Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DISCOVERY (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université polytechnique de Valence — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

MXenes were discovered in 2011 and, since then, have attracted attention as electro- and photocatalysts. In contrast, the ideal properties of MXenes as thermal catalysts remain almost unexplored, there being a very limited number of studies. The main reasons for this apparent lack of interest are: i) the shift in catalysis from heat as energy to overcome activation barriers to green electricity or sunlight, ii) the limited number of commercial MXenes and iii) the relative novelty of these materials. However, MXenes offer unique compositional range, structural flexibility and material properties that can make them disruptive catalysts. These properties include: i) prediction of the catalytic properties by DFT calculations, ii) possibility of metal alloying resulting in multimetallic MXenes, iii) absence or presence of surface terminal groups of various elements, including OH, -O- and halides, iv) control of lateral size from 2D to 0D forming MXene dots, v) strong metal support interaction making possible single atom catalysis. The aim of DISCOVERY is fill the current gap, applying MXenes to reactions in which their structure appears to be optimal according to the nature of active sites (Ti-OH or V=O) and DFT predictions (strong CO2 adsorption on surface-free MXenes). Specifically DISCOVERY will study two reaction types characteristic of some active sites such as titanol (alkene epoxidation) and vanadyl (CH4 oxidation to CH3OH and oxidative alkane dehydrogenation) or of metal nanoparticles (hydrogenation of CO2 and N2 and CH4 decomposition to H2 and carbon). DISCOVERY will not be a trial and error check of new catalysts, since it will be led be predictive DFT calculations and artificial intelligence tools. Extensive use of XAS (to monitor the changes in the metal elements during the reaction) and vibrational spectroscopy (detection of reaction intermediates) will shed light on the reaction mechanism.

Mots-clés : mxenes,alkene epoxidation,methane activation,oxidative dehydrogenation of alkanes,co2 hydrogenation to methanol,n2 hydrogenation,methane decompositionb
Projet ERC : K-S-H-Raksa (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : Université de Marbourg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499250.0 €

The importance of Kashmirian Sanskrit Literature was realised by scholars only in the late 19th century, when the literary canon and historiography of Sanskrit Literature in the Indian subcontinent had already taken shape. Texts and whole genres that were unique to Kashmir, as political history, were not properly recognised and led to a distorted view of South Asian literature. Much has changed, especially in the last decades, but the latest exodus and dissipation of the Kashmirian Hindu community is bound to have a lasting negative effect on such studies. A major effort to rescue the still unpublished and often unknown highlights of Kashmirian Sanskrit literature from oblivion is warranted.  In the present project a team specialising in editing Kashmirian texts will make a larger number of carefully selected texts accessible in first editions by utilizing the vast reservoir of manuscript scans that has sprung up online in recent years. Previous work on unknown texts from newly opened up archives has suggested that much more is to be discovered. One spectacular example would be a 17th century piece of visual poetry from Kashmir, the ``Wish-fulfilling Tree'', which is breaking several international records (for instance, for using thirty languages in its intexts), but has remained completely unknown until very recently.  The project will produce a careful selection of previously unknown Kashmirian Sanskrit works in ten volumes. They will be accompanied by studies of their literary, religious or philosophical aspects, from which their significance for the history of Sanskrit Literature can be grasped. The project is a bold attempt to drastically improve the basis of scholarship in Kashmirian Sanskrit, and we shall argue that as a result new genres in Sanskrit literature need to be defined.

Mots-clés : indology,sanskrit studies
Projet ERC : SymSim (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université technique de Rhénanie-Westphalie à Aix-la-Chapelle — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2495575.0 €

