Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Geometric aspects in pathwise stochastic analysis and related topics (GPSART)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-09-01
End date: 2022-08-31
Duration (months): 72.0
Total project cost (EUR): 1465000.0
EU funding (EUR): 1180000.0
Participants: 2
Project status: CLOSED

Recent years have seen an explosion of applications of geometric and pathwise ideas in probability theory, with motivations from fields as diverse as quantitative finance, statistics, filtering, control theory and statistical physics. Much can be traced back to Bismut, Malliavin (1970s) on the one-hand and then Doss, Sussman (1970s), Foellmer (1980s) on the other hand, with substantial new input from Lyons (from '94 on), followed by a number of workers, including Gubinelli (from '04 on) and the writer of these lines (also from '04 on). Most recently, the theory of such ``rough paths" has been extended to ``rough fields", notably in the astounding works of M. Hairer (from '13 on). The purpose of this project is to study a number of important problems in this field, going beyond the rough path setting, and with emphasis on geometric ideas. (i) The transfer of concepts from rough path theory to the new world of Hairer's regularity structures. (ii) Applications of geometric and pathwise ideas in quantitative finance. (iii) Obtain a pathwise understanding of the geometry of Loewner evolution and more generally explore the use of rough path-inspired ideas in the world of Schramm-Loewner evolution. (iv) Investigate the role of geometry in the pathwise analysis of non-linear evolution equations.

Keywords: pathwise stochastic analysis
ARGONAUT: from the synthesis of gAnglioside tumouR antiGens to a platfOrm for caNcer Active immUnoTherapy (ARGONAUT)

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: 2019-08-01
End date: 2021-07-31
Duration (months): 24.0
Total project cost (EUR): 207312.0
EU funding (EUR): 207312.0
Participants: 1
Project status: CLOSED

Immunotherapy is currently revolutionizing cancer therapy by harnessing the power of the innate and adaptive immune system against cancer cells, thus providing a more tumour-selective approach in assistance to traditional treatments. The identification of tumour-associated carbohydrate antigens (TACAs), aberrant types of glycans decorating the surface of tumour cells, has paved the way for the development of new types of cancer vaccines. However, while significant progress has been made in this area of research, TACA-based cancer vaccines have not yet reached the clinic. In this context, ARGONAUT will address some limitations that characterize classical approaches in carbohydrate cancer vaccine development, with the overall aim of establishing a strategy to access novel, more effective, and fully synthetic vaccine candidates. ARGONAUT’s journey aims at the preparation of vaccine candidates based on ganglioside-type TACAs (expressed in melanoma, neuroblastoma, and small cell lung cancer) that are easy to formulate, able to elicit a immune response independent from individual polymorphisms, and with better chances to reach the clinical environment. Employing a synthetic carbohydrate chemistry approach, ARGONAUT explores its application as a tool to contribute to H2020 European efforts in cancer research, while providing excellent training in a multidisciplinary and intersectoral environment through a well-implemented work-plan. From another perspective, ARGONAUT’s impact will also benefit from the transfer of knowledge to the host institution with the establishment of a new research line in active cancer immunotherapy.

Keywords: tumour associated carbohydrate antigens,neuroectodermal cancers,galcer,gangliosides,oligosaccharide synthesis,sialylation,liposomes,invariant nkt,cancer vaccine,self adjuvanting vaccine
Low Carbon Action in Ordinary Cities (LO-ACT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Institutions, Governance and Legal Systems
Panel description: Political science, international relations, law
Countries involved: Netherlands,United Kingdom,United Kingdom
Call: ERC Starting Grant (ERC-2018-STG, 2018)
Start date: 2019-02-01
End date: 2025-01-31
Duration (months): 72.0
Total project cost (EUR): 1393979.0
EU funding (EUR): 1330221.0
Participants: 3
Project status: SIGNED

The challenge of LO-ACT is to enable low carbon urban development in medium and small cities in rapidly urbanising areas in East, Central and West Africa, South Asia and South East Asia. The majority of emissions in the next century will be emitted by infrastructures that are yet to be built, particularly in rapidly urbanising areas where infrastructure is lacking. Population forecasts suggest that most population growth will take place in small and medium cities. Yet, to date, research on climate action has focused on showcasing strongly branded, successful initiatives in global cities. The low carbon transition depends on myriad of actions in ordinary cities, that is, cities outside global networks of climate innovation and leadership. LO-ACT will address this critical gap by delivering the first multi-dimensional, large scale assessment of low carbon action in ordinary cities. It will contribute a new framework to understand global environmental politics and urban governance. First, LO-ACT will analyse the imaginaries of local action that have shaped global environmental politics over 30 years (Objective 1). The work programme will also analyse the mobility of low carbon urban policies in transport, energy, and housing across different urban contexts (Objective 2). LO-ACT will deliver a comparative analysis of urban trajectories in 113 ordinary cities, and five in-depth ethnographic case studies (Objective 3). Finally, it will provide a critical assessment of governance theory and a revised framework to acknowledge the messy and ordinary contexts of urban action (Objective 4). LO-ACT will bring together an interdisciplinary, international team of researchers, an international network of academic advisors, and four regional hubs that will support context-specific data collection and analysis. The research will contribute to the fields of human geography, urban studies, environmental politics, sustainability transitions and science and technology studies.

