Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Earth-abundant metal-containing photosensitizers for sustainable photodynamic inactivation in plant protection and food safety (EcoPDI)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: France,Austria
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2023-04-01
End date: 2025-03-31
Duration (months): 24.0
Total project cost (EUR): 195914.88
EU funding (EUR): 195914.88
Participants: 2
Project status: CLOSED

In the world, the phrase "we are going through a major food crisis" is becoming more and more common. This is because our society is faced with managing an exponentially growing world population and a decrease in arable land per person. This rising demand for food in developing countries is at risk due to plant diseases induced by bacteria, fungi and viruses. At the same time, food is traded globally, enabling the dissemination of dangerous microorganisms worldwide. Therefore, creating alternative and ecologically friendly antibacterial and antifungal treatments is essential to address the growing demand for safe and healthful plant-based foods. EcoPDI aims to solve this current and critical problem by developing new earth-abundant metal compounds with natural ligands as photosensitizers for photodynamic inactivation (PDI) of resistant bacteria and fungi. For this, EcoPDI focuses on the "Sustainable-Economic-Applicable" triple approach. Thus, this multidisciplinary project will develop new sustainable treatments that avoid the use of pesticides and employ sunlight to activate the antimicrobial activity of the compounds, will use cheap earth-abundant metals and improve the disadvantages of natural compounds, and apply the new photosensitizers directly to plants through the planned secondment. EcoPDI includes both the transfer of knowledge to the host institution and the training of the candidate in new techniques and methods. The findings have the potential to open up space for additional basic and applied research on PDI in plant protection and food safety. This proposal responds to the European Green Deal which has as its objective to restore damaged ecosystems and bring nature back across Europe and reduce the use and risk of chemical pesticides by 50% by 2030.

Keywords: earth abundant metals,photodynamic inactivation,natural compounds,antibacterial,antifungal,sustainable,plant protection,food safety
Tuning Immune T cells for cancer therapy (Tune_IT)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Netherlands
Call: ERC PROOF OF CONCEPT GRANTS (ERC-2023-POC, 2023)
Start date: 2024-01-01
End date: 2025-06-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Adoptive cell therapy (ACT) recently became an important treatment modality for cancer . Since 2017, several chimeric antigen receptor (CAR)-T cell therapies approved by the FDA/EMA and more are expected to receive approval for clinical use. Currently, more than 250 clinical ACT trials are ongoing. Already in 2021, the market size was >$1 billion and is expected to grow tremendously to >$25 billion by 2030. ACT products require extensive ex vivo manipulation and expansion of patient derived T cells prior to reinfusion back into patients to attack cancer cells. Unfortunately, T cell exhaustion and loss of function after reinfusion form a major problem in currently used ex vivo expansion protocols. The solution. Dedicated tuning of T cells during ex vivo expansion to preserve their anti- cancer function and prevent exhaustion. In the body, T cells are activated by antigen presenting cells (APC) to initiate an immune response. As patient-derived APC are often immunosuppressed, much effort is spent on developing 'artificial antigen presenting cells' (aAPC) to expand immune cells for ACT. We developed a unique polymeric aAPC platform, termed immunofilaments, that provide a highly flexible-, scalable-, GMP compliant- and affordable- solution for robust production of T cells for ACT. Our initial findings indeed indicate that we can diminish T cell exhaustion and outcompete products currently used in the clinic for ex vivo T cell expansion. Tune-IT will validate the technical and commercial feasibility of this novel technology platform that exploits immunofilaments to significantly improve function and longevity of ACT products in patients. In Tune-IT, we will: 1) demonstrate that tuning of ex vivo cultured therapeutic T cells will prevent exhaustion and loss of tumor killing capacity after reinfusing T cells and 2) perform market and business case analyses to ensure commercial feasibility and market entry through Simmunext Biotherapeutics, a Radboudumc spin-off
Counterfactuals in Minds and Machines (Counterfact)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-11-01
End date: 2030-10-31
Duration (months): 60.0
Total project cost (EUR): 1997500.0
EU funding (EUR): 1997500.0
Participants: 1
Project status: SIGNED

