Wall slip of complex fluids: interfacial friction or slip length?

Using a dynamic Surface Force Apparatus, we demonstrate that the notion of slip length used to describe the boundary flow of simple liquids, is not appropriate for viscoelastic liquids. Rather, the appropriate description lies in the original Navier's partial slip boundary condition, formulated in terms of an interfacial friction coefficient. We establish an exact analytical expression to extract the interfacial friction coefficient from oscillatory drainage forces between a sphere and a plane, suitable for dynamic SFA or Atomic Force Microscopy non-contact measurements. We use this model to investigate the boundary friction of viscoelastic polymer solutions over 5 decades of film thicknesses and one decade in frequency. The proper use of the original Navier's condition describes accurately the complex hydrodynamic force up to scales of tens of micrometers, with a simple "Newtonian-like" friction coefficient, not frequency dependent, and reflecting closely the dynamics of an interfacial depletion layer at the solution/solid interface.Comment: 7 pages, 5 figure

Sulphur and Carbon Isotopes as Tracers of Past Sub-seafloor Microbial Activity

Microbial life below the seafloor has changed over geological time, but these changes are often not obvious, as they are not recorded in the sediment. Sulphur (S) isotope values in pyrite extracted from a Plio- to Holocene sequence of the Peru Margin (Ocean Drilling Program, ODP, Site 1229) show a down-core pattern that correlates with the pattern of carbon (C) isotopes in diagenetic dolomite. Early formation of the pyrite is indicated by the mineralogical composition of iron, showing a high degree of pyritization throughout the sedimentary sequence. Hence, the S-record could not have been substantially overprinted by later pyrite formation. The S- and C-isotope profiles show, thus, evidence for two episodes of enhanced microbial methane production with a very shallow sulphate-methane transition zone. The events of high activity are correlated with zones of elevated organic C content in the stratigraphic sequence. Our results demonstrate how isotopic signatures preserved in diagenetic mineral phases provide information on changes of past biogeochemical activity in a dynamic sub-seafloor biosphere

Mechanical behaviour of iron oxide scale: Experimental and numerical study

2nd International Conference on Tribology in Manufacturing Processes (ICTMP2004), Nyborg, Denmark, June 15-18, 2004International audienceThe paper addresses the identification of constitutive parameters of thick, brittle layers on metal substrates. Application is to the iron oxide behaviour during hot rolling processes of steel, where oxide scale breaking and embedding is one of the major causes of surface defects. Contact management of a FEM software has been adapted in order to address the transitions corresponding to transverse oxide fracture, along with two other mechanisms, namely delamination and interfacial stick/slip. It is applied to the hot strip rolling process to show pre-bite cracking and its consequences ("micro-extrusion" of the metal). To approximate the stress state prevailing at roll bite entry, the Four-Point Hot Bending Test (4PHBT) has been selected for the measurement of oxide properties. Oxidation is made in situ in the test rig under conditions similar to a hot strip mill (HSM) environment. Comparison of load-deflection curves for oxidized and non-oxidized samples allows the mechanical properties of the oxide to be determined. Above a critical temperature T-c - around 700 degrees C, but depending on strain rate - the oxide is ductile (with a very narrow plastic strain range, epsilon(p) < 10(-2)) and elastic-viscoplastic (EVP) constitutive parameters are identified numerically. Below T-c, brittleness is manifested by an array of transverse, through-thickness cracks. Acoustic emission (AE) has been used to help detect the onset of fracture, while numerical simulation gives the critical fracture stress at the corresponding point of the load-deflection curve. Results for four low carbon steel grades are compared

Nanorhéomètre pour l’étude des liquides confiné

International audienceNanorhéomètre pour la mesure des propriétés mécaniques sans contac

Photometric redshifts and quasar probabilities from a single, data-driven generative model

We describe a technique for simultaneously classifying and estimating the redshift of quasars. It can separate quasars from stars in arbitrary redshift ranges, estimate full posterior distribution functions for the redshift, and naturally incorporate flux uncertainties, missing data, and multi-wavelength photometry. We build models of quasars in flux-redshift space by applying the extreme deconvolution technique to estimate the underlying density. By integrating this density over redshift one can obtain quasar flux-densities in different redshift ranges. This approach allows for efficient, consistent, and fast classification and photometric redshift estimation. This is achieved by combining the speed obtained by choosing simple analytical forms as the basis of our density model with the flexibility of non-parametric models through the use of many simple components with many parameters. We show that this technique is competitive with the best photometric quasar classification techniques---which are limited to fixed, broad redshift ranges and high signal-to-noise ratio data---and with the best photometric redshift techniques when applied to broadband optical data. We demonstrate that the inclusion of UV and NIR data significantly improves photometric quasar--star separation and essentially resolves all of the redshift degeneracies for quasars inherent to the ugriz filter system, even when included data have a low signal-to-noise ratio. For quasars spectroscopically confirmed by the SDSS 84 and 97 percent of the objects with GALEX UV and UKIDSS NIR data have photometric redshifts within 0.1 and 0.3, respectively, of the spectroscopic redshift; this amounts to about a factor of three improvement over ugriz-only photometric redshifts. Our code to calculate quasar probabilities and redshift probability distributions is publicly available

