Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Drought discovery to improve drought tolerance in crops (DrugCrops)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Spain
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-03-03
End date: 2019-03-02
Duration (months): 24.0
Total project cost (EUR): 158121.6
EU funding (EUR): 158121.6
Participants: 1
Project status: CLOSED

Feeding 9 billion people by 2040 in a context of water shortage poses a critical challenge for agricultural practices, particularly under recurrent drought periods. The so-called Blue Revolution -evaluated by UN as an urgent priority- calls to develop innovative solutions to grow staple food crops in water-limited conditions. Increasing temperatures and reduced precipitation have severely impaired crop yields. Plants can be protected against these stresses by the action of the hormone abscisic acid (ABA), which orchestrates a multitude of adaptive responses that enhance plant survival. The major class of ABA receptors has been characterized and structural data are available for the receptors of the model plant Arabidopsis thaliana. However, in crops that provide more than 50% of the diet worldwide, this knowledge is limited. The goal of DrugCrops is to generate and exploit biochemical and structural data of the ABA receptors in the model crop plant Setaria viridis and in maize to develop novel ABA receptor agonists in order to enhance drought tolerance using small molecules. Towards this translational and multidisciplinary goal, we propose the use of high throughput technologies, X-ray crystallographic, chemical and genetic approaches to dissect the mechanism by which agonists engage and activate their receptors. This information will be leveraged for the design of new chemicals that can be used to control abiotic stress tolerance in crop plants. The ER will work in collaboration with different partner research organizations with recognized expertise in ABA signaling, chemical and structural biology that collectively bring experience ranging from big pharma drug discovery to the genetic engineering of drought tolerant crops. As a result, both the ER and Host could obtain new molecules for plant biotechnology in the field of plant drought tolerance, boosting knowledge-based bioeconomy in the EU and ER´s possibilities to reach a position in research.

Keywords: plant biology,plant biotechnology,chemical genetics,drug discovery,drought,stress,abscisic acid,aba receptor,protein phosphatase 2c,crystal structure
Molecular control of self-renewal and lineage specification in thymic epithelial cell progenitors in vivo. (TEC_Pro)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Immunity, Infection and Immunotherapy
Panel description: The immune system, related disorders and their mechanisms, biology of infectious agents and infection, biological basis of prevention and treatment of infectious diseases, innovative immunological tools and approaches, including therapies
Countries involved: Portugal
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2015-07-01
End date: 2022-10-31
Duration (months): 88.0
Total project cost (EUR): 1491749.0
EU funding (EUR): 1491749.0
Participants: 1
Project status: CLOSED

The development of vaccines for the treatment of infectious diseases, cancer and autoimmunity depends on our knowledge of T-cell differentiation. This proposal is focused on studying the thymus, the organ responsible for the generation of T cells that are responsive against pathogen-derived antigens, and yet tolerant to self. Within the thymus, thymic epithelial cells (TECs) provide key inductive microenvironments for the development and selection of T cells that arise from hematopoietic progenitors. As a result, defects in TEC differentiation cause syndromes that range from immunodeficiency to autoimmunity, which makes the study of TECs of fundamental, and clinical, importance to understand immunity and tolerance induction. TECs are divided into two functionally distinct cortical (cTECs) and medullary (mTECs) subtypes, which derive from common bipotent TEC progenitors (TEPs). Yet, the genetic and epigenetic details that control cTEC/mTEC lineage specifications from TEPs are unsettled. My objectives are to identify TEC progenitors and their niches within the thymus, define new molecular components involved in their self-renewal and lineage potential, and elucidate the epigenetic codes that regulate the genetic programs during cTEC/mTEC fate decisions. We take a global approach to examine TEC differentiation, which integrates the study of molecular processes taking place at cellular level and the analysis of in vivo mouse models. Using advanced research tools that combine reporter mice, clonogenic assays, organotypic cultures, high-throughput RNAi screen and genome-wide epigenetic and transcriptomic profiling, we will dissect the principles that underlie the self-renewal and lineage differentiation of TEC progenitors in vivo. I believe this project has the potential to contribute to one of the great challenges of modern immunology – modulate thymic function through the induction of TEPs - and therefore, represents a major advance in Health Sciences.

