Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ASTEASY (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : University of Verona — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Astaxanthin is a carotenoid with a high commercial value. Its high anti-oxidant activity makes Astaxanthin being used as a food/feed supplements, in cosmetics, and in nutraceutics. Microalgae are the main primary sources of Astaxanthin, being produced at industrial level mainly by cultivation of the green alga Haematococcus pluvialis with high costs for cultivation and extraction, hindering its market. In the ERC-StG-SOLENALGAE project the investigation of the role of carotenoids in photoprotection in microalgae led to the development of an innovative platform for Astaxanthin production. Strains with high Astaxanthin accumulation were indeed obtained by metabolic engineering in the green alga Chlamydomonas reinhardtii (usually not accumulating Astaxanthin), producing up to 4 mg/L per day in non-optimized growth conditions. Astaxanthin production by bkt15 strain revealed unique advantages compared to other source of natural Astaxanthin: production of Astaxanthin in continuous, in a single cultivation step; high bio-accessibility for animal or human assimilation; easier extraction of astaxanthin even without costly cell pre-treatments; lower extraction costs and no contamination from oxidant molecules as chlorophylls during extraction process. These advantages lead to a potential increase in pure Astaxanthin productivity up to 16-fold higher than the current methods. ASTEASY PoC aims to the technological development of the new system, by optimizing the cultivation conditions and extraction processes of Astaxanthin from the bkt15 strain and validating the performances in 60 litres demonstrator units. We will also identify and protect the IP generated and analyse the certification needed for commercialization. A business plan will be drafted as a result of interactions with stakeholders and literature analysis, to define market size and trends, and consolidate the business model (Astaxanthin production through a dedicated spin-off vs licensing to Astaxanthin producers).

Mots-clés : carotenoids,astaxanthin,microalgae,cosmetic,plant biotechnology,photosynthesis,pigments,antioxidants
Projet ERC : LENA (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Commissariat à l’énergie atomique et aux énergies alternatives — Pays : France — Rôle : PI
Acronyme de l'entité : CEA
Type d'entité : Recherche
Financement ERC de l'entité : 1497411.0 €

Astrophysics has arrived to a turning point where the scientific exploitation of data requires overcoming challenging analysis issues, which mandates the development of advanced signal processing methods. In this context, sparsity and sparse signal representations have played a prominent role in astrophysics. Indeed, thanks to sparsity, an extremely clean full-sky map of the Cosmic Microwave Background (CMB) has been derived from the Planck data [Bobin14], a European space mission that observes the sky in the microwave wavelengths. This led to a noticeable breakthrough: we showed that the large-scale statistical studies of the CMB can be performed without having to mask the galactic centre anymore thanks to the achieved high quality component separation [Rassat14]. Despite the undeniable success of sparsity, standard linear signal processing approaches are too simplistic to capture the intrinsically non-linear properties of physical data. For instance, the analysis of the Planck data in polarization requires new sparse representations to finely capture the properties of polarization vector fields (e.g. rotation invariance), which cannot be tackled by linear approaches. Shifting from the linear to the non-linear signal representation paradigm is an emerging area in signal processing, which builds upon new connections with fields such as deep learning [Mallat13]. Inspired by these active and fertile connections, the LENA project will: i) study a new non-linear signal representation framework to design non-linear models that can account for the underlying physics, and ii) develop new numerical methods that can exploit these models. We will further demonstrate the impact of the developed models and algorithms to tackle data analysis challenges in the scope of the Planck mission and the European radio-interferometer LOFAR. We expect the results of the LENA project to impact astrophysical data analysis as significantly as deploying sparsity to the field has achieved.

