Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Integrating Safety and Cybersecurity through Stochastic Model Checking (CAESAR)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Netherlands
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-06-01
End date: 2025-05-31
Duration (months): 60.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 1
Project status: SIGNED

Emerging technologies, like self-driving cars, drones, and the Internet-of-Things must not impose threats to people, neither due to accidental failures (safety), nor due to malicious attacks (security). As historically separated fields, safety and security are often analyzed in isolation. They are, however, heavily intertwined: measures that increase safety often decrease security and vice versa. Also, security vulnerabilities often cause safety hazards, e.g. in autonomous cars. Therefore, for effective decision-making, safety and security must be considered in combination. The CAESAR project will develop an effective framework for the joint analysis of safety and security risks. The successful integration of safety and security faces three challenges: 1. The complex interaction between safety and security, mapping how vulnerabilities and failures propagate through a system and lead to disruptions. 2. The lack of efficient algorithms to compute system-level risk metrics, such as the likelihood and expected damage of disruptions. Such metrics are pivotal to prioritize risks and mitigate them via appropriate countermeasures. 3. The lack of proper risk quantification methods. Numbers are crucial to devise cost-effective countermeasures. Yet, objective numbers on safety and (especially) security risks are notoriously hard to obtain. The CAESAR project will address these challenges by novel combinations of mathematical game theory, stochastic model checking and the Bayesian, fuzzy, and Dempster-Schafer frameworks for uncertainty reasoning. Key outcomes: • An effective framework for joint safety-security analysis • Scalable algorithms and diagnosis methods to compute safety-security risk metrics • Stochastic model checking in the presence of uncertainty CAESAR will not only yield breakthroughs in safety-security analysis, but also for quantitative analyses in other domains. It will make decision making on safety-security easier, more systematic, and transparent.

Keywords: stochastic model checking,safety and security engineering
Integrative metabolomics and genomics analysis for the development of markers of inherited kidney diseases: a personalised medicine approach (MODIRen)

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: Cyprus
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-01-04
End date: 2023-01-03
Duration (months): 24.0
Total project cost (EUR): 145941.12
EU funding (EUR): 145941.12
Participants: 1
Project status: CLOSED

Rare inherited kidney diseases (RIKDs) encompass over 150 different conditions. They often lead to patients requiring renal replacement therapy being a major cause of end stage renal disease, severely compromising the patients’ quality of life and posing a high financial burden in healthcare. They are characterised by a high degree of phenotypic heterogeneity and by the absence of biomarkers for disease diagnosis, prognosis and inadequate therapeutic management. The main aim of the proposed work is to develop new disease ontology for three RIKDs (Thin Basement Membrane nephropathy, CFHR5 nephropathy and MUC1 kidney disease) using a deep-phenotyping approach. Phenotypic and genetic data will be integrated for biomarker discovery and to provide new knowledge for the development of a novel theranostic tool. Whole exome sequencing (WES) of cases and controls is currently underway at the host for the identification of relevant genetic variants. Using a dual biofluid-dual platform approach to maximise metabolome coverage, the metabolic profiles of healthy individuals will be compared to those of RIKD patients to identify disease-specific metabolic markers. Rigorous data analysis methodologies will be employed to integrate WES, metabolomic and clinical data for the identification of robust composite genotype-phenotype signatures of the diseases. These will elucidate molecular disease pathomechanisms, enabling better clinical diagnostics and improved patient stratification. The proposed work will provide a vital genotype-phenotype framework from which future theranostic tools can be more precisely designed and evaluated, towards precision medicine. The proposed research and training program will complement the applicant’s skills in metabolomics and systems biology with the host’s expertise in genomics and molecular diagnostics to enhance her professional maturity and facilitate new international research and innovation initiatives and multidisciplinary collaborations.

