Projects

The vision of FoSSNet is a strengthened and deepened academic network to support a new Knowledge and Innovation governance structure for Europe’s food system. A new structure is needed as the current Knowledge and Innovation system in the European Research Area is insufficient to address the emerging challenges of nourishing the European food system in a healthy, sustainable and fair way. The aim of FoSSNet is twofold, on one hand to establish a permanent pan-European network for Food System Science and on the other hand to advance inter- and transdisciplinary Food System Science and education. This will contribute directly to the farm to fork objectives and FOOD2030 priorities. Developing the network and advancing Food Systems Science and education will be underpinned by an inclusive approach to ensure engagement of all relevant disciplines, researchers and non-academic actors in advancing Food System Science. In order to reach the vision and aim, FoSSNet will 1) develop a conceptual framework and a process for developing food system transformation pathways to create a common language and understanding among food system thinkers, 2) establish, mobilise and consolidate an inclusive inter- and transdisciplinary pan-European academic network for food systems science to bring European food systems scientists and the science institutions together, 3) enhance inclusivity of the Knowledge and Innovation system for a sustainability transformation of EU food systems by addressing sensitivities to power relations and inequities that pervade food systems and contested transformation processes, 4) co-produce research for sustainable food system transformation to remove existing barriers to interdisciplinarity in food system science, 5) build food systems capability through an academy and curricula to ensure the impact of future food system thinkers and 6) create scientific, economic and societal impact by ensuring sustainability of the network.

EU Data Governance Act and recent advances in technology provide a unique momentum to automate and expand livestock data collection, integration and exploitation by strengthening the coordination of efforts of science and industry. The ultimate goal of Digi4Live is to increase the capacity of livestock sector actors across Europe to benefit from data generating and digital technologies. By using a strong multi-actor and co-creation approach, which brings together livestock sector actors from farm to fork, from science to livestock and technology industries, competent authorities, and other key actors, and engages them in co-creation of digital & data concepts, Digi4Live enables greater use of current and new data & digital technologies in livestock tracking. Digi4Live is a 4.5 years coordination and support action that is reaching out to over 1000 organisations and initiatives across Europe to make an impact towards economically, environmentally and socially sustainable, digitalised livestock business that meets consumers’ expectations, more effective public administration and impactful policy. Digi4Live boosts the creation of standards and harmonised regulations, thus eliminating technical barriers for data and new data-generating technologies, and provides evidence on economic, social and environmental impacts of data-driven solutions in the livestock sector and boosts collaboration between R&I initiatives across all EU member states and beyond. It will point out how public administration and policy monitoring & assessment, businesses and consumers can benefit from digital technologies. Concepts for greater exploitation of data will be co-developed and examined in six thematic case study hubs and brought to the attention of end users to. Such an integrated approach can really make a difference by enabling substantially improved use of data for the benefit of science, policy and business. The project will provide policy and business conclusions.

Flexible Electronics has been one of the fastest developing technologies in recent decades. The traditional path is electronic components such as silicon chips (e.g., microcontrollers) integrated onto flexible substrates called “hybrid integration” or “flexible hybrid electronics” in integrated smart systems. We believe that this approach is not a viable long-term solution for future high-volume, low-cost and conformable integrated smart systems. Our vision is an integrated smart system that is built with only flexible electronic components including analogue circuitry, digital logic and memories. We call such a system a “Natively Flexible Integrated Smart System” or NFISS. NFISSes will enable new products in the Fast Moving Consumer Goods and healthcare wearables that have not been possible before because conventional silicon chips are too costly, too bulky and not conformable. The project will develop a flexible microcontroller unit (FlexMCU), which is the key component missing to enable NFISSes. The FlexMCU must be a low-power chip integrating a variety of functionality to address the functional requirements of the applications in FMCG and healthcare wearables. A novel hybrid complementary low-power thin-film transistor technology (100x per-transistor power reduction) will be developed to fabricate the FlexMCU in a sustainable flexible chip fab with 100-1000x less environmental footprint. The FlexMCU design is tailored to a specific domain composed of an open-source RISC-V based processor with built-in security features, an analogue frontend, on-chip memory and other peripherals. Then, the FlexMCU will be assembled using novel assembly and bonding methods onto a flexible film, which is, in turn, integrated onto a flexible substrate along with other flexible electronic components to build the first proof-of-concept NFISS that will be validated on two healthcare wearable applications.

The CATRINE project will focus on the atmospheric tracer transport research areas identified by the EU's CO2 Task Force, the CO2 Human Emissions (CHE) project, and the Copernicus CO2 service (CoCO2) projects. The accuracy and mass conservation of the tracer transport model is of utmost importance in the design of the CO2MVS. Any unaccounted systematic errors in the tracer transport model can lead to inaccuracies in the estimation of CO2 and other tracer emissions. Therefore, CATRINE aims to improve the methods used to represent resolved tracer transport by the winds, with a particular focus on mass conservation, and to identify other systematic errors associated with unresolved processes represented by parametrizations. The project will define protocols for evaluating tracer transport models at both global and local scales. Test beds based on field campaign case studies will be developed, along with suitable metrics for tracer transport evaluation, utilising a range of tracers and observations at both global and local scales. These metrics will be employed in the operational CO2MVS to evaluate the implementation of new transport model developments, characterise transport accuracy and representativity in data assimilation, and provide a quality control stamp of tracer transport accuracy. Lastly, CATRINE will provide clear recommendations to the CO2MVS and the Carbon Cycle Community which works with atmospheric inversion models for the evaluation and quality assessment of tracer transport models.

The DISCOVER-US project aims to (i) Strengthen long-term collaboration between the EU and the US by creating networking and collaboration opportunities to promote cooperation on new concepts and visions for the computing continuum, distributed computing and swarm intelligence. (ii) Facilitate brokerage events for on-going and future work streams in EU and US projects addressing the edge-cloud continuum. (iii) Implement research exchange and fellowship programmes to encourage and initiate collaboration. (iv) Create a EU-US collaboration support infrastructure consisting of various services: networking, brokerage, training, vision building, communication and dissemination. Content-wise, DISCOVER-US will focus on the following four key research topics for the collaboration. (i) Managing complexity through high levels of abstraction. (ii) New concepts for distributed computing, the computing continuum, swarm intelligence and edge intelligent things. (iii) AI-based concepts for self-organized, dynamic, and adaptive management. (iv) Collaborative programming frameworks and software development tools. By addressing these research topics, DISCOVER-US provides support and coordination for EU-US cooperation initiatives and the European priorities addressing fundamental research on new concepts for the continuum of computing, distributed computing and swarm intelligence to enable the emergence of technological developments in distributed computing supported by open technologies and platforms and through the coordination of complementary activities structured around the cloud-to-edge-to-IoT continuum. In this context, the DISCOVER-US project will boost synergies, experience and knowledge sharing and lay the groundwork for creating EU-US collaborative activities and address the selected European priorities for strengthening the European distributed computing research ecosystem by identifying a set of best practices and research models that will facilitate the replication of results, thus improving the overall impact of the simultaneously ongoing transatlantic activities. The project will run for 35 months.

Photonics is one of the first platforms explored for quantum computing (QC), bringing the advantage of low decoherence and natural connectivity for distributed and blind QC. Recent years have witnessed a step-change in the scale, complexity, and scope of QC with photons which recently led to 3 out of the 4 demonstrations of quantum advantage from Canadian and Chinese groups. These impressive achievements were obtained with squeezed light in bulky apparatus that are not fit for scalability. Europe shows strong leadership in development of integrated optical QC platforms, with breakthroughs in the development of high transmission dense photonic chips, record efficiency detectors and deterministic single photon sources. Photonic QC also benefits from a clear roadmap toward fault tolerant architectures proposed by leading EU quantum algorithm teams. EPIQUE gathers world leaders in photonics QC with expertise in both technology and algorithms from academia and SMEs who work together to deliver the technological breakthroughs required to push the platform toward general purpose QC. This will be achieved via new nanofabrication that combines novel switching with mature silicon compatible circuitry, via optimising both single photon sources and detectors, via new interfacing possibilities in silicon nitride and direct write modular chips, via fast low loss switching in lithium niobate, and via quantum architectures that leverage all of these advances. EPIQUE will develop three QC prototypes that will demonstrate essential building blocks of generating and fusing quantum states to entangle >10 qubits, and critical measurement and feedforward capabilities required to scale the platform to >1000 qubits. At the end of this project, we will have proven a route to general purpose quantum computing that will strengthen private investment in EU based optical QC companies.

IPMorama will improve the state of the art in variety-centric Integrated Pest Management (IPM) for important diseases in the wheat (rust pathogens), potatoes (blight) and the grain legumes soybean, pea (broomrape) and white lupin (anthracnose). IPMorama seeks to develop the infrastructure for a whole “practice ecosystem”, whereby the more efficient development of IPM-centric varieties is enabled, while at the same time developing tools and resources to efficiently exploit these in variety-centric IPM. The core innovation of IPMorama is to integrate knowledge of host resistance with the pathogen virulence landscape over space and time, to produce IPM tools (eg crowd source apps, vulnerability maps) and strategies, which will be validated at various scales and in conjunction with different agroecological practices. IPMorama will achieve these goals by enacting the following five components: 1] Understanding the genetic composition of varietal resistance in target crop/pest systems, and development of tools and resources to allow breeders to target the assembly of resistance components. 2] Understanding and mapping the landscape level distribution of the target pathogens/pests, especially in terms of their virulence against the available set of resistance and tolerance genes in varieties and breeding lines. 3] Developing specific integrated pest management practices for the optimal exploitation of pest and pathogen resistance in varieties on the basis of the first two components. 4] Developing the knowledge infrastructure for competent use of variety-centric IPM by actors across the variety-related value chain. 5] Understanding opportunities and barriers for scale-up of variety-centric IPM solutions.

