Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet FINE ReMorph (Horizon Europe, appel à projets 2024)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : SIGNED

There is still much room for improvement in reading intervention, testing and teaching in Europe. Morphology, in particular, has been neglected in reading acquisition theories, which have focused on narrow contexts including monomorphemic words, children in the first steps of reading acquisition, and the English language only. FINE ReMorph will determine whether morphological knowledge impacts reading development earlier in languages with richer morphology and whether different trajectories appear in languages with different orthographic and syllabic features. French, Italian, Norwegian, and English, four languages resulting in diverse combinations of morphological richness, orthographic depth, and syllabic complexity, will be compared. Language and reading will be tested in three different age ranges of school-aged children. Ocular movements will be tracked to determine the role of different morphological constituents in written-word recognition. I will coordinate my Associated partner and two Short-Visit Hosts remotely and through a 6-month secondment and two one-month short visits to ensure the smooth implementation of testing activities in every language under study. The project output will inform the scientific, clinical, and educational communities about the age of impact of morphology on reading in languages with different morphological, orthographic, and syllabic features. This will determine if, when, and how to introduce morphology instruction into scientific, clinical, and educational interventions in diverse languages. At my Host, I will acquire neuroscientific knowledge of neuroimaging techniques; on secondment, I will practice eye-tracking research; during my two short visits, I will improve my psychometric skills with the authors of the FINE ReMorph core test. The advanced technological/behavioral methods and transferrable skills acquired will increase my research profile competitivity and strengthen my interdisciplinary scientific network.

Mots clés : reading, morphological richness, orthographic depth, syllabic complexity, word decoding, pseudoword decoding, word recognition, eye tracking

Participants :
- Université norvégienne de sciences et de technologie (Norvège) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université Aston (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 276187.92 €
Projet MirrorBody (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : CLOSED

The central role of molecularly-targeted therapeutics and imaging probes in translational research entails the development of an ever-growing arsenal of “chemical biologics” endowed with optimal in vivo properties. In this regard, mAbs and their derivatives (e.g. ADCs) still suffer from unsettled drawbacks involving difficulties in production and characterization, leading to heterogeneous conjugates in terms of size, potency and toxicity. Chemical modifications on mAbs are highly unreliable due to their complex structure: a central problem in this discipline, where heterogeneous drug-to-antibody ratio (DAR) and conjugation site represent significative limitations. Immunogenicity is a major drawback which affects humanized, as well as fully-human mAbs, and is exacerbated by long half-lives. Cases of unwanted activation of the immune system reportedly degenerated to life-threatening conditions such as acute anaphylaxis, serum sickness and cytokine release syndrome. Their bulky size (≈150 kDa) hinders their extravasation, impairing their efficiency to enter tumors. Nanobodies (Nbs) are the smallest naturally-derived antibody fragments (≈13-14 kDa) that retain antigen-binding affinities in the same range of mAbs (nM to pM affinity range) while having extremely reduced half-lives ( ≈ 15 min.) when not bound to their target, thanks to a fast renal excretion. MirrorBody intends to push the boundaries of targeted “chemical biologics” via an interdisciplinary approach that exploits both immunology and synthetic chemistry techniques for the generation of synthetic D-nanobodies that bind natural L-targets with high affinity. Such unprecedented synthetic D-Nbs will be endowed with improved biocompatibility, and will enable “plug-and-play” approaches for the controlled conjugation of diverse moieties.

Mots clés : chemical protein synthesis, d protein, d peptide, single domain antibody, nanobody, molecular targeting, chemical ligation, glycopeptide, racemic crystallography, chirality

Participants :
- Centre national de la recherche scientifique (France) — Coordinator, beneficiary, Recherche, subvention : 195914.88 €
Projet DAMSECIS (Horizon Europe, appel à projets 2024)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : SIGNED