Keywords: thymus,thymic epithelium,cortex and medulla,progenitors,self renewal and differentiation,rnai screen,chromatin status
Paracoustics : System active sound reducing system against noise pollution due to transport (DIDSON)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: France
Call: Open Disruptive Innovation Scheme (implemented through the SME instrument) (H2020-SMEINST-1-2015, 2015)
Start date: 2016-04-01
End date: 2016-09-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

80 years of combined experience and 21 years of specific research allowed the team of DIDSON Company to develop and patent the Paracoustics® System: an active reducing sound system against noise pollution due to transport. This disruptive innovation is a revolutionary transducer for reflecting external noise waves. When this system is activated, it reflects the noise. As a result, there is a reduction of 25 to 30 dB of noise level, even when the windows are open. Our product is aimed at protecting coastal city centers, airports, ring roads, railway lines and places where heavy traffic disturbs life. The Paracoustics® system is a simple solution that allows residents to ventilate their building naturally while respecting the environment, saving energy and being in perfect harmony with the EU thermal regulations. The centerpiece of our system, the patented active Paracoustics® electroacoustic transducer is designed to be integrated as part of the closure elements: shutters, curtains and ventilation. A European market survey will be carried out to know the needs of our future clients and to verify that the market is ready to integrate this new innovation. We solicit the help of the EU-H2020 program - Phase 1, because this support would be for us a true accelerator to achieve the marketing of our product in optimal conditions. This will allow us to reach very quickly the European market and therefore to generate the jobs that go hand in hand with the development of our business.

Keywords: disruptive innovation,active sound reducing system
From Data-based to Model-based AI: Representation Learning for Planning (RLeap)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Germany,Spain
Call: ERC Advanced Grant (ERC-2019-ADG, 2019)
Start date: 2020-10-01
End date: 2025-09-30
Duration (months): 60.0
Total project cost (EUR): 2498625.0
EU funding (EUR): 1827325.15
Participants: 2
Project status: SIGNED

Two of the main research threads in AI revolve around the development of data-based learners capable of inferring behavior and functions from experience and data, and model-based solvers capable of tackling well-defined but intractable models like SAT, classical planning, and Bayesian networks. Learners, and in particular deep learners, have achieved considerable success but result in black boxes that do not have the flexibility, transparency, and generality of their model-based counterparts. Solvers, on the other hand, require models which are hard to build by hand. RLeap is aimed at achieving an integration of learners and solvers in the context of planning by addressing and solving the problem of learning first-order planning representations from raw perceptions alone without using any prior symbolic knowledge. The ability to construct first-order symbolic representations and using them for expressing, communicating, achieving, and recognizing goals is a main component of human intelligence and a fundamental, open research problem in AI. The success of RLeap requires the development of radically new ideas and methods that will build on those of a number of related areas that include planning, learning, knowledge representation, combinatorial optimization and SAT. The approach to be pursued is based on a clear separation between learning the symbolic representations themselves, that is cast as a combinatorial problem, and learning the interpretations of those representations, that is cast as a supervised learning problem from targets obtained from the first part. RLeap will address both problems, not just in the planning setting but in the generalized planning setting as well where plans are general strategies. The project can make a significant difference in how general, explainable, and trustworthy AI can be understood and achieved. The PI has made key contribution to the main themes of the project that make him uniquely qualified to carry it forward.

Keywords: planning,learning symbolic representations from data
The Next 100 Optimizing Compilers (FastCode)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2018-STG, 2018)
Start date: 2019-12-01
End date: 2024-11-30
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: CLOSED

Ideally, advances in hardware design would directly translate to performance or energy improvements in software. In reality, this involves a manual process of tuning a sophisticated production compiler or hardware-specific rewriting of code. This process is challenging even for the few experts who possess the required range of skills. Moreover, any errors introduced in this process affect the entire software stack and likely compromise its reliability and security. The aim of this project is to enable software to take full advantage of the capabilities of emerging microprocessor designs without modifying the compiler. Towards this end, we propose a new approach to code generation and optimization. Our approach uses constraint solving in a novel way to generate efficient code for modern architectures and guarantee that the generated code correctly implements the source code. Unlike existing superoptimization and synthesis methods, our approach shifts the entire search problem into the solver. Tight integration with the solver provides a way to reuse reasoning steps and guide the solver using domain specific information about the input program and the target architecture. This approach paves the way to employing recent advances in SMT solvers and has the potential to advance SMT solvers further by providing a new category of challenging benchmarks that come from an industrial application domain. I expect this project to revolutionize the way compilers perform hardware-specific optimizations. It will eliminate an entire class of software errors and unrealized potential performance gains caused by modern optimizing compilers. It will also aid hardware designers by providing greater flexibility for design explorations and faster deployment of new hardware. Thus, this project will lead to significant improvement in performance and stability of software systems, as well as a fundamental impact on several scientific fields.