Mots-clés : signal and image processing,sparsity,sparse representations,deep learning,proximal algorithms,blind source separation,cosmological microwave background
Projet ERC : ELECTRA (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Université de Bordeaux — Pays : France — Rôle : Partner
Acronyme de l'entité : UBx
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 36900.0 €

Asymmetry is a very common feature of many systems, objects and molecules, that we use in our daily life. Actually, it is in a majority of cases the absolutely crucial ingredient for conferring a useful property to a system, a prominent example being the chiral nature of pharmaceutically active compounds. Chemists have developed various approaches to generate asymmetry, from the molecular to the macroscopic scale, but are still facing major challenges when exploring efficient alternative physico-chemical concepts for symmetry breaking. The global aim of ELECTRA is to propose so far unexplored and versatile strategies, based on the unconventional use of electrochemical phenomena, to generate asymmetry in chemical systems at different length scales. Investigating simultaneously wired and wireless electrochemistry will open up unique possibilities for advancing the topic of asymmetry generation in an original and cross-disciplinary way. We will determine the utility of these strategies in the frame of two major challenges that are: -unconventional detection, separation and synthesis of enantiomers, based on chiral encoded metal phases, very recently pioneered by us; -design and characterization of Janus systems with complex structures and reactivity Carefully designed experiments at the forefront of electrochemical science will first enable us to gain a better understanding of the different mechanisms involved in symmetry breaking. An optimization by exploring new concepts with respect to their efficiency, yield and selectivity is the next step. This will prepare for the choice of the most innovative approaches of symmetry breaking, in view of the numerous highly relevant applications, ranging from analysis to catalysis and energy conversion. Furthermore, due to the interdisciplinary character of asymmetry, the findings of this project will not only have a major impact in various areas of chemistry, but will also be very interesting for physics and biology.

Mots-clés : electrodeposition,electroanalysis,electrosynthesis,chirality,asymmetry,janus particles
Projet ERC : CoSaQ (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1457063.0 €

At the heart of the multi-faceted enterprise of formal semantics lies a simple yet powerful conception of meaning based on truth-conditions: one understands a sentence if one knows under which circumstances the sentence is true. This notion has been extremely fruitful resulting in a wealth of practical applications. But to what extent can it also account for the human linguistic behavior? The past decade has seen the increasing interaction between cognitive science and formal semantics, and the emergence of the new field of experimental semantics. One of its main challenges is the traditional normative take on meaning, which makes semantic theories hard to compare with experimental data. The aim of this project is to advance experimental semantics by building cognitive semantics, that is semantics founded on cognitive representations instead of normative logical abstractions. Numerical information plays a central role in communication. We talk about the number of students in a class, or the proportion of votes for a particular political party. In this project, I will focus on the linguistic expressions of quantities, known as quantifiers. Recent progress in the study of computational constraints on quantifier processing in natural language laid the groundwork for extending semantic theory with cognitive aspects. In parallel, cognitive science has furthered the study of non-linguistic quantity representations. This project will integrate formal models of quantifier semantics with cognitive quantity representations in order to obtain cognitive semantics of quantifiers, which is both logically precise and psychologically plausible. The theory will have significant repercussions, not only in the immediately related disciplines as semantics and psycholinguistics, but also beyond, e.g., in philosophy and in language technology.

Mots-clés : quantifiers,formal semantics,experimental semantics,logic,cognitive modeling
Projet ERC : GASPARCON (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Helsinki — Pays : Finlande — Rôle : PI
Acronyme de l'entité : UH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1953790.0 €

Atmospheric aerosol particles impact Earth’s climate, by directly scattering sunlight and indirectly by affecting cloud properties. The largest uncertainties in climate change projections are associated with the atmospheric aerosol system that has been altered by anthropogenic activities. A major source of that uncertainty involves the formation of secondary particles and cloud condensation nuclei from natural and anthropogenic emissions of volatile compounds. This research challenge persists despite significant efforts within recent decades. I will build a research group that aims to resolve the atmospheric oxidation processes that convert volatile trace gases to particle precursor vapours, clusters and new aerosol particles. We will create novel measurement techniques and utilize the tremendous potential of mass spectrometry for detection of i) particle precursor vapours ii) oxidants, both conventional but also recently discovered stabilized Criegee intermediates, and, most importantly, iii) newly formed clusters. These methods and instrumentation will be applied for resolving the initial steps of new particle formation on molecular level from oxidation to clusters and stable aerosol particles. To reach these goals, targeted laboratory and field experiments together with long term field measurements will be performed employing the state-of-the-art instrumentation developed. Principal outcomes of this project include i) new experimental methods and techniques vital for atmospheric research and a deep understanding of ii) oxidation pathways producing aerosol particle precursors, iii) the initial molecular steps of new particle formation and iv) mechanisms of growth of freshly formed clusters toward larger sizes, particularly in the crucial size range of a few nanometers. The conceptual understanding obtained during this project will open multiple new research horizons from oxidation chemistry to Earth system modeling.