Currently there are no portable test or biosensors validated for air, soil or water quality control for pathogens, Chemicals of Emerging Concern (CECs) and Persistent Mobile Chemicals (PMCs), so such devices are much awaited by all stakeholders to ensure successful control and prevention of contamination and infections. Mobiles consortium will develop an interdisciplinary framework of expertise, and tools for monitoring, detection, and consequently mitigation of pollution from pathogens, CECs, PMCs, thus benefiting human and environmental health. Mobiles consortium will work to achieve the following objectives: Develop electronic biosensors for monitoring organic chemicals (pesticides, hormones) and antimicrobial resistance bacteria and pathogens in water, soil and air; Develop organism-based biosensor for detection of organic and inorganic pollution in water and soil; Study environmental performance of developed organisms and devices; Metagenomics analysis of organisms leaving in polluted areas in order to enable searches for diverse functionalities across multiple gene clusters Perform safety tests (e.g., EFSA) to assess the impact of developed organisms on the natural environment. Organism-based biosensor will consist on genetically modified chemiluminescent bacteria able to detect antibiotics, heavy metals, and pesticides in water; genetically modified plants that will change colour when in the soil is present arsenic; and marine diatoms that will be used to detect bioplastic degradation in marine and aquatic environments. Developed devices and organisms will be implemented by using flexible technologies, which can guarantee an easy adaptation to other biotic and abiotic pollutants. Devices and organisms, after proper validation and approval, could be used by consumers, inspection services and industry operators, as well as environmental emergency responders to monitor and detect PMCs, CECs and pathogens in water, air and soil

Air pollution poses a great environmental risk to health, accounting for nearly half a million premature deaths each year in Europe. Biogas production is an enabling technology to achieve net-zero emissions, while accelerating the energy diversification in Europe. Both, air quality control and biogas production demand critical improvements in sensor technology. SYMPHONY will develop a new technology enabling the implementation of dense networks of cloud-connected, low-cost, portable and easy-to-use sensors, capable of multi-target detection for applications in air quality control, pollution monitoring, industrial process control and safety. SYMPHONY will address this challenge by making key developments in silicon photonics, neuromorphic circuits, artificial intelligence, integration, and packaging, while exploiting state-of-the-art silicon microelectronics for ultra-low power edge computing with artificial intelligence, and the connected sensor network for spatially-resolved analysis and prediction. The main focus of SYMPHONY smart sensors are gases related to the biogas production and gases that have been identified by the European Environmental Agency (EEA) as highly pollutant and contributing to the greenhouse effect, such as CO2, CH4 and NO2. SYMPHONY smart sensors will be validated in three different relevant scenarios: city pollution monitoring in Cyprus, process control and leakage detection in biogas micro-plants in multiple locations in Europe. With this ambition in mind, SYMPHONY has gathered a transversal consortium, comprising three academic institutions, two research institutes, four companies and two end-users, coming from seven different countries in Europe. The consortium covers the full value chain, including silicon photonics, neuromorphic circuits, silicon microelectronics, integration, packaging, artificial intelligence, gas sensing, the internet of things, biogas production and air pollution monitoring.

Europe is facing unprecedented challenges, such as the health, migration, economic, climate, energy, and political crises, leading to a sharp increase in emergency public spending and relaxation of due diligence checks. This has resulted in a rise in corruption and fraudulent activities, which have significant negative impacts on the European economy, society, environment, and democracy. Despite emerging technology’s potential to become a powerful tool in the fight against corruption and fraud, the public sector has been slow to adopt digitalization, resulting in data NOT being shared, harmonized, or properly analysed, making evidence-based decision-making almost impossible. Governments are slowly adopting new approaches to ensure a more data-driven, transparent, and accountable public governance, but several fundamental data-related issues remain unresolved. With a team of 9 excellent research institutions and universities, 12 technology, business, and standards, developing companies, 7 public end users, and 3 domain-relevant, industry-exposed NGOs, CEDAR will: (1) Identify, collect, fuse, harmonise, and protect complex data sources to generate and share 10+ high-quality, high-value datasets relevant for a more transparent and accountable public governance in Europe. (2) Develop interoperable and secure connectors and APIs to utilise and enrich 6+ Common European Data Spaces. (3) Develop innovative and scalable technologies for effective big data management and Machine Learning (ML) operations. (4) Deliver robust big data analytics and ML to facilitate human-centric and evidence-based decision-making in public administration. (4) Validate the new datasets and technologies (TRL5) in the context of fighting corruption, thus aligning with the EU strategic priorities: digitalisation, economy, democracy. (5) Actively promote results across Europe to ensure their adoption and longevity, and to generate positive, direct, tangible, and immediate impacts.

To strengthen the competitiveness of the EU industry, there is an increasing need for flexible production, exploiting the capabilities of both the machinery and human workforce. The growing market of robots has reacted, adapting to the changing situation by providing collaborative robotic solutions with a variety of characteristics in terms of payload, type and mobility. A number of technological solutions for perception and safety allow their coexistence with humans. While several research activities have been conducted over the past 5 years on this topic, wider industrial adoption is lagging due to the following restrictions: • Limited cognition and intelligence • Low performance of collaborative operations • Collaboration fluidity is rather low as the operators have to adapt to the particularities of the robots. • Complexity in robot programming which requires the involvement of skilled engineers, does not provide flexibility in the execution phase, and does not benefit from the tacit knowledge of experienced operators. Thus, despite the fact the mechatronics are quite advanced, a perfect matching of mechanics and control is required to create robots that advance from repetitive and precision-oriented tasks to becoming intelligent and helpful co-workers. Proper human robot interaction is the most important ground to be covered. Thus, JARVIS aims to develop a reusable set of tools that enable AI driven multimodal means of interaction: a) involving interfaces for physical and remote information exchange, robot control and programming, b) providing social skills to a variety of robots to achieve seamless user-centric interaction that extends human ability for complex tasks and c) demonstrating scalability of application and ability to achieve economies at scale.

The Skyrmionic Artificial Neural Network (SkyANN) presents a groundbreaking paradigm for neuromorphic computing, closely emulating brain neurophysiology by combining skyrmionic quasiparticles, which mimic neurotransmitters and facilitate complex computations at the synapse level, with electrical CMOS connections that simulate the propagation of action potentials among neurons for rapid and dense inter-layer connectivity. Our innovative magneto-electric devices aim to achieve energy consumption four orders of magnitude lower than CMOS technology and double the bandwidth for the same device footprint, enhancing edge inference and learning capabilities. This approach challenges contemporary neural networks implemented with CMOS digital, mixed-signal, and emerging in-memory computing technologies, which are limited by lower energy efficiency and reliability. Building on preliminary results from SkyANN partners, we plan an ambitious endeavor to develop a first-of-its-kind magneto-electric neural network, showcasing the promising potential of this novel technology. Along the way, we will refine materials, processes, design methodologies, and architectures to prepare the European micro- and nano-electronics ecosystem for the future, while supporting the EU's Green Deal vision. Our well-balanced consortium brings together complementary expertise and extensive knowledge, spanning from device physics to circuits and architectures across multiple layers of design abstraction. As a result, the SkyANN consortium is poised to facilitate the rapid transfer of fundamental discoveries to relevant industrial stakeholders, accelerating impact and reinforcing European strengths in the economically, geopolitically, and socially vital semiconductor sector.

MANOLO will deliver a complete stack of trustworthy algorithms and tools to help AI systems reach better efficiency and seamless optimization in their operations, resources and data required to train, deploy and run high-quality and lighter AI models in both centralised and cloud-edge distributed environments. It will push the state of the art in the development of a collection of complementary algorithms for training, understanding, compressing and optimising machine learning models by advancing research in the areas of: model compression, meta-learning (few-shot learning), domain adaptation, frugal neural network search and growth and neuromorphic models. Novel dynamic algorithms for data/energy efficient and policy-compliance allocation of AI tasks to assets and resources in the cloud-edge continuum will be designed, allowing for trustworthy widespread deployment. To support these activities a data management framework for distributed tracking of assets and their provenance (data, models, algorithms) and a benchmark system to monitor, evaluate and compare new AI algorithms and model deployments will be developed. Trustworthiness evaluation mechanisms will be embedded at its core for explainability, robustness and security of models while using the Z-Inspection methodology for TrustworthyAI assesment, helping AI systems conform to the new AI Act regulation. MANOLO will be deployed as a toolset and tested in lab environments via Use Cases with different distributed AI paradigms within cloud-edge continuum settings; it will be validated in verticals such as health, manufacturing, and telecommunications aligned with ADRA identified market opportunities, and with a granular set of embedded devices covering robotics, smartphones, IoT as well as using Neuromorphic chips. MANOLO will integrate with ongoing projects at EU level developing the next operating system for cloud-edge continuum, while promoting its sustainability via the AI-on-demand platform and EU portals.

As in other Deep Tech areas, there is a shortage of qualified professionals in the field. This shortage is due to lack of education and training programs, unawareness of the career opportunities that the field poses, a rapidly evolving technology, and unfamiliarity with the different professional paths that the photonics ecosystems offers, among other. CARLA, the awarded project for the previous call, took on the challenge of promoting careers in photonics among students and researchers through the CARLA camps, photonics career camps. 360 CARLA seeks to build on the momentum created by the successful CARLA project, retain and increase the interest that the CARLA participants have acquired and expand the impact to more and more diverse university students and early-stage researchers. For that, we will create round up programs around photonics applications or markets, that we call verticals: 1) Health: Biotech and Medical Photonics; 2) Quantum Technologies/ Communications 3) Energy, Environment and Sustainability; and 4) Manufacturing/ Industry 4.0. These round up, cohesive programs will integrate career symposiums, mentorship, innovation and entrepreneurship experience and trainings. This will: - Increase the number of students and researchers interested in pursuing careers in photonics. - Appeal to additional STEM students and researchers attracted by the photonics application topic. - Provide participants with a round up, overall understanding of the landscape of the photonics ecosystem surrounding the corresponding vertical, supported by a network of contacts and mentors, experiences in photonics innovation and entrepreneurship and training. In addition, 360 CARLA will collaborate with other EU initiatives in the photonics space, working towards growing and better preparing the future workforce, or around the verticals, so that can leverage each other through sharing strategies, activities, content and dissemination channels.

Over the years sensors expanded their field of use from scientific exploration to consumer electronics, and their market evolved accordingly. Quantum technologies are expected to further push sensor’s performances, unlocking even more application domains, exploiting non-classical correlation of light and matter to extract the relevant information beyond the limit dictated by classical noise processes, improving performances such as sensitivity, specificity and uncertainty. The ability to produce, control and measure quantum states in transportable devices is the key to extend the sensors’ operating environment, lifetime, power consumption and costs. QUANTIFY fits perfectly this vision and the goal of Demonstrating quantum sensing beyond classical capabilities for real-world applications, in the Strategic Research Agenda of the Quantum Flagship Program. QUANTIFY objective consists in bringing photonic quantum enhanced sensors at the next level of integration developing the essential building blocks and novel quantum-enhanced techniques for future chip scale optical clocks, optically pumped magnetometers and optomechanical temperature sensors. QUANTIFY leverages different photonic platforms combined by a novel hybrid integration technique to bring the key optical and optomechanical functionalities on a single chip. To increase the clock and magnetometer performances, we introduce a photonic integrated squeezed light source, also becoming an important step for realizing a universal quantum computer based on photonics. Finally, we demonstrate a novel absolute temperature sensor with an extended detection range, from cryogenic to room temperature leveraging a nanoscale optomechanical approach coupling photonic and phononic degrees of freedom. All the free developed sensors will be assessed using metrological protocols and national primary standards in National metrological laboratories, to foster their feature exploitation in real application for end-users.