Renewable energy has become a crucial issue in the current socio-ecological crisis, but in recent years its generation through large wind and solar farms is causing environmental conflicts, as has happened with dams. However, the hegemonic narratives about dams tend to be very positive and there are few analyses of them as conflict and “sacrifice zone” from an environmental history and environmental justice perspectives that consider their impact on local communities along time. There is also a lack of studies on the construction of dams in a country as a whole and comparison between countries to get an international overview. This project aims to fill these historiographic gaps, identifying the elements that turned dams into environmental conflicts, analysing their impact on local communities since their planning or construction onwards, and constructing an overview of dam building in Spain and in Italy since 1900 to the present time, adopting a comparative and international perspective and revealing what hegemonic narratives have hidden and silenced. Both southern European countries are similar in terms of climate and rainfall pattern, internal territorial differences and political history last century, and they are the 1st and the 3rd more damned countries in the EU. The reconstruction of a comparative history of dam building can allow a better understanding of the current resistance phenomena to renewable energy projects and a territorial mediation in these conflicts. The research will be based on information gathered in archives, media, written and audiovisual materials and through interviews and field trips. Carrying out the project DAMSECIS at UniBg, I will enhance my training with new skills, as territorial mediation, and methods, as prosopography, comparative history, mapping and the construction of multidisciplinary digital research infrastructure such as databases with georeferenced historical series, and it will open new career opportunities in Europe.

Mots clés : dams, environmental conflicts, renewable energy, hydroelectricity, hegemonic narratives, urban rural, sacrifice zones, governance, italy, spain, fascism, francoism, environmental justice

Participants :
- Université de Bergame (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 193643.28 €
Projet OURLEM (Horizon Europe, appel à projets 2024)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : SIGNED

Gas turbines play several important roles in Europe, contributing to various sectors of the economy. According to the Polaris Market report, the global gas turbine market was valued at 22.25 billion USD in 2021 and is expected to grow at a CAGR of 6.3% till 2030. At this huge global market size, since fossil fuels are burned in gas turbines, they release greenhouse gases, including CO2. Based on the 2030 EU Climate Target Plan, sets Europe on a responsible path to becoming climate neutral by 2050, greenhouse gas emissions should be cut by at least 55% by 2030. Hydrogen gas turbines offer several advantages over fossil fuels, making them an attractive option for clean and sustainable energy generation (zero emissions), helping to face climate change, and reducing air pollution. However, hydrogen burns at a higher temperature compared to other fuels, which poses challenges for turbine blade cooling and requires an efficient cooling technique to maintain blade integrity. Film cooling, by injecting cold air at discrete locations over the exposed surfaces through holes and slots, is one of the available technologies. Additive structures, such as ramps, near the exit of the cooling hole geometry can be used to improve the film-cooling effectiveness, thus increasing the gas turbine efficiency. The geometrical configuration of the upstream ramp can significantly affect the cooling effectiveness on the surface and the mixing between coolant and mainstream. Therefore, the ramp configuration should be carefully designed. In this project, this goal will be achieved through a multidisciplinary optimization approach, based on the combination of experiments and high-fidelity Large Eddy Simulations, making use of Artificial Intelligence and Machine Learning approaches. The outcome of the project will be an optimization tool and an optimized ramp to be applied on the cooling hole and expected to result in better thermal efficiency in the gas turbines and lower fuel consumption.

Mots clés : large eddy simulation, gas turbine cooling hole, upstream ramp, machine learning, pressure sensitive paint

Participants :
- Université de Bergame (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 209483.28 €
Projet LIGNIN-IB-PEROXIDASE (Horizon Europe, appel à projets 2023)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : SIGNED

Context: Globally, 50-70 million tons of lignin, a highly branched heteroaromatic polymer, are discharged per year as a waste material from the paper and pulp industry despite being touted as the most abundant renewable source of different value-added products on earth. Leaving 98% of lignin underutilized, industries degrade only 2% of lignin and that also comes with environmentally hazardous thermochemical processes. Background: Recently, the discovery of heme-containing class II fungal peroxidases viz. lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), dye-decolorizing peroxidase (DyP) garnered a lot of attention due to their biodegradable ligninolysis. However, the industrial application of peroxidase-based lignin degradation still seems to be a far-flung dream owing to low availability of peroxidases in sufficient amount, enzyme instability in industrial effluent, high enzyme cost and long process times. Aims and objective: I hypothesize that a cocktail of engineered stress tolerant, active and stable peroxidases could lead to synergistic biodegradation of lignin. To achieve this, artificial intelligence (AI) tailored LiP, MnP, VP and DyP will be cloned and expressed as inclusion bodies (IBs) in E. coli using Prof. Spadiut’s expertise whereas mine will employ solubilization and refolding strategies to increase the overall yield of bioactive protein. An ideal stoichiometric combination of engineered peroxidases will be standardized to withstand the harsh conditions of industrial effluent, resulting in a sustainable and economic ligninolytic technology. Concluding remarks: The project is inspired from nature, backed with AI and stemmed with the expertise of mine and Prof. Spadiut’s in producing recombinant bioactive protein from bacterial IBs while TU Wien’s decades of experience in commercializing the technology will be a fertile playground to bow the seeds of a sustainable ligninolytic technology.