The goal of this project is to develop an algorithmic theory of similarity between graphs. Graphs are versatile models for representing complex data ranging from chemical molecules to social interactions. Dealing with graphical data and enabling modern data analysis techniques, a fundamental task is to compare graphs and to measure their similarity, preferably in a semantically meaningful and algorithmically efficient way. However, it is not clear at all how to achieve this. In many application areas, for example, computer vision, database systems, and formal verification, researchers have proposed (often ad-hoc) solutions to this problem tailored for the specific application, but a general theory is missing. We will develop such a theory in this project.  Similarity of graphs has many different facets. We will identify the common core of different approaches to similarity, but also exhibit their differences. We will design methods for comparing different similarity measures and for obtaining a semantic understanding of similarity. We will develop criteria for the suitability of various similarity measures for different types of applications.  A particular focus of our research will be on efficient algorithms for computing similarity. There is little use in having a perfect similarity measure if we have no efficient way of determining how similar two graphs are.  A classic algorithmic problem in this context is the graph isomorphism problem of deciding whether two graphs are structurally identical. Determining the precise computational complexity of this problem, or of the equivalent problem of computing all symmetries of a graph, is regarded to be one of the most important open questions in theoretical computer science. Building on recent progress, we will design new algorithms breaking barriers towards a polynomial-time algorithm for the isomorphism problem.

Mots-clés : graph similarity,graph isomorphism,vector embedding,constraint satisfaction,homomorphism counting
Projet ERC : MOD3CAT (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de technologie d'Eindhoven — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499481.0 €

This proposal is on modelling of 3 phase gas-solid-liquid multi-component flows with catalyst particles, which are frequently encountered in industrial applications, but have not been tackled fundamentally before due to their complexity.  Dense multi-phase flows have been intensively researched because of their scientifically interesting transport phenomena and industrial applications. Considerable progress has been made for gas-solid and gas-liquid two-phase flows. However, catalytic multicomponent three-phase flows have received relatively little attention despite their importance for the production of clean synthetic fuels, base chemicals, and many other products. Multiphase transport phenomena in such systems are poorly understood due to their complexity. Therefore the design of processes is cumbersome. In addition, the process operation is often far from optimal in terms of energy and feedstock utilization. Therefore significant improvements are required to boost the efficiency of three-phase systems, which demands for a better understanding of the transport fundamentals and complex interplay with chemical reactions and availability of predictive tools.  The main underlying problem is the wide range of length scales: suspended catalyst particles have a size of 100-200 μm, whereas the diameter of industrial reactors is 5-10 meters. To tackle this problem a multi-scale modeling strategy is required. At the finest scale detailed models take into account the interaction between the phases. These interactions are condensed in closure laws for mass, momentum and heat exchange that feed so-called Euler-Lagrange models, which can then be used to compute the flow structures on a much larger (industrial) scale. The key innovative aspect of this proposal is the integrated approach including incorporation of multi-component chemical transformations and the validation on basis of one-to-one comparison of the of the computational results with experiments.

Mots-clés : three phase flow catalytic reactive multi scale modeling experimental validation coupled mass,momentum and heat transfer
Projet ERC : PROACTHIS (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Université de technologie d'Eindhoven — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2498516.0 €

The field of control has been a key driver for major societal innovations in health, mobility, energy and manufacturing. At present, technological trends push the performance requirements for future applications to extreme levels that are far beyond current control solutions. Existing linear controllers for linear systems are supported by user-friendly time- and frequency-domain design tools, yet they lack the flexibility to overcome fundamental performance tradeoffs. Full nonlinear control structures provide the desirable flexibility, but they lack comprehensive frequency-domain design techniques. These observations indicate a lack of flexible control structures accompanied by systematic design and online optimization frameworks exploiting time- and frequency-domain information to realize the unparalleled performance needs of future engineering systems. In PROACTHIS, I will bridge this scientific gap by creating a new control paradigm based on projection operators. By introducing projections in control loops, specific signals are kept in well-chosen constraint sets inducing direct performance-enhancing benefits. I foresee that the mathematical structure of these projection-based controllers enables fundamental properties that were instrumental in the success of linear control and will be key to obtain effective design frameworks for this new class of hybrid controllers. Developing projection-based control theory has high risks, as even the mathematical formalization of these control schemes leads to a new class of dynamical systems never studied before. This scientific challenge calls for leveraging powerful multi-disciplinary methodologies from Hybrid Systems, Control Engineering, Networked Systems, Learning and Mathematics. Successfully developing this new system theory will pave the way towards game-changing cutting-edge control methodologies addressing the needs of future engineering systems, thereby enabling new breakthroughs in important societal domains.