A number of European leading Research Organizations (referred as RTOs hereafter) and research supporting organizations, with a long history of scientific and technology collaboration with Japan, are building a consortium for a proposal focusing on the development of joint High Performance Computing (HPC) applications for future generations of supercomputing platforms/architectures (preexascale, exascale, post-exascale) from Europe and Japan. European and Japanese research centers work together to develop and optimize applications of these methods in various scientific fields, such as material, biomedical and health (especially covid19 research, drug design …), and environmental sciences (such as climate modeling, seismology and prevention of natural disasters), and many other fields such as high energy physics, astrophysics, quantum computing, etc. The existing joint activities between the European consortium and the Japanese research institutes will bring together the required expertise to develop applications: this expertise ranges from fundamental research and applied science for designing new models, to the optimization, development and the integration of new and ambitious workflows and models to efficiently profit from pre-exascale, exascale, post-exascale and hybrid architectures deployed or already operational in Europe and Japan. The European consortium gathered in the HANAMI proposal is willing to support and foster joint scientific teams to improve the performance and transferability of European and Japanese HPC applications by leveraging the skills and expertise of the scientific community within Europe and Japan. This consortium focuses on the HPC, AI and DA application communities, represented by the CoEs, academic and industrial organizations addressing the strategic research areas that are material, biomedical and climate.

The ARTEMIs project aims to consolidate existing computational mechanistic and machine-learning models at different scales to deliver ‘virtual twins’ embedded in a clinical decision support system (CDSS). The CDSS will provide clinically meaningful information to clinicians, for a more personalised management of the whole spectrum of Metabolic Associated Fatty Liver Disease (MAFLD). MAFLD, with an estimated prevalence of about 25%, goes from an undetected sleeping disease, to inflammation (hepatitis), to fibrosis development (cirrhosis) and/or hepatocellular carcinoma (HCC), decompensated cirrhosis and HCC being the final stages of the disease. However, many MAFLD patients do not die from the liver disease itself, but from cardiovascular comorbidities or complications. The ARTEMIs will contribute to the earlier management of MAFLD patients, by prognosing the development of more advanced forms of the disease and cardiovascular comorbidities, promoting active surveillance of patients at risk. The system will predict the impact of novel drug treatments or procedures, or simply better life habits. The system will therefore not only serve as a clinical decision aid tool, but also as an educational tool for patients, to promote better nutritional and lifestyle behaviors. In more advanced forms of the disease, therapeutic interventions include TIPPS to manage portal hypertension, partial hepatectomy, partial or complete liver transplant. ARTEMIs will contribute to predict per- or post-intervention heart failure, building on existing microcirculation hemodynamics models. The model developers will benefit from a large distributed patient cohort and data exploration environment to identify patterns in data, draw new theories on the liver-heart metabolic axis and validate the performance of their models. The project includes a proof-of-concept feasibility study assessing the utility of the integrated virtual twins and CDSS in the clinical context.

GI SMART (Geographical Indications’ contribution to smart territorial development and sustainability. Insights for GIs producers, policy makers, consumers and local communities) is a four-year lump-sum project to undertake research and demonstration activities (innovative pilot action) and provide evidence-based recommendations to strengthen the contribution of the system of geographical indications (GIs) to sustainable development, in particular to achieve the objectives of the EU Farm to Fork strategy by fostering the implementation of sustainability strategies by producers and their recognition by consumers, as well as to propose a better design of GIs policy to foster their delivery of sustainable agriculture, aquaculture, fisheries, as well as more sustainable food systems. Our 17 partners (15 beneficiaries and 2 Associated Partners) representing 10 countries bring together leading academic, NGOs and stakeholder organisations to provide a multi-actor approach to ensure the project objectives are delivered with maximum impact. This proposal relates to the topic “Investigating the contribution of geographical indications to sustainable development and optimizing support for newly establish schemes” (HORIZON-CL6-2023-COMMUNITIES-01-04). GI SMART aims to assess and strengthen the contribution of GIs to the EU “Farm to Fork” strategy for sustainable food systems in Europe by providing: i) better understanding of the contribution of GIs schemes to sustainable development (including the F2F strategy); ii) improving the perception of sustainability attributes of GIs schemes that are widely implemented by the producers and their perception by consumers, local communities and society at large, iii) better and smart policy design and implementation of GIs policy to foster their delivery of sustainable agriculture and fishery, healthy and sustainable diets and sustainable food systems.

The recent variations in the price of fossil fuels and mineral fertilisers in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine threaten the incomes of primary producers and affordability of food for consumers. This threat will remain, as the pathway towards fossil fuel independence and related investments in less fossil-fuel-intensive technologies in the EU agricultural sector will take time. All this shows that there is an urgent need to design realistic, sustainable pathways for supporting the energy transition of the European agricultural sector and improving the income of primary producers. AgEnRes designs sustainable pathways for policy making to reduce direct and indirect dependence of farmers and the agricultural sector as a whole on fossil fuels and fertilisers, and increase the resilience to volatile energy prices, taking into account farmers’ behaviour and the synergies and trade-offs between European economic and environmental objectives at micro- and macro-level. Our approach consists of three components supported by outreach activities, which involve stakeholders and the general public throughout the project's lifespan. The first component develops a conceptual and data framework to identify policy targets and measures, promising technologies, and data and model requirements. Component one results among others in an EU wide database on energy use and mitigation potentials at different scales. The second component focuses on evidence of the past and present energy dependence of the European agricultural sector and preferred solutions. The third component builds on the first two and incorporates them into a set of foresight models at farm, regional, and market levels to evaluate the impacts of innovations and policy measures and targets at different scales. Ultimately, AgEnRes develops an innovative toolbox that will decrease the energy dependence and strengthen the resilience of the European agricultural sector.

STEP UP will generate clear, unambiguous and quantitative information to support greater sustainability, viability and resilience of environmentally friendly European Livestock Production Systems (ELPS). Through state-of-the-art research methodologies and thorough and effective stakeholder engagement, STEP UP will deliver a platform of measures to support European policy makers with science-based evidence on the impacts and externalities of ELPS, as part of the food and wider ecosystem. Existing knowledge on the positive and negative impacts and externalities of ELPS will be collated following a comprehensive science-based analysis of published research and policy literature. Data gaps towards improving the sustainability of ELPS across diverse social and environmental contexts will be identified. In-depth case-study analysis to harmonise existing data, identify deficits in, and opportunities for, new data collection and systems development will be carried out. New indicators for assessing the externalities of sustainable ELPS, considering all relevant value-chain factors will be developed. The multi-actor approach (MAA) will be invoked to ensure “real-life” contextual reference points and testbeds for these new indicators including evaluation and impact, followed by a comprehensive impact assessment and cost-benefit quantification of current and innovative ELPS under various socio-ecological-economic contexts, using best quantitative data modelling methods. Transition pathways for more sustainable and diverse ELPS, forecast scenarios including monetizing impacts, will be identified. Evidence-based STEP UP knowledge of ELPS as part of the food system and wider ecosystem will be disseminated using MAA. Finally, STEP UP will provide a unique and warranted platform to support the development of informed and objective policy measures to optimise the central role of livestock in meeting the nutritional and societal needs of the European and global population.

AWARD recognises the urgency of action due to water scarcity and climate change impacts as well as the need to engage simultaneously the society, the science and the policy into the development of knowledge and strategic water planning. Therefore, AWARD will provide evidence-based solutions to consider AWRs into water supply strategic plans, based on socio-political engagement. The 4 Demo Cases of AWARD are already implementing AWRs (storm water, rainwater and aquifer recharge in Bucharest in Romania as well as in Milano in Italy; water reuse in Cyprus, storm water and rainwater in an industrial park in Santiago di Compostel in Spain). Through the project activities, Demo Cases will consider scaling up their actions taking in account a broader range of AWRs together with conventional water resources for planning future water supply systems at local or regional level using AWARD instruments (Local Water Fora, Digital Platform for decision making, training and guidance). They will address similar issues in a harmonised and coordinated way. Societal awareness to support the decision process on AWRs supply solutions will lead to the recommendations for further use of AWRs encompassing the 4 dimensions of social innovation (Technological, Capacity development, Governance & Policy, Economics & assessment). The AWARD AWRs catalogue will gather the project results and additional solutions which will be benchmarked. The digital platform provided by AWARD will support the exploration of resilient scenarios that will be promoted beyond the scope of the project thanks to dedicated networking activities. AWARD general objective is to provide evidence-based knowledge and lessons learnt on how to effectively integrate affordable, acceptable and reliable AWRs solutions into water supply strategic planning and implementation considering the effect of global changes.

In the EU, about 165 million people are affected each year by mental disorders, and estimates indicate that mental disorders will become the number 1 economic cost factor in medicine in 2030. Schizophrenia alone affects approximately 1% of the world's population. The clinical effectiveness of the antipsychotics on the market remains limited with 30 to 50% of schizophrenic patients showing an insufficient response to treatment. Several factors, from genetic to psychological and social, may lie behind poor treatment outcomes or side effects and varies from patient to patient. Therefore, the central aim of the VIRTUAL BRAIN TWIN project is to create an ecosystem for generating virtual brain twins for psychiatric patients, by leveraging the consortium’s detailed knowledge and expertise in neuronal microcircuit simulation, mathematical analysis, innovative AI tools, and psychiatric care and clinical studies. This ecosystem will guide clinicians to optimise medication type and dosage, and to evaluate alternative treatments, such as brain stimulation and lifestyle changes. Multiscale cause-effect simulations and virtual brain simulations based on fMRI or sMRI data from the individual patient, will bridge the gap between molecules and the patient's brain. At the centre of this ecosystem will be the Virtual Brain Twin platform, which will make use of big data, multiscale modelling, and high-performance computing (HPC) that will be secured by appropriate data safety and protection. The platform will be embedded in the European digital neuroscience research infrastructure EBRAINS and will be initially accessible to neuroscientists, clinical researchers, and mathematical modellers, and in the future, to clinicians, and patients as well. This ground-breaking project will pave the way for personalised treatment of psychiatric disorders, with the potential to significantly improve the quality of life of patients suffering from these conditions.

