Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Lithium-ion battery control for faster charging and longer life (BatCon)

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: Sweden
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-11-01
End date: 2022-12-31
Duration (months): 24.0
Total project cost (EUR): 191852.16
EU funding (EUR): 191852.16
Participants: 1
Project status: CLOSED

Meeting the European industrial and political ambition of making the transport sector free of fossil fuel in the near future depends heavily on continued advancement of battery technology. Safe and optimal use of battery systems is crucial but difficult due to the lack of accurate internal state information and optimal battery control algorithms. This project aims to make step changes in research and innovation of battery management by developing health-aware fast charging strategies as well as realise an advanced career development for the experienced researcher using a clearly defined training-through-research approach. The proposed battery charging management will benefit from and integrate advanced mathematical modelling, robust state estimation and a holistic control framework within this project, along with several on-going battery energy management projects at Chalmers University of Technology. The research outcomes will include faster charging capability and prolonged lifetime for batteries on the premise of a safety guarantee, which will significantly improve the cost and resource efficiency and the convenience of battery powered devices. The hosting research group at Chalmers has a reputation for working closely with industry (e.g., Volvo Cars, Volvo Group and ABB) and applying their research to real world problems, therefore maximising the opportunity for the results to be commercially implemented in the shortest possible time. Ultimately, this project will contribute to UN Sustainable Development Goals in terms of “Affordable and clean energy” and “Sustainable cities and communities.” Furthermore, this fellowship will provide an excellent opportunity for the experienced researcher to advance the career training and secure a leading independent position at the end of the fellowship.

Keywords: battery management systems,electric vehicles,fast charging,battery modelling,optimal control
Autonomous, self-loading and unloading ground-based robots (ELIPORT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-02-01
End date: 2019-07-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Despite rapid advancements in the way that we receive packages, current last mile delivery solutions are still antiquated in comparison to the technology that has been deployed in other sectors of the industry. This causes PROBLEMS: for end consumers (failed deliveries, damaged items), for businesses (unsustainable costs for delivery) and for society and the environment (traffic congestion, pollution). To solve this, Eliport is creating a fleet of AUTONOMOUS ground-based ROBOTS. They will travel in pedestrian spaces in order to cover the distance between the pick-up point (e.g final logistics point) and the drop-off point (e.g the customer’s home). The robot will be intelligent because software will allow it to do its delivery duties, orient in the environment and be a smart participant in human traffic. We are also developing a delivery receptacle. This trunk or gate system will be installed at/in customer’s premises and will only be accessible to Eliport autonomous robots, the intended recipient of the delivery or somebody with a unique code for each trunk/gate (e.g courier, mailman). With this PATENT-PENDING delivery system we are aiming to completely remove the human from the delivery process. The ELIPORT system has many different potential use cases that vary in technical difficulty: limited open environments such as gated communities, closed industrial environments like warehouses and factories, public industrial environments such as airports and hospitals and finally fully open environments like typical suburban or urban residences. The first target market will be gated-communities in the EU and USA that contain primary residences. The feasibility will determines three key requirements for further project execution: i) if the market conditions favor ELIPORT, ii) if the solution has reached the maturity needed to proceed to further product development and iii) if the company has the necessary resources to move on to the next phase.

Keywords: autonomous robots,last mile delivery
Fifth Generation Cross-Border Control (5GCroCo)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Spain,Germany,Germany,Austria,Austria,Germany,Germany,Germany,Germany,Germany,Germany,Italy,Greece,Belgium,Sweden,Sweden,France,France,France,France,Luxembourg
Call: 5G for cooperative, connected and automated mobility (CCAM) (H2020-ICT-2018-2, 2018)
Start date: 2018-11-01
End date: 2022-06-30
Duration (months): 44.0
Total project cost (EUR): 16951183.59
EU funding (EUR): 12874676.0
Participants: 31
Project status: CLOSED