Keywords: climate change governance,urban transitions
A collaborative and augmented-enabled ecosystem for increasing SATISfaction and working experience in smart FACTORY environments (SatisFactory)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Technologies for Factories of the Future
Action type: Innovation actions
Countries involved: Italy,Germany,Italy,Switzerland,Greece,Greece,France
Call: Developing smart factories that are attractive to workers (H2020-FoF-2014, 2014)
Start date: 2015-01-01
End date: 2017-12-31
Duration (months): 36.0
Total project cost (EUR): 5253580.0
EU funding (EUR): 4024712.0
Participants: 11
Project status: CLOSED

Known as either "Industrial Revolution 4.0" or as "Industrial Renaissance", the need for new manufacturing approaches is widely accepted in the EU. SatisFactory aims to contribute to the transformation of traditional industrial environments using cutting-edge technologies in ways that are both productive and appealing to youth. The fundamental component of the proposed system will be the assessment and storage of the explicit and tacit knowledge created on the shop floor by aggregating a set of heterogeneous smart devices and sensors (Linksmart/FIT, Smart Sensors/ISMB) and extracting context-aware information based on their measurements (Semantics Engine/EPFL). The distribution of this knowledge will be based on 3 important system tools. Firstly, a training platform will allow the fast and intuitive education of employees (R3Donline/Regola). Secondly, a collaboration platform (CoSpaces/FIT) will stimulate and promote team interactions. Finally, ubiquitous user interfaces (BRIDGE/FIT) will support all employees seamlessly in real time and on the move. SatisFactory will also utilise the aggregated knowledge in order to leverage the control and re-adaptation of facilities (mainDSS/ABE) and streamline the workload (Human Behavior Analysis/CERTH). In order to enhance working experience and thus increase the workplace attractiveness, augmented reality and gamification (CollabReview/FIT) approaches will be utilized. Additionally modern wearable devices (ISMB; Glasses/GlassUp) will allow the interaction of workers with the system without disrupting their workflow. All 12 foreseen products of SatisFactory will be deployed and evaluated in two industrial sites representing automotive industry (COMAU) and battery construction (SUNLIGHT). Validation will assess the impact and reveal the capabilities of SatisFactory towards the promotion of novel and viable business models for increased innovation potential, flexibility and productivity,while enhancing workplace attractiveness

Keywords: next generation hmis ar glasses,worker safety and satisfaction,re adaptation of production facilities,intelligent manufacturing,social networking and collaboration,gamification approaches
Assessment of human Dermal exposure to microPlastics additive chemicals and the risk arising from such exposure using innovative 3D-human skin equivalents (DermPlast)

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: Environment and Geosciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-11-03
End date: 2023-11-02
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: SIGNED

Dermplast is a multidisciplinary project that combines advanced environmental analytical chemistry with innovative 3D-human skin equivalent models (3D-HSE) to study the dermal absorption of toxic plastic additives (e.g. plasticizers and flame retardants) upon skin contact with microplastics (MPs) and assess the risk arising from such exposure. Recent studies have revealed direct human exposure to MPs externally and internally, confirmed by detection of MPs in human stool. However, very little is known on the extent of human exposure to MPs via different pathways and the risk it poses to human health. While there is little evidence of adverse effects associated directly with exposure to pristine MPs, there is major concern over potential toxicity from released plastic additives (e.g. plasticizers and flame retardants), many of which have been associated with serious adverse effects including cancer. The main hypothesis that Dermplast tests is that MP additive chemicals can leach out into sweat and be absorbed through human skin; thus frequent contact with MPs can lead to significant body burdens of hazardous chemicals, with consequent adverse health impacts. This will be achieved using innovative 3D-HSE cultures as sustainable, efficient alternatives to animal/human tissues. The results will be applied to develop an advanced pharmacokinetic exposure model to estimate human uptake of toxic chemicals from dermal contact with MPs and assess the risk against current exposure guidelines and toxic endpoints for these chemicals. With current research focused mainly on isolation and characterisation of MPs in different matrices (e.g. food, water and air), DermPlast will make substantial advances to the state-of-knowledge by providing novel insight into risk assessment of MPs exposure in humans. This will benefit public health and regulators by providing the essential knowledge base required to inform policies to control human exposure to MPs.