Planetary health requires a better understanding of the reciprocal negative effects and co-benefits between environmental changes, degradations and human health. This holds at all levels. Local communities of low- and medium-income countries, living in cross-border zones, face both the negative effects of environmental changes and degradations, impacting their health and well being, and particular socio-political contexts that enhance their vulnerability. MOSAIC states that these populations can be best suited to interpret and exploit complex and multi-thematic information about their surroundings, in order to identify and understand the impacts of the environment on their wellbeing and to develop locally feasible, acceptable, and sustainable adaptation and mitigation solutions. However, usually, access to information is weak and local communities do not necessarily have the required scientific literacy skills to fully benefit from it. MOSAIC aims to design and implement open, multimodal and replicable information ecosystems intended to support cross-border communities to i) understand the impacts of the environment on their well-being, ii) build a health-promoting environment, iii) influence public debate, public policies and public decisions. It relies on the Open Science principles, making: i) participatory and data sciences work together, with multiple disciplines and stakeholders, ii) scientists and society co-produce and make use of data and knowledge, with shared values. It will consider two bio-regions particularly affected by climate change, extreme climatic events, and land cover degradation, East Africa and the Amazon, with three cross-border study areas as “laboratory sites”. These study sites allow for implementation and evaluation of project developments, the testing of the reproducibility and reusability of methods, data and tools, and the facilitation of inter- and transdisciplinarity through the joint mobilisation of a multidisciplinary team.

The HYway project will be the most comprehensive study on environmental effects of large-scale hydrogen usage to date. HYway is led by a team of experienced scientists who have already conducted extensive research on the climate effects of hydrogen. To fully understand the climate effect of hydrogen emissions, HYway will constrain the hydrogen budget by novel work on surface emissions, measurements of leaks and soil uptake fluxes, and application of a global atmospheric model ensemble combined with observations to quantify the atmospheric sources and sinks of hydrogen. To improve monitoring tools for hydrogen leakages, HYway will develop novel emission modelling and installation-level emission measurements. We will measure the hydrogen soil sink using flux chambers and instrumented drones, and we will use this knowledge to improve process-based models of the sink. The Global Warming Potential of hydrogen and its Effective Radiative Forcing will be quantified, including the component contributions from methane, ozone, stratospheric water vapour and aerosols. HYway will also quantify several environmental effects associated with hydrogen emissions such as stratospheric ozone depletion and air pollution. HYway will build on existing methods to create realistic future scenarios to fully explore the climate and environmental impacts of a hydrogen economy, including co-emissions and associated reductions in fossil fuel-related emissions. HYway includes a large advisory board of industry partners, several of them from established hydrogen collaborations. The advisory board will assist in estimating hydrogen leakage rates and in establishing realistic scenarios for a future hydrogen economy. By evaluating the potential climate and environmental impacts of a hydrogen economy, HYway will provide critical information to policymakers and stakeholders, allowing them to make informed decisions about the role of hydrogen in the transition to a low-carbon economy.

Aerosol-cloud interactions (ACI) remain the largest source of uncertainty in past, present, and future radiative forcing, impeding credible climate projections. ACI effects are expected to change dramatically as we enter a post-fossil world, characterized by strong reductions in anthropogenic aerosol emissions but with increasingly larger impacts from natural aerosols. Although we expect cleaner clouds compared to today, ACI in this post-fossil state may considerably differ from preindustrial conditions, owing to shifts in climate and changes in sources region characteristics. CleanCloud will address the major gaps impeding robust ACI assessments, improve their representation in current and next generation kilometer-scale climate models , quantify and understand their regional and temporal effects, and how they will evolve in the transition to the post-fossil regime. To accomplish this, CleanCloud will 1) carry out targeted field experiments in European climate hotspots; 2) develop state-of-the-art algorithms and analysis tools to obtain new proxies and diagnostics for key ACI-related processes; 3) contribute to the calibration and validation of upcoming satellite missions in coordination with the satellite community; 4) improve and better constrain kilometer- and large-scale climate models using advanced machine learning, data assimilation and model calibration, confronting perturbed physics ensembles with existing and new satellite and in-situ data; and 5) assess the role of aerosols in the life cycle of convective systems, focusing on precipitation formation and the impacts on the hydrological cycle, and 6) enhance the exploitation of data centres, measurement programs, international campaigns, laboratory studies, and models. With these, CleanCloud will profoundly strengthen European Research on climate change, significantly contribute to upcoming climate assessments, and benefit society through models that enable improved weather and seasonal predictions.

Experimental research on solar radiation modification (SRM) is controversial and feared to distract from climate change mitigation or leading to dangerous SRM use. It is not clear whether and under which conditions and governance arrangements experimental SRM research may be desirable for reducing uncertainties and lowering the probability of problematic outcomes including unilateral deployment elsewhere. Co-CREATE seeks to help structure this decision problem through co-creative scoping, analysis, and engagement for the development of principles and guidelines. The project starts with a series of scoping notes that outline key dimensions of experimental SRM research including possible cases and their geographical, stake- and rightsholder, and regulatory implications, which ground the conceptual work. Co-CREATE then analyses and develops decision-support tools by asking what we can learn from governance analogues, and how various (risk) evaluation frameworks may help identify key characteristics of research proposals. Co-CREATE furthermore analyses possible legal and procedural conditions including appropriate participation. Co-CREATE itself will for the development of these governance elements enter an extensive stakeholder and rightsholder dialogue that validates preliminary analytical work, ensures stakeholders’ diverse dimensions of concern are included, and strengthens deliberative capacity. Co-CREATE proposes guidelines and principles to facilitate decision-making by the relevant authorities on broader categories of experimental research of SRM as well as case-by-case decisions. A draft will be discussed at a Co-CREATE hosted conference and later refined based on feedback received. Proposed principles and guidelines will be grounded in a understanding of scientific merit, physical and political dimensions of risk and risk-attenuation benefit, and consideration of broader sets of values and concerns – co-creatively identified during the project.

TipESM brings together scientists from a range of disciplines to deliver a step change in our understanding of climate tipping points in the Earth system, including their impact on ecosystems and society, combined with a set of early warning indicators and safe future emission pathways that minimise the risk of exceeding such tipping points. TipESM assembles the latest Earth System Models (ESMs), including recent improvements to key processes: ice sheets, vegetation and land use, permafrost, marine and terrestrial biogeochemistry. In cooperation with the WCRP/Future-Earth project TIPMIP, TipESM will organise an international collaboration to design and realise a common ESM experiment protocol that will facilitate analysis of the likelihood of occurrence, and potential reversibility, of tipping elements at different levels and duration of global warming. These experiments, will be combined with more project-specific ESM experiments, designed to investigate interactions and feedbacks across the Earth system. Based on the TipESM experiments, existing simulations and observations, we will investigate tipping points, their driving processes, potential early warning signals and cascading effects across the climate, ecosystems and society. Including the most important components of the Earth system in our ESMs will also allow TipESM to identify potentially unknown tipping elements, their precursors and impacts. TipESM brings together expertise from climate science and climate impacts to investigate both the role of gradual climate change for tipping in individual ecosystems and society, and the impact of crossing specific climate tipping points for society, ecosystems, and biodiversity. Project findings will be synthesised into a tipping points risk register. New knowledge and data from TipESM will be regularly communicated to a broad range of research communities, policymakers and the public, contributing to a prepared and resilient society.

Cloud, aerosols and their interactions are key regulators of climate. However, uncertainties in the magnitude of the net cooling impact of aerosols on climate and in the cloud response to evolving anthropogenic emissions and climate change induced feedbacks on natural emissions are major challenges that limit our understanding of how global and regional climate, including extremes, respond to changes in greenhouse gases. It is of paramount importance to better understand aerosol-cloud processes and their role in the Earth System, from regional to global scales, and over different time scales, from days to decades. Over the last decade, extensive research networks, infrastructures, satellite instruments, and atmospheric models have been developed, making it possible to obtain a holistic view of the effects of clouds and aerosols on climate and weather. CERTAINTY will capitalise on this available data together with advanced algorithms, machine learning and data assimilation methods, high resolution models, and Earth system models to bring the fundamental knowledge of interactions between clouds, aerosols, and radiation to a new level. The consortium partners are in key roles as operators, data originators, developers, providers, and users of European aerosol and cloud data and ESMs/high resolution models. The consortium leads the activities of next generation satellite missions (such as EarthCARE), and the development of new satellite products, to facilitate their scientific use in CERTAINTY by preparing tools for early adoption of data. CERTAINTY will bring the observation-based knowledge to be used in modeling frameworks to improve predictive models and knowledge of processes controlling aerosols, clouds, and their interactions from hours to decades. The ultimate outcome will be better understanding and predictions of extreme events that facilitates planning of climate mitigation/adaptation strategies for the good of European citizens and global society.

Global warming continues at an alarming rate, presenting unprecedented challenges to society that require urgent, science-led mitigation and adaptation. Earth system models (ESMs) are essential tools for projecting climate change, providing important information to decision makers. However, confidence in predicted climate change is undermined by a number of uncertainties; (i) ESMs disagree on how much the Earth will warm for a given increase in atmospheric carbon dioxide (CO2) (Earth’s equilibrium climate sensitivity); (ii) how much emitted CO2 will stay in the atmosphere to warm the planet (half the CO2 emitted by humans has been absorbed by the land and ocean) and (iii) how much excess heat in the Earth system will enter the ocean interior, delaying surface warming (~90 % of the heat in the Earth system goes into the ocean). Central to these uncertainties are poorly understood, and poorly modelled, Earth system feedbacks, in particular cloud feedbacks, carbon cycle feedbacks and ocean heat uptake. Poor representation of these phenomena degrades the accuracy of ESM projections, with implications for anticipating future climate extremes and societal impacts. We aim to improve the representation of these feedbacks in ESMs, reducing uncertainty in global warming projections. We propose a multidisciplinary approach, focused on “learning” how to accurately describe processes underpinning these feedbacks, through a fusion of observations with advanced machine learning (ML) and artificial intelligence (AI). Such data and approaches, constrained by the laws of physics, will deliver a step change in the accuracy of Earth system models. AI4PEX will place Europe at the forefront of a revolution in Earth system modelling, leading to increased accuracy of climate change projections and superior support for implementation of the Paris Climate Agreement and the European Green Deal.