Keywords: kidney diseases,metabolomics,genomics,whole exome sequencing,bioinformatics,nephrogenetics
Ultra-small Nanohybrides for Advanced Theranostics (UNAT)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Italy,Ukraine,Greece,France
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2020, 2020)
Start date: 2021-04-01
End date: 2026-03-31
Duration (months): 60.0
Total project cost (EUR): 832600.0
EU funding (EUR): 832600.0
Participants: 5
Project status: SIGNED

Nowadays, research focusing on control and use of nanomaterials in different areas including life sciences has become a key driver of innovation. UNAT project aims at a systematic interdisciplinary study of metal-carbon nanohybrides (NHs) for advanced theranostic application. Indeed, development of NHs based on organic & inorganic moieties can synergistically or antagonistically influence functional properties of engineered nanotheranostic medicines. UNAT will develop innovative approaches for synthesis and multi-functional application of ultra-small (<10 nm) carbon-based NHs functionalized with various metal atoms for diagnostics and therapy of cancer. In particular, carbon cores of NHs will be chemically synthesized from biomasses and bio-wastes. The combination of pre-clinical in-vitro & in-vivo experiments will allow to evaluate theranostic potential of the NHs. UNAT will associate an industrial partner from Greece (Bioemtech), a research and innovation center from Ukraine (Science Park) and 2 academic research groups from France (UCBL) and Italy (CNR). The uptake efficiency and specific localization of the NHs in biological cells depending on their intentionally designed surface chemistry will be studied in details. Extremely rich physico-chemical properties of the NHs will allow their application as universal multi-modal (MRI, PET, X-ray, Fluorescence, Photoacoustic) in-vivo bio-imaging agents. The multimodal imaging strategy will allow us to correlate the images obtained with the use of various imaging facilities to increase general reliability of visualization of the NHs localization in tumours. Various exciting electro-magnetic sources used for medical purposes will be simultaneously used for therapy of cancer tissues containing the incorporated NHs. Strongly complementary research experiences of the partners involved in UNAT and a high degree of cooperative integration between them will allow a deep scientific study of the theranostic potential of the NHs.

Keywords: nanohybrids,bio imaging,nanomaterials for cancer therapy
GaN for Advanced Power Applications (GaN4AP)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Public-private partnerships
Destination: Electronic Components and Systems
Action type: Innovation actions
Partnership: ECSEL (Art-187)
Countries involved: Germany,Germany,Italy,Italy,Italy,Italy,Italy,Italy,Italy,Germany,Germany,Germany,Germany,Germany,Germany,Italy,Italy,Italy,Germany,Germany,Germany,Italy,Italy,Italy,Poland,France,France,France,France,France,France,Czechia,Czechia,Netherlands
Call: ECSEL-IA (H2020-ECSEL-2020-1-IA-two-stage, 2020)
Start date: 2021-06-01
End date: 2024-05-31
Duration (months): 36.0
Total project cost (EUR): 63631020.53
EU funding (EUR): 15320914.36
Participants: 46
Project status: SIGNED

GaN4AP project has the ambitious target of making the GaN-based electronics to become the main power active device present in all power converter systems, with the possibility of developing a close-to-zero energy loss power electronic systems. GaN4AP project will… 1. Develop innovative Power Electronic Systems for power conversion and management with advanced architecture and circuit topology based on state of the art GaN-based High Electron Mobility Transistors (HEMTs) available in a new concept high-frequency packages that can achieve the requested 99% power conversion efficiency. 2. Develop an innovative material (Aluminium Scandium Nitride, AlScN) that combined with advanced growth and process solutions can provide outstanding physical properties for highly efficient power transistors. Therefore, a new HEMT device architecture will be fabricated with much higher current (2x) and power density (2x) than existing transistors. 3. Develop a new generation of vertical power GaN-based devices on MOSFET architecture with vertical p-GaN inversion channel for safe power switching up to 1200 V. We will cover all the production chain from the device design, processing and characterization up to tests in low inductance half bridge power modules and their implementation in high speed power switching systems. 4. Develop a new intelligent and integrated GaN solutions (STi2GaN) both in System in Package (SiP) and Monolithic variances, that will allow the generation of E-Mobility power converters. The projects will focus on scalable concept for 48V-12V bidirectional Buck Boost converters for conventional and ADAS applications combining, in a novel wire-bond free package, a state of the art BCD driver & controller along with a common substrate Monolithic 100V e-GaN Half Bridge. The development of new device technologies and innovative power circuits, employing the GaN-based devices is a crucial factor for the world-wide competitiveness of EU industries.