Keywords: microplastics,plasticizers,flame retardants,dermal bioavailability,human exposure,risk assessment,hazardous chemicals
TAWNY - An Artificial Intelligence Project to Make Things Empathic (TAWNY)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Germany
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-05-01
End date: 2018-09-30
Duration (months): 5.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The number of things oneThe number of things one can do in a connected and digitized world has become so enormous that no-one is able to actively use even a tiny fraction of all those possibilities, oftentimes leading to a technological overload. This situation has led to the rise of products and services which try to be “smart”, i.e., which try to automatically adapt themselves to the needs and preferences of a user. While at the moment, these smart things require explicit user interaction and feedback to be able to adapt and learn, the TAWNY project aims at introducing the so called “emotional intelligence” - typical in human interaction – in smart products, services, and environments. Based on physiological signals like heart rate and skin resistance – measured with off-the-shelf wearables – and the help of machine learning, TAWNY is able to recognize human affects like emotions, stress, or other kinds of mental state. The technology will be offered as an AI-as-a-Service platform, allowing other developers to easily integrate emotional intelligence into their products and freeing them from having to deal with low-level physiological data directly. Out of the numerous psychological models of interest, the widely-known mental state called "flow" – i.e., being highly productive and content at the same time – has attracted interest in talks with potential clients. Preliminary experiments of TAWNY have suggested that flow might be measurable with TAWNY's approach which would allow for dynamically adapting a workplace or task to keep users in the state of flow – a win-win situation for the employer and employee. In the feasibility study, TAWNY wants to run a series of experiments and develop a prototype to validate and demonstrate the flow measurement technology. Additionally, market research will be conducted to evaluate the economic viability of such a technology. TAWNY, in general, has the potential to become a core component for smart systems across all industries.

Keywords: emotional intelligence,artificial intelligence,affective computing,machine learning,flow classification,emotion ai
Mechanisms to emerge and replicate the first sequence information of life in geothermal microfluidics of early Earth (EvoTrap)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Condensed matter physics
Panel description: Structure, electronic properties, fluids, nanosciences, biological physics
Countries involved: Germany
Call: ERC Advanced Grant (ERC-2017-ADG, 2017)
Start date: 2018-10-01
End date: 2023-09-30
Duration (months): 60.0
Total project cost (EUR): 2364500.0
EU funding (EUR): 2364500.0
Participants: 1
Project status: SIGNED

Can we reconstruct in the lab the onset of molecular evolution? To trigger the autonomous emergence of the first oligonucleotide sequences, we will explore non-equilibrium boundary conditions and selective mechanisms to host the fast progressing prebiotic replication chemistry of oligonucleotides. We will explore novel water-fog microfluidic settings to boost the replication and selection of the first RNA sequences. The findings aims to enable the creation of primitive life forms in the lab, starting from simple molecules in heated rock pores of early Earth. Autonomous replication and metabolism. We will expand our thermal gradient expertise to host three replication chemistries. Using 3D printed microfluidics, we will mimick conditions in pores on early Earth. Thermophoresis will select long over short strands, accumulate small food molecules and strands will be separated by thermal convection and novel mechanisms in water-air systems. With respective collaboration partners, we will drive the replication from RNA ribozymes (Joyce), base-by-base RNA replication (Szostak) and EDC activated DNA ligation (Richert) and monitor the results with Illumina sequencing and TOF LC/MS. The ligation will be also explored with Taq ligase since we expect a cooperative replication dynamics with hypercycle-like characteristics. Thermal gradients will drive early metabolism to boost RNA polymerization and select ATP over ADP to drive modern biochemistry. Sequence selection in low pressure water-air systems. Oligonucleotides bind to water-air interfaces. and can be accumulated 800-fold by heat-driven capillary flows. Based on this, we expect interesting selection effects under microfluidic boiling, fog formation and recondensation dynamics. The settings are tested for sequence selective hydro-gelation of RNA/DNA and enhanced replication chemistry. The temperature of boiling water will be limited below 60°C by using air pressures <200mbar, mimicking very early Earth conditions.