To mitigate the impact of greenhouse gas on the environment and climate, the gas turbine power generation industry must rapidly reduce its emissions. This requires abandoning the traditional combustion of carbon-based natural gas in favour of carbon-free fuels. ACHIEVE aims at developing the fundamental knowledge to enable a transition to unconventional carbon-free fuel blends based around H2 and NH3 to achieve zero carbon emissions, ultra-low NOx emissions, and stable gas turbine operation. ACHIEVE proposes a three-pronged strategy consisting of (a) experimental and (b) numerical activities, that will advance the technology readiness level (TRL) up to 4 for practical low emissions combustors for realistic and representative blends of fuels, as well as (c) system level engagement with OEMS, end users, and stakeholders. Experimental campaigns will explore combustor stability limits, emissions, and fundamental aspects of the combustion of hydrogen blends, with the complexity of the experimental burners and operating conditions increasing over time and culminating in tests performed at intermediate pressures and powers relevant for gas turbine conditions. Numerical activities will address combustion modelling challenges, including chemical kinetics, fundamental physics governing flame dynamics, ushering in new modelling techniques such as artificially thickened flames coupled with virtual chemistry, sub-grid LES models for thermo-diffusive instabilities and stability analysis aimed to understand and predict NOx formation mechanism, lean blow off, flashback limits and thermoacoustic instabilities. Real-time monitoring and predictive capabilities for practical combustion systems will also be developed. Finally, in the third prong, engagement with industry, OEMs, and other target groups will leverage the results of ACHIEVE with the necessary stakeholders to progress the transition to a carbon-free fuels for power generation.

RENEE envisions flexible remanufacturing using AI and advanced robotics for circular value chains in EU industry. The objective of RENEE is to implement human-centric production systems relying on advanced robotics and AI to accommodate the remanufacturing of diverse states of used products. Additionally, RENEE will accelerate the workforce upskilling/reskilling by deploying a remanufacturing educational platform and a set of operator support technologies. RENEE follows a holistic approach providing product, process and resource-level enablers for remanufacturing applications including: - Circular value chains configuration toolbox: Including software solutions for product state diagnosis and classification, methods for product ‘design for remanufacturability’, Digital Product Passport, and for remanufacturing value chain configuration and planning. - Digital infrastructure for remanufacturing management: including a) tools for the planning and orchestration of flexible remanufacturing systems, b) deployment of Digital Twins customized for the remanufacturing process, and c) tools to enable product traceability and efficient management of the remanufacturing supplier network. - Robot skills & flexible production modules for remanufacturing: Enabling the resource level autonomy for remanufacturing through the deployment of dedicated robot skills libraries, AI methods for decision-support and process optimization as well as advanced robotics integrated in hybrid production specialized in remanufacturing, - Upskilling/reskilling the workforce for remanufacturing: Supporting operators both during the remanufacturing tasks via inclusive interfaces as well as providing the infrastructure (Educational platform) and required material (courses) for training them to meet the requirements of diversified remanufacturing operations. The RENEE modules will be validated in 4 pilots from the household appliances (refrigerators), robotics, and mobility (electrical motors and bikes) sectors

The past years have shown the vulnerability of rigid international supply chains. The ability to adapt to changes and create resilient supply chains will be a key competitive advantage for manufacturers in the future. RAASCEMAN tackles three different possibilities to react to unforeseen events: adapting the production plan based on supply chain data adapting the supply chain by switching the supplier using a MaaS network integrating remanufacturing as procurement alternative leveraging circularity. The project aims to enable companies to mitigate short- and medium-term unforeseen events and to enable companies to participate in a dynamic MaaS-network lowering the market barriers for companies specialized in remanufacturing or alternative technologies such as 3D printing. RAASCEMAN designs and demonstrates a series of software tools digitizing supply chains by using digital twins and an infrastructure for data-exchange based on European values. RAASCEMAN will develop its overall ambition by the means of five scientific objectives namely: Actionable propositions for adapting supply chains or internal production and logistics based on reliable quantification and impact prediction of unforeseen events Dynamic supply chain generation enabling resilience and self-adaptation of MaaS networks, Building Trust in MaaS networks auditing suppliers’ reliability and testing plausibility of offers Dynamic planning and scheduling of production processes enabling companies to swiftly adapt logistics and production to varying external conditions and Dynamic assembly and disassembly to enable machines in the field level We demonstrate our solutions in two industrial use-cases of the automotive and bike industry and create a MaaS network connecting five pilot lines distributed over Europe. The majority of project results will be made available under appropriate open-source licensing schemes to allow further maturation in integration after the RAASCEMAN project concludes.

The INSTINCT project is going to enable globally sustainable, interactive, immersive, and intelligent ‘beyond communications’ 6G connectivity by developing three complementary but critical breakthrough technology pillars: ·sensing-assisted communication technologies, thus allowing localization, tracking, mapping, monitoring, imaging, incident detection and semantics become integral parts of connectivity services (Pillar 1), ·intelligent surfaces, holographic radios and cell free systems, which offer wavefront engineering functionalities and tuneability of the wireless environment and can act as reconfigurable and intelligent sensors (Pillar 2), and ·Machine Learning (ML) techniques-based co-design of Sensing and Communications INSTINCT proposes a revolutionary path to 6G and has the ambition to specify the relevant KPIs/KVIs, formulate suitable models, devise the theoretical framework, invent new technologies, evaluate via simulations and validate by means of 2 HW and 1 SW demonstrators, a networked intelligence concept able to meet the unprecedented 6G requirements. To realise this vision, INSTINCT consortium brings together all relevant stakeholders from across Europe, with an impressive record of interdisciplinary research excellence, technology innovation, standardisation and transfer, and implementation expertise.

The OPTI-6G project develops a Photonic near IR Cell Free 5G Network, which does not suffer from interference because of the propagation characteristics of EM waves in this part of the spectrum and provides universal broadband coverage within buildings from pervasively located OWC access points. The benefits of applying cell free near IR networks in buildings are (1) multi-connectivity can be configured with cell free network thereby improving link quality and reliability; (2) there is no longer the need for building owners to subdivide their non-public mobile building network into cellular areas; (3) building owners no longer need to request permission from MNOs to use their licensed spectrum since the system operates at the optical unlicensed bands; (4) interference between inside and outside access is managed by an AI Based Distributed Scheduler; (5) position and orientation of end user equipment can be measured very accurately. It provides solutions to two main barriers to develop this challenge: (i) Brings together a select multi-disciplinary team of research institutions and industries in a collaborative project to develop and demonstrate this vision, who otherwise would not have assembled to achieve this goal; (ii) Develops a proof of concept demonstrator in OLEDCOMM and RUNEL; (ii) Performs experiments to measure position and orientation of end user equipment at UVSQ and UBRU. The starting point is (1) state-of-the-art cell free 5G RAN solution and very high accuracy sub cm accuracy localisation measurement system developed by RUNEL; (2) the state of the art VCSEL infrared source and high-speed PIN photodiodes receivers and that supports 1 Gbps data rates up to 5 m over a field of emission of 25° developed by OLEDCOMM. The project brings together these technologies to produce an easy installation and operation, License Free broadband Network for indoor buildings. The outcome will be low-cost commercially attractive broadband cellular access within buildings

The HAL4SDV proposal aligns with the EU Strategic Research and Innovation Agenda 2022 on Electronic Components and Systems. It aims to pioneer methods, technologies, and processes for series vehicle development beyond 2030, driven by anticipated advancements in microelectronics, communication technology, software engineering, and AI. HAL4SDV envisions a future where vehicles are fully integrated into smart cities, intelligent highways, and cyberspace, blurring the lines between inside and outside the vehicle. Assumptions include data-centricity, code portability, efficient data fusion, unlimited scalability, real-time capabilities, and robust cybersecurity. The objectives encompass unifying software interfaces, creating a hardware abstraction framework, enabling Over-The-Air (OTA) updates, designing platform architectures, ensuring hardware abstraction and virtualization, offering hardware support, automating integration, supporting safety features, harnessing edge computing, implementing security measures, and providing essential development tools. By focusing on these objectives, HAL4SDV aims to establish a unified ecosystem for software-defined vehicles, positioning Europe's automotive industry for continued leadership post-2030 while leveraging existing results and technologies to accelerate progress.

Recent advances in environmental microbiology, metagenomics and phylogenomics strongly suggest that the eukaryotic cell evolved from symbiotic consortia involving an Asgard archaeon and, at least, the alphaproteobacterial ancestor of the mitochondrion. However, many genes of prokaryotic origin in the last eukaryotic common ancestor (LECA) appear to originate neither from archaea nor alphaproteobacteria, suggesting that other bacteria (e.g. Deltaproteobacteria) may have contributed to eukaryogenesis as additional symbionts or gene donors. To ascertain the origin of these genes, it is essential to better understand the ecology of symbiotic microbial consortia involving Asgard archaea (AA), and in particular, to identify the partners with which they interact in natural ecosystems. In this project, I will combine metagenomics, phylogenomics, fluorescence-activated single-cell/consortium sorting, high-throughput microfluidics, state-of-the-art fluorescence and electron microscopy techniques and cultivation approaches to identify and characterize members of AA syntrophic consortia and their associated viruses in a broad variety of microbial mats and oxygen-poor environments. With this information, I aim to i) identify the partners of AA syntrophic consortia across ecosystems, determine whether they co-evolve and unravel their ecological preferences; ii) characterize the metabolic interactions and phenotypic properties of AA symbiotic consortia in culture and/or from sorted consortia populations; iii) characterize the cell ultrastructure and potential presence of endomembranes in members of AA consortia, their three-dimensional organization and their spatial distribution in microbial mats; and iv) identify potential bacterial symbiotic partners involved in eukaryogenesis, in addition to the mitochondrial alphaproteobacterial ancestor, and/or gene donors to the LECA or its Asgard archaeal ancestor. Our results should substantially advance understanding of eukaryogenesis.