Mots-clés : secondary aerosol formation,clusters,oxidation
Projet ERC : OXYFLUX (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Göttingen — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : GAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1827410.75 €

Atmospheric oxygen (O2) measurements have proven to be one of the most powerful tools to study the carbon cycle at global scale, quantifying the carbon dioxide (CO2) sink of terrestrial ecosystems and oceans. At ecosystem level, O2 is closely related to CO2 through photosynthesis and respiration, and is influenced by sources of nitrogen during plant uptake. O2 thus carries valuable information about ecosystem processes that cannot be learned from CO2 alone. However, the potential of O2 measurements at ecosystem level has not been exploited. The major hindrance has been the technical challenges faced to measure atmospheric O2 at ppm level against a background concentration of 21%. Motivated by the enormous insights gained from O2 measurements at global level, and with the assistance of proven experts in O2 measurement, OXYFLUX will provide pioneering breakthroughs in both measurement techniques and scientific knowledge of terrestrial ecosystems. Specifically, OXYFLUX will perform the methodological, experimental and modelling work needed to develop O2 as a new tracer for carbon and nitrogen cycle processes at ecosystem level. We will establish the first research group worldwide to perform continuous O2 flux measurements at forest and agricultural field sites, using gas exchange chambers and micrometeorological approaches. These measurements will be utilised further in modelling work where we will integrate O2 into two complementary terrestrial ecosystem models. This will provide the mechanistic understanding for a unique approach to (a) partition CO2 fluxes in e.g. forest ecosystems, (b) improve understanding of the carbon and nitrogen cycle in arable land, and (c) identify the sensitivity of O2 fluxes in terrestrial ecosystems to environmental change. OXYFLUX will firmly establish O2 as a new research tool that can be applied to promote further breakthroughs in a large range of scientific disciplines including environmental, forest and agricultural sciences.

Mots-clés : carbon cycle,eddy covariance,atmospheric oxygen,micrometeorology,land surface modelling,terrestrial ecosystems
Projet ERC : HDEM (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Vienna — Pays : Autriche — Rôle : Partner
Acronyme de l'entité : Univie
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 369835.31 €

Atomic resolution microscopy relies on beams of energetic electrons. These beams quickly destroy fragile materials, making imaging them a major challenge. I have recently developed a new approach that provides the greatest possible resolving power per electron. The method provides both double resolution and excellent noise rejection, via multidimensional data acquisition and analysis. Here I propose to couple the new method with breakthroughs in high speed cameras to achieve unprecedented clarity at low doses, almost guaranteeing major advances for imaging beam sensitive materials. Proof of principle will be achieved for biochemical imaging using the easy to handle, commercially available GroEL chaperone molecule. We will combine our enhanced imaging capabilities with the averaging methods recently recognized by the Nobel prize in chemistry for imaging biomolecules at ultra low doses. After proving our low dose capabilities we will apply them to imaging proteins of current interest at greater resolution. Similar techniques will be used for fragile materials science samples, for instance metal organic framework, Li ion battery, 2D, catalyst and perovskite solar cell materials. Furthermore the same reconstruction algorithms can be applied to simultaneously acquired spectroscopic images, allowing us to not only locate all the atoms, but identify them. The properties of all materials are determined by the arrangement and identity of their atoms, and therefore our work will impact all major areas of science, from biology to chemistry and physics.

