Apis mellifera L. (HB) is the most influential pollinator in the world. HB colony decline worldwide has been associated to multiple stressors. The EFSA recently devised an integrated framework focused on developing a holistic approach to the risk assessments (RA) of multiple stressors on HB. It requests research data on the influence of genetic diversity on toxicological sensitivity at subspecies (SBP) level. HB is the model organism for RA studies, and there are at least 24 SBP described. Surprisingly, RA require no distinction among them. TOPRA-B will push the known boundaries of RA, by examining for the first time the genetic background of HB. Using 3 SBP and SNP markers, TOPRA-B will perform an innovative study connecting the genetic diversity in the cytochrome P450 to the pesticides and pathogens exposure in HBs. WP1 entails the application of bioinformatic tools on over 176 whole genome sequences owned by the host institution. WP2 will consists of designing the reduced assay from the list of SNPs generated in WP1. WP3 will consist of laboratory-based bioassays of exposure of bees to pesticides and pathogens, and by employing the link between genotypes to the phenotypic responses. The WPs will help solve four of the nine data gaps raised by the current RA, addressing the results for the EFSA’s policymakers. TOPRA-B brings a strong interdisciplinary, intersectoral and international framework. Since it will deal with the principal model organism of RA, the magnitude of this innovative technology and approach will be available worldwide with a high potential of being adopted for universal RA schemes. The importance of the results consists of the optimization of the current and future RA, and the efficiency in genotyping large sample sizes. TOPRA-B will be committed to the United Nations’ 2030 Agenda, lined with Sustainable Development Goals and European Green Deal.

The STEP project aims to enhance the scientific capacity and innovation of the consortium partners, with a principal focus on the Instituto Politécnico de Bragança (IPB, Portugal), and to raise its research profile in the field of Science, Technology, Engineering and Maths (STEM) throughout the cross-fertilisation with the Social Sciences and Humanities, in particular by introducing in the STEM domain the Equality, Diversity and Inclusion (EDI) principles, that have considerable potential in terms of solving the global challenges for wellbeing and the quality of life. The 4 internationally research-intensive leading partners in the project will accompany and guide IPB. Resources and competencies will be shared and advanced across strategic plans for improving and empowering the IPBs capacity-building focus areas. The activities targeting the researchers and administrative and managerial staff will strengthen the scientific excellence, innovation capacity (non-academia/academia collaboration), and skills for research communication and societal acceptance (social sciences and humanities, SSH involvement, in the STEM area). Activities for researchers will include mobility rounds, master classes, training, industry and SSH mentoring, attendance at conferences and workshops. This project will lead to an increased number of high-impact articles, research grants, EU projects, service contracts to the international and non-academic sectors (respectful of the EDI principles), new research topics and wide-scale impact. The Twinning Programme will gradually shift focus from research to innovation-driven implementation of the promising research outcomes. Altogether, the EU-funded STEP project will help the IPB become a regional actor for EDI/STEM innovation studies.

Increased introduction of digital technologies into manufacturing is leading to increased automation. Estimates indicate that the potential for automation in predictable physical work is at 33% followed by 22% in data collection and 11% in data processing. The increased globalisation in manufacturing also introduces requirements in terms of team work, intercultural and language capabilities, the need to deal with shorter production cycles, and changes in demographics requiring workers to stay active for longer. Europe faces considerable challenges in addressing future skills needs. From the perspective of the workforce the issues are increasingly complex where current training and educational solutions are discrete and lack interconnections and are largely dissociated from work activities. Growing gaps in knowledge and know-how make it increasingly challenging to adapt, work proactively and contribute to innovations. FIT4FoF aims at addressing a range of these issues by analysing current skills initiatives, better to understand how to address workers' needs, analysing technology trends across 6 industrial areas of robotics, additive manufacturing, mechatronics/machine automation, data analytics, cybersecurity and human machine interaction, to define new job profiles, which will inform education and training requirements. FIT4FoF will develop a new education and training framework, which places workers (women and men) at the centre of a co-design and development process that recognises and addresses their skills needs. By applying educational approaches based on Communities of Practice, FIT4FoF will empower workers to be drivers of the design, development and delivery of their own upskilling programmes. FIT4FoF will develop Alliances of Communities of Practice to broaden the approach across Europe, creating replication strategies enabling educational/training design and development practices to be transferred between regional communities across Europe.

Multi-stage manufacturing, which is typical in important industrial sectors such as automotive, house hold appliance and semiconductor manufacturing just to name few, is inherently complex. The main idea of GO0D MAN project is to integrate and combine process and quality control for a multi –stage manufacturing production into a distributed system architecture built on agent-based Cyber-Physical Systems (CPS) and smart inspection tools designed to support Zero-Defect Manufacturing (ZDM) strategies. Data analytics tools provide a mean for knowledge build-up, system control and ZDM management. Real time and early identification of deviations and trends, performed at local level, allow to prevent the generation of defects at single stage and their propagation to down-stream processes, enabling the global system to be predictive (early detection of process faults) and proactive (self-adaptation to different conditions). The GO0D MAN project is based on the results of previous successful EU projects and integrates them to realize and deploy a Zero Defect Manufacturing framework for multi-stage production lines, in collaboration with industry partners, a system integrator, two technology providers and three end users. The use cases are representative of key European industrial sectors and have different types of multi-stage production systems: the first use case concerns highly automated serial mass production of automotive components, the second use case is about batch production of high precision mechanical components for automotive electro valves, the third use case produces professional customized products such as ovens for restaurants. Successful completion of this project will provide a replicable system architecture for ZDM. The results will be broadly applicable in a variety of industries to improve the overall quality and productivity of production systems.