Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
970
result(s) for
"Brunet, P"
Sort by:
The crackling sound of Leidenfrost stars
Liquid drops deposited on a hot plate can experience a boiling crisis, when the vapour flux is strong enough to ensure the levitation of the drop and the relative insulation of the liquid from the solid. It is often denoted Leidenfrost effect, after the German Johann Gottlob Leidenfrost, who first reported it in 1756. While many studies have encompassed various applied issues associated with this phenomenon, aiming to control and prevent its appearance, Ma & Burton (J. Fluid Mech., vol. 846, 2018, pp. 263–291) focused on the spontaneous appearance of a standing wave at the free surface, together with temporal oscillations, making the drop adopt the shape of a star. Their far-reaching study presents exhaustive results using six different liquids with a range of different volumes and temperatures, in which they systematically extracted the drop dynamics together with the pressure fluctuations in the vapour cushion below.
Journal Article
On causal roles and selected effects: our genome is mostly junk
The idea that much of our genome is irrelevant to fitness—is not the product of positive natural selection at the organismal level—remains viable. Claims to the contrary, and specifically that the notion of “junk DNA” should be abandoned, are based on conflating meanings of the word “function”. Recent estimates suggest that perhaps 90% of our DNA, though biochemically active, does not contribute to fitness in any sequence-dependent way, and possibly in no way at all. Comparisons to vertebrates with much larger and smaller genomes (the lungfish and the pufferfish) strongly align with such a conclusion, as they have done for the last half-century.
Journal Article
On the influence of viscosity and caustics on acoustic streaming in sessile droplets: an experimental and a numerical study with a cost-effective method
When an acoustic wave travels in a lossy medium such as a liquid, it progressively transfers its pseudo-momentum to the fluid, which results in a steady flow called acoustic streaming. This phenomenon involves a balance between sound attenuation and shear, such that the streaming flow does not vanish in the limit of vanishing viscosity. Hence, the effect of viscosity has long been ignored in acoustic streaming experiments. Here, we investigate the acoustic streaming in sessile droplets exposed to surface acoustic waves. According to experimental data, the flow structure and velocity magnitude are both strongly influenced by the fluid viscosity. We compute the sound wave propagation and hydrodynamic flow motion using a numerical method that reduces memory requirements via a spatial filtering of the acoustic streaming momentum source terms. These calculations agree qualitatively well with experiments and reveal how the acoustic field in the droplet, which is dominated by a few caustics, controls the flow pattern. We evidence that chaotic acoustic fields in droplets are dominated by a few caustics. It appears that the caustics drive the flow, which allows for qualitative prediction of the flow structure. Finally, we apply our numerical method to a broader span of fluids and frequencies. We show that the canonical case of the acoustic streaming in a hemispherical sessile droplet resting on a lithium niobate substrate only depends on two dimensionless numbers related to the surface and bulk wave attenuation. Even in such a baseline configuration, we observe and characterize four distinct flow regimes.
Journal Article
What is Interpretability?
We argue that artificial networks are explainable and offer a novel theory of interpretability. Two sets of conceptual questions are prominent in theoretical engagements with artificial neural networks, especially in the context of medical artificial intelligence: (1) Are networks explainable, and if so, what does it mean to explain the output of a network? And (2) what does it mean for a network to be interpretable? We argue that accounts of “explanation” tailored specifically to neural networks have ineffectively reinvented the wheel. In response to (1), we show how four familiar accounts of explanation apply to neural networks as they would to any scientific phenomenon. We diagnose the confusion about explaining neural networks within the machine learning literature as an equivocation on “explainability,” “understandability” and “interpretability.” To remedy this, we distinguish between these notions, and answer (2) by offering a theory and typology of interpretation in machine learning. Interpretation is something one does to an explanation with the aim of producing another, more understandable, explanation. As with explanation, there are various concepts and methods involved in interpretation: Total or Partial, Global or Local, and Approximative or Isomorphic. Our account of “interpretability” is consistent with uses in the machine learning literature, in keeping with the philosophy of explanation and understanding, and pays special attention to medical artificial intelligence systems.
Journal Article
Blowing a liquid curtain
We study the response of a steady free-falling liquid curtain perturbed by focused air jets blowing perpendicularly against it. Asymmetric and symmetric perturbations are applied by using either a single pulsed jet or two identical steady jets facing each other. The response strongly depends on the curtain flow rate, and the location and strength of the perturbation. For pulsed asymmetric perturbations of increasing amplitude, sinuous wave, drop ejection, bubble ejection and hole opening are successively observed. For steady symmetric perturbations, a steady hole forms downstream in the wake. For this latter case, we present a model for the curtain thickness and the location of the hole in the wake in terms of the curtain flow rate and the size, flow rate and location of the jets. The adjustable-parameter-free expression we obtain compares favourably to the experiments provided that the perturbation is sufficiently small (jet stagnation pressure smaller than curtain stagnation pressure) and the liquid viscosity is negligible.
Journal Article
Categorial modal realism
The current conception of the plurality of worlds is founded on a set theoretic understanding of possibilia. This paper provides an alternative category theoretic conception and argues that it is at least as serviceable for our understanding of possibilia. In addition to or instead of the notion of possibilia conceived as possible objects or possible individuals, this alternative to set theoretic modal realism requires the notion of possible morphisms, conceived as possible changes, processes or transformations. To support this alternative conception of the plurality of worlds, I provide two examples where a category theoretic account can do work traditionally done by the set theoretic account: one on modal logic and another on paradoxes of size. I argue that the categorial account works at least as well as the set theoretic account, and moreover suggest that it has something to add in each case: it makes apparent avenues of inquiry that were obscured, if not invisible, on the set theoretic account. I conclude with a plea for epistemological humility about our acceptance of either a category-like or set-like realist ontology of modality.
Journal Article
Local causation
The counterfactual and regularity theories are universal accounts of causation. I argue that these should be generalized to produce local accounts of causation. A hallmark of universal accounts of causation is the assumption that apparent variation in causation between locations must be explained by differences in background causal conditions, by features of the causal-nexus or causing-complex. The local account of causation presented here rejects this assumption, allowing for genuine variation in causation to be explained by differences in location. I argue that local accounts of causation are plausible, and have pragmatic, empirical and theoretical advantages over universal accounts. I then report on the use of presheaves as models of local causation. The use of presheaves as models of local variation has precedents in algebraic geometry, category theory and physics; they are here used as models of local causal variation. The paper presents this idea as stemming from an approach using presheaves as models of local truth. Finally, I argue that a proper balance between universal and local causation can be assuaged by moving from presheaves to fully-fledged sheaf models.
Journal Article
AI4GEO: A DATA INTELLIGENCE PLATFORM FOR 3D GEOSPATIAL MAPPING
The availability of 3D Geospatial information is a key issue for many expanding sectors such as autonomous vehicles, business intelligence and urban planning. Its production is now possible thanks to the abundance of available data (Earth observation satellite constellations, insitu data, …) but manual interventions are still needed to guarantee a high level of quality, which prevents mass production. New artificial intelligence and big data technologies adapted to 3D imagery can help to remove these obstacles. The AI4GEO project aims at developing an automatic solution for producing 3D geospatial information and new added-value services. This paper will first introduce AI4GEO initiative, context and overall objectives. It will then present the current status of the project and in particular it will focus on the innovative platform put in place to handle big 3D datasets for analytics needs and it will present the first results of 3D semantic segmentations and associated perspectives.
Journal Article