Mots-clés : atomic resolution scanning transmission electron microscopy,electron ptychography,single particle analysis,phase contrast imaging,adf imaging,elemental mapping,low dose imaging
Projet ERC : HDEM (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 0.0 €

Atomic resolution microscopy relies on beams of energetic electrons. These beams quickly destroy fragile materials, making imaging them a major challenge. I have recently developed a new approach that provides the greatest possible resolving power per electron. The method provides both double resolution and excellent noise rejection, via multidimensional data acquisition and analysis. Here I propose to couple the new method with breakthroughs in high speed cameras to achieve unprecedented clarity at low doses, almost guaranteeing major advances for imaging beam sensitive materials. Proof of principle will be achieved for biochemical imaging using the easy to handle, commercially available GroEL chaperone molecule. We will combine our enhanced imaging capabilities with the averaging methods recently recognized by the Nobel prize in chemistry for imaging biomolecules at ultra low doses. After proving our low dose capabilities we will apply them to imaging proteins of current interest at greater resolution. Similar techniques will be used for fragile materials science samples, for instance metal organic framework, Li ion battery, 2D, catalyst and perovskite solar cell materials. Furthermore the same reconstruction algorithms can be applied to simultaneously acquired spectroscopic images, allowing us to not only locate all the atoms, but identify them. The properties of all materials are determined by the arrangement and identity of their atoms, and therefore our work will impact all major areas of science, from biology to chemistry and physics.

Mots-clés : atomic resolution scanning transmission electron microscopy,electron ptychography,single particle analysis,phase contrast imaging,adf imaging,elemental mapping,low dose imaging
Projet ERC : SMARTSOUND (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Tampere University — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Audio communication is a major tool for businesses to maintain their competitiveness in the global market. This market is expected to treble by 2020 to $2.145 billion and creates a great demand for novel ideas, such as acoustic pattern recognition technologies. Similarly, the explosion in big data is calling for new data classification methods for improved data indexation and real-time monitoring of the data streams. We have developed acoustic pattern classification methods that are able to detect and recognise a large number of different types of sounds in various everyday contexts. Current acoustic monitoring solutions are able to detect only a small number of very prominent sound events (e.g. baby crying, doorbell), and are not able to operate in realistic environments, where other interfering sounds and reverberation is present. In real life sound recognition recordings, we have recently advanced the deep neural network state-of-the-art by a large margin. The advancement of the methods has enabled recognition of new types of sounds in realistic environments, which were considered infeasible just a few years ago, allowing development of novel applications of sound analysis. We’d expect our technology find its way to various applications, such as 1) surveillance of homes and other buildings for threat detection, 2) navigation, interaction and self-awareness of robots as well as interconnected smart devices, and 3) data indexation operations in video management, just to name few. Within this PoC project, we will prove the efficiency of our technology in real life setting. The goals of the PoC project are to establish the technical feasibility of our idea, implement a commercial prototype of the proposed software and establish its commercialisation potential via various activities.

Mots-clés : pre commercialisation,proof of concept,acoustic pattern classification,sound event detection,audio content analysis,acoustic surveillance,acoustic monitoring,industrial applications
Projet ERC : VEST (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : University of Cyprus — Pays : Chypre — Rôle : PI
Acronyme de l'entité : UCY
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 147687.5 €

Autism spectrum disorder (ASD) is a clinical diagnostic label used to characterize a wide array of individuals exhibiting some common degree of core difficulty in the domain of social communication. This difficulty is reflected in contextually inappropriate social behavior, limited understanding of social norms, expectations, and others’ mental states, eye gaze abnormalities, etc. Such impairments often lead to social exclusion and failure to develop age-appropriate peer relationships. Although current behavioral interventions for autism show some effectiveness, their generalizability is limited insofar as they are often set in structured settings that are decontextualized from situations of everyday life. Also, most of the interventions that have been effective tend to train skills that do not pertain to core areas of social communication where individuals with autism encounter difficulties (e.g. they target improvements in language, IQ etc.). To overcome the shortcomings of traditional interventions we have begun exploring how to train social skills through interactive role-playing scenarios experienced through immersive Virtual Reality (VR). With VR autistic individuals can practice, in realistic but safe environments, useful and typical tasks from everyday life. We have designed a prototype software package with a number of tasks embedded in virtual environments aiming at (1) capitalizing on known cognitive strengths of autistic individuals (e.g., good skills in visual search) and generalizing them to social settings, and (2) improving the transfer of skills across tasks that are conceptually similar despite surface differences. This software runs on a variety of platforms including low-cost Head-Mounted-Displays and 3D TVs. Based on what we know about autism and current interventions, with this PoC grant we aim to explore the potential of commercializing affordable software/hardware VR systems for social skills training in clinical settings and at home.

Mots-clés : virtual reality,virtual environments,autism