The BioDiMoBot project will deliver a system for autonomous, long-term robotic assessments of aquatic biodiversity and ecology. This project will develop an innovative measurement system to monitor biodiversity and provide insight into the drivers of ecosystem degradation. Additionally, it will assess organismic and environmental stress levels by using novel biohybrid sensors. With the BioDiMoBots' ability to perform autonomous and automated multimodal long-term data collection, the project will create a user-friendly robotic tool that provides detailed insights into the ecological health of aquatic environments. The project will be driven by the needs of potential stakeholders such as researchers, small and medium-sized enterprises (SMEs) in water-related industries and policy makers. Field operations will demonstrate the transformative power of the BioDiMoBot systems by monitoring aquatic ecosystems over a long period of time. The collected data will be highly accessible to enable interdisciplinary collaboration between scientists, society and policy makers. We will respond to the need to disseminate the new methodology to a wide audienThe proposed "BioDiMoBot" project aims to enhance Biohybrid sensors focusing on biodiversity measurement. Key goals include tailoring sensors for comprehensive water column investigation, ensuring long-term autonomy, establishing efficient data transfer, and integrating classical aquatic and biohybrid sensors for ecosystem evaluation. The robotic system comprises a "surface unit" with solar cells for energy and communication, a "ground unit" for microbial activity investigation, ropes connecting these elements, and "rope-climbing modules" with additional sensors for sampling. This integrated system offers a precise and adaptable solution for biodiversity monitoring. Emphasis will be placed on advancing the concept of "biohybrid robots" through market analysis, stakeholder engagement, and company founding.

The main goal of TraDE-Opt is the education of 15 experts in optimization for data science, with a solid multidisciplinary background, able to advance the state-of-the-art. This field is fast-developing and its reach on our life is growing both in pervasiveness and impact. The central task in data science is to extract meaningful information from huge amounts of collected observations. Optimization appears as the cornerstone of most of the theoretical and algorithmic methods employed in this area. Indeed, recent results in optimization, but also in related areas such as functional analysis, machine learning, statistics, linear algebra, signal processing, systems and control theory, graph theory, data mining, etc. already provide powerful tools for exploring the mathematical properties of the proposed models and devising effective algorithms. Despite these advances, the nature of the data to be analyzed, that are “big”, heterogeneous, uncertain, or partially observed, still poses challenges and opportunities to modern optimization. The key aspect of the TraDE-Opt research is the exploitation of structure, in the data, in the model, or in the computational platform, to derive new and more efficient algorithms with guarantees on their computational performance, based on decomposition and incremental/stochastic strategies, allowing parallel and distributed implementations. Advances in these directions will determine impressive scalability benefits to the class of the considered optimization methods, that will allow the solution of real world problems. To achieve this goal, we will offer an innovative training program, giving a solid technical background combined with employability skills: management, fund raising, communication, and career planning skills. Integrated training of the fellows takes place at the host institute and by secondments, workshops, and schools. As a result, TraDE-Opt fellows will be prepared for outstanding careers in academia or industry.

BeeGuards aims to strengthen the resilience of the European beekeeping sector by providing sustainable management practices, novel breeding strategies and digital and forecasting tools that allow the sector to adapt to a changing environment. We focus on determining how abiotic factors such as management practices, climate change, nutrition and resource limitations drive emerging biotic stressors that threaten colony health and erode the resilience of European beekeeping. BeeGuards comprises multiple actors and adopts a multi-actor approach from inception which has led to an open and inclusive design of the work programme. As a community, we will perform European-wide field studies evaluating and validating innovative threshold-based management and breeding strategies for resilience, using hives equipped with technological measurement tools. Complementary detailed immunological, behavioural, microbiological, pathological, ecological investigations will elucidate the ways in which management and climate act on honey bees and other pollinators. In this way, BeeGuards will, for the first time, provide a truly holistic view of the mechanisms determining beekeeping resilience and implement nature-based, local solutions for adaption, including model-based advisory tools for stakeholders. Our open and participatory actions include development of a WikiBEEdia community website where we will share and promote the BeeGuards concepts and results, including a Quest for sustainable beekeeping practices. Ultimately, BeeGuards will show the way for a change of perspective that is needed to achieve resilient beekeeping. BeeGuards will mitigate the environmental impact of beekeeping in terms of impact on wild pollinators and of carbon footprint, protect pollinator biodiversity, ensure the future provision of pollination services and support the economic development and inclusiveness of beekeeping, preparing the European apicultural sector to meet the climate challenge.