover groups of cultural heritage objects and associations between these groups not previously explained and exploited to amend the semantic models. Task 4 : enactive interface .It is to propose a method of natural and immersive interaction can self-organize in order to provide a context for cultural heritage interpretation in line with the questioning of the user. Task 5 : integration . This task has several objectives: (1) ensure the exchange of data between different modules and their synchronization, (2) ensure the integration of software modules developed by the partners and (3) ensure the system's portability between different platforms material forms

In the biomedical research field, high-throughput genotyping provides massive data (between a few hundred thousands to one or two millions genetic markers for each INDIVIDUAL observed). Downstream high-throughput genotyping, genome-wide association studies (GWASs) aim at identifying DNA variations responsible for genetic diseases, and have to cope with such vast amounts of data. Besides, these data, which consist in genetic markers called « SNPs », are complex since they are characterized by short and long-range dependences between variables, along the genome. These dependences are called linkage disequilibrium (LD). The connecting thread of this interdisciplinary project is the concept of graphical models used for the design of advanced algorithms dedicated to GWAS-purpose data mining. The project will explore strategies based on the use of Bayesian networks on the one hand and on specific random forests on the other hand. There exist indeed very few approaches attempting to model dependences between SNPs while addressing the scalability problem of GWASs. Complexity and high-dimensionality advocate the use of specific Bayesian networks (BNs) to model the LD: a novel purpose-design type of BN will be defined and implemented, the forest of hierarchical latent class models (or F model). Such a model will reduce the data dimensionality through latent variables, thus allowing scalability. On top of this model, integration of supplementary data (transcriptomic data) and additional knowledge (from ontologies and from gene annotation databases) will allow cross-confirmation of putative associations between genetic factors and disease. In parallel with data integration combined with the use of an F model, the potentiality of specific random forests (or T models) combined with data integration will be investigated. Besides data integration, integration of models will be explored: an hybrid model obtained through the integration of F and T models will be proposed and evaluated. To evaluate the power of the model-based GWAS strategies and their integrative variants, an innovative method will be developed for the fast simulation of realistic datasets. In summary, this project will design, implement and test advanced algorithms and strategies to propel progress in the field of GWASs. Modeling a complex natural system from massive data and scalability are two keywords of this project; in addition, the evaluation of the innovative GWAS strategies will require the fast generation of genome-wide simulated data. Simulation of massive data is therefore another dimension of the SAMOGWAS project. Finally, be it for speed increase or tractability purpose, this project will deploy intensive calculations on grids; any stage is likely to be concerned: modeling, use of model for a GWAS purpose, simulation of GWAS data, thorough evaluation of GWAS strategies. In the SAMOGWAS project, targets to be met are advances in machine learning techniques, data mining and knowledge discovery dealing with very high-dimensional data, including highly correlated data. Such advances will be enhanced through the integration of heterogeneous sources of data. To serve the purpose of advances in the biomedical research domain, through scientific advances in computer science, this multidisciplinary methodological project will make available innovative software prototypes dedicated to GWASs. Finally, as more and more plant genomes are sequenced, genetics of plant biology is currently opening to genome-scale analyses. Not only will the biomedical research domain draw benefit from the methodology and prototypes developed (e.g. personalized medicine, public healthcare control in western aging populations), the animal and plant biology domains are also concerned with respect to the selection of phenotypes of interest in agronomy.

Oceans are particularly affected by global change, which can cause e.g. increases in average sea temperature and in UV radiation fluxes onto ocean surface or a shrinkage of nutrient-rich areas. This raises the question of the capacity of marine photosynthetic microorganisms to cope with these environmental changes both at short term (physiological plasticity) and long term (e.g. gene alterations or acquisitions causing changes in fitness in a specific niche). Synechococcus cyanobacteria are among the most pertinent biological models to tackle this question, because of their ubiquity and wide abundance in the field, which allow them to be studied at all levels of organization from genes to the global ocean. In SAMOSA, we plan to develop a systems biology approach to characterize and model the main acclimation (i.e., physiological) and adaptation (i.e. evolutionary) mechanisms involved in the differential responses of Synechococcus clades/ecotypes to environmental fluctuations, with the goal to better predict their respective adaptability, and hence dynamics and distribution, in the context of global change. First, we will measure, on synchronized and asynchronized cultures of the model Synechococcus strain WH7803, the effects of a variety of environmental stresses (high light, high and low temperature, UV exposure) on the whole transcriptome and a number of key physiological processes. These data, complemented with published data on oxidative and nutrient stress, will allow us to build a first global gene regulation network. Using the same approach, we will then study the effects of high light and temperature stresses on four additional Synechococcus strains, representative of the most abundant clades in the field, with the aim to unveil ecotype-specific responses. This will allow us to add subnetworks to the global gene regulation model that will translate the extent of ecotypic variability of the stress response within the Synechococcus genus. In parallel, systematic comparisons of the 42 marine Synechococcus genomes available, including 2 to 10 strains for each clade, will allow us to identify the ecotype-specific core genomes. Knowledge of these gene sets should allow us to decipher the genetic basis of specific adaptive responses to changes in environmental factors among ecotypes. By combining comparative genomics and transcriptomics analyses, we expect to delineate a limited set of genes that are both ecotype-specific and differentially regulated in response to one or several specific stresses. Such genes will constitute privileged targets for further functional analyses, including gene knockout approaches followed by physiological characterization of the mutants. The role of these genes in stress adaptation of Synechococcus ecotypes will be further checked by screening metagenomes and metatranscriptomes from various oceanic regions and depths showing contrasted environmental parameters, which we will get from the TARA-Oceans cruise and other sources. The SAMOSA project is both ambitious by the extent and variety of analyses that will be made and innovative since it proposes to build a gene regulation network not limited to a 'model strain', but including ecotypic variability, an important step towards the development of a 'model genus'. We aim at constructing a gene network model sufficiently flexible to allow the integration of forthcoming transcriptomic and physiological data. Many results should be extendable to other ecosystems, since relatives of these microorganisms are found in virtually all illuminated aquatic environments including rivers, lakes, hotsprings, etc. Other outcomes include a better appraisal of the ecosystemic and industry-related services potentially offered by these marine cyanobacteria, and hence will be useful for durable management and valorization of marine ecosystems in which these microorganisms constitute a significant and potentially exploitable component.