Taxonomy - the science of defining and naming groups of biological organisms based on shared characteristics - faced a significant crisis in the last decades and nowadays a rejuvenation of this discipline is required. For this reason, we recently proposed the integration in taxonomy of the most advanced genomics and bioinformatics techniques, taking into account also the holobiont concept (Serra et al., 2019): we named this approach Next Generation Taxonomy. NGTax will explore and expand this rationale establishing an international and inter-sectoral network of organisations across the EU, Africa, China and Russia. The consortium will work on a joint research programme in Next Generation Taxonomy of ciliates and their symbionts, constituting a holobiontic unit. The proposed approach is strongly multidisciplinary including classical morphological analyses, ultrastructure, molecular tools, genomics and bioinformatics. NGTax will pursue six central objectives: i) validate the NGTax approach on many holobiont systems from different ciliate Classes; ii) contribute rejuvenating taxonomic discipline to ensure traditional expertise is not lost but complemented with state of the art sequencing technologies; iii) consolidate and disseminate the NGTax approach to perform the characterization of eukaryotic organisms to let it become a “new reference standard”; iv) train staff members in NGTax, in order to outline novel scientific positions, boost their careers and import/export useful know-how across sectors, disciplines and countries; v) provide advanced training to male and female researches, including researchers from cultural and religious minorities, from developing countries in order to contribute to boost their academic careers and their integration in international collaborative research networks; vi) support European companies in performing know-how exchange with academic sector, developing new services, and creating new interaction with developing countries.

Large-scale simulations of lattice Quantum Chromodynamics (QCD) can provide crucial input for searches of new physics at the precision frontier, like in the calculation of the hadronic contribution to the anomalous magnetic moment of the muon. To find evidence of new physics beyond the current knowledge provided by the Standard Model will require to reach per-mille precision. Attaining such accuracy in the hadronic contribution to the anomalous magnetic moment of the muon in lattice QCD can only be achieved by controlling lattice systematics, such as logarithmic terms in the continuum extrapolation, finite volume effects and exponentially increasing noise at large time distances. Simulating gauge ensembles at lattice spacing a<0.04 fm is impossible with current algorithms due to topological freezing. Generative models based on gauge equivariant flows can unfreeze the charge but scale badly with the volume, limiting, up to now, their applicability to toy models. We propose a solution to overcome topological freezing and suppress exponential noise by developing scalable algorithms for lattice QCD simulations closer to the continuum limit and at physical quark masses based on domain decomposition. By combining machine-learned flow proposals with hierarchical accept/reject steps of the factorized fermion determinant, ensembles at very small lattice spacings can be generated using upcoming european exascale supercomputers. We will implement multi-level sampling techniques within a flexible framework to enable good performance of the here developed novel Markov Chain Monte Carlo algorithm on exascale systems. By the newly generated gauge ensembles lattice QCD will provide a leap in the precision frontier thereby critically contributing in the unraveling of new physics.

The new technology envisioned in CIRCULIGHT will establish a breakthrough in Photonic Integrated Circuit (PIC) capabilities, with impact across a wide range of applications of high economic and societal value. It will lay the foundations of a new class of PICs which are highly functional, miniaturized and low power-consuming, as well as being manufacturable at low cost, thereby contributing significantly to environmental protection and related quality of life. The essential building block that will be created in this project is a truly integrated optical circulator, which protects active and passive integrated functions from each other, distributes light between them, and finally allows very large scale integration of photonic components within diversified PIC architectures. The practical realization of such a structure will be a world-first and a breakthrough in PIC technology. CIRCULIGHT technological decisive progress is based on magneto-optical (MO) nanoparticle-composite sol-gel material and on magneto-biplasmonic (MBP) effect, which will enable the monolithic insertion of circulators on any photonic platform. Within the project, a demonstration will be made on two of them, based on InP and Si respectively, operating at 1.3 or 1.5 µm. While PIC foundries rely on specific and independent technologies, our solution will bypass these specificities, thanks to a universal integration of functional materials. In addition, our interdisciplinary approach is based on the analysis of real world needs, feeding the co-creation of an exploitation roadmap together with end users, industrial and societal stakeholders, in preparation for the scaling up of our technology developments to transform society for the better. To reach these objectives, our consortium of nine partners encompasses competencies in material sciences, photonics, plasmonics, PICs technology and social science, and includes two SMEs.

MISEL aims at bringing artificial intelligence to the edge computing (decisions made on-device) through a low-power bio-inspired vision system with multi-spectral sensing and in sensor spatio-temporal neuromorphic processing based on complex events. The science-to-technology breakthrough is the heterogeneous integration of a neuromorphic computing scheme featuring three different abstraction levels (cellular, cerebellar and cortex processors) with high-density memory arrays and adaptive photodetector technology for fast operation and energy efficiency. The context-aware, low power and distributed computation paradigm supported by MISEL is promising alternative to the current approach relying on massive-data transfers and large computational resources, e.g., workstations or cloud servers. This answers to the challenges and related scope presented in the Work Programme towards "more complex, brain mimicking low power systems" "exploiting a wider range of biological principles from the hardware level up" by introducing the human eye like adaptivity with cellular processor and the data fusion, learning, reasoning, and “conscious” decisions performed by the cortex. The stand-alone system fabricated in MISEL will be tested on timely and challenging applications such as distinguishing birds from drones through their spatio-temporal flying signature, and scene anomaly detection from a mobile platform. From the technology development and industrialization point of view, MISEL includes the whole value chain: materials research for back-end of line (BEOL) processing-compatible densely-packed ferroelectric non-volatile memories (FeRAMs) and intensity adaptive photodetectors, novel neuromorphic computing algorithms and circuit implementations, and system level benchmarking. This is all in line with the challenge and scope of "outperforming conventional SoA with relevant metric" and benchmarking "challenging end-to-end scenarios of use" for industrial adaptation.