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Pierre Martin

Publications and source records attributed to Pierre Martin.

5 recordsLinked to original sources

E. coli bacterium near corrugated surfaces: near-surface swimming, escape, and hydrodynamic trapping

Bacteria often swim in complex environments where surfaces are ubiquitous and rarely flat. Surface topography and curvature can strongly affect bacterial motility, with important consequences for surface exploration, adhesion, and biofilm formation. Here, we investigate the swimming of a non-tumbling Escherichia coli bacterium near an undulating no-slip surface using hydrodynamic simulations of a detailed model bacterium. The latter is described by a rigid spherocylindrical cell body and flexible flagella modeled with the Kirchhoff rod theory, while the surrounding fluid is simulated using the method of multi-particle collision dynamics. At low curvatures of the sinusoidal surface modulations, the bacterium exhibits persistent near-surface swimming and clockwise trajectories, consistent with the known behavior near flat no-slip walls. As the curvature increases, bacteria swimming toward a ridge can escape from the surface, which we use to estimate a critical curvature where surface detachment is more likely. At larger curvatures, we find that the surface geometry promotes oscillatory swimming along the groove direction, which reduces escape opportunities and, therefore, enhances bacterial trapping. Indeed, the confinement around the groove reverses the swimming of the bacterium from clockwise to counter-clockwise, as we demonstrate by two minimal models. Thus our work highlights the importance of the three-dimensional surface topography in bacterial surface exploration.

cond-mat.soft

A Variability-Based Framework for Interpretable Naming in Formal and Relational Concept Analysis

Knowledge extraction from symbolic data often produces abstractions that are formally defined but not immediately interpretable by users. Formal Concept Analysis (FCA) and Relational Concept Analysis (RCA) provide representative settings for this issue: they generate explicit conceptual structures, implications, and relational dependencies from object descriptions and relations. Although these structures are explainable by design, their concepts are often identified by technical labels, which limits their use as human-interpretable knowledge units. Assigning meaningful names to such concepts is therefore a key issue for interpretation, navigation, validation, and reuse by domain experts. This paper investigates concept naming in FCA and RCA from a symbolic knowledge representation perspective. We first characterize the linguistic and terminological challenges involved in naming generated symbolic abstractions, including ambiguity, discrimination, concision, and consistency across related concepts. We then propose a configurable framework for LLM-assisted concept naming. The framework relies on a variability model that controls which sources of information are exposed during naming, such as intent, extent, inherited information, neighboring concepts, implications, and relational attributes. It thereby makes explicit the semantic choices involved in moving from formal concept descriptions to human-readable names. The approach is illustrated as a proof of concept on a small relational dataset in the pizzeria domain. This illustration shows how different configurations influence the names suggested by an LLM, and how naming variability can reveal interpretation choices, relational dependencies, and possible modeling issues in the underlying symbolic data.

cs.AI

E. coli bacterium tumbling in bulk and close to surfaces: A simulation study

Motility is fundamental to the survival and proliferation of microorganisms. The E. coli bacterium propels itself using a bundle of rotating helical flagella. If one flagellum reverses its rotational direction, it leaves the bundle, performs a polymorphic transformation, and the bacterium tumbles. The E. coli bacterium is hydrodynamically attracted to surfaces. This prolongs its residence time, while tumbling facilitates surface detachment. We develop a model of E. coli that uses an extended Kirchhoff rod theory to implement flagellar flexibility as well as different polymorphic conformations and perform hydrodynamic simulations with the method of multiparticle collision dynamics (MPCD). To establish a reference case, we determine the distribution of tumble angles in the bulk fluid, which shows good agreement with experiments for a fixed tumble time. Increasing the hook stiffness, narrows the tumble angle distribution and reduces the flagellar dispersion during tumbling. Close to a bounding surface, the tumble angle distribution is shifted to smaller angles, while flagellar dispersion is reduced. Reorientation within the plane favors the forward direction, which might be an explanation for prolonged run times observed in experiments

cond-mat.soft

Variability-Driven User-Story Generation using LLM and Triadic Concept Analysis

A widely used Agile practice for requirements is to produce a set of user stories (also called ``agile product backlog''), which roughly includes a list of pairs (role, feature), where the role handles the feature for a certain purpose. In the context of Software Product Lines, the requirements for a family of similar systems is thus a family of user-story sets, one per system, leading to a 3-dimensional dataset composed of sets of triples (system, role, feature). In this paper, we combine Triadic Concept Analysis (TCA) and Large Language Model (LLM) prompting to suggest the user-story set required to develop a new system relying on the variability logic of an existing system family. This process consists in 1) computing 3-dimensional variability expressed as a set of TCA implications, 2) providing the designer with intelligible design options, 3) capturing the designer's selection of options, 4) proposing a first user-story set corresponding to this selection, 5) consolidating its validity according to the implications identified in step 1, while completing it if necessary, and 6) leveraging LLM to have a more comprehensive website. This process is evaluated with a dataset comprising the user-story sets of 67 similar-purpose websites.

cs.SE

Impact of Phonon Surface Roughness Scattering on Thermal Conductivity of Thin Si Nanowires

We present a novel approach for computing the surface roughness-limited thermal conductivity of silicon nanowires with diameter D < 100 nm. A frequency-dependent phonon scattering rate is computed from perturbation theory and related to a description of the surface through the root-mean-square roughness height Delta and autocovariance length L. Using a full-phonon dispersion relation, we find a quadratic dependence of thermal conductivity on diameter and roughness as (D/Δ)^2. Computed results show excellent agreement with experimental data for a wide diameter and temperature range (25-350 K), and successfully predict the extraordinarily low thermal conductivity of 2 W.m^{-1}.K^{-1} at room temperature in rough-etched 50 nm silicon nanowires.

cond-mat.other