This project is an innovative opportunity to mend several gaps in the research capacity in Croatia in Archaeology, Genetics, and other ‘Sciences of the Past’ by twinning a consortium of Croatian researchers (CrEAMA Initiative) with archaeological scientists from the University of Cambridge (UCAM) and the University of Pisa (UP). The project exploits location-specific advantages that arise from two crucial facts. Firstly, there is large number of archaeological sites and remains in Croatia that are relatively understudied. Secondly there is a group of researchers (CrEAMA Initiative) whose research capacity, impact, and grant success at the European level has not realised full potential owing to a relative lack of resources, coordination, and strategic planning. This project will unlock this latent scientific potential by developing multi-inter-trans- disciplinary (MIT disciplinary) expertise. Our ultimate vision is to develop a research group capable of using an MIT disciplinary approach to Sciences of the Past; this will be a powerful force for innovation and will contribute to resolving contemporary issues. This vision will be realised through support from our partners: the UCAM and the UP. Both institutions display success in Archaeology, Genetics and other Sciences of the Past, and have proven track records in applying for and completing EU-funded research projects. The first goal is to establish and integrate the existing MIT disciplinary scientific research community in Croatia. The second goal is to upgrade and intensify scientific research of CrEAMA Initiative by utilising recent methodological achievements in genetics (NGS) and other biological disciplines (GMM). The third goal is to foster integration of the CrEAMA Initiative into ERA. Our last goal is to commercialise and integrate the CrEAMA Initiative research with the needs of society (local community) at the local (Korčula Island), regional (Dalmatia), national, European (web) and global (web) level.

NextAIRE is focused on boosting the interoperability, expanding expertise and providing a more balanced geographical and cross-sectoral circulation of European R&I talents in the field of air quality monitoring, actively involving environmental scientists, experts in hardware and Internet of Things (IoT) and machine learning engineers. The project is centred around a cross-sectoral and cross-country approach, with a strong focus on Widening countries. The training methodology, including 40 planned secondments and numerous collaboration activities, such as buddy systems, workshops, hackathons and ongoing assessment, is expected to drive sensor development and environment-related public health findings. The project is made up of 16 partners forming a highly interdisciplinary consortium with numerous SME-sized hardware producers. From a scientific perspective, air quality monitoring through low-cost sensorics and artificial intelligence is at the project's core. However, NextAIRE will use these topics to provide R&I talents hands-on experiences to increase their research, entrepreneurial and other transferable skills, strengthening the R&I human capital base and improving the excellence of the research carried out in Widening countries and beyond. NextAIRE will also generate outcomes that will positively impact the employability and sustainable career prospects for European R&I talents in the field of air quality monitoring, in both the academic and non-academic sectors alike. Results such as the NextAIRE Competency framework, mathematical and AI models and an e-learning platform featuring training materials on topics such as AI, data science and air pollution research, will help to achieve this goal.

Indoor air pollution, an emerging threat recognized by European society, is claiming millions of lives annually. In the heat of current COVID-19 pandemic, elevated exposure to indoor air pollutants due to increased time spent indoors further faces a significant increase in negative effect on both physical and mental health and well-being not only in Europe, but also worldwide. When it comes to indoor air quality itself, serious knowledge gaps remain in understanding complex nature of indoor-outdoor pollution relationships, pollution sources and exposure pathways, health effects of emerging pollutants, ventilation of indoor spaces on wide spatial and long temporal scales. This is mainly because air quality monitoring in European Union (EU) is primarily focused on outdoor air quality, which paradoxically is a result of regulatory target compliances, which is lacking for indoor environments. To increase the resilience of EU for emerging threats of indoor air pollution and to promote living and working in healthy environments, project EDIAQI aims at conducting characterization of sources and routes of exposure and dispersion of chemical, biological, and emerging indoor air pollution in multiple cities in EU. Quantification of the main properties of pollutants and processes that governs its fate in indoor environments will be investigated on two levels: a) the-state-of-the-art, small-scale, high-intensity scientific focus measurement campaigns; and b) long-term, large-scale monitoring of target indoor air pollutants. The chosen project strategy for developing, characterization, and deployment of cost-effective/user-friendly monitoring solutions, together with the-state-of-the-art scientific instrumentation will allow to create new knowledge on sources, routes of exposure, and body burdens of indoor multipollutant.

unCoVer is a functional network of research institutions collecting data derived from the provision of care to COVID-19 patients by health systems across Europe and internationally. These real-world data allow for studies into patient’s characteristics, risk factors, safety and effectiveness of treatments and potential strategies against COVID-19 in real settings, and complement findings from efficacy/safety clinical trials where vulnerable groups, and patients with comorbidities are often excluded. The network will facilitate access to otherwise scattered datasets, and build computational and analytical platforms to streamline studies on risk characterisation, and prediction modelling using standardised pooled data derived from real life practices. It will fill data gaps, unify current initiatives and create downstream exploitation opportunities for researchers and public health strategies to optimise COVID-19 strategies and minimise the impacts of future outbreaks