TThe 6GTandem project will demonstrate ultra-high-capacity coverage, off-load of lower frequency bands and new services such as sub-cm resolution sensing and positioning in high traffic areas by adding sub-THz carriers to lower frequency bands in a seamless, tightly coordinated fashion. The two frequency bands will form a network collaborating and supporting each other in a “tandem” configuration enabling an introduction of high capacity, energy efficient, sub-THz enabled services, while mitigating known drawbacks of the sub-THz frequency bands such as susceptibility to line-of-sight blockage, coverage, and cost. Deployment will be addressed through the introduction of a thin and light dielectric waveguide to distribute a sub-THz RF signal through a daisy chain of integrated low-power antenna units, referred to as a “radio stripe”. We will demonstrate the use of lower, sub-10 GHz frequency bands to support the sub-THz band with resilience and coverage and the implementation of a distributed MIMO system to extend the coverage of the sub-THz band as well as offering capacities in the order of Tbps system throughput. We will demonstrate the possibility to implement local fronthaul solutions for added sub-10GHz access points using the high bandwidth of sub-THz radio stripes. Key elements for 6GTandem: - A system defining an ‘aligned tandem’ dual-frequency distributed MIMO architecture - Medium-aware waveforms, transmission schemes and communication strategies for energy-efficient operation and development of cross-layer solutions to offer required service levels on the novel dual-frequency infrastructure - Novel, “radio stripe” hardware including transceivers at 130GHz-175GHz, packaging, integration, and plastic waveguide for a low-cost, easy-deployable sub-THz infrastructure - Conception of a combined low-frequency and sub-THz distributed MIMO system supporting joint high-resolution sensing, high-accuracy positioning, and high-resilience and reliability communication.

The design and realization of age-friendly living and working environments is a huge challenge that we have just only started to address as the number of older citizens who are and want to continue being active members of society and live independently is constantly increasing. SmartWork builds a worker-centric AI system for work ability sustainability, integrating unobtrusive sensing and modelling of the worker state with a suite of novel services for context and worker-aware adaptive work support. The unobtrusive and pervasive monitoring of health, behaviour, cognitive and emotional status of the worker enables the functional and cognitive decline risk assessment. The holistic approach for work ability modelling captures the attitudes and abilities of the ageing worker and enables decision support for personalized interventions for maintenance/improvement of the work ability. The evolving work requirements are translated into required abilities and capabilities, and the adaptive work environment supports the older office worker with optimized services for on-the-fly work flexibility coordination, seamless transfer of the work environment between different devices and different environments (home, office, on the move), and on-demand personalized training. The SmartWork services and modules also empower the employer with AI decision support tools for efficient task completion and work team optimization through flexible work practices. Optimization of team formation, driven by the semantic modelling of the work tasks, along with training needs prioritization at team level to identify unmet needs, allow employers to optimize tasks (e.g. needed resources), shifting focus on increased job satisfaction for increased productivity. Formal and informal carers are able to continuously monitor the overall health status and risks of the people they care for, thus providing full support to the older office worker for sustainable, active and healthy ageing.

Reducing lead times of new medicinal drugs to the market by reducing process development and clinical testing timeframes is a critical driver in increasing European (bio)pharmaceutical industry competitiveness. Despite new therapeutic principles (e.g. the use of pluripotent stem cells, regenerative medicine and treatments based on personalised medicine or biosimilars) or regulatory initiatives to enable more efficient production, such as Quality by design (QbD) with associated Process Analytical Technology (PAT) tools , the slow progress in the development of new bioactive compounds still limits the availability of cheap and effective medicines. In addition, the competitiveness of European (bio)pharma industry is impacted by the unavailability of suitably trained personnel. Fundamental changes in the education of scientists have to be realised to address the need for changes in the traditional ‘big pharma’ business model and the focus on ‘translational medicine – more early stage clinical trials with patients, more external innovation and more collaboration’ . These changes in education should be based on combining cutting-edge science from the early stage of product development through to manufacturing with innovation and entrepreneurship as an integral part of the training. The Rapid Bioprocess Development ITN, employing 15 ESRs, brings together industrialist and academic experts with its main aim to address this critical need by developing an effective training framework in rapid development of novel bioactive molecules from the very early stages of potency and efficacy testing to the biomanufacturing process characterisation and effective monitoring. The main focus of the research is on oncology related proteins and recombinant proteins to be used in diabetes treatment, although the resulting monitoring and modelling methods will be applicable to other bioactive molecule process development as demonstrated by validation on a range of relevant bioactives.

Alcohol addiction ranks among the primary global causes of preventable death and disabilities in human population, but treatment options are very limited. Rational strategies for design and development of novel, evidence based therapies for alcohol addiction are still missing. Within this project, we will utilize a translational approach based on clinical studies and animal experiments to fill this gap. We will provide a novel discovery strategy based on systems biology concepts that uses mathematical and network theoretical models to identify brain sites and functional networks that can be targeted specifically by therapeutic interventions. To build predictive models of the ‘relapse-prone’ state of brain networks we will use magnetic resonance imaging and neurochemical data from patients and laboratory animals. The mathematical models will be rigorously tested through experimental procedures aimed to guide network dynamics towards increased resilience. We expect to identify hubs that promote ‘relapse-proneness’ and to predict how aberrant network states could be normalized. Proof of concept experiments in animal will need to demonstrate this possibility by showing directed remodeling of functional brain networks by targeted interventions prescribed by the theoretical framework. Thus, our translational goal will be achieved by a theoretical and experimental framework for making predictions based on fMRI and mathematical modeling, which is verified in animals, and which can be transferred to humans. To achieve this goal we have assembled an interdisciplinary consortium (eight European countries) of world-class expertise in all complementary skills required for the project. If successful this project will positively impact on the development of new therapies for a disorder with largely unmet clinical needs, and thus help to address a serious and widespread health problem in our societies.