The interplay between viral infection, host response, development of (hyper)inflammation and cardiovascular injury in COVID-19 is currently poorly understood which makes it difficult to predict which patients remain with mild symptoms only and which patients rapidly develop multi organ failure. The solution offered by DIGIPREDICT is an Edge Artificial Intelligence (AI) based, high-tech personalized computational and physical Digital Twin vehicle representing patient-specific (patho)physiology, with embedded disease progression prediction capability, focusing on COVID-19 and beyond. DIGIPREDICT proposes the first of its kind Digital Twin, designed, developed and calibrated on i) patient measurements of various Digital Biomarkers and their interaction, ii) Organ-On-Chips (OoCs) as physical counterpart using patient blood for personalized screening and iii) integration of those physiological readouts using AI at Edge technologies. The final goal is to identify and validate patient-specific dynamic digital fingerprints of complex disease state and prediction of the progression as a basis for assistive tools for medical doctors and patients. Using and improving state-of-the-art OoCs and Digital Biomarkers (for physiology and biomarkers in interstitial fluid) we will measure detailed response to viral infection. By closely monitoring the response with wearable multi-modal Edge AI patches, we aim to predict in near real-time the progression of the disease, support early clinical decision and to propose patient-specific therapy using existing drugs. We will combine scientific and technical excellence in a highly multi- and inter-disciplinary project, bringing together medical, biological, electronical, computer, signal processing and social science communities around Europe to setup Digital Twin at Edge. We will enable an Edge-to-Cloud vision, significantly advancing current state of the art and setting up a new European community for researching and applying Digital Twins.

Irregular and unaccountable transactions, cyber threats, non-user-friendly inefficient or impractical banking processes, complex contracting procedures and cumbersome financial market and insurance infrastructures constitute obstacles to European open market development. CRITICAL-CHAINS delivers a novel triangular accountability model and integrated framework supporting accountable, effective, accessible, fast, secure and privacy-preserving financial contracts and transactions to protect against illicit tranasctions, illegal money trafficking and fraud on FinTech e-operations. This is an innovative cloud-based “X-as-a Service” solution stack including several layers: 1) Data integrity checking by involving financial institutions in the distributed Blockchain network; 2) Transaction and financial data flows analytrics, modelling and mining; 3) Threat Intelligence & Predictive Modelling for Inter-Banks and Internet Banking, insurnace and financial market infrastructures; 4) Multilateral Biometric-based and Role-based Authorisation & Authentication; 5) Hardware Security Module (HSM) enabled Cyber-Physical Security, embedded systems & IoT security for secure access using Security-Privacy-Contexts Semantic Modelling; 6) Secure and smart use of Blockchain based on keyless signature infrastructure and hybrid (a)symmetric cryptography utilising truly random key generation. CRITICAL-CHAINS is to be validated within 4 case studies aligned with 3 critical sectors: banking, financial market infrastructures and the insurance sector. This will evaluate system reliability, usability, user-acceptance, social, privacy, ethical, environmental and legal compliance by scrutiny of the geo-political and legal framework bridging the European economy with the rest of the world. The Consortium respresents a strong chemistry of relevant expertise and an inclusive set of stakeholders comprising end-users (customers), CERTS, the financial sector (Banks & CCPs) and the Insurance sector

The REMPOWER project embarks on a pioneering journey to harness the untapped potential of space-based solar power (SBSP) through innovative rectenna technology and sub-THz wireless energy transmission. However, SBSP also faces many challenges, such as high launch costs, technical difficulties, and potential safety and security issues. At its core, REMPOWER is driven by four pivotal technical objectives associated with the capture and rectification of a sub-THz high energy beam: 100 GHz Modular, Flexible and Lightweight Rectenna: REMPOWER will develop rectenna technologies capable of capturing energy at 100 GHz. These modular rectenna technologies will provide modularity, flexibility at panel level and will allow the reduction of the weight of the final solution. High Efficiency and high power rectification: REMPOWER’s advanced diode and rectifier modeling and design will allow tackling high rectification efficiency, and high power handling capability, despite the sub-THz constraint. This will yield high output DC power while limiting the cost related to the number of required non-linear devices. Nonlinear Rectifier and Rectenna Characterization: REMPOWER will introduce a novel approach by subjecting rectifiers to wideband signals, enabling a comprehensive analysis of amplitudes and phases across multiple intermodulation frequencies. This breakthrough will unveils intricate nonlinear behaviors for heightened efficiency. Scalable Rectenna Arrays for Large Surfaces: REMPOWER will focus on scalability to enable high-power transmission, to reduce design and manufacturing costs and to improve modularity and flexibility. The progress within REMPOWER transcends current technological boundaries, offering promise for sustainable in-space mobility solutions and renewable energy generation. By conquering the challenges of high-frequency energy capture, REMPOWER will reshape the future of space exploration, energy generation, and sustainability.

The fundamental goal of the ANDANTE project is to leverage innovative hardware platforms to build strong hardware / software platforms for artificial neural networks (ANN) and spiking neural networks (SNN) as a basis for future products in the Edge IoT domain, combining extreme power efficiency with robust neuromorphic computing capabilities and demonstrate them in key application areas. The main objective of ANDANTE is to build and expand the European eco-system around the definition, development, production and application of neuromorphic hardware through an efficient cross-fertilization between major European foundries, chip design, system houses, application companies and research partners, as presented by the European Leader Group (ELG). The project brings together world class expertise to bring the world class expertise and infrastructures of Imec, CEA and FhG together with semiconductor companies, fabless, system houses, SMEs and application experts to explore and demonstrate the capabilities provided by the developed technologies. In the project, several applications will be assessed in key domains where Europe is strong (automotive, digital farming, digital industry, mobility and digital life). The aim is to reinforce and maintain strong leadership in these areas by bringing industry in contact with future memory technologies at a low TRL level (MRAM, OXRAM, FeFET). These cross-disciplinary efforts will lead to development of innovative hardware / software deep learning solutions, based on high TRL level RRAM/PCM and FeFET, to enable future products which combine extreme power efficiency with robust cognitive computing capabilities. This new kind of computing technology, combining ANN and SNN capabilities, will open new perspectives, for instance, environmental monitoring, and wearable electronics.