Normandie Université

Thermal radiation is the dominant mode of heat transfer in large-scale pool fires, making accurate prediction of radiative heat flux essential for fire safety assessment and hazard analysis. Traditional approaches often rely on simplified representations, such as point-source models or the solid-flame model, in which the target is assumed to view only the “half-flame” surface in view factor calculations. This study develops a mathematical framework to quantify the influence of the field-of-view (FOV) angle on view factor estimation between a differential target and a circular pool fire, considering both cylindrical and conical flame geometries. The view factor integrals are derived using contour formulations and solved numerically with high accuracy. Results show that neglecting the actual FOV systematically underestimates the view factor, with deviations dependent on sensor height, flame radius, and target separation. For cylindrical flames, deviations can exceed 5% at near-field distances and large radii, while conical flames exhibit smaller deviations that remain within acceptable accuracy limits. Time-resolved analyses further demonstrate that temporal variations in flame height have little effect on the resulting view factor. Overall, these findings emphasize the importance of incorporating realistic FOV effects in radiation modeling, while also identifying conditions under which simplified assumptions remain sufficiently accurate. • Improved radiation modeling for cylindrical and conical pool fires. • Field-of-view approach enhances flame–target heat transfer prediction. • Corrects half-flame assumption used in pool fire radiation models. • Analytical formulation offers a low-cost substitute for Monte Carlo.

Characterizing nanoparticles in terms of size and morphology is essential to understand their physical and optical properties. Small or Ultra Small-Angle X-ray Scattering (SAXS/USAXS) is a powerful in situ technique that allows the analysis of such nanostructures exhibiting size and morphology through the Guinier and Porod regimes, which can be repeated at different scales (e.g., primary spheres and Agglomerates for mass fractal agglomerates, as focused on in this study). This is the principle of the widely used Beaucage’s unified model, built in reciprocal q -space (the momentum transfer or scattering wave vector) in order to interpret experimental results. An alternative method based on pair correlation modeling can be used. Indeed, by definition, the scattered signal corresponds to the Fourier transform of the particles’ pair correlation function. The present study compares the two approaches for fractal agglomerates of point-contact spheres. It is shown that the Beaucage’s model is limited to agglomerates consisting of a large number of primary spheres and that certain destructive interferences, not taken into account in this model, can affect data inversion, potentially affecting the extraction of the primary sphere size distribution. In this work, both models are compared in the direct way applied on synthetic data, and used to invert experimental SAXS data from soot particles in a laminar ethylene diffusion flame measured at the European Synchrotron Radiation Facility (ESRF) and processed via Abel inversion. This study puts in evidence the fundamental differences between both models and highlight their respective limitations. Nevertheless, both models provide similar results except for the mass fractal dimension and primary sphere geometric standard deviation. The present study demonstrates thus the potential of the pair correlation modelling and encourages its further development. • A critical analysis and comparison is carried out between unified scaling approaches, commonly used in interpreting electromagnetic wave scattering signals in visible or X-ray ranges, and a more rigorous method based on modeling the pair correlation function. • The results highlight a significant shortcomings in classical modeling, particularly its neglect of destructive interference effects that crucially influence the amplitude and slope of modeled signals. • A new expression for the polydispersity index (PDI) tailored for lognormal distributions is introduce. • The application of Abel inversion to scattering spectra in laminar diffusion flames has a strong impact on inverted parameters. • Applying both models to experimental data obtained by small-angle X-ray scattering (SAXS) reveals significant impacts on most of the measured parameters when the new expression for PDI is taken into account.

Ion implantation is introduced as a novel and controllable approach to incorporate hydrogen into α-MoO3 crystals and induce the formation of hydrogen molybdenum bronze phases (HxMoO3) below the implanted layer. By tuning the ion fluence, this technique enables precise defect engineering and phase transformation, offering a versatile and reproducible strategy for tailoring the material functional properties. High-resolution X-ray diffraction (HRXRD) reveals a gradual expansion of the b lattice parameter for fluences up to 1 × 1017 cm-2, attributed to defect-induced lattice distortion. For higher fluences, instead of typical strain saturation, a new diffraction peak emerges, revealing the formation of type-I HxMoO3, as also confirmed by Raman spectroscopy. This phase forms below the implanted layer and extends up to ∼1µm into the material, as confirmed by transmission electron microscopy (TEM). This phase transformation demonstrates reversibility, with the HxMoO3 signature disappearing upon air annealing at 300°C. HRXRD curve fitting enables assessment of strain/damage profiles evolution with fluence, providing insight into the defect creation and accumulation mechanisms. These structural and compositional changes are accompanied by a quasi-linear increase of electrical conductivity with fluence, by several orders of magnitude, attributed to the presence of HxMoO3 phases, extended defects, and new suboxide minority phases.

Therapeutic Communities (TCs) are long-term residential treatment settings for individuals with substance use disorders, who often present with neuropsychological impairments. These impairments may influence treatment retention, yet little is known about their evolution in TCs or their association with dropout. This study aims to: (1) identify early risk factors for dropout; (2) investigate the potential recovery from the risk of neuropsychological impairment during an 8-mont stay in a TC; and 3) identify variables at TC entry that may predict the risk of neuropsychological impairment during follow-up. Fifty-seven residents from 3 French TCs completed clinical, substance use, and medical assessments, along with a neuropsychological screening (BEARNI) at entry. Twenty-four completed the 8-month follow-up. The dropout rate was 47%. The only significant predictor of dropout was the BEARNI total score, with residents at lower risk of neuropsychological impairment more likely to leave the TC prematurely. Among completers, BEARNI total scores improved at follow-up, primarily explained by improvements in balance rather than in cognitive areas. Lower education, unemployment, recent alcohol use, depressive symptoms, and a history of hepatic disease were consistently associated with a higher risk of neuropsychological impairment at both time points. Unlike other treatment settings, the TC care framework may be particularly appropriate and supportive for residents who are more cognitively vulnerable, as they may be better able to benefit from TCs. Motor recovery among those who remain in treatment is encouraging. However, demographic, addiction-related, and comorbidity factors are consistently associated with the risk of neuropsychological impairment, both at baseline and after 8 months, suggesting a stable and persistent influence over time. Not applicable.

Nonparenchymal central nervous system (CNS)-associated macrophages (CAMs) mediate immune responses at brain boundaries. Perivascular and leptomeningeal CAMs are collectively termed subdural CAMs (sdCAMs). Both sdCAMs and juxtaneuronal microglia are derived from embryonic yolk sac precursors, long-living and maintain their populations through self-renewal. Following depletion, microglia autonomously repopulate from single surviving cells. In contrast, the course of sdCAM repopulation remains poorly understood. Here, by combining multilineage fate mapping, multiomic profiling and high-resolution imaging, we demonstrate divergent repopulation dynamics between sdCAMs and microglia. Unlike microglia, sdCAMs do not renew cell-autonomously, but become transiently accessible to CCR2+Ly6C+ monocyte engraftment after niche induction in an integrin-dependent manner. Moreover, replenished monocyte-derived sdCAMs remain transcriptomically, epigenetically and functionally distinct from their embryo-derived counterparts. Finally, we present a protocol enabling selective exchange of sdCAMs, modulating disease response without functionally affecting microglia. These new insights into CNS immune biology suggest new therapeutic avenues for neuroinflammatory and neurodegenerative diseases.