Reasoning about what might have been, about alternatives to our own pasts, is a landmark of human intelligence. Such type of reasoning, called counterfactual reasoning, is often evaluative, specifying alternatives that are in some sense better or worse than our past reality, and has been shown to play a significant role in the ability that humans have to learn from limited past experience and improve their decision making skills over time. In recent years, there has been an increasing excitement on the potential of machine learning models and algorithms to support human decision making in a variety of high-stakes domains such as medicine, education or science. However, these models and algorithms have been traditionally unable to perform, nor benefit from, counterfactual reasoning. In this project, our goal is to bridge this gap. We will develop machine learning models and algorithms for automated decision support that are able to perform and benefit from counterfactual reasoning in multiple ways. For example, they will perform counterfactual reasoning about human behavior to anticipate how humans incorporate algorithmic advice into their decisions. This will enable a new generation of decision support systems that can only increase and never decrease the average quality of human decisions. Moreover, they will use the structural similarities and shared properties across different counterfactual decision making scenarios to significantly reduce their computational and data requirements. In addition, these models and algorithms will also help humans learn from their own past decisions by identifying alternative decisions that would have led to better outcomes. Finally, we will perform large-scale human subject studies with both laypersons and experts to evaluate their effectiveness in a wide variety of decision making tasks.

Keywords: human aspects of machine learning,human ai collaboration,decision support systems,counterfactual reasoning,causality,uncertainty quantification
Knowledge building and social innovation for a successful, more effective and CO-produce urban SECURity solutions (CO-SECUR)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Civil Security for Society
Theme: Civil Security for Society
Destination: Strengthened Security Research and Innovation
Action type: Research and Innovation actions
Countries involved: Spain,Finland,Germany,Portugal,Romania,Poland,Greece,Lithuania,Belgium
Call: Social innovations as enablers of security solutions and increased security perception (HORIZON-CL3-2022-SSRI-01, 2022)
Start date: 2023-12-01
End date: 2026-11-30
Duration (months): 36.0
Total project cost (EUR): 1999957.5
EU funding (EUR): 1999957.5
Participants: 10
Project status: SIGNED

CO-SECUR aims to build knowledge and a suite of tools, including a Societal Development Plan (SDP) to foster and accelerate the adoption of social innovations and responsible innovation principles that contribute to successful, more effective, and co-produced security solutions for public spaces (with special focus on massive events and crowded places), generating trust, acceptance, increasing security, security perception, and security behavior. For that, CO-SECUR will follow a methodology of 4 phases: 1) Literature review of evidence in security and security perception; 2) Security practices mapping and selection; 3) Descriptive analysis of 72-180 case studies from 9 European countries and critical synthesis of results; and 4) Co-writing and validation of the SDP and tools involving the Quintuple helix + media through participative activities (i.e. hybrid seminars, national working groups, national workshops, public consultation at EU level). As a result, the SDP will contain a depth description of Social Innovation on Security in Europe, a compendium of good practices, and a roadmap of actions. The suite of tools will provide additional supportive material in terms of best practices on fostering smart local communities; policy recommendations on how to orientate security solutions towards RRI and social innovation involving the Quintuple helix + media; benchmarking for industry; and a summary of the innovative, transferable, and scalable Security Technologies. Partners will continue to disseminate and communicate the project progress and outcomes and organize a final Security Perception Conference. At the Conference, a Memorandum of Understanding will be launched and opened to be signed by any city/region willing to promote social innovation and RRI in the security solutions implemented in public spaces.

Keywords: quintuple helix,massive events,crowded places,societal development plan,policy recommendations,co creation,participative approaches,security behaviour and security perception
AI and machine learning for less overproduction and more sustainable consumption in the fashion industry - a deep learning approach to understand products and customers better. (SAIZ)

Framework: Horizon Europe — Innovative Europe
Programme: European innovation ecosystems
Theme: Elevating the scalability potential of European business
Destination: Elevating the scalability potential of European business
Action type: Coordination and support actions
Countries involved: Germany
Call: Women TechEU (HORIZON-EIE-2022-SCALEUP-02, 2022)
Start date: 2023-06-01
End date: 2024-05-31
Duration (months): 12.0
Total project cost (EUR): 107142.86
EU funding (EUR): 75000.0
Participants: 1
Project status: CLOSED