The possibility of providing connected, cooperative and autonomous mobility (CCAM) services along different countries when vehicles traverse various national borders has a huge innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of services along borders also poses interesting technical challenges. The situation is particularly challenging given the multi-country, multi-operator, multi-telco-vendor, and multi-vehicle-OEM scenario of any cross-border layout. Motivated by this, 5GCroCo brings together a strong consortium from both, European automotive and mobile communications industries, with the explicit support or road traffic authorities and the respective national governments (through letters of support), to develop innovation at the intersection of these two industrial sectors. The aim is to define a successful path towards the provision of CCAM services along cross-border scenarios and reduce the uncertainties of a real 5G cross-border deployment. 5GCroCo aims at trialling 5G technologies in the cross-border corridor connecting the cities of Metz-Merzig-Luxembourg, traversing the borders between France, Germany and Luxembourg. The objective is to validate advanced 5G features, such as New Radio, MEC-enabled distributed computing, Predictive QoS, Network Slicing, and improved positioning systems, all combined together, to enable innovative use cases for CCAM. 5GCroCo aims at defining new business models that can be built on top of this unprecedented connectivity and service provisioning capacity, also ensuring that relevant standardization bodies from the two involved industries are impacted. 5GCroCo validation will focus on three use cases: 1) tele-operated driving, 2) high definition maps for autonomous vehicles, and 3) Anticipated Cooperative Collision Avoidance (ACCA) and will also provide general recommendations for any other use cases.

Keywords: v2x communications,autonomous,connected and cooperative vehicle mobility,ccam,cross border ccam,teleoperated driving
Autonomous Linguistic Emergence in neural Networks (ALiEN)

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: Spain
Call: ERC ADVANCED GRANT (ERC-2020-ADG, 2020)
Start date: 2022-01-01
End date: 2026-12-31
Duration (months): 60.0
Total project cost (EUR): 2489541.0
EU funding (EUR): 2489541.0
Participants: 1
Project status: SIGNED

Deep neural networks (DNNs) are specialized computational models lacking a standard interface. If a complex task requires different DNNs, an ad-hoc connection must be laboriously designed. Inspired by human language, ALiEN wants to replace such ad-hoc interfaces with generic communication protocols optimized for ease of learning by DNNs that might have different architectures and functions. ALiEN “languages” are not hand-crafted: they emerge by training DNNs to share information through communication, offering the scalability and robustness to noise that is an asset of learned systems. A first set of experiments will study, in tightly controlled settings, the impact of input, training community size and communication channel on the expressiveness and ease of acquisition of emergent protocols. The emergence of general protocols will be encouraged by a training environment characterized by varied inputs and interaction among numerous DNNs. The best emerged protocols will also be taught in a supervised way to new DNNs, with the final aim of establishing a “universal” DNN language. Next, I will explore how emergent protocols can help interfacing out-of-the box, state-of-the-art DNNs, only requiring the addition of light input and output layers to existing pre-trained models. Finally, a simplified home automation use case will demonstrate the usefulness of emergent protocols in a scenario that features some of the complexities to be expected in real-life applications. The project will also thoroughly analyze the emerging protocols, with the concurrent aims of i) identifying and favoring features that make them more expressive and easier to learn; ii) enhancing interpretability; and iii) gathering scientific insights into communication emergence in a non-human “species”. All in all, ALiEN will take a first bold step towards enabling autonomous DNN interaction, and thus genuinely adaptive AI systems.

Keywords: deep neural networks,emergent communication,generalization,deep neural network analysis
BIOgas membrane reformer for deceNtralIzed hydrogen produCtiOn (BIONICO)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Public-private partnerships
Destination: Fuel Cells and Hydrogen
Action type: Research and Innovation actions
Partnership: FCH2 (Art-187)
Countries involved: Germany,Spain,Italy,Spain,Italy,Switzerland,Netherlands,United Kingdom,Portugal
Call: Decentralized hydrogen production from clean CO2-containing biogas (H2020-JTI-FCH-2014-1, 2014)
Start date: 2015-09-01
End date: 2019-12-31
Duration (months): 52.0
Total project cost (EUR): 3396640.0
EU funding (EUR): 3147640.0
Participants: 11
Project status: CLOSED