Learning via Surrogate PAC-Bayes

PAC-Bayes learning is a comprehensive setting for (i) studying the generalisation ability of learning algorithms and (ii) deriving new learning algorithms by optimising a generalisation bound. However, optimising generalisation bounds might not always be viable for tractable or computational reasons, or both. For example, iteratively querying the empirical risk might prove computationally expensive.In response, we introduce a novel principled strategy for building an iterative learning algorithm via the optimisation of a sequence of surrogate training objectives, inherited from PAC-Bayes generalisation bounds. The key argument is to replace the empirical risk (seen as a function of hypotheses) in the generalisation bound by its projection onto a constructible low dimensional functional space: these projections can be queried much more efficiently than the initial risk. On top of providing that generic recipe for learning via surrogate PAC-Bayes bounds, we (i) contribute theoretical results establishing that iteratively optimising our surrogates implies the optimisation of the original generalisation bounds, (ii) instantiate this strategy to the framework of meta-learning, introducing a meta-objective offering a closed form expression for meta-gradient, (iii) illustrate our approach with numerical experiments inspired by an industrial biochemical problem

Learning via Surrogate PAC-Bayes

PAC-Bayes learning is a comprehensive setting for (i) studying the generalisation ability of learning algorithms and (ii) deriving new learning algorithms by optimising a generalisation bound. However, optimising generalisation bounds might not always be viable for tractable or computational reasons, or both. For example, iteratively querying the empirical risk might prove computationally expensive. In response, we introduce a novel principled strategy for building an iterative learning algorithm via the optimisation of a sequence of surrogate training objectives, inherited from PAC-Bayes generalisation bounds. The key argument is to replace the empirical risk (seen as a function of hypotheses) in the generalisation bound by its projection onto a constructible low dimensional functional space: these projections can be queried much more efficiently than the initial risk. On top of providing that generic recipe for learning via surrogate PAC-Bayes bounds, we (i) contribute theoretical results establishing that iteratively optimising our surrogates implies the optimisation of the original generalisation bounds, (ii) instantiate this strategy to the framework of meta-learning, introducing a meta-objective offering a closed form expression for meta-gradient, (iii) illustrate our approach with numerical experiments inspired by an industrial biochemical problem

On change of measure inequalities for ff-divergences

17 pagesWe propose new change of measure inequalities based on $f$-divergences (of which the Kullback-Leibler divergence is a particular case). Our strategy relies on combining the Legendre transform of $f$-divergences and the Young-Fenchel inequality. By exploiting these new change of measure inequalities, we derive new PAC-Bayesian generalisation bounds with a complexity involving $f$-divergences, and holding in mostly unchartered settings (such as heavy-tailed losses). We instantiate our results for the most popular $f$-divergences

Fin whales of the Great Bear Rainforest : Balaenoptera physalus velifera in a Canadian Pacific fjord system

Funding: This research was supported by a Mitacs Accelerate Internship (IT21479); the Save Our Seas Foundation; Willow Grove Foundation; Donner Canadian Foundation; Tides Canada; LUSH Charity Pot; private donations to North Coast Cetacean Society; Fisheries and Oceans Canada; and the Canada Nature Fund for Aquatic Species at Risk (CANAFSAR 2019-2021).Fin whales (Balaenoptera physalus) are widely considered an offshore and oceanic species, but certain populations also use coastal areas and semi-enclosed seas. Based upon fifteen years of study, we report that Canadian Pacific fin whales (B. p. velifera) have returned to the Kitimat Fjord System (KFS) in the Great Bear Rainforest, and have established a seasonally resident population in its intracoastal waters. This is the only fjord system along this coast or elsewhere in which fin whales are known to occur regularly with strong site fidelity. The KFS was also the only Canadian Pacific fjord system in which fin whales were commonly found and killed during commercial whaling, pointing to its long-term importance. Traditional knowledge, whaling records, and citizen science databases suggest that fin whales were extirpated from this area prior to their return in 2005-2006. Visual surveys and mark-recapture analysis documented their repopulation of the area, with 100-120 whales using the fjord system in recent years, as well as the establishment of a seasonally resident population with annual return rates higher than 70%. Line transect surveys identified the central and outer channels of the KFS as the primary fin whale habitat, with the greatest densities occurring in Squally Channel and Caamano Sound. Fin whales were observed in the KFS in most months of the year. Vessel- and shore-based surveys (27,311 km and 6,572 hours of effort, respectively) indicated regular fin whale presence (2,542 detections), including mother-calf pairs, from June to October and peak abundance in late August-early September. Seasonal patterns were variable year-to-year, and several lines of evidence indicated that fin whales arrived and departed from the KFS repeatedly throughout the summer and fall. Additionally, we report on the population's social network and morphometrics. These findings offer insights into the dynamics of population recovery in an area where several marine shipping projects are proposed. The fin whales of the Great Bear Rainforest represent a rare exception to general patterns in this species' natural history, and we highlight the importance of their conservation.Peer reviewe