Potential applications of electromagnetic absorbers strongly increased over the past few years. Radar absorbing materials were mainly used for stealth applications in the past but are now also integrated in industrial processes (electromagnetic compatibility in RF systems, antennas…). Moreover, the strong development of wireless technologies has led to an increase in the human exposure to electromagnetic waves. This fact gives rise to new public health issues and house protection against electromagnetic radiations is thus a pretty hot topic. Potential applications of radar absorbers are nowadays numerous and new technologies have thus to be developed to answer to these growing needs. This project has two main objectives: i) ultra-thin absorbers for low frequency applications (<4 GHz) and ii) 3D absorbers or Frequency Selective Surfaces (FSS). The need in ultra-thin low-frequency absorbers concerns both military and civil engineering. Indeed, at these frequencies, the most efficient solutions consist in using ferrite ceramics (heavy and expensive) or loaded polymer foams (thick). Flexible magnetic composites can also be used but their absorption capacities are lower. This project proposes to design and fabricate ultra-thin absorbers thanks to the coupling of metasurfaces and composite materials. Considering the frequency band of interest (1-4 GHz), potential applications will concern not only stealthiness of military systems but also the house protection against radiations (GSM, Wifi, 3G, 4G) and a decrease of the electromagnetic interactions between civil radars and wind plants. The second objective of the project is to develop technological means for the realization of 3D absorbers and FSS. These 3D objects will be applied to electronic war (protection against electromagnetic attacks) or to electromagnetic compatibility issues (absorbent packaging for microwave devices). 3D printing of composite materials and 3D selective metallization processes will be used to realize the demonstrators.

Phytoplankton is an essential component in the functioning of marine ecosystems and in the carbon cycle. It is therefore essential to assess its variability and its main drivers. However, unlike seasonal and interannual variations, fluctuations of phytoplanktonic biomass and communities on decadal to multi-decadal timescales remain hampered by the lack of long-term observations at global scale and the uncertainties related to the complex balance of the processes that control their fate. These processes are imperfectly and diversely parameterized in biogeochemical models, limiting their use to document long-term phytoplankton variability. Yet, it is crucial to detect natural low-frequency cycles in phytoplankton biomass (and thus carbon fluxes) because they can enhance, weaken or even mask climate-related trends. In this context, the inter/transdisciplinary DREAM project proposes to investigate and benchmark different deep learning (DL) frameworks (learned from satellite and in situ observations) to emulate past and future multi-decadal time-series of surface phytoplankton biomass and communities. This approach will allow us to assess the relative contribution of the different processes (e.g. physical, predation, community structures) involved in phytoplankton dynamics over the last decades in response to natural climate low-frequency variability but also to past and future anthropogenic forcing. Ultimately, DREAM will also contribute to characterizing and better constraining the uncertainties in the climate projections of the different Earth System Models gathered in the Coupled Model Intercomparison Project Phase 6 (CMIP6).

The French team of the Lab-STICC (UMR CNRS), specialized in adaptive human-system interactions, and the DOMUS laboratory in Quebec, which specializes in cognitive assistance to the individual, will be partnering to design, produce and evaluate smart technology to assist occupational therapists in their interventions with individuals living with cognitive impairments. These tools will enhance the work of occupational therapists by allowing them to monitor their work more accurately at a distance, using observation, analysis and synthesis devices for patient activity as well as a virtual assistant that can be used to monitor the work of occupational therapists. The virtual assistant will be autonomous and configurable by the occupational therapist. We will use the DOMUS COOK culinary assistant and the virtual assistant of the STICC-Lab to explore how occupational therapists can master these new technologies and how the latter can assist them in their practice, particularly in the design of rehabilitation plans developed in accordance with the objective data they collect during the evaluations they carry out within the homes of individuals living with cognitive impairments. The overall idea of the project is to explore how these data can be used by smart technology to propose interventions that will be later given by the virtual assistant to continue the person’s cognitive rehabilitation within their homes.

This project which includes three teams of physicists and biologists (F. Livolant, LPS Orsay; D. Durand, IBBMC Orsay and D. Chretien, TIPs Rennes), aims to elucidate the interactions and correlations between DNA helices maintained at very close interdistance. The incidence of such correlations may be essential in terms of biological functionality. The objectives are to understand these interactions in three different conformations (bundles, toroids and related shapes and globules). Bacteriophages (viruses that infects bacteria) present the advantage of maintaining in their protein capsid a long chain of DNA at concentrations that cannot be achieved in vitro. By inducing a controlled partial ejection of the genome, we can perform experiments on individual DNA chains, confined in the volume of the capsid itself. Based on the experience of some partners with bacteriophage T5, our objectives are: 1. To study the interactions between DNA. We plan: - To identify the interactions and possible correlations between DNA chains by varying several experimental parameters (ionic conditions, osmotic stress). We will also test the effect of chain length (50 nm to several microns). The methods of X-ray diffraction and cryo-electron microscopy will be used to complement one another in order to get the best resolution. - To elucidate the crystal structure of DNA in the volume of the full capsid by cryo-electron microscopy and tomography of individual particles. This will be complemented by X-ray diffraction experiments on solutions of phages. This study will need to overcome the resolutions currently available by cryo-electron tomography. Capsids of different sizes will be used to vary the confinement stress and curvature of the chains. - To elucidate by the same methods the structure of the toroids and related forms of DNA under confinement (intracapsid) and to identify deviations from the canonical helical structure of DNA. 2. To consider the phages in their natural context (interacting with their host bacteria) to identify the native conformation of the DNA in the capsid i) during the ejection of the phage genome into the host bacterium and ii) during the packaging of DNA into newly formed capsids. The DNA/DNA and DNA/capsid interactions will be analysed and we will test the hypothesis of non symmetry of the ejection and packaging processes. The consortium brings together all skills required for the preparation of the biological material and for structural analyses by cryo-electron microscopy and cryo-tomography and by Xray diffraction.

Improving mobility systems is a key issue for assisting people with disabilities. These systems help developing people’s autonomy, increasing social opportunities and reducing dependency. A representative use case, considered within the framework of the DyNNAMO project, corresponds to that of electric wheelchairs for which several types of sensors are used for the observation and analysis of the physical environment. The purpose of the project concerns the definition and validation of a modeling and analysis flow for the design and optimization under constraints of an innovative hardware and software architecture, proposed in order to improve the detection process within electric wheelchairs. To do this, the targeted architecture will consider the use of dynamic neural networks, whose computation workload automatically adapts during operation taking into account the operating conditions. The scientific contributions of the DyNNAMO project will concern the study and design of dynamic neural network architecture with the identification of effective adaptation mechanisms taking into account the case study and the extra-functional constraints considered. The project aims to propose a hybrid approach to adaptation management based on the static preparation of configurations and a selection during operation of optimized deployments with regard to the functional and extra-functional constraints of the system. Finally, the project will address the optimization of the performance of a hardware and software architecture by taking advantage of variations in the computational load of neural networks during operation.