Keywords: software synthesis,smt solvers,code generation and optimization,compilers,programming language implementation,superoptimization,program analysis and verification
Acoustic monitoring of railway track quality (AMONTRACK)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2018-05-01
End date: 2019-06-30
Duration (months): 14.0
Total project cost (EUR): 100018.8
EU funding (EUR): 100018.8
Participants: 1
Project status: CLOSED

The need for reduced costs and higher system reliability will make condition-based maintenance a key technology in the railway sector in the nearer future. However, reliable and adequate methods for monitoring track conditions, preferably by adding monitoring devices to ordinary rolling stock, are still far from being in place. The proposed project focuses on acoustic track monitoring and aims at pushing forward this monitoring technique to a point, where track faults such as squats, deteriorated rail joints or hanging sleepers can be automatically detected and quantified. This is achieved by combining advanced measurement techniques - involving sound pressure signals due to radiation from rail and wheel as well as axle box vibrations – with advanced simulation techniques for wheel/rail interaction. DB Systemtechnik GmbH as my host supplying all needed measurement techniques and myself as expert in the modelling of wheel/rail interaction will meet and utilize synergy effects from merging our competences in order to design and implement a methodology for acoustic track monitoring that is clearly beyond today's state-of-the-art. Furthermore, being an active member of the group at DB Systemtechnik will give me access to experience, knowhow and education in the railway technology sector. This is a unique possibility for me to broaden my career profile. It will make me an attractive employee both in the railway technology sector as well as in academia. Crossing the boarders of academia and preparing myself for leadership during my fellowship will be a strong support for my goal to become a research leader in academia. It will widen my professional network and offer a possibility for strong cooperation beyond the lifetime of the project.

Keywords: acoustic monitoring,railway track maintenance
Action selection under threat: the complex control of human defense (ActionContraThreat)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: Germany,Switzerland,United Kingdom
Call: ERC Consolidator Grant (ERC-2018-COG, 2018)
Start date: 2019-10-01
End date: 2025-09-30
Duration (months): 72.0
Total project cost (EUR): 1998750.0
EU funding (EUR): 688356.45
Participants: 3
Project status: SIGNED

Run away, sidestep, duck-and-cover, watch: when under threat, humans immediately choreograph a large repertoire of defensive actions. Understanding action-selection under threat is important for anybody wanting to explain why anxiety disorders imply some of these behaviours in harmless situations. Current concepts of human defensive behaviour are largely derived from rodent research and focus on a small number of broad, cross-species, action tendencies. This is likely to underestimate the complexity of the underlying action-selection mechanisms. This research programme will take decisive steps to understand these psychological mechanisms and elucidate their neural implementation. To elicit threat-related action in the laboratory, I will use virtual reality computer games with full body motion, and track actions with motion-capture technology. Based on a cognitive-computational framework, I will systematically characterise the space of actions under threat, investigate the psychological mechanisms by which actions are selected in different scenarios, and describe them with computational algorithms that allow quantitative predictions. To independently verify their neural implementation, I will use wearable magnetoencephalography (MEG) in freely moving subjects. This proposal fills a lacuna between defence system concepts based on rodent research, emotion psychology, and clinical accounts of anxiety disorders. By combining a stringent experimental approach with the formalism of cognitive-computational psychology, it furnishes a unique opportunity to understand the mechanisms of action-selection under threat, and how these are distinct from more general-purpose action-selection systems. Beyond its immediate scope, the proposal has a potential to lead to a better understanding of anxiety disorders, and to pave the way towards improved diagnostics and therapies.