Mots-clés : hybrid systems,stability,control systems,networked systems,networked control systems,projected dynamical systems,piecewise linear systems,linear matrix inequalities,iterative learning control,extremum seeking,circle criterion,integral quadratic constraints,frequency response functions,projection,lure systems,linear parameter varying systems,switched systems
Projet ERC : EmergAI (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université d'Uppsala — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2497200.0 €

* Background: Emergency care costs are increasing in developed societies, both in rates of emergency department (ED) visits per person and in costs per visit, and are growing faster than other areas of healthcare spending. With limited and unstructured data, ED staff make quick decisions about probabilities for multiple diagnoses and risks. Both underestimation and overestimation of these probabilities lead to increased costs and patient harm. Hence, there is desperate need for clinical decision-support systems in the ED. * Aim: To develop a clinical decision support system for emergency medicine doctors, using sensor data, health records data and patient-reported data, validated in a randomized clinical trial, in order to improve the safety, efficacy and cost-effectiveness of emergency care. * Objectives: We will: Develop machine learning (ML)-powered diagnosis and risk prediction algorithms for common and dangerous conditions based on age, sex, presenting complaints, previous diagnoses, ECGs, and vital parameters; develop and validate a patient-centred technical platform for collecting, storing and sharing patient-reported data and three-dimensional symptom drawings; develop ML-powered diagnosis and risk prediction algorithms for common and dangerous conditions based on patient-reported data and symptom drawings; conduct a large-scale prospective ED data collection for internal and external validation of ML models using a common format for online applications and for further data collection; develop a Bayesian network-powered ED-based clinical decision support system that generates probabilities for diagnoses and 30-day mortality risks and suggestions for the most valuable next step, from data in multiple formats, with visual representation of probabilities, risks and uncertainties and Bayes factors for potential next steps; and conduct a randomized clinical trial investigating the usefulness, effectiveness and safety of the new decision support system.

Mots-clés : emergency medicine,machine learning,decision support
Projet ERC : CardioGROWTH (Horizon Europe, appel 2024, Advanced grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems E ngineering
Entité participante : Institut für Molekulare Biotechnologie — Pays : Autriche — Rôle : PI
Acronyme de l'entité : IMBA
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 2500000.0 €

Cardiovascular disease (CVD) is the leading global cause of death. Yet, breakthroughs in cardiac therapies are limited due to the poor predictive power of current models. While the animals fail to accurately replicate human heart physiology, the human pluripotent stem cell-derived models remain underdeveloped and immature for reliable disease modeling and therapy development. To address these challenges, we propose to further develop our cardiac organoid (“cardioid”) model and recapitulate the key stages of heart growth, including trabeculation, compaction, vascularization, and postnatal hypertrophy, resulting in physiological-like maturation. We hypothesize that these processes lead synergistically to postnatal heart maturation. Guided by developmental principles, we will combine signaling, metabolic, and genetic manipulations, as well as quantitative morphometric, functional, and molecular readouts on our high throughput cardioid platform. By leveraging advanced technologies (e.g., light sheet microscopy and single-cell proteomics), we will develop a physiologically relevant cardiac model that enables predictive cardiac disease modeling and drug discovery, paving the way for innovative therapies and regenerative medicine.
Projet ERC : PastSolarStorms (Horizon Europe, appel 2023, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : Université de Lund — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2498835.0 €

Our Sun is a remarkably stable energy source which is crucial for life on Earth. However, we know that the Sun exhibits variations on a wide range of time scales. Occasionally, violent eruptions on the Sun’s surface, so-called solar storms, release energetic particles that can damage our modern society. Nowadays the Sun is constantly monitored and a wealth of information has been obtained about its variability from ground-based and satellite observations. However, our Sun exhibits variations that exceed the range measured during the space era as evidenced from sunspot observations over the past 400 years. Similarly, as demonstrated by historical observations and indirect proxy data, the Sun can produce solar storms orders of magnitudes larger than anything observed during the space era. Presently, we do not know the recurrence rate of large solar storms and how these are linked to solar activity. Mapping out the linkages may help to understand underlying processes and to predict the risks for future events.  To achieve this we can take advantage of the “natural detector” of past solar activity – cosmogenic radionuclides in highly resolved and well-dated natural archives. I am proposing to develop this natural cosmic ray detector to increase its detection limit, resolution and reliability for assessing solar storms and solar variability in the past. This involves an assessment of the complete chain from solar energetic particles to cosmogenic radionuclide deposition for ground-truthing of the natural cosmic ray detector. Furthermore, novel ice core sampling and improved analytical methods will allow us to produce an unprecedented database for these studies. We will test hypotheses of the recurrence rate of solar storms and their relationship to solar activity. Our results will extend space weather research to millennial time scales and lead to a ground breaking new understanding of the temporal variability of our star.

