Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Selective electrocatalytic CO2 reduction to oxalic acid (CO2Rox)

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: Chemistry
Countries involved: Denmark
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-08-01
End date: 2023-01-31
Duration (months): 18.0
Total project cost (EUR): 164484.0
EU funding (EUR): 164484.0
Participants: 1
Project status: CLOSED

This project is about computer modeling of the electrocatalytic CO2 reduction to oxalic acid in ionic liquids. My objectives are (1) defining the selectivity criteria, (2) developing original double-site model, and (3) significant improvement of the computational method. I will start with the computational method developed in the host group and then augment the approach basing on my vast experience in modeling ionic liquid at interfaces. I also propose an original double-site catalyst model to optimize electronic, geometric, and entropy factors against the defined criteria for higher catalytic activity. The model essentially represents a slit pore with two metal–nitrogen–carbon sites that, together with the ionic liquid, have a stabilizing effect on CO2⁻ intermediate and a catalytic effect on the C–C bond formation leading to the desired product. This fellowship will help me reach my short-term career goal – establishing a group (PI, 2 ER, and 4 PhD) and obtaining National funding to continue the research on CO2 reduction. I will complete the project within 1.5 years under the supervision of prof Rossmeisl at Copenhagen University. Rossmeisl's group is currently leading the computer modeling of electrocatalytic reactions, including CO2 reduction. Herewith, I have unique expertise, outside from electrocatalysis, needed to implement the project.
CHEAP AND EFFICIENT APPLICATION OF RELIABLE GROUND SOURCE HEAT EXCHANGERS AND PUMPS (Cheap-GSHPs)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Low-cost, low-carbon energy supply
Action type: Innovation actions
Countries involved: Germany,Spain,Italy,Germany,Ireland,Spain,Spain,Italy,Italy,Romania,Switzerland,Belgium,Greece,Belgium,France
Call: Demonstration of renewable electricity and heating/cooling technologies (H2020-LCE-2014-2, 2014)
Start date: 2015-06-01
End date: 2019-05-31
Duration (months): 48.0
Total project cost (EUR): 5717356.26
EU funding (EUR): 4844652.0
Participants: 19
Project status: CLOSED

To reduce the total cost of low enthalpy geothermal systems by 20-30 % the project will improve actual drilling/installation technologies and designs of Ground Source Heat Exchangers (GSHE’s). This will be combined with an holistic approach for optimum selection, design and implementation of complete systems across different underground and climate conditions. The proposal will focus on one hand on the development of more efficient and safe shallow geothermal systems and the reduction of the installation costs. This will be realized by improving drastically an existing, innovative vertical borehole installation technology of coaxial steel GSHE and by developing a helix type GSHE with a new, innovative installation methodology. These GSHE’s will be installed to a depth of 40 – 50 meters ensuring improved safety and faster permitting. On the other hand, the proposal will develop a decision support (DSS) and other design tools covering the geological aspects, feasibility and economic evaluations based on different plant set-up options, selection, design, installation, commissioning and operation of low enthalpy geothermal systems . These tools will be made publicly available on the web to users, including comprehensive training to lower the market entry threshold. Given that drilling and GSHE technologies are mature but costly, this holistic approach is included in the proposal to bring the overall cost of the total project down, i.e. not just the cost of the GSHE itself but the avoidance of ground response tests, the engineering costs for the design of the GSHE and the integration of heat pumps with building heating and cooling systems. Also the use of novel the heat pumps for higher temperatures developed within the project will reduce the costs in the market for retrofitting buildings. The developments will be demonstrated in six sites with different undergrounds in different climates whilst the tools will be applied to several virtual demo cases.

Keywords: shallow geothermal,ground source heat exchanger,drilling machines,heat pumps,nanofluids
The Future of Prediction: The Social Consequences of Algorithmic Forecast in Insurance, Medicine and Policing (PREDICT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: The Social World and Its Diversity
Panel description: Sociology, social psychology, social anthropology, education sciences, communication studies
Countries involved: Germany,Italy
Call: ERC Advanced Grant (ERC-2018-ADG, 2018)
Start date: 2020-02-01
End date: 2026-01-31
Duration (months): 72.0
Total project cost (EUR): 2084429.0
EU funding (EUR): 1658012.0
Participants: 2
Project status: SIGNED