Mots clés : bacterial inclusion bodies, protein folding, protein engineering, protein aggregation, biophysics and biochemistry

Participants :
- Université technique de Vienne (Autriche) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 183600.96 €
Projet VOCfireDRONE (Horizon Europe, appel à projets 2024)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : SIGNED

Climate change is one of the most pressing environmental challenges of our time that has led to a dramatic escalation in the frequency and intensity of forest fires. As global warming continues to increase, addressing the challenge to investigate their effects has never been more urgent. A major concern that arises during a forest fire is the rapid and intense release of hazardous volatile organic compounds (VOCs) into the environment that can be toxic and potentially carcinogenic. These hazardous compounds continue to be emitted even after the extinguishment of a forest fire, while new toxic compounds can be also formed. Focusing on minimizing their adverse effects on human health, the comprehensive monitoring of VOCs release during and after a forest fire is of utmost importance. To be able to obtain an as realistic and comprehensive estimate as possible on the chemical identity, concentration, and temporal profile of hazardous compounds, it is imperative to do the sampling as close as possible to the point of emission, which indicates the demand for a remote-controlled drone-sampling device. The overall aim of this project is thus to develop a powerful drone sampling system that can be used for the monitoring of toxic VOCs during and after a forest fire, focusing on decreasing the risks that occur from human exposure to these compounds. The drone will be equipped with a novel type of sorptive extraction samplers and laboratory analysis will be performed using one- and comprehensive two-dimensional gas chromatography-mass spectrometry to elucidate the extremely complex pattern of VOCs being produced by these events. This aims to provide a comprehensive understanding of the damage caused to first responders and the exposed population due to the emission of toxic and harmful compounds during forest fires.

Mots clés : separation science, climate change, wildfires, environmental analysis, sample preparation, sorptive extraction techniques, gas chromatography

Participants :
- Université technique de Vienne (Autriche) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 214344.72 €
Projet ARIADNE (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

In this project (ARIADNE) I will address several key challenges of today’s hardware-based neuromorphic computing by developing a novel AI system based on a highly complex, dynamical and nonlinear integrated photonic neural network that is easy to fabricate and consumes low power. The proposed implementation is enabled by an original machine learning approach which allows to considerably relax the requirements on fabrication reproducibility and on observability and tunability of the network parameters. The AI system is expected to learn to perform multiple complex and time-dependent computational tasks at high speed within a compact device, finding application in real-time control with enhanced cybersecurity (robotics, autonomous vehicles, internet of things, …) and physiological signals analysis (e.g. prediction of epileptic seizures). ARIADNE will be hosted by the NanoLab research group at the University of Trento (UNITN).  The project acronym is inspired by the ancient Greek myth of Theseus and the Minotaur, where princess Ariadne comes up with an ingenious way to help Theseus escape the labyrinth. In ARIADNE I aim to let a reinforcement learning algorithm learn to solve, loosely speaking, the spatio-temporal maze represented by the complicated dynamics in the considered networks of integrated optical resonators. In particular, the reinforcement learning algorithm will learn to control a complex feedback loop in order to set favorable dynamical network properties that allow to carry out target computational tasks.  The AI system is expected to learn to perform multiple complex and time-dependent computational tasks at high speed within a compact device, finding application in real-time control with enhanced cybersecurity (robotics, autonomous vehicles, internet of things, …) and physiological signals analysis (e.g. prediction of epileptic seizures).

Mots clés : neuromorphic photonics, spiking neural networks, integrated silicon photonics, machine learning, ring resonators, reservoir computing, reinforcement learning, on chip learning, edge computing

Participants :
- Université de Trente (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 188590.08 €
Projet ProSVED (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

ProSVED stands for Projection of Security Vulnerabilities caused by Exploits in Dependencies, and targets the prognosis of software vulnerabilities via security exploits in third-party libraries. The code controlled by developers, e.g. to add security patches, is a small fraction of the whole codebase that supports any software project today. Most lines of code reside in external dependencies whose security vulnerabilities pose threats to the entire project. This can be mitigated via strategic update policies. However, measuring the risks to find optimal policies constitutes a tremendous prognosis problem, to find the needle of offending lines that hide in a haystack of third-party libraries. ProSVED proposes a novel rare-event approach to the challenge, to estimate the most promising update policies in order to reduce the security risks inherited from external code. Working with experts from the University of Trento, ProSVED will thus push the frontiers of software security analysis, taking it beyond its classical empirical approach, and into the horizon of formal risk modelling for prediction and mitigation.

