BECOME will use UNESCO Biosphere Reserves (BRs) as model systems to understand how to manage synergies and trade-offs between conservation objectives and human development, through pluralistic and inclusive landscape-scale approaches to conservation. BECOME will take an interdisciplinary and transdisciplinary approach, combining diverse methodologies for evaluating effectiveness of BR management in supporting conservation and biocultural diversity. BECOME will harness existing data resources and infrastructure, including longitudinal governance and biodiversity data, to analyze BR effectiveness across temporal and spatial scales. The project will contribute to the implementation of global and national policy frameworks towards the conservation of biological diversity by generating actionable knowledge. The research design will specifically account for priority areas of the new post-2020 Global Biodiversity Framework of the Convention on Biological Diversity. BECOME is uniquely positioned to perform much-needed longitudinal research on BR effectiveness across different metrics. BECOME will go beyond evaluating BR effectiveness through actors' self-evaluations, to help reduce bias and develop common methods to facilitate both compliance monitoring and adaptive management learning outcomes. BECOME will use existing data infrastructure to analyze changing trends in over 100 BRs worldwide whose management approaches have been followed for over 10 years, to understand changes in effectiveness. We will then harness big-data approaches to understand changes in land-use and modeled biodiversity change. The long-term monitoring of ecological and social variables performed in BECOME will help provide rare longitudinal trends related to social-ecological change and effectiveness of BRs. We will investigate the effectiveness of the zonation system as a combined “land-sharing” and “land-sparing” approach, to understand how this system supports biodiversity conservation and sustainable use of landscape resources. In addition to longitudinal studies supported by governance and big-data infrastructure, we will use case studies to take a mixed-methods approach to evaluate management and context-dependent meanings and measures of BR success, both present and future. BECOME will explore the potential of combining intergenerational practice with participatory scenario planning, collaborating with BR stakeholders to explore desired futures in BRs which work for biodiversity and people. BECOME will work with stakeholders to capture and develop context-dependent but generalizable metrics which are adapted to BR objectives, facilitate the adaptive co-management learning feedback loop, and reflect synergies between conservation and development objectives. By evaluating both process and outcomes of BR implementation, BECOME will help to capture the complexity of social-ecological phenomena while encouraging learning through participatory transdisciplinary processes.

Atrial Fibrillation (AF) is the most common cardiac arrhythmia, with incidence increasing with age: 10% of the population >80 years is afflicted with it. As AF is progressive, over time it is harder to treat, which increases risk of stroke, dementia and heart failure. The most effective treatment is catheter ablation which selectively destroys tissue to create lesions blocking conduction; however, ablation follows generic patterns, without personalisation. AF often recurs after treatment, with >20% of patients requiring re-ablation after 2 years. We aim to develop a personalised medicine approach based on computer modelling, to plan AF ablation to prevent recurrence. We propose to use physiological digital twins of patient hearts, created from imaging (MRI/CT), and calibrated using machine learning to analyse and fit ECG and electrogram recordings acquired clinically, from implantable devices or wearables. Novel technology for real-time simulation of AF in humans will be developed and integrated in a clinically viable platform to support the easy flow, robust analysis and interpretation of information, to achieve a scalable translation to large cohorts, and, thus, to enable clinicians to speed up the translation of observations to diagnosis and therapy planning. Due to inherent uncertainty, multiple AF scenarios will be simulated to derive biomarkers for assessing risk of AF progression, and to determine ablation sets optimal for each individual prior to ablation. Intraoperatively, electroanatomic recordings will be used to determine which simulations correspond best to the patient, and to further optimise ablation sets. Platform development will be performed on large-scale retrospective clinical data, but will be equally applicable to prospective trials. Economic analysis will evaluate benefits arising from early preventative and longer-lasting treatment, reduced duration and procedural risks of interventions.

In woodwind instruments (flute, clarinet, etc), the different notes are played by opening/closing side-holes. The size and location of each hole can influence the sound characteristics of all the notes of the instrument (pitch, timbre, etc.). In order to play in tune and with a homogeneous timbre, the musician must adapt his/her control for each note (mouth pressure, lip configuration, etc.). If the changes between notes are too important, the musician may have difficulty playing a musical sequence. Modifying or designing a new instrument while ensuring sufficient playing comfort for the musician is therefore a challenge in itself. The main goal of “OWN-MUSIC” project is to give manufacturers the possibility to customize this note-to-note adaptation, by guiding them on the geometrical modifications to be made. This project will focus on instruments of the flute family (recorder and flute). More precisely, the first objective is to quantify the adaptation effort required between two notes and to establish models predicting this quantity from the geometry. This will be based on high-precision acoustic simulations and on the design of perceptual experiments with musicians and manufacturers. These models will be validated by using and refining adapted artificial mouths. Specially designed and manufactured instruments will be used to test the predictions of these models with these devices and musicians. A second objective is to develop a digital tool that can be used directly by manufacturers to provide them with a decision aid for modifying the geometry of an instrument. It will enable geometric modifications to be proposed to correct defects in existing instruments and to design instruments with customized control. This requires the establishment of a suitable optimisation problem including the definition of cost functions and the implementation of advanced numerical techniques. An online graphical interface will be developed with the craftsmen to enable them to use these features.

The study of minimal Cantor systems and zero entropy dynamical systems provided recently striking results. Topological full groups of minimal subshifts provide finitely generated groups with original properties: they are simple, amenable, may have intermediate growth for some zero entropy subshifts. Frantzikinakis-Host proved the Sarnak conjecture for the logarithmic average and zero entropy dynamical systems with at most countably many invariant measures. Adamczewski-Bugeaud constructed transcendantal numbers from zero entropy subshifts. Hence a deep understanding of zero entropy systems is of particular importance by itself and for other topics like number, group theory but also for applications to quasicristallography, computer science or statistical physics. Despite substantial efforts to understand zero entropy and although many families are well understood few general results have been obtained. We aim to unify parts of existing results and to go deeper into zero entropy.