Resistance of cancers to immune checkpoint blockade (ICB) can result from a deviated taxonomic composition of the intestinal microbiota. A surge in the Enterocloster genus, for instance following discontinuation of antibiotics or chronic inflammation caused by tumors, induces the downregulation of MAdCAM-1 in the ileal lamina propria and mesenteric lymph nodes through perturbations of biliary salts. In turn, the ileal MAdCAM-1 loss induces the exodus of immunosuppressive T lymphocytes expressing the MAdCAM-1 receptor α4β7, i.e., FoxP3+ RAR-related orphan receptor gamma t (RORγt+) regulatory (Tr17) cells, from the gut to distant tumors. Disruption of the MAdCAM-1–α4β7 axis compromises the efficacy of immunotherapy and reprograms the tumor microenvironment towards a regulatory phenotype. Moreover, serum soluble MAdCAM-1 is a proxy of intestinal dysbiosis and a robust predictor of survival in cancer patients treated with ICB. To decipher the biological significance of these findings, we will first investigate the transcriptional and post-translational mechanisms regulating MAdCAM-1 expression and function (Task 1), in particular neuroendocrine and metabolic cues. Next, a comprehensive phenotyping of the emigrating enterotropic T cells reaching the tumor by single cell transcriptomics and genomics, as well as specific genetic and immunopharmacological intervention on T lymphocytes and cancer cells will lead to the identification of the molecular mechanisms regulating the gut-tumor axis (Task 2). We will investigate how enterotropic T cells homing to cancers maintain their proliferative and suppressive capacities, in particular in the light of the recognition of tumor and/or commensal antigens (Task 3). Altogether, this approach will lay the molecular and metabolic foundations governing the MAdCAM-1–α4β7 gut immune checkpoint

The HPC Digital Autonomy with RISC-V in Europe (DARE) will invigorate the continent’s High Performance Computing ecosystem by bringing together the technology producers and consumers, developing a RISC-V ecosystem that supports the current and future computing needs, while at the same time enabling European Digital Autonomy. DARE takes a customer-first approach (HPC Centres & Industry) to guide the full stack research and development. DARE leverages a co-design software/hardware approach based on critical HPC applications identified by partners from research, academia, and industry to forge the resulting computing solutions. These computing solutions range from general purpose processors to several accelerators, all utilizing the RISC-V ecosystem and emerging chiplet ecosystem to reduce costs and enable scale. The DARE program defines the full lifecycle from requirements to deployment, with the computing solutions validated by hosting entities, providing the path for European technology from prototype to production systems. The six year time horizon is split into two phases, enabling a DARE plan of action and set of roadmaps to provide the essential ingredients to develop and procure EU Supercomputers in the third phase. DARE defines SMART KPIs for the hardware and software developments in each phase, which act as gateways to unlock the next phase of development. The DARE HPC roadmaps (a living document) are used by the DARE Collaboration Council to maximize exploitation and spillover across all European RISC-V projects. DARE addresses the European HPC market failure by including partners with different levels of HPC maturity with the goal of growing a vibrant European HPC supply chain. DARE Consortium partners have been selected based on the ability to contribute to the DARE value chain, from HPC Users, helping to define all the requirements, to all parts of the hardware development, software development, system integration and subsequent commercialization.

The key element to ensure efficient use of HPC infrastructures is to optimize the performance and efficiency of the applications. The Centre of Excellence on Performance Optimization and Productivity (POP CoE, www.pop-coe.eu) was initiated in October 2015 with the fundamental purpose of assisting a broad community of HPC application developers and users in both science and industry domains helping them to understand the performance-related issues of their applications and thus improve their efficiency and productivity. This fundamental purpose is reached by externally and objectively auditing the performance of the codes to all interested users, by providing not only qualitative but also quantitative analysis through the use of POP tools and methodology. The current proposal, Performance Optimization and Productivity 3 (POP3), is articulated in 3 main pillars: services, users, and co-design. POP services mainly focus on performance assessments with the goal to evaluate code performance and scaling, identifying the main sources of inefficiency and providing some insight and recommendation about how to improve it. POP3 also provides second level services that have been extended and include proof of concepts, energy efficiency and advisory studies. Although POP3 will continue targeting all scales and types of users, with this proposal we will focus our efforts on larger scales, assessing the execution on the EuroHPC sites of some of the European flagship HPC applications for other CoEs. However, POP3 will still provide services to prescribers and SMEs to promote an efficient usage of the computing resources. The co-design will be covered in two dimensions. Internally in POP3 we will co-design the tools and methodology to be able to analyse the applications on the selected platform at the selected scale. Externally, POP3 will identify best practices and kernels that will be offered to other European projects as well as the wide audience of parallel applications.

The Energy-oriented Centre of Excellence for exascale HPC applications (EoCoE-III) applies cutting-edge computational methods in its mission to foster the transition to decarbonized energy in Europe. EoCoE-III is anchored both in the High Performance Computing (HPC) community and in the energy field. It will demonstrate the benefit of HPC for the net-zero energy transition for research institutes and also for key industry in the energy sector. The present project will draw the experience of two successful previous projects EoCoE-I and EoCoE-II, where a set of diverse computer applications from four energy domains achieved significant efficiency gains thanks to its multidisciplinary expertise in applied mathematics and supercomputing. During this 3rd round, EoCoE-III will channel its efforts into 5 exascale lighthouse applications covering the key domains of Energy Materials, Water, Wind and Fusion. A world-class consortium of 18 complementary partners from 6 countries will form a unique network of expertise in energy science, scientific computing and HPC, including 3 leading European supercomputing centres. This multidisciplinary effort will harness innovations in computer science and mathematical algorithms within a tightly integrated co-design approach to overcome performance bottlenecks, to deploy the lighthouse applications on the coming European exascale infrastructure and to anticipate future HPC hardware developments. New modelling capabilities will be created at unprecedented scale, demonstrating the potential benefits to the energy industry, such as accelerated design of photovoltaic devices, high-resolution wind farm modelling over complex terrains and quantitative understanding of plasma core-edge interactions in ITER-scale tokamaks. These lighthouse applications will provide a high-visibility platform for high-performance computational energy science, cross-fertilized through close working connections to the EERA consortium.

SPADES’ mission is to develop, test and implement soil-inclusive spatial planning strategies to support the transition towards soil health in Europe. Soil health is highly under pressure and the soil’s ability to perform essential ecosystem services should be improved to cope with pressures such as climate change and need such as a healthy living environment. Spatial planning and design are practices that, when enriched by soil care, can enhance the current status of soils and support societal challenges and needs, while avoiding unwanted trade-offs towards other areas, generations or functions. SPADES will therefor provide a comprehensive state of the art on both planning and design practices, as on soil instruments. To be able to make a transition in spatial planning and design towards healthy soils a fundamental understanding of the current mechanisms is key. SPADES will develop integrative instruments and improve the information basis and brokerage to bring the spatial planning and design field and soil sector together. This will contribute to the methodological basis. SPADES will work in 17 pilots in 10 member states, covering a broad range of land uses (urban, peri-urban and rural areas), time and spatial scales, and soil and planning challenges. This is done together with local practitioners and policy makers to develop fit-for-purpose soil-inclusive spatial strategies to support different goals such as land degradation neutrality and no net land take. The SPADES instruments will be presented in such a way (manual and navigator) so that they can be found by the right user, at the right phase of the planning and design process, and for the right purpose. SPADES supports soil literacy (by capacity building and communication, dissemination and exploitation activities) to a broad range of target groups to enable current practice to improve. To make this most effective, SPADES case partners are involved in these CDE and training activities.

III-nitride semiconductors (GaN/AlGaN) are strategic materials for photodetection in a broad spectral range from deep ultraviolet to far infrared. These domains can be addressed thanks to interband and intersubband transitions respectively, which cover wavelengths inaccessible to standard III-V semiconductors. Heterogeneous integration of III-N nanowires (NWs) on 2D materials at the same time opens new technological opportunities for advanced optoelectronics and presents fundamental interest to elucidate the physics of van der Waals epitaxy (vdWE). Available research on epitaxial growth of GaN NWs on 2D graphene has demonstrated its promise; however, the scope for improvement remains limited. A number of questions with fundamental significance e.g. the influence of the 2D material in NW growth, controlling factors for NW size/size-distribution, and generalized understanding of vdWE with experimental authentication remain open. INTEGRASION proposes to address these open questions and to achieve a general understanding of vdWE of nitrides on 2D materials for advanced optoelectronic devices. To reach this goal, GaN/AlGaN NWs will be grown on 2D transition metal dichalcogenides (WS2) and comparative analysis will be performed with growth on graphene. The fundamentals of growth process will be assessed experimentally and theoretically emphasizing the impact of 2D materials on the NW growth which is pivotal for heterojunction formation. GaN/AlGaN heterojunctions in multi-quantum well structure will be grown on 2D platforms to demonstrate interband UV photodetection as well as intersubband photodetection in mid- and far-infrared domains. Besides, heterogeneous integration of GaN NWs on 2D platforms will facilitate the post-growth transfer of III-N NWs to flexible substrates where monolithic integration is not possible. INTEGRASION will address these three key aspects: (i) heterogenous growth, (ii) interband/intersubband photodetection and (iii) hybrid integration.

EBRAINS is a collaborative European Research Infrastructure designed to advance and accelerate progress in neuroscience and brain health. This innovative infrastructure, a legacy of the Human Brain Project (HBP), is an ecosystem where researchers, clinicians and experts from various disciplines converge to explore and analyze brain complexity – from molecular and cellular levels to the functioning of the entire organ. Therefore, the project aims to create a new standard for brain atlases from the micro- to the macro-scale, link foundational multi-level data and connectomes in the healthy and pathological brain with atlases and models, create digital twins through modelling and simulation as well as unique, excellent, and preferred services for FAIR neuroscience data. The overarching goal of EBRAINS 2.0 is to foster a deeper understanding of brain structure and function with dedicated and mature software tools, to facilitate the development of more effective treatments, new drugs, diagnostics and preventive measures for neuro-psychiatric disorders. We expect that EBRAINS 2.0 catalyzes progress in the field of large-scale models running on HPC towards Exascale and leads to innovative solutions for neuro-inspired computing, and cognitive technologies such as neurorobotics and AI. Sophisticated digital modeling and data analytics capabilities will benefit communities beyond neuroscience, such as biomedicine. We will advance EBRAINS technology, platform services and the base infrastructure roadmap, educate and train a new community of users and developers from academia, industry and SMEs, and ensure knowledge transfer. EBRAINS 2.0 will become the neuroscience hub in the European infrastructure landscape, through building strong links with the European data spaces, EOSC and EuroHPC JU, centers of excellences and other initiatives. Globally, EBRAINS 2.0 will make a strong contribution to the new era of digital neuroscience and foster European leadership in this field.

A century after its discovery, the atomic nucleus remains a subtle organization of protons and neutrons interacting through QCD. Its properties are the driving mechanism of cataclysmic events in the cosmos like those leading to the synthesis of medium-to-heavy elements. Unfortunately, precise, fundamental nuclear data, which are essential both to the sustainability of our civilization through technological applications, and to our understanding of the universe, are still a considerable undertaking to measure or to compute. Our objective is to unlock the applicability of ab initio predictions of nuclear collisions, which have been, so far, lagging behind that of static properties of nuclei. To reach this goal we aim: 1) To develop perturbation theory to ab initio reaction modeling, and by this means to open up to reacting systems above the p-shell; 2) To exploit the aforementioned development in the context of strict effective field theory for nucleons. We expect these achievements to allow us to contribute to the understanding of the detailed balance between nucleons that will be uncovered at the edges of nuclear stability at facilities like Spiral2 in France and FAIR in Germany. The experience researcher (ER) will bring to the host group its know-how in perturbative methods, of which he has been a practitioner in nuclear structure, and, in doing so, he will boost the applicability of the host ab initio reaction tools. In turn, he will benefit from the supervisor’s expertise in reaction theory and effective field theoretical tools thereby acquiring a strong and valuable portfolio aiming to perform nuclear evaluation of data and predictions for supporting both theoretical and experimental nuclear astrophysics needs. In conclusion, this project is mutually beneficial to the host group and the ER. It will increase the ER visibility both at the EU and international levels, ready his managerial and mentoring skills for future career opportunities in academia or industry.