BIONICO will develop, build and demonstrate at a real biogas plant (TRL6) a novel reactor concept integrating H2 production and separation in a single vessel. The hydrogen production capacity will be of 100 kg/day. By using the novel intensified reactor, direct conversion of biogas to pure hydrogen is achieved in a single step, which results in an increase of the overall efficiency and strong decrease of volumes and auxiliary heat management units. The BIONICO process will demonstrate to achieve an overall efficiency up to 72% thanks to the process intensification. In particular, by integrating the separation of hydrogen in situ during the reforming reaction, the methane in the biogas will be converted to hydrogen at a much lower temperature compared with a conventional system, due to the shifting effect on the equilibrium conversion. The fluidization of the catalyst makes also possible to (i) overcome problems with temperature control (formation of hotspots or too low temperature), (ii) to operate with smaller particles while still maintaining very low pressure drops and (iii) to overcome any concentration polarization issue associated with more conventional fixed bed membrane reactors. Dedicated tests with different biogas composition will be carried out to show the flexibility of the process with respect to the feedstock type. Compared with any other membrane reactor project in the past, BIONICO will demonstrate the membrane reactor at a much larger scale, so that more than 100 membranes will be implemented in a single fluidized bed membrane reactor, making BIONICO’s In this way a more easy operation can be carried out so that a stable pure hydrogen production can be achieved. BIONICO project is based upon knowledge and experience directly gained in three granted projects: ReforCELL, FERRET and FluidCELL.

Keywords: biogas,membrane reactor
Structure of a Human GABA(A) Receptor Complex (GABAARComp)

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: Life Sciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-09-01
End date: 2023-08-31
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: SIGNED

GABA(A)Rs are the principal neurotransmitter receptors at the inhibitory synapses. The majority of these receptors are anchored at the inhibitory postsynaptic compartment by the central scaffolding function of gephyrin. A dysfunctional receptor clustering by gephyrin leads to abnormal neurotransmission and neurodevelopmental disorders, including anxiety disorders and epilepsy. Recent advances in the structural studies, most recently by cryo-electron microscopy (cryo-EM), have elucidated several heteropentameric GABA(A)R structures. All of these illustrate receptors in isolation. However, in a physiological synaptic context, GABAARs exist and function in close association the auxiliary protein LFPLH4 as well as with anchoring proteins including gephyrin, collybistin (CB) and the adhesion molecule neuroligin 2 (NL2). To understand the architecture and function of this fundamental complex, I will work on the structural elucidation of the human GABA(A)R-gephyrin-CB-NL2 supramolecular complex by single-particle cryo-EM. Structural studies will be followed by validation using additional biochemical, biophysical and electrophysiological analysis of mutant constructs. These data will not only provide the first insights into the supra-molecular organization of a major human neurotransmitter receptor. As the dysfunctional GABAergic neurotransmission manifest itself in lethal neurodevelopmental disorders such as Alzheimer’s and also epilepsy, structural insight into the central complex will also help to understand the molecular basis of these disorders.

Keywords: gaba a receptor,gephyrin,cryo em,collybistin,neuroligin,inhibitory postsynapses
Nature-inspired Circular Recycling for Polymers (NaCRe)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Switzerland
Call: ERC Advanced Grant (ERC-2019-ADG, 2019)
Start date: 2021-01-01
End date: 2025-12-31
Duration (months): 60.0
Total project cost (EUR): 3375000.0
EU funding (EUR): 3375000.0
Participants: 1
Project status: SIGNED

In 2070, 10^12 Kg of plastics (polymers) could be produced yearly in a world inhabited by 11 billion people. Hence, we have ~50 years to address this sustainability challenge. The sourcing and disposing of such quantities without a significant environmental impact will not be possible, even if everything is bio-sourced and bio-degraded. Yet, on earth, there are >10^12 Kg of proteins (one of Nature’s polymers). They are sustainable because they are recycled in a circular way. If we exemplify their metabolism, proteins are decomposed by living organisms into their monomeric constituents (the amino acids, AAs); the cell machinery uses such AAs to synthesize new proteins that have little in common with the original ones. This is only possible because a protein is a specific sequence of AAs bound together by cleavable peptide bonds, i.e. proteins are sequence-defined polymers, SDPs. Nature reuses and does not degrade AAs, thus assuring protein sustainability. This project aims at showing that such a circular approach to recycle SDPs is possible for technologically-relevant polymers using engineering-sound laboratory processes. One aim is to show that b-Lactoglobulin, a milk protein used as a component for water filtration membranes, can be digested into its AAs, that, in turn, can be used to form Fibroin, a silk protein used in resistive switching memory devices. Fibroin will be converted into Keratin, a wool protein, that will be converted back into b-Lactoglobulin. Another aim is to perform the whole process within an automated and scalable robotic platform. The final aim is to expand this concept from natural proteins to DNA and non-natural SDPs. There would be a paradigm shift in plastic recycling, if a random mixture of any polymers could be used to produce any other polymer on earth, without taxing the planet with degradation products. Scope of this project is to show that such a vision in the circular use of polymers is scientifically and technologically possible.
aXiom – a first of its kind Human-Machine Interface Chip designed for the automotive industry (HMI4auto)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Norway
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2019-10-01
End date: 2022-03-31
Duration (months): 30.0
Total project cost (EUR): 3518753.5
EU funding (EUR): 2463127.45
Participants: 1
Project status: CLOSED