Keywords: defensive behaviour,threat related processes,defensive systems theory,anxiety disorders
Reusing precast concrete for a circular economy (ReCreate)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Ensuring the sustainable supply of non-energy and non-agricultural raw materials
Action type: Innovation actions
Countries involved: Germany,Germany,Germany,Germany,Croatia,Sweden,Finland,Finland,Sweden,Finland,Netherlands,Netherlands,Netherlands,Netherlands,Netherlands
Call: Raw materials innovation for the circular economy: sustainable processing, reuse, recycling and recovery schemes (H2020-LCCI-2020-EASME-twostage, 2020)
Start date: 2021-04-01
End date: 2025-03-31
Duration (months): 48.0
Total project cost (EUR): 14333122.75
EU funding (EUR): 12494045.02
Participants: 25
Project status: SIGNED

Concrete is the most significant construction material and C&D waste stream globally and in the EU. ReCreate aims at closing the loop for concrete at the highest level of utilization by demonstrating the deconstruction and reuse of precast structural components, which retains the secondary material at its highest value. Compared to virgin production, aggregate recycling and backfilling, reusing can reduce energy consumption and carbon footprint by 93-98%. The main objective is to pilot deconstruction and reuse towards maturity as a socio-technical system. The project develops the transition towards circular construction by investigating the systemic changes needed in the whole ecosystems of construction and demolition. Drawing from partnerships that cover the entire value chain, ReCreate will demonstrate deconstruction of intact precast components from condemned buildings and reuse thereof in new buildings in four real-life innovative pilots. The pilots examine the challenge of circularity against the feature of the industry being relatively local, taking into account differences in precasting technologies, building types, construction industry structures and regulatory environments in the different countries. To develop technology and integrate the value chain so that the businesses can become viable, the project advances smart pre-deconstruction audit and deconstruction methods; rapid low-cost quality assurance and standardization; logistics, traceability, and BIM and digital market place integration; and novel design practices and reassembly techniques. In addition ReCreate analyses the potential volume of the supply and demand for secondary concrete components in the EU; reviews how concrete reuse can help the EU to reach its ambitious energy and climate targets for 2030; investigates how secondary components can become socially acceptable for relevant stakeholders and citizens; and elaborates on the changes needed to the regulatory environment to support reuse.

Keywords: precast concrete,salvaged components,panels,deconstruction,reuse,circular construction,business models,value chain integration,technology development,quality assurance,regulatory,support
Aligned one-dimensional nanostructure electrodes from Electrically Conductive pOrous coordiNation polymer for proton exChange mEmbrane fueL celLs (EconCell)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-09-01
End date: 2024-04-20
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: CLOSED

To address environmental hazardous impact of fossil fuel energy technologies and the high dependency on them, clean energy systems have been developed for future energy fulfilment. Among them, the proton exchange membrane fuel cell (PEMFC) is considered as a highly potential electrochemical energy conversion technology because of its low operation temperature, quick start-up and shutdown, high energy efficiency and power flexibility. However, the sluggish cathodic oxygen reduction reaction (ORR) undermines the overall performance. Up to now, the commonly used catalysts are still carbon supported Pt-based nanoparticles, with which the high cost of Pt undesirably increases the overall cost of the system. In EconCell, we will develop a new generation of low-cost, active site enriched and durable PEMFC electrodes from three-dimensional (3D) nanostructures of non-platinum group metal (non-PGM) electrocatalysts. It consists of protic hydrophobic ionic liquid (IL) encapsulated nanowire arrays (NWAs) of electronically conductive porous coordination polymer (E-PCP) selectively assembled on N-doped aligned carbon nanotubes (N-CNTs). The ambitious aim will be achieved with the complementary skills of Experienced Researcher (E-PCPs and nanowires) and supervisors (fuel cells and ionic liquids), based on the unique porosity, conductivity and stability of E-PCPs, the excellent catalytic activities of nitrogen-containing (N) transition metal complexes (MCs), and oxyphilicity and hydrophobicity of ILs. EconCell will extend significantly the existing knowledge of coordinated N active sites, transition metals, ILs and 1D nanostructure electrodes, making available for predicting the catalytic performance of new non-PGM catalyst systems for PEMFCs. The advancement will improve the development level of related fields, bringing about both fundamental and practical impact on various electrochemical energy conversion systems, e.g. electrolyzers, batteries, supercapacitors, etc.

Keywords: polymer electrolyte membrane fuel cell,electrode,one dimensional 1d,porous coordination polymer,ionic liquid