An exciting area of research in quantum condensed matter physics involves the exploration of Majorana bound states (MBS) to create topologically protected qubits for fault-tolerant quantum computing. In the quest for experimental evidence of these quasiparticles, the most frequently observed indication of MBS is considered as a peak in the differential conductance spectra at zero bias voltage. While this observation could be easily detected in scanning tunneling microscopy/spectroscopy experiments, it does not serve as a piece of conclusive evidence for the Majorana nature of a state as other topologically trivial bound states, such as Yu-Shiba-Rusinov states, can also exhibit the same zero-bias conductance peak. In this direction, recent theoretical investigations have extensively examined how shot noise at atomic could serve as a distinctive tool to differentiate between MBS and trivial bound states in vortex matter and nanowires. However, experimental verification of these theories has not been feasible so far due to the underlying challenge of measuring shot noise with high enough sensitivity at a nanometer resolution. Although experimentally challenging, in this project we will combine atomically resolved differential conductance and shot noise together by using a home-built shot-noise scanning tunneling microscope (SN-STM). The unprecedented power of this technique will be exploited to measure shot noise which provides direct evidence to distinguish the MBS from any conventional in-gap mode. We propose to investigate a couple of different scenarios such as single atomic impurities and vortex cores in a variety of iron-based superconducting quantum material, magnetic nanostructure (1D chains) coupled to an s-wave superconductor.

Brain tumors strike people in the prime of life. Surgical resection is the initial treatment for nearly all brain tumors and aims at maximizing the extent of tumor resection while preserving the patient's cognitive function. To optimize this tradeoff, neuronavigation systems have been developed to provide intraoperative guidance to surgeons. These systems allow for the visualization of the position of surgeons' surgical tools relative to the tumor and critical brain areas visible in preoperative Magnetic Resonance Imaging. However, these systems become inaccurate as the surgery progresses since they do not account for brain deformation and tissue resection occurring during surgery. In an interdisciplinary effort, project SafeREG combines the researcher's background to the expertise of computational scientists from INRIA and clinicians from Parisian hospitals. Its objective is to invent a novel image registration methodology with intraoperative ultrasound that is rich enough to capture complex deformations occurring at the tumor and resection cavity boundaries, fast enough to be employable clinically, and interpretable enough for informed decision-making by neurosurgeons. This will be accomplished by pushing the envelope of scientific knowledge in (1) cross-modality domain adaptation for weakly- and unsupervised image segmentation; (2) modality-invariance representation learning using contrastive learning; (3) non-rigid registration with discrete probabilistic methods; (4) simulated-based variational inference for registration uncertainty quantification that leverages biomechanical knowledge. This research has the potential to deliver accurate and informed image-guided surgery, conferring a lower risk of new neurologic deficits and improved patient prognosis. Beyond neurosurgery, it has broad applications to additional areas of image-guided therapy, including spine, liver, and prostate surgery.

The European Rare Diseases Research Alliance (ERDERA) aims to improve the health and well-being of the 30 million people living with a rare disease in Europe, by making Europe a world leader in Rare Disease (RD) research and innovation, to support concrete health benefits to rare disease patients, through better prevention, diagnosis and treatment. This Partnership will deliver a RD ecosystem that builds on the successes of previous programmes by supporting robust patient need-led research, developing new diagnostic methods and pathways, spearheading the digital transformational change connecting the dots between care, patient data and research, while ensuring strong alignment of strategies in RD research across countries and regions. Structuring goal-oriented public-private collaborations targeted at interventions all along the R&D value chain will ensure that the journey from knowledge to patient impact is expedited, thereby optimising EU innovation potential in RD. To support its ambition and missions ERDERA has been designed as a comprehensive and integrated ecosystem of which structure can be compared to an institute encompassing three main parts: (i) funding, (ii) internal (in house) Clinical Research Network that implements research activities targeting clinical trial readiness of RDs and accelerating diagnosis and translation of research discovery into improved patient care, and (iii) related supporting services (Data, Expertise, Education and Training) as well as an acceleration hub that serve external and internal RD community, all supported by all-embracing coordination and strategy and foundational (inter)national alignment.

LANDFEED will focus on creating value from under-utilised waste from the agro-food industry, forestry, urban and natural waste, implementing circular and local solutions that allow waste to be valorised by placing it in a circular framework, and producing innovative biofertilisers to improve Europe's self-sufficiency. In addition to optimising and implementing innovative nutrient recovery technologies, work will be carried out on a new generation of coatings for these bio-based fertilisers, capable of improving their efficiency through controlled nutrient release mechanisms. In this way LANDFEED will contribute to a better management of the fertiliser provided, we will contribute to lower greenhouse gas emissions and a reduced impact on the environment's water resources. LANDFEED will ensure that the solutions and results of the project are locally driven through the different use cases. The use cases will consider all links in the value chain that will participate as lighthouses, serving as demonstrators and disseminators of the technologies, results and applications developed during the project. These use cases will also contribute to the objectives of the Soil Strategy by enabling the restoration of soil health through the enhancement of its specific and functional biodiversity. At the global level, the business model will be defined in its entirety, with the aim of maximising the replicability of these Use Cases and facilitating their implementation in other European areas and regions.

ASCLEPIUS’s overall aim is to boost the scientific excellence and innovation capacity of Giorgi Eliava Institute of Bacteriophagy, Microbiology and Virology (Eliava) and its high-quality Twinning partners - l’Institut national de recherche pour l’agriculture, l’alimentation et l’environnement, Universidade do Minho and Intelligentsia Consultants Sarl – to expand their insights in phage therapy for treating Pseudomonas aeruginosa and Staphylococcus aureus. To achieve this aim, ASCLEPIUS will implement a research and innovation strategy over three years based upon five objectives: Objective 1: Conduct exploratory research on phage therapy for treating Pseudomonas aeruginosa and Staphylococcus aureus. Objective 2: Transfer knowledge between experienced researchers of Eliava and the Twinning partners. Objective 3: Enhance career prospects of early-stage researchers of Eliava and the Twinning partners. Objective 4: Improve Eliava’s management and administrative capacity for European R&D programmes. Objective 5: Raise the research profile of Eliava and the Twinning partners.

VASSAL project focuses on leveraging the scientific excellence and innovation capacity of the consortium in the field of software engineering to support safety and security of digitised economies and societies. The key objective is to bring together expertise of the consortium in specific domains to enhance and create a new knowledge for robust and resilient SW engineering through scientific strategy combining model-based design, formal methods and economics for source-codes and systems. As SW becomes more complex, ensuring its safety and security (vulnerabilities free) becomes increasingly challenging and vital, not only in safety-critical systems but across various operation systems and IoT as well. Formal methods and model-based design are taking an increasingly significant role, building upon its already widespread use in safety-critical applications, such as automotive or aerospace. As basic building blocks in engineering process, they enable to build robust and resilient SW and HW systems (security-/safe-by-design) ensuring the reliability and correctness, leveraging cybersecurity, and improving the development life-cycle, that lead to savings in operational costs of systems. The economic assessment and implications of advanced SW engineering tools are not commonly available. VASSAL will deliver a rare opportunity to explore and document the potential benefits of and challenges in deployment in order to leverage the awareness and make inroads to broader exploitation by end-users (especially SMEs) in segments, where these issues are being overlooked due to the alleged non-returnability of the investment.

PRIVIDEMA represents an industry-driven initiative to advance privacy-preserving technologies in the application areas of cyber threat intelligence, data protection, and identity management. This multifaceted project operates across various research and innovation maturity levels, with the overarching goal of introducing more robust, user-friendly and scalable privacy and security technologies for the European ecosystem. Key components of PRIVIDEMA include: 1. Development of open-source tools, hosting networking events, and initiation of capacity-building efforts to democratize technology access and empower cybersecurity professionals. 2. Advancement of homomorphic encryption capabilities, implementation of hardware acceleration methods, and improvement of Fully Homomorphic Encryption (FHE) usability. 3. Creation and demonstration of a prototype European identity wallet featuring issuer and relaying party functionalities. 4. Development and demonstration of a prototype European privacy-preserving cyber threat data processing system, with real-world testing and validation of innovative technologies. Aligned with the objectives of Horizon Europe, PRIVIDEMA actively contributes to increased cybersecurity, data and network protection, and the establishment of robust digital infrastructures. The project distinguishes itself through its commitment to supporting SMEs as well as promoting open-source development, cross-disciplinary collaboration, and privacy-by-design principles. The solution-oriented approach positions PRIVIDEMA as a pivotal force in advancing cyber-resilient digitalization and the data economy in Europe. PRIVIDEMA's connection to various European strategic initiatives underscores its relevance, with a clear emphasis on real-world applications, innovation beyond the state-of-the-art, and a strategic trajectory toward market-ready solutions.

Technology advancements enhance everyday life, but they also provide numerous opportunities for the proliferation of advanced cybercrimes, which, via innovative tactics and techniques, pose serious security and financial risks to EU and beyond. ENSEMBLE aims to provide a well-rounded response to the fight against (cross-border) cybercriminal activities, at the nexus of advanced AI-based technological solutions, (multi-stakeholder) investigations processes, training, and awareness in order to detect and prevent cybercrime-related activities, with particular focus on ransomware, cyber fraud, data theft and extortion as well as unauthorised access and crypto-jackings. This will be achieved via a three-pillar approach. ENSEMBLE will develop a modular AI-based, forensically sound investigation toolbox based on user centric criteria, to assist Police Authorities in detecting, extracting, processing, and analysing online information relevant to cybercrime activities, thus fighting sophisticated cyber-threats, capitalising also in joint multi-stakeholder operations both at national and cross border level and in secure data and information sharing mechanisms. Police Authorities, prosecutors, and judicial actors involved in such investigations will be offered innovative training curricula and methods as well as synchronous and/or asynchronous learning methodologies that will be aligned to their needs and improve their current capacity, taking into consideration the technological, procedural, operational, legal/multi-jurisdictional dimensions. Finally, public awareness and engagement with relevant actors for early identification and prevention of cybercrimes will be cultivated through targeted awareness raising campaigns and specific policy recommendations. Having brough together a multidisciplinary team of five LEAs, seven research/academic institutions and six industry partners (including five SMEs) with a wide range of expertise in the field, ENSEMBLE provides a compelling

Understanding the interaction between electromagnetic radiation and matter is crucial for unravelling the internal structure and processes of materials. Electromagnetic waves exhibit both wave-like and particle-like behaviour, with the quantized nature of light becoming apparent in the realm of quantum technologies. The QU-ATTO network aims to merge the fields of quantum optics and quantum information science with attosecond physics. This involves focusing on experimental campaigns to highlight quantum aspects in the interaction of intense laser fields with matter and advancing theoretical descriptions for a comprehensive understanding of the quantum state of light associated with intense laser fields. Traditionally, attosecond pulses have been generated using table-top femtosecond lasers. However, recent experiments performed at free-electron lasers (FELs) have demonstrated the production of isolated attosecond pulses and precise control of attosecond waveforms for pulse trains, leading to remarkable advancements in attosecond science. The network also aims to leverage recent advances in seeded FELs and high-intensity high-harmonic generation (HHG)-based attosecond sources to demonstrate the coherent control of electronic dynamics in systems of increasing complexity. The QU-ATTO network represents a comprehensive effort to advance the understanding and control of the interaction between electromagnetic radiation and matter, with a specific focus on merging quantum optics, quantum information science, attosecond physics, and free-electron laser science. The doctoral candidates (DCs) in the network will receive multifaceted scientific training encompassing experimental and theoretical aspects of quantum information science, strong-field physics, and soft X-ray and X-ray science, as well as extensive training in transferable skills and self-management techniques.

