University of Technology of Compiègne

Scaffolds' production for hard to soft tissues recently become of great interest, as bone-tendon insertion tissue engineering, where injuries mainly occur. Interfacial tissue engineering aims at developing grafts to mimic the gradients of those tissues as far as composition, mechanical properties and structures are concerned. Additive manufacturing can offer solutions to meet these requirements, but still requires to improve processes to achieve such gradients in a few steps. In this study, we developed a 3D-printed collector to combine gap-spinning and micropatterning. We were able to manufacture a scaffold (60mm long, 5mm wide) with a smooth gradient of 5mm long from honeycomb structure to aligned fibers (promoting bone and tendon fate, respectively) in a single step. We estimated a gradient in Young modulus from 20MPa to 30MPa from the bone to the tendon side. Deformation tracking permitted to highlight significant difference of local strains between both areas, which could then impact cells' response. Murine stem cells C3H10T1/2 were then seeded at both scaffold parts and cultivated without any growth factors in stretching conditions. Alkaline phosphatase staining and tenomodulin immunostaining suggested the effect of stretching to cells' behavior between the bone and tendon area, compared to static condition. However, benefit of topographical and mechanical cues only cannot be fully established to foster cells to specific fate probably due to the limits of this cell line. This novel collector system however permitted to produce a relevant scaffold to study interfaces where a topographical gradient might be needed.

Five biomass-based materials: sesame straw (SS), corn cobs (CC), bamboo powder (BP), wheat straw (WS), and furfural residue (FR), were sulfonated using sulfuric acid, as well as some commercial sulfonated catalysts, like Amberlyst, Nafion were compared for the production of ethyl levulinate (EL) from furfuryl alcohol (FAL). Remarkably, under optimum conditions (50 mg of 8% SO3H-FR at 170 °C for 5 h), 100% FAL conversion and 90% EL yield were achieved, along with stable recyclability in continuous flow. Dynamic evolution of GC in the function of reaction time under different temperatures was performed, indicating that FAL conversion to ethoxymethylfuran (EMF) occurs under a lower temperature (150 °C) and short time (45 min). On the contrary, the intermediates 5, 6, and 7 required a higher temperature for EL formation with the concomitant release of diethyl ether (DEE). Comprehensive characterizations demonstrated significant changes in the chemical composition of sulfur- or nitrogen-containing functional groups after sulfonation. In particular, the −S–O types (especially −SO3H) play a more critical role in EL production than the sulfur content alone. The adsorption energies and charge density differences of FAL (Eads) on pristine FR and the sites of −SO3H, −SO4, pyrrolic N, pyridinic N, and their complexes were compared. The FAL adsorption energy followed the order: Eads (complex) > Eads (−SO4) > Eads (−SO3H) > Eads (pyrrolic N) > Eads (pyridinic N)>Eads (pristine), indicating a synergistic adsorption effect among these functional groups in FR. Additionally, the electron transfer capacity was significantly enhanced after −SO3H doping.

The atmospheres surrounding metal parts in many industrial processes rarely comprise a single oxidant. Whether in fossil energy conversion plants, nuclear power plants, jet engines, chemical or petrochemical production routes, several molecules, sometimes present as main components, sometimes at the impurity level, play a role in corrosion mechanisms. Current research into the development of low-emission technologies also clearly demonstrates the importance of considering, in addition to O 2 , the effects of H 2 , H 2 O, NH 3 , etc. in the development and selection of alloys.

Acoustic imaging for the monitoring of industrial infrastructures remains a common feature to address numerous issues, such as diagnosing faults in rotating machinery or detecting gas leaks. Simultaneously, autonomous vehicles have emerged as a strong tool to automate various maintenance and diagnostic tasks, incorporating increasingly diverse sensors, including microphone arrays. The objective of this work is to present a new control strategy for an autonomous vehicle equipped with a microphone array, aimed at mapping its environment completely blindly. The system must be robust to background noise and to a wide range of sound levels from sources, in order to be effective in an industrial setting. The control strategy proposed in this preliminary work meets these expectations and allows for mapping a large number of sources in a noisy environment, with a wide range of sources sound levels. Its versatile approach allows adapting the localization algorithm used between MUSIC and constrained-MUSIC depending on the situation and acoustic environment, leveraging the information the robot will have collected during its measurement. Its performances are evaluated in a simulation study.

ABSTRACT U-statistics represent a fundamental class of statistics that emerge from modelling quantities of interest defined by multi-subject responses. These statistics generalize the empirical mean of a random variable X to summations encompassing all distinct k-tuples of observations drawn from X . A significant advancement was made by Stute [ConditionalU-statistics. Ann. Probab. 19 (1991), pp. 812–825], who introduced conditional U-statistics as a generalization of the Nadaraya–Watson estimates for regression functions. Stute demonstrated their robust pointwise consistency towards the conditional function r ( k ) ( φ , t ~ ) = E ( φ ( Y 1 , … , Y k ) ∣ ( X 1 , … , X k ) = t ~ ) , for t ~ ∈ R pk , where φ is a measurable function. In this investigation, we develop oracle inequalities and upper bounds for kernel-based estimators of conditional U-statistics of general order, applicable across a wide range of metric spaces associated with operators. Our analysis specifically targets doubling measure metric spaces, incorporating a non-negative self-adjoint operator characterized by Gaussian regularity in its heat kernel. Remarkably, our study achieves an optimal convergence rate in certain cases. To derive these results, we explore the regression function within a general framework, introducing several novel insights. These findings are established under sufficiently broad conditions on the underlying distributions. The theoretical results serve as essential tools for advancing the field of general-valued data, with potential applications including the examination of conditional distribution functions, relative-error prediction, the Kendall rank correlation coefficient, and discrimination problems – areas of significant independent interest.

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