The algorithmic turn of prediction, connected with Big Data and Machine Learning, presents an exciting and urgent challenge for the social sciences. Recent advances in digital forecasting claim to provide a predictive score for individual persons or singular events, thereby introducing a new way to manage the uncertainty of the future. But knowing the future in advance is not only advantageous. In fact, for our society, uncertainty about the future is also a resource. Since modernity, with the support of probability calculus various social institutions in different domains have developed means of coping with ignorance of the future by starting with the one thing that we all share – uncertainty. What happens to the stabilized forms of management of the future when their first resource – shared uncertainty – is missing? There is still no systematic research on this groundbreaking transformation. This project proposes a set of theory-driven empirical studies of the transition from probabilistic forms of uncertainty management to the new algorithmic forms of prediction. We will investigate three important social areas highlighting three fundamental dimensions with which digital forecast must deal. 1) First we will focus on personalized insurance. Here the key dimension is individualization of prediction, where the challenge is that such prediction could undermine the mutualization principle organized around actuarial practices. 2) Our second research area is precision medicine, highlighting the dimension of generalization where the challenge is the combination of algorithmic procedures with established statistical methods. 3) In the third field, predictive policing underscores the problem of bias while it challenges the distinction between prevention and repression. Exploring these transformation and its consequences, the project aims at developing a comprehensive approach to study the social, technical and theoretical aspects of prediction in digital society

Keywords: sociology of algorithms,prediction,precision medicine,predictive policing,sociology of risk,insurance
DARE Special Needs Lump Sum for ESR9 Edmore Masendeke (DARE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Action type: Marie Skłodowska-Curie actions
Countries involved: United Kingdom
Call: MSCA Special Needs Allowance (H2020-IBA-MSCA-SNLS-2019, 2019)
Start date: 2019-12-01
End date: 2022-12-31
Duration (months): 37.0
Total project cost (EUR): 24560.0
EU funding (EUR): 24560.0
Participants: 1
Project status: CLOSED

Request of financial support to cover the additional costs that researchers/staff members with disabilities face due to the increased costs of their mobility and/or to ensure necessary assistance by third persons or for adapting their work environment

Keywords: disability access needs
Imaging Biomarkers (IBs) for Safer Drugs: Validation of Translational Imaging Methods in Drug Safety Assessment - Sofia ref.: 116106 (IB4SD-TRISTAN)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Public-private partnerships
Destination: Innovative Medicines Initiative 2
Action type: Research and Innovation actions
Partnership: IMI2 (Art-187)
Countries involved: Germany,Germany,Germany,Germany,Germany,Sweden,Sweden,Belgium,France,France,Netherlands,Netherlands,United States,Netherlands,United Kingdom,United Kingdom,United Kingdom,Denmark,United Kingdom,United Kingdom,United Kingdom
Call: VALIDATION OF TRANSLATIONAL IMAGING METHODS IN DRUG SAFETY ASSESSMENT (TRISTAN) (H2020-JTI-IMI2-2015-07-two-stage, 2015)
Start date: 2017-01-01
End date: 2024-12-31
Duration (months): 96.0
Total project cost (EUR): 22724621.87
EU funding (EUR): 12000000.0
Participants: 28
Project status: SIGNED

1.Our consortium has broad, deep experience of drug development and imaging biomarker (IB) validation. We are internationally recognized experts in transporter biology, animal models of lung injury, toxicology, DCEMRI, compartmental modeling, 1H&129Xe lung MR, and labeling of biologicals with PET and fluorescence tags, together with physicians who care for relevant patients. We have an outstanding record of translating IBs: (a) into animals, (b) into man, (c) into tools which drug developers use with confidence in clinical trials of investigational agents, (d) into regulatory drug development and healthcare. We will develop and validate the required IBs and make them commercially available. 2.Building on our previous work with gadoxetate DCEMRI IBs we will develop and standardise, define sensitivity and specificity in rats, and show valid and comparable data multicentre in human volunteers and patients. 3.We believe the search for IBs of Drug Induced Interstitial Lung Disease (DIILD) should start in DIILD patients. Cancer and rheumatology patients receiving, in their standard care, drugs with DIILD liability, and whose physicians withdraw the drug due to suspected DIILD, will be imaged when symptomatic and followed up. From this we will derive IBs of DIILD which predict outcome. We will also develop IBs from 1H/129Xe MRI and PET to further characterise DIILD, and will back-translate and validate all these IBs in rat models. 4.To better assess biodistribution of biologics, we will thoroughly characterise two well-chosen exemplars in rats, pigs and humans: an antibody biologic and a peptide biologic. We will use 89Zr, 18F and 68Ga PET, fluorescence and MALDI imaging. 5.We will follow an imaging biomarker roadmap to establish (a) that the IBs can be deployed robustly in whatever centre they are needed, (b) the relationship of the IB to underlying biology, (c) how well the IB forecasts clinical outcome, and make appropriate arrangements for dissemination.