Radiotherapy (RT) is a mainstay of modern cancer treatment. Conventionally, RT is delivered to the patient lying on a treatment couch, while a beam steering device (gantry) aims the radiation from any angle around the target. Positioning the patients in upright body posture (upRT) instead enables to orient the patient arbitrarily toward a fixed beam. This enables smaller facility footprint and reduced treatment cost, placing upRT in the core of the UN sustainable development goals, and opening global access to advanced treatment options: 80% of cancer patients live in countries which host only 5% of the world’s RT resources. Moreover, upRT improves patient comfort and is associated with anatomical and physiological advantages, such as reduced breathing motion. It therefore comes as no surprise that, with new upright patient positioning & imaging solutions entering the market, upRT is enjoying a surge in interest. Yet, key scientific questions remain, international guidelines for upRT are lacking, and existing RT workflows are geared to lying patients. As the first clinics adopt new upRT technologies, there is a global need for trained professionals in industry, clinics and academia, to reach the promised benefits for patient care. UPLIFT builds this next generation of experts by addressing key research questions related to: treatment planning, clinical workflow and equipment design. Leveraging latest upRT technology available through our world-class consortium, UPLIFT propels Europe to the forefront of the upRT paradigm shift. UPLIFT focuses on: Learning (through its academic and clinical centres of excellence); Innovation (through its leading industrial partners); Fellowship & Training (through an outstanding cross-sector programme of workshops, secondments & mentoring). Input from patient advocacy groups and an internationally renowned advisory board will maximise its impact. UPLIFT will revolutionize modern RT, making it more human, accessible and sustainable.

Organisms that inhabit the surface of the Earth have evolved an endogenous 24 hour clock that infiltrates every level of biological organisation from the molecular to the ecological. This biological timer is a critical adaptation to living on a rotating planet with predictable daily and seasonal cycles of light and dark, warmth and cold. The fruitfly Drosophila melanogaster has provided the model system by which the highly conserved genetic and molecular basis of animal rhythmicity was initially dissected, winning a Nobel Prize in 2017 to its discoverers. Our network INCITE (INsect Clock Initial Training Experience) will provide state-of-the-art doctoral training to doctoral candidates (DCs) in insect molecular chronobiology using a comparative approach in which the circadian clock will be studied from a variety of perspectives. These will include the recruitment of the clock for i) insect seasonal ‘hibernation’ or diapause, a critical life-history feature that has important implications for range expansion under global warming, ii) in pollination, ii) in pest control, iv) in optimising the development of insects mass-reared as a protein source for human/animal consumption – asustainable model for agriculture and vi) in fundamental circadian biology of the model insect, D. melanogaster. In addition to their research projects, DCs will be seconded to partners both academic and industrial within the network and be further exposed to a variety of successful well-defined and time-tested courses that supplement those already offered at their local institutions, and will enhance and develop their scientific, entrepreneurial and transferable skills. INCITE will generate highly-trained, mobile and employable graduates that will be welcomed both in academia and industry.

The HINA project proposes to consider the hybrid integration of alkaline niobate-tantalate thin films (materials with the highest known experimentally measured electro-optic, nonlinear, piezoelectric, elasto-optic coefficients) in photonic and acoustic devices for advanced semiconductor photonics platforms. The final goal of the project is to develop a thin film technology not only offering the state-of-the-art performances but also with reasonable price and viable for real industrial applications in order to stimulate the transfer of newly developed products and technologies by the industry and to help enterprises to withstand global competitive pressures. The HINA project links world-leading research groups at Academia and Industry to give a combined, integrated approach of synthesis/fabrication, characterization, modeling/theory linked to concepts for materials integration in devices and systems. Such a science-supported total engineering approach will lead towards highly efficient electro-active and nonlinear materials designed towards integrated device needs and viable for industry. Doctoral Candidates will focus on this common research objective, applying a multidisciplinary bottom-up approach, which can be summarized by: "engineered molecule- advanced material- designed device - smart system". The HINA project also seeks to intensify the relationship between academic and private sectors, and to train highly skilled young researchers for new materials and device technologies. Both are essential to provide a strong European lead over the rest of the world in this highly competitive technologies.

Electrification coupled with renewable electricity supply is a key pathway to achieve a deep decarbonization of our society and contribute to an energy transition in a sustainable way. The electric energy demand based on distributed renewable sources is going to be even more important and a more efficient, secure, flexible and affordable energy distribution should be envisaged for the next future. If these requirements are not met, the replacement of well-established solutions based on fossil fuels will be unfeasible. Consequently, apart from the evident environmental impacts, collateral effects could occur, such as great blackouts at national and continental level. In this scenario, SAFEPOWER first explores and investigates on essential digital, enabling, and emerging technologies to achieve a new generation of power converters for solar applications: i) capable of anticipating failures to prevent downtime using effective Condition and Health Monitoring (C&HM) solutions assisted by AI strategies, ii) based on more compactly-packaged, efficient, rugged and affordable Silicon Carbide (SiC) power MOSFETs, diodes and solid-state DC breakers with a more sustainable manufacturing, and iii) prospecting on Ga2O3-based emerging power devices (MESFETs, diodes and solid-state DC breakers) especially designed for this application. Leveraging these technologies, SAFEPOWER studies and proposes new converter topologies and control schemes to enhance their compactness, sustainability, competitiveness, and security. Additionally, these technologies streamline cost-effective maintenance through AI-assisted intervention plans and AI-enabled "limp mode" operation with derating strategies, which can be extended to offshore wind energy conversion. Therefore, the adoption of SAFEPOWER's technological solutions in the EU solar sector not only will establish a competitive advantage against non-EU power converter manufacturers, but also will enable their initial deployment within the EU.

Quantum computing can be thought of in multiple ways. Among those ways, it can be seen as a computational model of quantum mechanics. Studying this model may have implications for our understanding of physics. It can also be seen as a new computational paradigm, with implications for computation, algorithms, and logic. Additionally, it can be viewed as a computational device that requires programming. Therefore, it is necessary to design and study programming languages for this purpose. The study of the foundations of quantum programming languages, type theory, and logic through the Curry-Howard correspondence may shed light on our understanding of quantum mechanics. Furthermore, it may lead to the development of new logics or the understanding of new structures in classical logic. Lastly, implementing these languages will enhance the way we program the new computers when they become widely used. In this project, we propose to study these various aspects of quantum computing, specifically focusing on the foundations of programming languages.

SIROCO (SImple and RObust laser source with EU supply chain and Cavity and injection-free Optical parametric oscillator for spaceborne lidar) aims to reach EU independence for high-power lasers in the eye-safe region. A solution based on wavelength conversion from a 1µm laser will be matured, ensuring EU supply chain independence for power laser emission in the 1.5-3µm range. Such breakthrough laser will build the foundation of next greenhouse gases (GHG) spaceborne sensors by Integrated Path Differential Absorption Lidar (IPDA), by which GHG of interest can be probed in the 1.6μm or 2μm eye-safe regions. To meet the stringent spectral, spatial beam, and power properties required, efficient and versatile wavelength converters such as Optical Parametric Oscillators (OPOs) pumped by mature 1μm power lasers are key enabling technologies. This is also the approach in the European Methane Remote Sensing Lidar Mission (MERLIN). SIROCO will mature innovative critical optical space technologies to TRL6, including a hybrid fiber/bulk 1μm laser combined with a new Backward Wave OPO (BWOPO) concept. This will lead to a simplification shock compared to the state of the art, as no optical cavity is required (higher robustness and easier integration), nor any OPO seed source (higher compactness and simplicity in wavelength control). It will increase EU competitiveness by faster integrated, less risky, more sensitive future space IPDA. SIROCO will develop nonlinear crystals to ensure an EU supply chain, which are key components for various applications (general laser physics, IPDA emitters, quantum applications). Their exploitation path towards future space LIDAR and quantum communications will be delivered through two public technical roadmaps. SIROCO is a 4-year 3MEuros valued action, gathering renown research & academic organisations and SMEs, and supported by an Advisory Board with experts from the European Space research, Atmosphere Science and Quantum communities.

In today's Europe, software is pivotal for societal progress, deeply ingrained in our lives, and essential for the EU's competitiveness. The European Commission's Digital Strategy positions software at the heart of digital transformation, targeting a sustainable economy and broad digital tech benefits. This era underlines software engineering's crucial role in creating functional, reliable, and efficient software systems. The advent of AI, especially in robotics, poses new challenges, demanding a rethink of traditional software engineering. The engineering of robotics faces ongoing issues such as complex operational states, environmental unpredictabilities, and critical safety needs. These are amplified by the diversity in robots, use cases, AI technologies, and development settings, calling for a significant evolution in robotics software engineering. The rise of intelligent robots, with their ability to learn, adapt, and make independent decisions, highlights the need for improved engineering tools and methods. ASTIR aims to address these challenges by developing an AI-augmented engineering workbench for intelligent robotics software, supporting all lifecycle phases from requirements engineering to system maintenance. This workbench, leveraging trustworthy generative AI, aims to integrate with current engineering practices, enhancing collaboration and productivity. ASTIR will validate the technological offering in 3 novel and open-access use cases targeting diverse robotics markets, namely service robotics, manufacturing robotics, and drones.