Keywords: power semiconductors,robustness,power conversion,energy efficiency,automotive,on board charger,industrial motor drive,photovoltaic inverter,system reliability,packaging
A Genetic Data CUBE - An innovative business model applied to predictive and prescriptive analytics, exploring Big Data and empowering cloud-services and urgent computation (GDC)

Framework: Horizon 2020 — Societal Challenges
Programme: Europe in a changing world - inclusive, innovative and reflective societies
Action type: SME instrument
Countries involved: Italy
Call: SME business model innovation (H2020-SMEINST-1-2015, 2015)
Start date: 2015-09-01
End date: 2016-02-29
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Business Intelligence, Decision Making Processing, Predictive Analysis for economic and financial forecasting represent today a brick and mortar set of tools and methodologies to support important business functions aiming at investing purposes, storing customer information, marketing analysis and related tracking activities. Predictive analysis is therefore of paramount importance to diagnose and solve business problems and issues in our VUCA world (dominated by Volatility, Uncertainty, Complexity, Ambiguity). To meet this EU as well as global challenge, we intend to bring Genetic Data Cube (GDC) to market maturity. GDC is a data driven innovative business model powered by a huge trove of real-world, real-time preference/usage /feedback data coming from experienced business experts as well as end- users. Our goal is to architect, develop, and deploy world-class data systems to empower multiple services and facilitate SMEs as well large enterprises or industries in diagnosing and solving relevant business problems or challenges. We are introducing a new paradigm in predictive analysis, a step-change to “prescriptive” analysis, not only processing-based but also human-centred. Considering that Big Data are defined as the “oil of our times”, Big Data Analytic stands at the forefront to data management for economic and financial forecasting: to have a crystal-clear picture of the business opportunity, 90% of the data in the world has been created in the last 2 years alone; present estimates project that the Big Data market will top $84B in 2026. GDC will provide a unique, brand new business model supporting customers in understanding the past unstructured data to predict future activities in customers, investments and business development/growth perspective. Main benefits rely on improving quick-decision, profit, measure social media impact and prevents fraud by making application of advanced analytics and decision optimisation.

Keywords: big data,genetic algorithm,predictive analysis,capital investments,health,customers behaviours,fluid maps,real time,real world,hounds,experts
Nanotextured surfaces for membranes, protective textiles, friction pads and abrasive materials (NanoTextSurf)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Nanotechnologies
Action type: Innovation actions
Countries involved: Austria,Austria,Germany,Spain,Germany,Switzerland,Slovenia,Sweden,Finland,Switzerland,Slovenia,Finland,United Kingdom
Call: Pilot Lines for Manufacturing of Nanotextured surfaces with mechanically enhanced properties (H2020-NMBP-PILOTS-2017, 2017)
Start date: 2017-11-01
End date: 2020-11-30
Duration (months): 37.0
Total project cost (EUR): 6599711.25
EU funding (EUR): 5800241.25
Participants: 13
Project status: CLOSED

Cellulose, the most abundant polymer on Earth, is a classic example of a high reinforcement materials produced from renewable resources. Cellulose nanomaterials produced either with chemical and/or mechanical means from cellulose fibres are safe, biodegradable, ultra-strong, durable and suitable for novel functional applications. Cellulose nanomaterials strengthen the production of lean added value products. They enable novel functional products and improve the competitiveness of European industry. However, it is necessary to further develop application processes for cellulose nanomaterials. NanoTextSurf aims to upgrade existing pilot lines for manufacturing and demonstrating nanotextured surfaces with mechanically enhanced properties. The focal approach of the surface manufacturing concept is to construct nanostructured surfaces based on nanoscale biomaterials. Formation of surfaces will be realised by utilising these building blocks with on-line application techniques (cast and foam coating and screen-printing), which enable the formation of the true nanotextured architecture. This approach will guarantee that robust, efficient and easily up-scalable processes with in-line controlling methods will be available as open access services with reasonable costs. The nanotextured products and their mechanically enhanced performance will be demonstrated as value added products of the existing and novel bio-based membranes at liquid purification, functional textiles for fire retardant fabrics and linings, novel friction materials for transport applications and abrasive materials for surface finishing. Their economic feasibility, safety and environmental acceptability will be evaluated with life cycle sustainability assessment. The results can be exploited in the existing manufacturing lines. Besides these products, NanoTextSurf partners have recognised additional markets such as hospital textiles, industrial wipes, air purification filters and food packaging materials.