SAIZ - AI for product development optimization in the fashion industry. SAIZ enables fashion brands to optimize product development towards their own specific target groups, thereby minimizes the overproduction in the fashion industry. Hugely analog and non-data-driven processes have caused extreme inaccuracy when producing fashion. An average fit rate (garment fits the target group) is estimated to be at 15%, sell-through rates (what gets sold during the season) is at 60-70%. Production of fashion items is water, energy and pollution intensive, but a large part of the produced garments are produced so poorly, that they never even make it to a customer. SAIZ enables a fashion brand to fit their products to 2 Million bodies (of their target customers) virtually to prevent products going into mass-production that will not fit and will not be sold. A huge monetary game changer for the industry, and a big relief for the planet. SAIZ estimates to be able to save 400Mio tonnes of CO2 with data-driven product development in the next 5 years.

Keywords: sustainability,artificial intelligence,retail and fashion,fittechnology
Artifical spider silk textiles (ArtSilkTex)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Sweden
Call: ERC PROOF OF CONCEPT GRANTS1 (ERC-2022-POC1, 2022)
Start date: 2022-09-01
End date: 2024-02-29
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

ArtSilkTex builds on the ERC-funded project ARTSILK, in which we recently have succeeded in 1) producing artificial spider silk on a scale that, for the first time, opens up the possibility of producing the material for industrial use and 2) inventing engineered spider silk proteins that can be spun into fibers with significantly enhanced mechancial properties. In this project we will manufacture artificial spider silk yarns that will be benchmarked against commonly used yarns on the market. The breakthrough potential of an environmentally friendly, biobased high-performance fiber is great and our work is expected to result in a material that can be used or many applications and replace some of the petroleum-based synthetic fibers on the market. To pinpoint which markets and applications that are most suitable to target, get a better understanding of our competitors, and to ensure the best possible prerequisites for taking this material to the market, the project comprise four main activities: 1) generation of an IP strategy, 2) a thorough analysis of the material's life cycle, cost of goods and carbon footprint, 3) generation of artificial spider silk yarns and benchmarking against other materials, and 4) business development including setting up a business plan and the launch of a spinn-off company. We have a strong project team with highly motivated and experienced members with complimentary backgrounds, and we have an established collaborations with large international companies and potential future customers.
Intelligent Sensing and Communication as Training Network for Perceptive Mobile Networks in 6G (ISAC-NEWTON)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Doctoral Networks
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Greece,Spain,Germany,Bulgaria,United Kingdom,Austria,Cyprus,Netherlands,Italy
Call: MSCA Doctoral Networks 2023 (HORIZON-MSCA-2023-DN-01, 2023)
Start date: 2025-02-01
End date: 2029-01-31
Duration (months): 48.0
Total project cost (EUR): 3691104.69
EU funding (EUR): 3253593.6
Participants: 17
Project status: SIGNED

ISAC-NEWTON addresses critical challenges within various 6G wireless application scenarios, necessitating precise environmental information. Integrated Sensing and Communication (ISAC) emerges as a promising paradigm to harness the synergy between sensing and communication, where perceptive mobile networks (PMNs) have been proposed to enhance existing wireless networks by incorporating accurate sensing capabilities. Established cellular networks offer opportunities for sensing with extensive coverage, robust computation, communication power, and networking sensing from multiple nodes for the same target. However, PMNs encounter significant hurdles, including inherent interference, complex sensing environments, and high-speed target tracking by cellular networks. ISAC-NEWTON aims to overcome these challenges through an exceptional research and training program. The vision is a fully integrated system where sensing and communication coexist, sharing resources across time, frequency, space and power domains, alongside key elements like signal processing, machine learning and hardware. The project adopts a multidimensional information perception: (1) of the physical layer by employing innovative metasurfaces to effectively address challenges in both line-of-sight and non-line-of-sight scenarios; (2) for robust and reliable sensing by novel prediction and situational algorithms, and optimised monostatic, bistatic or multistatic design for adaptive location-time aware scheduling and improved coverage; (3) for intelligent wireless radio resource management by novel machine learning enabled radio access network mechanisms for real-time decision making and zero-trust security. ISAC-NEWTON will provide a unique, advanced, multi-disciplinary training programme covering all aspects of intelligent communication and sensing science field: modelling, design, development, data analysis, validation, and translation to the application, in an harmonious synergy that enconpasses future wireless networks.