Mots-clés : ice core research,cosmogenic radionuclides,solar activity,solar storms
Projet ERC : CHAPLIN (Horizon Europe, appel 2022, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Université de Lund — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

The goal of the proposed study is to obtain a fundamental understanding of the molecular mechanism and thermodynamics of chaperone action. Chaperones are critical components of all organisms and serve to ensure a healthy state of the proteome. The proposal concerns a class of chaperones that increases the solubility of client proteins. The activity of these chaperones exhibits a number of crucial but poorly understood features; for instance, there is a remarkable specificity in action combined with promiscuous recognition across sequence space. These features are challenging to achieve through molecular design and raise the question of the general physical principles which govern chaperone activity. Our research aims to reach a general understanding, beyond specific effects, and we will study nine binary combinations of three chaperones and three client proteins. Our strategy is to first characterize in detail the aqueous solubility and self-assembly of each chaperone alone including the phase behaviour. With this knowledge, and our existing deep understanding of client self-assembly, we turn to chaperone action to study the thermodynamics of chaperone-client mixtures to determine the phase behaviour, structure of chaperone-client co-assemblies, the mixing stoichiometry and quantitative equilibrium parameters. We use state-of-the art scattering, spectroscopy, and microscopy methods and develop new methodology.  Common to the field is a mechanical view and search for specific sites in chaperone and client proteins that mediate their mutual interaction, but the promiscuity makes us question whether such sites exist. We take a new approach, not pursued by others in the field, in that we search for general molecular and thermodynamic principles of chaperone action. Our results may guide the design of small molecules that operate according to the same principles, which can serve as therapeutics toward some of the most devastating diseases affecting humans.
Projet ERC : MEDAPP (Horizon Europe, appel 2021, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Université de l'Algarve — Pays : Portugal — Rôle : Partner
Acronyme de l'entité : UALG
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 224173.46 €

The Islamic conquest of Iberia in the 8th century brought in profound changes in the political, social and economic realms that transformed the everyday life of local rural and urban communities. Technological innovations and the arrival of new crops impacted their agriculture, diet and culinary practices. Plants were present in almost all aspects of medieval people’s ordinary lives (food, crafts, medicines, etc.). However, they have been commonly sidelined in discussions of the past. Most of what we know about plants in this multicultural period in Iberia is based on a limited number of archaeobotanical studies and on written sources, which despite their undeniable value they often reflect issues related to the elites. By contrast, archaeology, and more specifically archaeobotany and their associated science-based techniques, are placed in an extraordinary position for approaching issues related to plant production, processing, preparation and consumption, and how these connect to broader societal changes. By integrating archaeobotany and written sources, as well as applying ground-breaking techniques (plant genomics and food remains analyses), MEDAPP aims to disentangle what range of plants were used in Medieval Iberia (6th-11th CE); where new species came from and when were they introduced, who brought them, and how people engaged with them through different practices. The project sets a new holistic agenda for understanding the impact of the new political, economic and social system on agriculture, eating habits and culinary practices of Iberian medieval communities. This project aims at providing a step-change in the way agriculture, plant production, preparation and consumption have been studied in Medieval Iberia. It represents a golden opportunity to fill the voids of texts, looking for clues in the archaeobotanical record; an occasion to approach, with a suite of scientific and innovative methods, the unspoken information contained in these silences.

Mots-clés : archaeobotany,written sources,islamic,food,identity,storage,food remains,isotopes,genetics,