Keywords: cellulose,nanofibrils,nanocrystals,cast coating,foam coating,screen printing,pilot,antifouling,absorption,durability,strength,membrane,textile,friction,abrasive,sustainable
NOn-contact STRucturAl DAMage for fUture Safety and lightweight (NOSTRADAMUS)

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: Slovenia
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-10-01
End date: 2023-09-30
Duration (months): 24.0
Total project cost (EUR): 162040.32
EU funding (EUR): 162040.32
Participants: 1
Project status: SIGNED

The decarbonisation of transport requires the design of lighter components for electric vehicles. To ensure that new components meet safety requirements in terms of their susceptibility to vibration fatigue (VF) and to facilitate shorter development times, a new VF identification tool is required. Nostradamus aims to deliver tool that will enable fast and non-contact damage identification caused by VF using the High-speed (HS) camera. Optimisation of digital replicas of the actual products (digital twins) will become easier, to deliver of Safer, Lightweight, Green and Quiet (SLGQ) products. The primary objective is to develop a new method called the Optical vibration fatigue damage identification (OptiViFa). It will enable close to real-time identification of fatigue damage with high spatial density. This will be possible with a ground-breaking extension of the recent scientific progress in HS camera measurements and modal-domain VF. The research objectives are to: 1) identify material strain with a HS camera; this will be achieved through developing a new method for identification of strain mode-shapes using HS camera measurements. 2) Develop OptiViFa for VF identification; this will be achieved through experimental verification in the laboratory and industry via a secondment with a research and development SME within the car industry. 3) Implement OptiViFa as an open-source Python package, enabling other researchers to use and further develop the new methods from the on-line repository. The training and development component of this fellowship will position the fellow at the forefront of research in HS image processing, and vibration fatigue. The inter-sectorial secondment will provide understanding of the crucial relationship between academic research and industry. The results will be open-science and open-source. Finally, the proposal results will help EU industry in developing SLGQ products and citizens of the EU to have a safer, greener and quieter lifestyle.

Keywords: high speed camera,image based damage identification,full field strain measurement,multiaxial vibration fatigue,spectral methods,open source
Studying Neutrinos at the High Energy Frontier (FASERnu)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Switzerland
Call: ERC CONSOLIDATOR GRANTS (ERC-2020-COG, 2020)
Start date: 2021-09-01
End date: 2026-08-31
Duration (months): 60.0
Total project cost (EUR): 1998125.0
EU funding (EUR): 1998125.0
Participants: 1
Project status: SIGNED

Although the properties of neutrinos have been intensively studied, we are still missing data about their behaviour in the TeV energy scale, as well as conclusive tests of lepton universality in neutrino scattering. Embracing the discussions on recently identified flavour anomalies, which hint at lepton universality violation, the study of high-energy neutrino interactions involving both heavy leptons and heavy quarks may be a powerful and complementary tool to search for new physics effects. Such interaction channels require high neutrino energy. Here I propose to measure high energy neutrinos with a detector sensitive to heavy flavour particles. This project (FASERnu) employs a novel approach to exploit the CERN Large Hadron Collider (LHC) as an intense neutrino source, which allows for the study of the high energy frontier of man-made neutrinos. An emulsion hybrid neutrino detector with a target mass of 1.2 tonnes will be employed. Such a detector structure has been well proven to be sensitive to heavy flavour particles: tau, charm and beauty. Data taking will be carried out during the forthcoming Run 3 of LHC operation (2021-2024), which would yield >20,000 neutrino interactions in the detector. During the timeline of this grant, neutrino cross sections will be measured for all three flavours in the uncharted energy range between 360 GeV and 6 TeV. Furthermore, the channels associated with heavy quark (charm and beauty) production will be studied. I established this project within the framework of the FASER experiment. The letter of intent and technical proposal of this project were approved by the CERN committees and I presently act as one of the project leaders of the neutrino program in FASER. FASERnu will not only investigate an unexplored energy regime, but will also provide relevant inputs to future neutrino experiments at the High-Luminosity-LHC (HL-LHC) and then at the Future Circular Collider (FCC).

Keywords: neutrino,flavor physics