Keywords: molecular evolution,minimal replication,selection,oligonucleotides,sequencing,symmetry,breaking,ligation,molecule thermophoresis,non equilibrium physics,thermal gradients,microfluidics
Dendritic encoding of movement in space (SUBDECODE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Neuroscience and Disorders of the Nervous System
Panel description: Nervous system development, homeostasis and ageing, nervous system function and dysfunction, systems neuroscience and modelling, biological basis of cognitive processes and of behaviour, neurological and mental disorders
Countries involved: Germany,Germany
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-05-01
End date: 2022-04-30
Duration (months): 60.0
Total project cost (EUR): 1806068.0
EU funding (EUR): 482906.19
Participants: 2
Project status: CLOSED

Understanding the neuronal basis of behaviour is a central quest for neuroscience. Neurons are the fundamental units of computation in the brain. Thus, any attempt at unravelling the relationship of neural networks activity and behaviour must be based on an understanding of the transformation of inputs to outputs in single neurons. One of the greatest challenges that our field faces is to make sense of inputs. Without knowing how different synaptic inputs are engaged during behaviour, it is impossible to decode the neuronal input to output conversion. We have developed an approach that allows both the dissection of inputs and the prediction of output during behaviour. We will apply this functional decoding approach to pyramidal neurons in the dorsal subiculum. These neurons form a hippocampal-neocortical interface and are important for memory-guided navigation. The output of subicular neurons contains a dense, distributed representation of space, but the functional input diversity is unresolved. Following the generation of a spatial tuning map during navigational tasks with two-photon Ca2+ imaging at cellular-resolution, we will map the input origins of individual neurons by using targeted single-cell initiated mono-transsynaptic tracing. Then, we will dissect the function of the input from different origins by chemogenetic silencing of input synapses. As a central component of the project, we will map dendritic input patterns in navigating mice with two-photon imaging of Ca2+ transients on dendritic spines. These patterns will be incorporated into a data-driven biophysical model capable of converting realistic synaptic inputs into output. We will tune the model parameters using whole-cell patch-clamp recordings during free behaviour. The final models will be capable of predicting the membrane potential of subicular neurons from precise behavioural observations, offering exciting new perspectives for network analysis and neuroengineering.

Keywords: dendritic computation,synaptic integration,neural computation,connectivity,neuronal networks,patch clamp recordings,two photon imaging,hippocampal activity,behavior,in vivo
NAture Insurance value: Assessment and Demonstration (NAIAD)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Protection of the environment, sustainable management of natural resources, water , biodiversity and ecosystems
Action type: Research and Innovation actions
Countries involved: Spain,Germany,Spain,Italy,Spain,Sweden,Poland,Romania,Slovenia,Slovenia,France,France,France,Netherlands,United Kingdom,Denmark,United Kingdom
Call: Operationalising insurance value of ecosystems (H2020-SC5-2016-OneStageB, 2016)
Start date: 2016-12-01
End date: 2020-08-31
Duration (months): 45.0
Total project cost (EUR): 5081176.25
EU funding (EUR): 4994370.0
Participants: 26
Project status: CLOSED

NAIAD aims to operationalise the insurance value of ecosystems to reduce the human and economic cost of risks associated with water (floods and drought) by developing and testing - with key insurers and municipalities - the concepts, tools, applications and instruments (business models) necessary for its mainstreaming. We will do this in detail for 8 demonstration sites (DEMOs) throughout Europe and develop tools and methods applicable and transferable across all of Europe. The assumption is that Natural Assurance Schemes can reduce risk, especially to drought and flooding, and this risk reduction can be assessed and incorporated within insurance schemes. NAIAD´s conceptual frame is based on three pillars: (i) to help build a resilience approach to risk management through nature based solutions, (ii) the operationalisation and testing of scientific methods using a source-to-sea in DEMOs, (iii) the uptake of nature based solutions that are cost-effective and provide environmental, social and economic benefits. Trans-disciplinarity and stakeholder engagement are at the core of NAIAD for two reasons: first, because the conceptual and assessment methodologies combine physical, social and cultural and economic aspects, integrated into tools and methods but second, and most importantly “road tested” and validated with the stakeholders and end users themselves at the DEMOs. NAIAD will contribute to providing a robust framework for assessing insurance value for ecosystem services by (i) enabling full operationalisation through improved understanding of ecosystem functionality and its insurance value at a broad range of scales in both urban and rural context; (ii) making explicit the links between ecosystem values and social risk perception; and (iii) the application of developed methods and tools in water management by relevant stakeholders, especially businesses, public authorities and utilities.

Keywords: natural assurance schemes,assessment of ecosystem services,demonstration living labs,stakeholders and industry engagement,transferability,policy mainstreaming