Over the last decade, digital innovations have transformed a fundamental aspect of our societies: money. These innovations have brought new actors to the realm of issuing currencies, leading to what some have defined as the end of an era in which money was defined by the state. DIGIMONEY will study two of these developments. On one hand, cryptocurrencies. Thanks to blockchain technology, these would allow a decentralized and state-independent access to money. On the other hand, central bank digital currencies (CBDCs). These would serve to reaffirm state regulatory power in the face of private and anti-state monetary initiatives. In short, while CBDCs seek to uphold the nation-state political structures, cryptocurrencies aim to transcend them. Through an anthropological approach, DIGIMONEY main objective is to study the critical role of digital money in shaping both established and emerging forms of political collectivities. Instead of treating money as a purely market catalyst (as orthodox economic theory often does), project’s originality lies in its analysis of money as a battleground where diverse political collectivities attempt to reaffirm their power and trace the boundaries of their presence and sovereignty. To achieve this, DIGIMONEY research will be developed in two countries that constitute paradigmatic cases in relation to each digital currency: Mexico (where the state is on the verge of launching its CBDC) and Venezuela (the third country in the world with the highest volume of cryptocurrencies transactions). By integrating an outstanding international research environment and developing an adapted training program, the candidate will qualify as a leading researcher in a new and promising field of research at the crossroads of anthropology of money and political economy of money. Furthermore, he will acquire new writing, communicative, and management skills that will allow him to reach a position of professional excellence and independence.

Loiasis, an infectious disease caused by the parasitic worm Loa loa, affects more than 15 million individuals in central Africa, and more than 100 million people are potentially exposed to infection. Since its first description in 1770, the international scientific community has considered this filarial disease as benign. I recently demonstrated that loiasis significantly reduces the life expectancy of infected people. I aim to definitively shift the prevailing paradigm of “benign loiasis” by showing that it can induce severe complications in various organs. I will conduct the first population-wide evaluation of morbidity in rural areas of Central Africa by performing systematic examinations on 4,900 selected individuals. This sample size will enable accurate estimation of prevalences of cardiovascular and renal diseases and of functional asplenia. Our results may lead to the recognition of loiasis as a significant public health problem. Such recognition could motivate integration of loiasis into the WHO’s list of Neglected Tropical Diseases. In addition, should loiasis be found to induce a functional asplenia, combating this disease could have a huge impact on the incidence and severity of other severe and common infections favoured by asplenia, such as malaria and pneumonia. Incidentally, specific recommendations regarding pneumococcal vaccination in loiasis-endemic areas could be made. Another possible consequence of our findings is changes in the management of people identified as having high levels of Loa loa infection during routine surveys or onchocerciasis elimination activities. Presently, these people are excluded from ivermectin treatment (because of the risk of post-treatment encephalopathy), and little is done to lower their level of infection. Confirmation that loiasis can cause serious complications would motivate an ethical obligation to develop strategies to manage these cases in order to lower their burden of the disease.

Earthquakes caused nearly one million fatalities in the last two decades. The hazardous nature of earthquakes is largely due to their unpredictability. The question of whether this unpredictability is ontological (i.e. earthquakes are a chaotic phenomenon that physics cannot predict) or a consequence of our incapacity to model them is still open. In the first case, one may never hope to predict earthquakes and efforts should be focused towards developing early-warning approaches so that the population can prepare for imminent shaking and tsunami. In the second case, earthquake prediction becomes theoretically achievable. In both cases, Artificial Intelligence (AI) may lead to giant steps in anticipating destructive events. I propose here to use AI to identify weak early seismic signals to both speed up early-warning and explore the possibility of earthquake prediction. The first part of the project will be devoted to implementing an early-warning approach not based on P-waves as all current systems but on an earlier signal recently identified. This signal is due to the perturbation of the gravity field generated by an earthquake – which propagates at the speed of light – but is ~6 orders of magnitude smaller than seismic waves, strongly limiting its detection with standard techniques. AI has proven very efficient at detecting low-amplitude signals. I will implement an AI algorithm to systematically detect gravity perturbations generated by magnitude > 7 earthquakes and rapidly estimate from them the location and magnitude of the earthquake. Though the existence of earthquake precursors (i.e. signals preceding the origin of earthquakes themselves) is hypothetical, AI represents a new prowerful mean to discover them. In the second part of the project, I will adapt the AI algorithm developed in the first part to search for earthquake precursors.

Phenotypes are largely determined by genetic factors. However, a given genotype can give rise to very distinct phenotypes, as exemplified by the diversity of cell types in multicellular organisms. This phenotypic plasticity results from epigenetic changes; that is, reversible modifications to the DNA molecule and its associated proteins that modulate gene expression patterns. Epigenetic changes are critical to the establishment of developmental programs, but also to adjust transcription in response to the environment. The latter is particularly important for plant adaptation: owing to a sessile (immobile) lifestyle, plants cannot run away from adversity, and thus adapt to their environment by tuning gene expression in response to changing conditions. Most epigenetic information is erased from one generation to the next, so that new organisms start their life cycle with a “fresh” potential. However, there are instances in nature of heritable epigenetic marks that can be transmitted to the next generation. Thus, owing to their role in shaping gene expression, and the potential for heritable changes, epigenetic factors are of great interest for plant breeders, in their quest for adaptable, high yielding phenotypes. Most of our current understanding of epigenetic processes in plants has been developed in Arabidopsis, a key model system. However, the Arabidopsis epigenome is rather idiosyncratic, and this knowledge might translate poorly to crops. Here, we will use an interdisciplinary approach combining original genetic materials and bioinformatics to analyze epigenetic regulatory pathways in maize, with a focus on reproductive development. Maize is an important model plant, with a large and dynamic epigenome much more typical of crops. It is also a crop of great economic importance. Better understanding the epigenome of maize will open the door to the manipulation of key agronomic traits, including reproductive development, which is under strong epigenetic influence.