The classification of ancient coins, the numismatic foundation of studies on exchanges and economies, is at a standstill due to the difficulty of adopting a method and collective standards. Over the past 4 years, exploratory work has been carried out to formalise methodological perspectives and put them to the test on a limited panel of coins. The contribution of the life sciences is crucial, both for the classification methodology and for the quality of the works made available to the scientific community. The aim of the ClaMoMed project is threefold: (1) to establish consolidated numismatic classification standards, (2) to carry out a scientific classification of a large panel of medieval coins (5th-15th centuries) from the current French area using digital tools, (3) to complete a publishing project designed to invent and produce new tools providing easy access to rigorous information on these coins. The partnership formed for this project brings together medieval numismatists from the teams of three French UMRs (CRAHAM, IRAMAT, IDEES) and France's leading archaeological operator (INRAP), as well as the Digital Document Unit of the MRSH in Caen and the Presses universitaires de Caen.

Artificial metalloenzymes represent a new class of catalysts, which combine the properties of proteins and metal complexes. Such hybrid species associate the main advantages of biocatalysis (highly chemo-, regio- and stereoselective reactions under environmentally benign conditions) and of homogeneous catalysis (a plethora of chemical transformations involve transition metal-catalyzed reactions). In the past ten years, several artificial metalloenzymes have been developed for epoxidation, hydrogenation, oxidation reactions, C-H activation and olefin metathesis... However, until now, no artificial metalloenzyme has been described for enantioselective dual photoredox reactions. Within this ANR program, we aim at developing new hybrid catalysts involving earth-abundant metal complexes for these yet challenging enantioselective reactions in homogeneous catalysis.

Achieving the UN sustainable development require a global-applied effort, it is essential to consider cultural relevance to effectively motivate sustainable consumption. The proposed research aims to create culturally relevant messages to encourage people to engage in sustainable actions aimed at combating climate change. Past research on environmental decision-making have primarily used generic messages to motivate sustainable decisions, such as recycling and purchasing environment-friendly products; with a couple exceptions, they have not taken culture into account, assuming their findings are applicable across all cultures. However, extensive research in cultural psychology suggests that culture shapes people's cognition, emotion, motivation, and decision making. The PIs’ preliminary research has found that invoking culturally important concepts can increase the effectiveness of messages motivating sustainable behaviour. For example, American students have shown a keen interest in courses promoting environmental sustainability that emphasised concepts of independence and choice, an ethos dominant in the United States, over the ones advocating interdependence. Such findings show the potential for culturally appropriate messaging. The goal of the proposed research is to expand these findings across a wider range of countries by building upon the recent theory of "varieties of interdependence”, i.e., independence and analytic thinking in the West, harmony-promoting interdependence and holistic thinking in North-East Asia, logic-based argumentative interdependence in South Asia, self-assertive interdependence combined with holistic thinking in the Arab world, and emotionally expressive interdependence in Latin America. Our research will invoke these dominant cultural frames to promote two forms of sustainable behaviour: carbon offset purchase and eating plant-based foods.

Public spaces in large cities are increasingly becoming complex and unwelcoming environments. Public spaces progressively become more hostile and unpleasant to use because of the overcrowding and complex information in signboards. It is in the interest of cities to make their public spaces easier to use, friendlier to visitors and safer to increasing elderly population and to citizens with disabilities. Meanwhile, we observe, in the last decade a tremendous progress in the development of robots in dynamic, complex and uncertain environments. The new challenge for the near future is to deploy a network of robots in public spaces to accomplish services that can help humans. Inspired by the aforementioned challenges, COACHES project addresses fundamental issues related to the design of a robust system of self-directed autonomous robots with high-level skills of environment modelling and scene understanding, distributed autonomous decision-making, short-term interacting with humans and robust and safe navigation in overcrowding spaces. To this end, COACHES will provide an integrated solution to new challenges on: a knowledge-based representation of the environment, human activities and needs estimation using Markov and Bayesian techniques, distributed decision-making under uncertainty to collectively plan activities of assistance, guidance and delivery tasks using Decentralized Partially Observable Markov Decision Processes with efficient algorithms to improve their scalability and a multi-modal and short-term human-robot interaction to exchange information and requests. COACHES project will provide a modular architecture to be integrated in real robots. We deploy COACHES at Caen city in a mall called “Rive de l’orne”. COACHES is a cooperative system consisting of fixed cameras and the mobile robots. The fixed cameras can do object detection, tracking and abnormal events detection (objects or behaviour). The robots combine these information with the ones perceived via their own sensor, to provide information through its multi-modal interface, guide people to their destinations, show tramway stations and transport goods for elderly people, etc.... The COACHES robots will use different modalities (speech and displayed information) to interact with the mall visitors, shopkeepers and mall managers. The project has enlisted an important an end-user (Caen la mer) providing the scenarios where the CAOCHES robots and systems will be deployed, and gather together universities with complementary competences from cognitive systems (SU), robust image/video processing (VUB, UNICAEN), and semantic scene analysis and understanding (VUB), Collective decision-making using decentralized partially observable Markov Decision Processes and multi-agent planning (UNICAEN, Sapienza), multi-modal and short-term human-robot interaction (Sapienza, UNICAEN).