The project idea is focusing on AI-augmented automation supporting modeling, coding, testing, and monitoring as part of a continuous development in Cyber-Physical Systems (CPSs). The growing complexity of CPS poses several challenges throughout all software development and analysis phases, but also during their usage and maintenance. Many leading companies have started envisaging the automation of tomorrow to be brought about by Artificial Intelligence (AI) tech. While the number of companies that invest significant resources in software development is constantly increasing, the use of AI in the development and design techniques is still immature. The project targets the development of a model-based framework to support teams during the automated continuous development of CPSs by means of integrated AI-augmented solutions. The overall AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, along with software models and measurements. The infrastructure is intended to operate within the DevOps process combining software development and information technology (IT) operations. Moreover, AI technological innovations have to ensure that systems are designed responsibly and contribute to our trust in their behaviour (i.e., requiring both accountability and explainability). AIDOaRT aims to impact organizations where continuous deployment and operations management are standard operating procedures. DevOps teams may use the AIDOaRT framework to analyze event streams in real-time and historical data, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection.

The long-term goal of MX-MAP is to develop a functional pipeline for the immune characterization of new 2D nanomaterials of MXene family, for the qualitative and quantitative assessment of the human immune compatibility and immune activity towards biomedical applications. The immune characterization of the tested materials on the basis of intrinsic physical-chemical and immunological properties, through the combination of the most innovative technologies such as single-cell mass cytometry (CyTOF), will open breakthrough perspectives for the development of new therapeutic approaches applying nanomaterials as immunomodulators, scaffolds for tissue engineering, cancer therapy, and antibacterial agents. MX-MAP will develop key chemistry and immune-based strategies for MXene medical applications. The implication of this project extends beyond the specific nanoscience program greatly advancing the engineering process of 2D materials and their use in biomedicine. The MX-MAP project involves fourteen key players in European and non-European countries, including the United States, Canada, Saudi Arabia, and three partners from Ukraine, coming from academia and SMEs. This program will provide strong support for the development of the careers of young brilliant scientists who want to grow towards an interdisciplinary vision of Science. Chemistry, biology, immunology, engineering, and cancer research are the expertise of MX-MAP. The senior team members are among the most influential scientists, including Prof. Yury Gogotsi (H-index=168) - inventor of MXenes, Prof. Klaus Ley (H-index=147) - one of the most cited immunologists worldwide, and Prof. Husam N Alshareef (H-index=99). The Consortium is perfectly balanced in terms of equal gender presence; the project Coordinator Lucia Gemma Delogu is a female, and 2 out 4 of four WP leaders are female. The project embraces a large view of inclusiveness and diversity, including countries with smaller economies such as Ukraine.

As the ongoing robotic exploration to Mars has made some tantalising discoveries, the next major step should be retrieving samples from the Martian surface, so they can be investigated in detail in terrestrial laboratories. However, considering the huge costs associated to suh missions, an in-situ dating of rock samples is a more cost-effective approach. Accurate estimation of absolute ages is required in order to understand Mars surface and atmosphere evolutionary processes. Furthermore knowledge on occurrence and time frequency of such processes allow a hazard evaluation for locations/areas, essential for future deployments, missions and eventually humans on Mars. However, a chronology for recent events on Mars is problematic, as uncertainties associated with current methodology (crater counting) are comparable to the younger ages obtained (~ 1 Million years). IN-TIME project addresses the technological and economic viability of a leading-edge instrument for dating of Mars’ surface: a miniaturized Luminescence dating instrument for in-situ examination. Thanks to the development of its innovative technology, and in addition to planetary exploration application, it will also address Earth's field applications as a light and portable dating instrument in geology and archaeology as well as a risk assessment tool for accident and emergency dosimetry and nuclear mass-casualty events.

AI-TranspWood ambition is to create an AI-driven multiscale methodology for new Safe and Sustainable by Design (SSbD), and functional wood-based composites and demonstrate the concept for Transparent Wood (TW), a promising composite with potential applications in several industrial fields, such as construction, automotive, electronics and furniture. By developing AI supported SSbD framework for TW, we contribute to European Green Deal by providing innovative sustainable materials and cost-effective tools for European industries paving the way towards green and sustainable transition. SSbD tools used by the chemicals and materials community with new transparent wood materials, increases the innovation capacity of SMEs and industry for future sustainable products. With the help of AI-tools and advanced experiments we develop multiscale models from the atomistic scale to continuum for the manufacturing process and the mechanics of the transparent wood allowing for virtual screening of bio-sourced alternatives for hazardous and petrochemical-based chemicals required for manufacturing Transparent Wood using the current solutions. The built computational models are openly shared within the European environment for scientific software (EESSI). The user-friendly surrogate model is also made available in the VTT Modeling Factory environment, along with an LCA tool, for industrial use. Four TW business cases are conducted, with the aim to be commercialized in the construction, automotive, electronics and furniture industries. The SSbD framework will guide the whole creation of the TW products providing a competitive advantage to the European manufacturers interested in introducing the TW composites in the European market, also as substitutes of glass and plastic in various applications. This can considerably increase the European share in the global production of sustainable TW composites.