In this feasibility study we will explore the market potential for software that applies Artificial Intelligence (AI)-driven prediction models to EEG data for patients in post-anoxic coma in the Intensive Care Unit (ICU). EEG is a powerful tool for outcome prediction in these patients, yet current visual analysis methods and full EEG interpretation are highly labor-intensive. By automating this process with AI, we seek to improve efficiency and accessibility of prognostic assessments. This study will assess the commercial feasibility and potential adoption of such software in clinical practice.

Neuromuscular disorders, which affect millions of people in Europe alone, lead to (progressive) muscle weakness or sensory deficits that gravely affect life expectancy and quality of life. To diagnose the disorders, needle electromyography (nEMG) data must be assessed audio-visually by experts, which is subjective and time-consuming. In this project, experts in clinical neurophysiology, data science and instrumentation will develop an artificial-intelligence platform to automatically, objectively and accurately interpret nEMG data. They will validate the method using real nEMG data from around the world, and take first steps towards integrating the platform into existing software for clinical use.

The global carbon cycle represents the collection of complex biogeochemical processes that influence our climate and link all carbon pools on Earth. Soils play a very active and key role in this cycle, as upon sequestration in marine sediments they act as long-term sink of atmospheric CO2. A large part of organic carbon (OC) stored in soils is continuously mobilized and either returned to the atmosphere or transported by rivers to the oceans. However, the fate and residence time of soil OC within in a river basin is often overlooked, and our understanding of potential feedback mechanisms to our climate remains far from complete. In this project I aim to determine the origin of soil OC in a river, the transformations that soil OC undergoes during its transport from land to sea, the duration of this transport, as well as to assess the factors that control these processes. For this I will utilize a suite of soil bacterial membrane lipids, branched glycerol dialkyl glycerol tetraethers (brGDGTs), as specific molecular tracers of soil OC. River-transported brGDGTs stored in continental margin sediments may reflect the integrated climate history of the river basin, as their initial distribution in soils is determined by temperature and soil pH. The novelty of my approach lies in the combination of these molecular tracers with an array of advanced isotopic techniques (13C, D/H, 14C) and inorganic chemistry (Neodymium isotopes). This allows me to monitor soil OC during its complete journey from terrestrial source to sedimentary sink. The new information resulting from this project will deepen our understanding of the role of soils in OC storage and export, and thus the carbon cycle, and will improve our interpretation of paleoclimate records based on down-core variations in brGDGTs preserved in marine sediments.

The immune system is a complex network of cells that works to maintain balance in the body, pretty much like an internal sensing organ. Its responses are shaped by environmental factors such as viruses and microplastics, which can influence chronic diseases like diabetes and cancer. Recent advances in single-cell technologies provide deeper insights into immune function, aiding personalized treatments like immunotherapy. Our consortium consists of academic experts that will work together to identify immune markers for chronic diseases, using new technologies and involving patient organizations, clinicians, and even an art gallery to make a broad scientific and societal impact.

Classical gravity can be formulated in terms of a theory, called Shape Dynamics (SD), of dynamic locally scale-invariant geometry. SD, discovered by myself and two other collaborators, can be proven to be equivalent to General Relativity (GR), despite having a different fundamental symmetry, because local foliation invariance is traded for local scale (or conformal) invariance. Broadly, the purpose of my proposed research is to try to understand the structure and implications, both classical and quantum, of SD. Towards this end, I have identified three distinct, but related, research directions. The first is an attempt to formulate SD, in the presence of a cosmological constant, in terms of conformally invariant connection variables. The hope is to generalize work done in 2+1 dimension to the physical case, which presents important new difficulties. Discovering such a formulation would: i) help to understand the mechanism behind the symmetry trading, and ii) allow for Loop Quantum Gravity-like methods of quantization to be utilized. The second direction would be to explore the effect of the unimodular condition (i.e., the condition that sets the local volume to a fixed density) on the quantization of SD. The unimodular condition is known not to modify the classical theory; but, because it excludes degenerate spacetime metrics that would otherwise be integrated over, the quantum theory could be very different. The last project is to understand the Hamiltonian of SD from knowledge only of conformal spatial geometry. Currently, the Hamiltonian is chosen uniquely to reproduce GR evolution. However, Machs principles suggest that physics should only depend upon scale-invariant information. Thus, we propose to search for a holographic definition of SD where Hamiltonian evolution is reproduced by the Renormalization Group flow in a Conformal Field Theory in one less dimension.