Keywords: imaging biomarker validation,lung,rhematology,toxicology
Motif in T cells for the Prediction of INTeractions (MT-PoINT)

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: Switzerland
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-07-01
End date: 2023-06-30
Duration (months): 24.0
Total project cost (EUR): 191149.44
EU funding (EUR): 191149.44
Participants: 1
Project status: SIGNED

T cells are a key element of the human immune system. Upon binding to antigenic peptides (called T cell epitopes), T cells can induce the death of infected cells or prime and regulate other immune cells. In cancer immunotherapy treatments, T cells are genetically re-engineered to recognize cancer epitopes and destroy malignant cells. Unfortunately, it still remains challenging to determine which T cells can target a specific epitope, both from a computational and experimental point of view. This limits mechanistic understanding of T-cell-mediated immunity and translational applications for disease treatments. Thanks to advances in high-throughput sequencing technologies, sequence data of T cells coupled with their cognate epitopes are accumulating at an unprecedented pace, offering unique opportunities to develop data-driven T cell-epitope interaction predictors. The goal of the MT-PoINT project (Motif in T cells for the Prediction of INTeractions) is to identify patterns in T cells sequences that underlie the binding specificity, interpret them at the structural level, and to develop sequence-based predictors of T cell-epitope interactions (Aim1) with a special focus on T cells targeting cancer epitopes (Aim2). My project will capitalize on a unique dataset of publicly available and in-house generated data that was not available in previous studies, and T cell sequence data from cancer patients of Lausanne University Hospital will allow me to benchmark the in-silico predictors in a clinically relevant setting. Accurate predictions of TCR-epitope interactions can narrow down the list of T cell candidates for personalized cancer immunotherapies, and significantly accelerate cancer immunotherapy clinical developments.

Keywords: computational immunology,computational cancer biology,t cell epitope prediction,t cell based immunotherapies
Interplay between genetic control and self-organization during embryo morphogenesis (Self-Control)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Cellular, Developmental and Regenerative Biology
Panel description: Structure and function of the cell, cell-cell communication, embryogenesis, tissue differentiation, organogenesis, growth, development, evolution of development, organoids, stem cells, regeneration, therapeutic approaches
Countries involved: France
Call: ERC Advanced Grant (ERC-2017-ADG, 2017)
Start date: 2018-11-01
End date: 2024-10-31
Duration (months): 72.0
Total project cost (EUR): 2862571.0
EU funding (EUR): 2862571.0
Participants: 2
Project status: SIGNED

Morphogenesis seeks to understand how information and mechanics emerge from molecular interactions and how they are regulated in space and time. Two parallel legacies are now intertwined: the conceptual framework of developmental patterning that explains how cells acquire positional information during development and control cell behaviors, and the description of biological processes in physical terms. The current framework explains how genetic and biochemical information controls cellular mechanics, in particular contractility mediated by actomyosin networks, and thus cell and tissue shape changes. However, newly reported contractile dynamics, namely pulses, flows and waves, cannot be explained in this framework: they are self-organized in that they depend on local mechano-chemical interactions and feedback that cannot be accounted for by upstream genetic control. This project will explore the interplay between genetic control and self-organization in Drosophila embryos. We will study the emergence of multicellular flow and the mechanism of newly characterized tissue-level trigger wave dynamics associated with endoderm invagination, a poorly studied process. We will ask: 1) how do patterns of apical and basal contractility drive cell dynamics; 2) what is the contribution of geometrical feedback, e.g. tissue curvature, in amplifying the effect of contractile asymmetries; and 3) what is the nature of mechanical feedback and cell spatial coupling underlying trigger wave dynamics in the tissue? We will use an interdisciplinary approach, combining live imaging, capturing the 3D shape of cells/tissues, genetic/optogenetic/mechanical perturbations and theoretical/computational methods to model mechanics and geometry. We expect to unravel how organized multicellular dynamics emerge from genetic, mechanical and geometric “information”, and feedback during morphogenesis. This work will shed new light on a variety of morphogenetic processes occurring during development.

Keywords: morphogenesis,mechanics
Digital Alfieri. Dynamic Digital Editions: Case study Alfieri 13 (DIGITAL ALFIERI)

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: Social Sciences and Humanities
Countries involved: France
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-03-01
End date: 2018-02-28
Duration (months): 24.0
Total project cost (EUR): 173076.0
EU funding (EUR): 173076.0
Participants: 1
Project status: CLOSED