Keywords: joint sensing and communications space time modulated metasurfaces reconfigurable intelligent surfaces signal processing digital cyber twin cell free networks
Recycling technologies for ELV components to create a sustainable source of market grade materials for EU applications (CRUSADE)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Industry
Destination: Increased Autonomy in Key Strategic Value Chains for Resilient Industry
Action type: Innovation actions
Countries involved: Greece,Italy,Germany,Belgium,Poland,Spain,Cyprus,Türkiye
Call: Recycling technologies for critical raw materials from EoL products (IA) (HORIZON-CL4-2023-RESILIENCE-01, 2023)
Start date: 2024-01-01
End date: 2027-12-31
Duration (months): 48.0
Total project cost (EUR): 8777756.25
EU funding (EUR): 6956943.75
Participants: 19
Project status: SIGNED

CRUSADE upscales novel technologies to TRL7 integrated in a universal hydrometallurgical method to recycle up to 500 tn/year of spent automotive components (autocatalysts, fuel cells, batteries and printed circuit boards) from end-of-life vehicles and recover ca 40 tn/year of critical raw materials (Cu, C, Co, Mn, Ni, Pt, Pd, Rh, Li, Ru) at commercial specifications. The project leverages predeveloped technologies to establish a market ready pilot unit utilising novel concepts for material tracing using blockchain (AKO, SAISLAB, ENTE) and pan European collection network establishment from the pioneers of the automotive components manufacturers (SUN, ADV, CRF, MONO, ACU) which guarantee the long term sustainable operation of the unit. The material processing covers the whole chain from pre-treatment using validated technologies from the experts on the CRMs recovery (MONO, TUBAF, KUL) and upstream processing using a microwave assisted leaching methodology enabling a 15-80% lower CO2 emission process (depending on the feed), compared to commercial processing. High specification market ready materials are prepared as outputs of the project undergoing a downstream purification and recovery process using solvent extraction and electrowinning, guided by industrial standards for end-use applications, while validated and benchmarked during the course of the project in new automotive products. The processing is automated aiming to a 15% time reduction compared to current processes with the use of an industrial robot and artificial technology guiding the sorting and the hydrometallurgical treatment (Industry 4.0 concept). The materials are commercialised at 15% lower price compared to market standards due to the automated innovative cost efficient processing, CAPEX/OPEX reaching max 70% of product cost (average 30% gross profit margin depending on feed).

Keywords: recycling,critical metals,sorting technologies
Human-Machine Social Systems (HUMANET)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Soci al World and Its Interactions
Panel description: Sociology, social psychology, education  sciences , communication  studies
Countries involved: United Kingdom
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-05-01
End date: 2030-04-30
Duration (months): 60.0
Total project cost (EUR): 1999974.0
EU funding (EUR): 1999974.0
Participants: 1
Project status: SIGNED

Bridging sociology, social psychology, human-computer interaction, and web science, HUMANET combines experimental and computational research methods to study a pressing new social challenge: the ever-increasing interdependence between humans and autonomous machines such as robots, bots, and algorithms. Starting from the idea that humans and machines form a complex adaptive social system, HUMANET investigates how human-machine, machine-machine, and human-human interactions influence and affect each other and how they add up to different collective outcomes. Conceptually, we distinguish between three levels of analysis: interactions, networks, and communities, and study direct, indirect, and strategic influence, network composition and structure, and techno-organizational constraints and sociocultural context. In terms of methodology, we combine controlled virtual lab experiments, agent-based models, digital-trace data, online field interventions, and heterogeneity and case comparison to conduct and integrate comprehensive analyses at the three levels. Empirically, we focus on the problem of social influence and contagion and provide causal and observational evidence from a range of online human-bot communities, including an online collaboration community, a discussion site, and a crowdfunding platform. HUMANET aims to expand our empirical knowledge of existing human-machine social systems, generate testable theories about human-machine interactions and networks, advance methods for modelling and conducting experiments with artificial agents, and bring public attention to the increasing algorithmization of our daily lives. Its ultimate goal is to build the foundations of a new cumulative empirical sociology of humans and machines. A better understanding of human-machine social systems is becoming crucial for reducing misinformation, preventing financial crashes, improving road safety, adapting to labor market disruptions, and more.

Keywords: computational social science,analytical sociology,network experiments,agent based modeling,online communities,bots,social contagion