The aim is to bring our disruptive aXiom Human-Machine Interface (HMI) chip family to full market maturation, to industrialise/ qualify and pilot aXiom in a real automotive OEM programme and prepare it for scale-up. We will disrupt the global touch-based HMI market and qualify as full-range supplier to the global automotive industry - serving the full market range of automotive touchscreens. Annually, 25,000 people die on EU roads and driver’s distraction is responsible for 10-20% of car accidents. Addressing driver’s distraction requires a new approach for the HMI. However, currently the automotive industry relies on HMI chips developed for the consumer market, far from industry requirements and needs. aXiom is tailored for automotive use and will eliminate the dependence on retrofitted touchscreen products. The overall objective of the HMI4auto project is to implement the findings of our Feasibility Study to enable rapid and successful commercialisation. Key objectives can be grouped in three categories and achieving them will bring us to a wide global market uptake: 1) Technology maturation objectives will industrialise and qualify the aXiom chip family prior to piloting and validation in a real automotive OEM programme. The objective is to raise the TRL of our technology from its current TRL7 to 8 (WP1-3). 2) Pilot and validation objectives to demonstrate and validate the performance, functionality and user benefits through a real automotive OEM programme under the supervision of TouchNetix. This will elevate aXiom from TRL8 to 9 (WP3). 3) Market maturation, project and communication management objectives enabling us to successfully bring aXiom to the market and reach sales traction beyond Phase 2 (WP4-5). We will significantly boost our growth - with accumulated sales revenues of €93.5m for the 5-year post-project, with accumulated operating profit of €35.5m (5.47 ROI) and employment growth of 38 FTEs at MyWo and 120 FTEs in our value chain.

Keywords: fabless,automotive human machine interface,touch based hmi,haptic,touchscreen,high signal to noise,ratio,distance sensing,drivers distraction,road safety,cispr 25,aec q100,enc61000
Measuring GENomic diversity change over time in avian enDANGERED species (GENDANGERED)

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: Life Sciences
Countries involved: Denmark
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-06-01
End date: 2022-05-31
Duration (months): 24.0
Total project cost (EUR): 219312.0
EU funding (EUR): 219312.0
Participants: 1
Project status: CLOSED

Biodiversity is declining at alarming rates mostly due to anthropogenic impacts, such as climate and land-use change. This in turn generates reductions in the genomic diversity that species require to persist and adapt in the face of future environmental change. Thus, a thorough understanding of how genomic diversity changes in the face of species’ declines is essential for planning conservation actions. The use of genetics in conservation biology has been extremely valuable in recent decades, and the quick adoption of cutting-edge genomics tools offer new and powerful insights, however, important challenges are yet to be tackled. Crucially, the conditions that lead to genomic diversity decline, and the details of how exactly genomic diversity is lost in response to population decline are currently unknown. Current approaches focusing on reduced portions of the genome, and/or limited to the use of contemporary samples, are not enough. To fill these gaps in knowledge, I propose a plan that combines computer modelling with empirical genomic data to unveil signatures of genomic diversity change over time after recent global environmental change. The proposal consists of three complementary steps. (1) Simulate how genomic diversity declines across the genome according to different demographic models. (2) Obtain the first directly observed estimates of the pace, amount and type of genomic diversity change using whole-genome sequencing from historical (i.e. pre-decline) and contemporary (i.e. post-decline) avian samples. (3) Simulate common conservation practices to develop a predictive modelling tool capable of guiding conservation management in light of future environmental change. Altogether, this approach will allow me to dissect how genetic diversity is lost across the genome after population declines, estimate the pace at which this happens over recent time-scale and generate predictions for the efficacy of conservation actions into future environmental conditions.

Keywords: evolutionary genomics,biodiversity,population genetics,conservation,conservation genetics,climate change,adaptation,biological collections