The aim of this project is to provide a dynamic digital edition of the manuscript Alfieri 13 (Biblioteca Medicea Laurenziana of Florence), in order to provide new perspectives on at least three fields: digital humanities, textual criticism, and 18th century literature. Alfieri 13 is a miscellaneous scribbling-book (232 pages) which is of a capital importance for the understanding of the evolution of Alfieri's thinking: in fact, it is a crossroad of several literary projects of Vittorio Alfieri (Asti 1749 – Florence 1803, one of the most important European writers of the 18th century). The digital output (allowing to link and cross-referring information in a non-sequential way) is the best way to highlight how the physical (static) conformation of the object (the manuscript) portrays the intellectual (dynamic) evolution of an individuality (the writer). The applicant will take the innovative approach of combining two concurrent (but complementary) perspectives on the study of manuscripts: filologia d'autore and critique génétique. Those approaches are now getting closer thanks to the recent establishment of an Italian research team at the hosting laboratory, the CNRS-ITEM (Institut des Textes & Manuscrits Modernes). This research team, Manuscrits Italiens du 18e siècle (Italian Manuscripts of the 18th century) is leaded by Christian Del Vento (supervisor for this project) and it will focus on methodological aspects and on controversial case studies, among which the manuscript Alfieri 13. The proposed digital edition of Alfieri 13, will be of a fundamental relevance for various fields, and especially: 1) Digital Humanities: it will provide digital textual criticism with an effective model, exploitable for other manuscripts and authors; 2) methodology: it will serve as a bridge between filologia d'autore and critique génétique; 3) literature and culture of the 18th: it will lay the foundations for a reliable edition of Alfieri's Vita and Rime.

Keywords: textual criticism,critique g n tique,filologia d autore,digital humanities,autobiography,18th century,italian literature,vittorio alfieri,manuscript,vita,rime
META DATA ANALYSIS LAB to Enhance Training Quality (MyGoalMEDAL)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Germany
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-12-01
End date: 2020-05-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

How are you? A simple question and people’s answers to it lead to a disruptive plan. The interdisciplinary approach to semantic analysis and machine learning is a shift of paradigm in endurance training, rehabilitation, and health precaution. It will boost our business and solve a problem all personal trainers have. There is a natural growth limitation in 1:1 care because of time consuming efforts. Machine learning helps us to systemize and up-scale what we already do successfully. Listening and understanding are the key competences for our corporate promise: “Achieve Your Goal Healthy!” We have developed a plan with global implications for e-health. We will show how we are going to transform the results of machine learning from particular data sources into a must-have application for trainers and for their clients. The proposal shows how this can be done on large scales with a little help from our competitors. Thereby we include an underestimated data perspective in sports, but health care too. We want to find out, how to implement and up-scale our strategy that leverages trainer’s best practice internationally. A simple solution and a starting point from within a market niche will lead to a disruptive innovation. The outcome will enable huge business opportunities not only in sports, but in rehabilitation and health precaution.

Keywords: sports,training,endurance training,triathlon,running,cycling,rehabilitation,health precaution,obesity
Multivalent interactions driving RNP dynamics in development and disease (RNPdynamics)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Integrative Biology: from Genes and Genomes to Systems
Panel description: Genetics, epigenetics, genomics and other ‘omics studies, bioinformatics, systems biology, genetic diseases, gene editing, innovative methods and modelling, ‘omics for personalised medicine
Countries involved: Slovenia,United Kingdom,United Kingdom
Call: ERC Advanced Grant (ERC-2018-ADG, 2018)
Start date: 2020-01-01
End date: 2025-09-30
Duration (months): 69.0
Total project cost (EUR): 2396261.25
EU funding (EUR): 1827418.25
Participants: 4
Project status: SIGNED

Ribonucleoprotein complexes (RNPs) play many key regulatory roles in development. Moreover, mutations causing cancer or neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS), often occur in RNA-binding proteins (RBPs). These mutations are concentrated in the intrinsically disordered regions (IDRs), which play a central role in the control of RNP assembly and disassembly. RNP dynamics is often driven by multivalent interactions that are mediated by multiple elements within IDRs of RBPs, which can condense the RNP such that it separates from the surrounding liquid through the phenomenon of liquid-liquid phase separation. Transcriptomic insights into the physiological functions of such multivalent RNP assembly are needed to understand their regulation, or deregulation through disease-causing mutations. Here, we will build a framework of experimental and computational methods to study the mechanisms by which the dynamic multivalent interactions drive RNP remodelling, and how such RNP dynamics contributes to cellular transitions in development and disease. The first objective will be to identify the functions of specific RBPs in cell-state transitions during neuronal differentiation, and the mechanisms of IDR-mediated multivalent interactions in these functions. The next objective will be to establish new tools to manipulate RNP assembly through multivalent RNA binding sites and IDRs. Finally, the new insights and tools will be integrated with the goal to fine-tune the RNP assembly of ALS-mutant RBPs, and thereby ameliorate their toxicity.

Keywords: gbp gfp binding protein nanobody,idr intrinsically disordered region,line long interspersed nuclear element,llps liquid liquid phase separation,rbp rna binding protein,rnp ribonucleoprotein complex,rte retrotransposable element,slim short linear motif