Mots clés : rare event simulation, risk prognosis, cybersecurity, library dependencies

Participants :
- Université de Trente (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 172750.08 €
Projet MultiMeans (Horizon Europe, appel à projets 2022)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : SIGNED

Language is our most potent cognitive and cultural tool, through which we can shape one another’s minds, share information and build knowledge collectively across generations. This is crucial during development: infants build knowledge to the extent that adults offer the appropriate scaffold, i.e. if the teaching material is tuned to the infant’s current understanding. At present, it is hotly debated whether we can open communication and share knowledge with infants only by means of spoken words, or whether gestures offer equal scaffolding. The growing "baby sign" movement may offer this possibility. Baby sign is a system of symbolic gestures, i.e. signs that have meaning and symbolize concepts. As a result, symbolic gestures are a potential means for exchanging meanings in the preverbal infant/adult dyad. However, this exciting scenario cannot be proved by the existing research, which shows contrasting views that only rely on the indirect interpretation of infant behaviour. Using EEG, the present project will be the first to directly decode the baby brain and establish a direct quantitative comparison with the adult brain to verify whether the two share a common multimodal conceptual space, essential for exchanging meanings before and beyond spoken language. At the scientific level, the project will provide an unprecedented understanding of the origins of human language and symbolic cognition, which are essential hallmarks of our species. By testing whether these core abilities develop not only via the verbal channel (spoken words) but also via the visual channel (symbolic gestures), it may support a paradigm shift in favor of human language as inherently multimodal. At the societal level, the project will test key assumptions of baby signing, whose widespread interest is not equally paralleled by compelling scientific evidence; thus, it will directly impact intervention models that aim to support human language and symbolic cognition during (a)typical development.

Mots clés : multisensory processing, language, communication, gestures, semantics, preverbal infants, eeg

Participants :
- Université de Trente (Italie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 188590.08 €
Projet BluE (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : SIGNED

A deeper understanding of marine ecosystems is crucial to enforce protective actions and promote a sustainable exploitation of the oceans’ resources. Adequate spatial and temporal coverage of data can be obtained by resorting to a network of fixed and mobile platforms to combine the advantages of different types of units. Existing mobile platforms, such as autonomous underwater vehicles (AUVs) and seabed crawlers, present intrinsic limitations when operating in the benthic environment which can be overcome by underwater legged robots (ULRs). ULRs, with arthropod-like versatile locomotion, are not much affected by currents, drain little power while keeping a fixed position, exhibit a gentler interaction with the seabed and produce a lower acoustic signature in comparison with propeller driven vehicles. The BluE project aims at bringing the advantages of bioinspired ULRs in ecological monitoring applications by combining their capabilities with those of fixed and mobile platforms. This aim will be pursued by (1) demonstrating tethered integration of a bioinspired ULR with a fixed monitoring platform (i.e., underwater cabled observatory) to perform visual census of the ictic community, and by (2) implementing a collaboration between a bioinspired ULR and an AUV to demonstrate obstacle free navigation. To undertake this research, I will join the Marine Science Institute of the Spanish National Research Council, world’s expert in the ecology of the Mediterranean Sea. Additionally, I will carry out two secondments at the University of Girona and at the Polytechnic University of Catalonia to receive training on mobile and fixed monitoring platforms and gain access to unique facilities such as the AUV Girona500 and the OBSEA cabled observatory. This project will contribute to the development of new tools for underwater operations with potential impact in scientific and commercial sectors and will establish the proponent as a prominent researcher in underwater robotics.

Mots clés : marine robotics, underwater cabled observatories, ecological monitoring, autonomous underwater vehicles auvs , marine ecology, benthic environment

Participants :
- Université polytechnique de Catalogne (Espagne) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Conseil supérieur de la recherche scientifique (Espagne) — Coordinator, beneficiary, Recherche, subvention : 165312.96 €
- Université de Gérone (Espagne) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €