Flow-Based Network Analysis of the Caenorhabditis elegans Connectome

We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios

Wake Induced Long Range Repulsion of Aqueous Dunes.

Sand dunes rarely occur in isolation, but usually form vast dune fields. The large scale dynamics of these fields is hitherto poorly understood, not least due to the lack of longtime observations. Theoretical models usually abstract dunes in a field as self-propelled autonomous agents, exchanging mass, either remotely or as a consequence of collisions. In contrast to the spirit of these models, here we present experimental evidence that aqueous dunes interact over large distances without the necessity of exchanging mass. Interactions are mediated by turbulent structures forming in the wake of a dune, and lead to dune-dune repulsion, which can prevent collisions. We conjecture that a similar mechanism may be present in wind driven dunes, potentially explaining the observed robust stability of dune fields in different environments

Coarsening Dynamics of 2D Subaqueous Dunes

Abstract: Fluid flow over an initially flat granular bed leads to the formation of a surface‐wave instability. The sediment bed profile coarsens and increases in amplitude and wavelength as disturbances develop from ripples into dunes. We perform experiments and numerical simulations to quantify both the temporal evolution of bed properties and the relationship between the initial growth rate and the friction velocity u∗. Experimentally, we study underwater bedforms originating from a thin horizontal particle layer in a narrow and counter‐rotating annular flume. We investigate the role of flow speed, flow depth and initial bed thickness on dune evolution. Bedforms evolve from small, irregular disturbances on the bed surface to rapidly growing connected terraces (2D equivalent of transverse dunes) before splitting into discrete dunes. Throughout much of this process, growth is controlled by dune collisions which are observed to result in either coalescence or ejection (mass exchange). We quantify the coarsening process by tracking the temporal evolution of the bed amplitude and wavelength. Additionally, we perform Large Eddy Simulations (LES) of the fluid flow inside the flume to relate the experimental conditions to u∗. By combining the experimental observations with the LES results, we find that the initial dune growth rate scales approximately as u ∗ 5 ${u}_{\ast }^{5}$ . These results can motivate models of finite‐amplitude dune growth from thin sediment layers that are important in both natural and industrial settings

Flux-dependent graphs for metabolic networks

Cells adapt their metabolic fluxes in response to changes in the environment. We present a framework for the systematic construction of flux-based graphs derived from organism-wide metabolic networks. Our graphs encode the directionality of metabolic fluxes via edges that represent the flow of metabolites from source to target reactions. The methodology can be applied in the absence of a specific biological context by modelling fluxes probabilistically, or can be tailored to different environmental conditions by incorporating flux distributions computed through constraint-based approaches such as Flux Balance Analysis. We illustrate our approach on the central carbon metabolism of Escherichia coli and on a metabolic model of human hepatocytes. The flux-dependent graphs under various environmental conditions and genetic perturbations exhibit systemic changes in their topological and community structure, which capture the re-routing of metabolic fluxes and the varying importance of specific reactions and pathways. By integrating constraint-based models and tools from network science, our framework allows the study of context-specific metabolic responses at a system level beyond standard pathway descriptions

Dynamics of migrating sand dunes interacting with obstacles

Wind- and water-driven migrating sand dunes frequently interact with elevated natural and manmade topographical features. The dune-obstacle interaction can alter the migrating behaviour of the dune and, depending on the nature of the obstacle, it may generate various societal and technological risks. Here we study the problem of dune-obstacle interaction in a paradigmatic quasi-2D domain realised in a subaqueous laboratory experiment. Generically, dunes interact with obstacles either by ‘crossing’ over the obstacle or by being ‘trapped’. We describe how the selection of these two distinct dynamical behaviours depends on the size and shape of the obstacle, focusing in particular on the fluid flow in the immediate vicinity of the obstacle. Specifically, we perform a modal decomposition of the measured flow field and we discover that the outcome of the dune-obstacle interaction is closely related to the flow structure above the obstacle.KAB acknowledges the support of a sponsored PhD studentship from Schlumberger Cambridge Research. NMV is supported by a Royal Society University Research Fellowship URF/R1/191332