STREP ambition is to empower the European textile (recycling) industry with a solution for sustainable processing of textile waste by developing and rolling out of a novel and systemic waste sorting solution based on cost-efficient sensor and automation technology, self-learning AI, as well as a novel solution for textile disintegration and mechanical recycling. Furthermore, STREP develops chemical recycling solutions, to facilitate the production of a 100% closed loop recycled yarn based exclusively on post-consumer textile waste, creating a perfect balance between sustainability, cost, and quality. The overall ambition is enhancing European industrial sustainability, competitiveness, and resource independence through producing more sustainable products, while increasing consumer benefits. STREP integrates value chain, product quality, and environmental impact perspectives in its different phases. Two of the innovations are placed in the pre-consumer phases. One of these relates to developing and testing guidelines and matrix that can support product design phase, and implementing recycling-friendly assembly of textile products. The other one innovates the traceability of the products and the related waste to enable allocating different product (waste) streams to the right flows and processing alternatives. The rest of the innovations are positioned after the textile waste collection and include: technology for recognition and removal of hardware and prints as well as characterizing the waste (fiber length, humidity, dirt, etc.), developing innovative recycling methods based on solvolysis, enzymatic processing, pyrolysis and hydrothermal conversion to treat the appropriate textile waste fractions depending on the composition and the length of the fibers. Targeted products are new fibers out of mechanical and chemical recycling processes as well as (bio-crude) oils and biochar out of the textile fibers that cannot be used in new fibers.

The HEATWISE project aims to tackle various thermal management challenges in tertiary buildings with a significant IT load. The project has specific objectives to develop and validate (to TRL 4 and 5) its technological innovation in two interrelated aspects: for IT system equipment in facility rooms and for a complete building management level. The innovation toward achieving energy efficiency and thermal management optimization follows up on a detailed thermal need analysis framework and theoretical validation, and is fulfilled through four novel solutions: i) Hybrid future-proof cooling hardware solution for high-density data processing based on two-phase dielectric liquid cooling and air immersion ii) Digital twin-supported holistic high-density data processing management system with a smart workload orchestration system, iii) Integrated multi-objective building energy management system covering both IT equipment needs and human presence, and iv) Self-assessment tool for energy management needs in tertiary buildings with power-intensive IT systems. On top of that, the project will develop a knowledge-sharing platform to showcase potential improvement pathways in energy optimization of tertiary buildings and maximize the project's impact. The project consortium consists of 12 partners from 8 different countries across the EU and with a more global inclusion; including 3 universities, 3 research centers, 4 SMEs, 1 large company, and 1 national standardization body, making sure that all the required expertise for a successful accomplishment of the project and future exploitation exist, and the partners complement each other in the most optimal manner. The technologies will be demonstrated in different specific designs and integrations in a university, a supercomputing research centre, industrial and office buildings, in Denmark, Poland, Turkey, and Switzerland, with extended investigations for medical centres and hotels as impactful tertiary building categories.

OBAMA-NEXT aims to develop a toolbox for generating accurate, precise and relevant information characterising marine ecosystems and their biodiversity. This will be achieved by integrating new/emerging technologies, including remote sensing, eDNA, optical instruments and citizen science, with existing marine monitoring techniques for improving our capacity to describe ecosystem function and biodiversity with higher spatial and temporal resolution. The project will contribute to shaping next generation monitoring programs and defining Essential Ocean/Biodiversity Variables (EOVs/EBVs). Stakeholders will be involved from the onset of the project to identify products needed in an iterative co-creating and specification process. These specifications will guide the application of algorithms, including advanced statistical analyses and artificial intelligence, which combine and translate different data sources into information products (i.e., maps and indicators) to fulfil stakeholders’ needs. Routines for visualisation and methods for uncertainty assessment are also important components of the toolbox development. The toolbox will be evaluated and improved based on 12 selected Learning Sites (LS), representing diverse ecosystems and data sources within the four European regional seas. The applicability of the information products, compiled with the toolbox on LS data, will be evaluated as input to models for predicting biodiversity and as support for environmental and biodiversity policies. The project will also assess the usefulness of the products with respect to the EU objective of designating an ecologically coherent MPA network and the applicability of C-burial rates in angiosperm habitats for carbon offsetting and Nationally Determined Contributions. OBAMA-NEXT will strengthen Europe’s capability in acquiring and utilising biological ocean observations for better management of marine resources through strong public outreach and active stakeholder communication.

The EU Mission ‘Restore our Ocean and Waters’ (Mission Ocean) aims at protecting and restoring the health of our ocean and waters through research and innovation, citizen engagement, and blue investments by 2030. The creation of the European Digital Twin Ocean (EU DTO) supports this mission as well as the key initiative of the European Commission, Destination Earth (DestinE), aiming at developing a highly accurate digital model of the Earth on a global scale to be able to monitor, simulate, and predict the interaction between natural phenomena and human activities. Addressing the Horizon Europe call HORIZON-MISS-2023-OCEAN-01-8, SEADITO focuses on the need for a targeted set of analytical methods and tools to support the development of the EU DTO including integrating social-ecological models in order to establish a comprehensive decision support platform. SEADITO aims at increasing transdisciplinary abilities of social-ecological models by updating and integrating them for improved Ecosystem-based Management, and a set of case studies in the Baltic Sea, the North Sea and the Mediterranean as well a Pan-European case study will provide the contexts for the multi-actor processes identifying user needs, as well as co-designing and testing components and services in the targeted user communities. The results will include sets of interoperable, spatial explicit, and DTO compliant social-ecological decision-support components based on FAIR principles (e.g. to be integrated with EDITO-Model Lab), as well as scalable and multi-level social-ecological models, integrated quantitative and qualitative social-ecological indicators, and workflows quantifying and integrating cultural and behavioural aspects. The components will be tested through an interactive spatial platform, the SEADITO Explorer equipped with visual demonstrators of social-ecological models and a Scenario Toolkit (WIST). Learning materials will target young researchers, decision-makers, and the public.

The ARISTOTELES project aims to build a multinational harmonized data platform to develop and implement novel artificial intelligence (AI) approaches for management of complex diseases, where progression and manifestations of comorbidities are via multiple interacting pathways. We aim to apply our novel approach to a population of great need due to atrial fibrillation (AF), but our outputs can be extended to other complex diseases with multimorbidity. By integrating AIs into clinical practice, our platform will form a backbone for acceptable, responsible, and respectful uses of patient/participant data to develop and validate novel trustworthy AI tools for more personalized risk assessment and management. This represents a paradigm shift in AF treatment, moving from a focus on individual risk factors and selected outcomes (eg. stroke) to a holistic approach, underpinning timely diagnostic and therapeutic interventions to reduce disease progression, disability, hospitalizations and mortality, as well as improve patient adherence to lifestyle modifications, medications, and other treatment regimens. ARISTOTELES will be delivered through 8 inter-linking work-packages (WPs): WP1 is study management/coordination. WP2 provides the ethical/legal requirements for the development of a trustworthy AI. WP3 addresses stakeholder understanding of AI, needs assessment, and engagement in all the phases of the AI development. In WP4, granular data on genotype and phenotype characteristics, are harmonized from different datasets into a common platform. In WP5, AI algorithms/tools are developed and connected to an interactive output interface for patients and clinicians. In WP6, we test the AI tool developed in WP5 in a clinical trial simulation (in silico trial). In WP7 a multicenter randomized trial runs across multiple countries including both primary care and secondary care. WP7 and WP8 drive the clinical implementation and dissemination of results.