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Evolution of microclimate following small patch de-sealing and revegetation in urban context
No full textInternational audienceThis research explores the impact of de-sealing a 64 m 2 patch (Oasis) after introducing indigenous vegetation, four trees and herbaceous species, on local microclimate conditions in an urban context. Over two years, microclimate variables were monitored and thermal comfort was evaluated with the Universal Thermal Climate Index (UTCI). The Oasis experienced a noticeable reduction in Ts compared to surrounding asphalted areas, with a daily mean difference in maximum surface temperatures of 18.4 • C the first summer and 23.0 • C the second, attributed to the development of the herbaceous layer, which covered 60 % of the Oasis three months after sowing and above 90 % from the second year. This Ts is partly responsible for improving thermal comfort during the day. Tree shading induced further local cooling, with a decrease of up to 8 • C of UTCI in shaded areas. No evidence of lower nocturnal Ta compared to sealed reference was shown, possibly due to the small size of the patch and air mixing with the surroundings. However, as the low vegetation grew, the nocturnal de-sealed patch Ta got closer to mature meadow values. Modeling using UMEP and SOLWEIG projected further improvements in thermal comfort in the coming years during the daytime considering future tree dimensions. During nighttime, the trees would induce a significant radiative trapping. This study demonstrates that small-scale de-sealing and revegetation projects can provide meaningful microclimate improvements in urban environment as early as the first year. In the following years, the development of vegetation further helps cities to adapt to climate change
Letting ecosystems speak for themselves: An unsupervised methodology for mapping landscape acoustic heterogeneity
No full textInternational audiencePassive Sonic Monitoring (PSM) refers to the analysis of patterns and structures shaped by sound, offering a complementary approach to traditional landscape analysis methods, such as satellite imagery. In particular, satellite-based methods alone may overlook specific dynamics of the organism at multiple taxonomic levels and local abiotic interactions. This paper introduces a novel unsupervised methodology for mapping similarities between soundscapes. Using Gaussian Mixture Models (GMM), this approach generates soundscape maps that reveal ecological processes throughout the day. We applied our methodology to data from 94 sites within a heterogeneous Colombian Orinoquia ecosystem. We found correlations between the cluster maps, satellite images, and biotic presences (bird and amphibian sonotypes). Our results align with established remote-sensing data and uncover previously unrecognized sonic patterns, offering new ecological insights that complement traditional landscape assessments. Our approach bridges the gap between image satellite-based assessments and ecological sonic processes, paving the way for comprehensive long-term biodiversity monitoring
Une nouvelle méthode de partitionnement de séquences avec motifs interprétables
No full textÀ l'ère du « tout numérique », la génération et l'exploitation de données constituent un défi d'envergure pour la recherche et l'innovation. Le regroupement de données, ou clustering, repose sur de nombreuses approches (Ghosal et al., 2020), mais les solutions traditionnelles ne parviennent à partitionner les données complexes, comme les séquences, qu'après un prétraitement consistant à effectuer un plongement numérique des données. Cette transformation rend difficile l'explication des partitions obtenues. Dans cet article, nous proposons une nouvelle méthode de partitionnement de données séquences à partir d'une hiérarchie de concepts, calculée par l'algorithme NEXTPRIORITYCONCEPT (Demko et al., 2020), issu de l'Analyse Formelle de Concept, avec motifs interprétables
Window Airflow Rates and Pollutants Emission Rates Determined by an Inverse Method Applied to IAQ Measurements in a Low-Energy House
No full textIn the climate change context, future building regulations will consider their global performance, which includes energy performance and indoor environmental quality. To push towards global performance-based approaches, especially indoor air quality (IAQ), we still miss data entry to calculate the performance indicators. A scientific barrier identified is the lack of knowledge about pollutant emission rates at the house scale, which could be used in such IAQ calculations at the building design stage. In this study, an inverse method procedure is used to retrieve the pollutant emissions and the window airflow rate. The approach is based on the minimization between the indoor measurements and the prediction of the mathematical model. The CO 2 measurements have been collected in the main bedroom of a low-energy occupied house during a 2-week winter campaign, with a 10 min time-step. The unknown parameters are retrieved at the same time step. The emissions resulting from the occupants are identified. The retrieved window airflow rate scales around 500 m 3 /h. Our study constitutes a worthwhile contribution to the field, demonstrating the strength of the approach to the IAQ scientific field. This first step allows us to test the developed methodology before applying it to other pollutants measurements performed during the same campaign. Indeed, for CO 2 , it is possible to compare the results with emission rates from the literature. Lastly, we identified several applications of this promising methodology, including calculating other pollutants' emission rates, such as formaldehyde, and calculating airflows through open windows.</div
A Bayesian Network Framework to Predict Compressive Strength of Recycled Aggregate Concrete
No full textInternational audienceIn recent years, the use of recycled aggregate concrete (RAC) has become a major concern when promoting sustainable development in construction. However, the design of concrete mixes and the prediction of their compressive strength becomes difficult due to the heterogeneity of recycled aggregates (RA). Artificial-intelligence (AI) approaches for the prediction of RAC compressive strength (fc) need a sizable database to have the ability to generalize models. Additionally, not all AI methods may update input values in the model to improve the performance of the algorithms or to identify some model parameters. To overcome these challenges, this study proposes a new method based on Bayesian Networks (BNs) to predict the fc of RAC, as well as to identify some parameters of the RAC formulation to achieve a given fc target. The BN approach utilizes the available data from three input variables: water-to-cement ratio, aggregate-to-cement ratio, and RA replacement ratio to calculate the prior and posterior probability of fc. The outcomes demonstrate how BNs may be used to forecast both forward and backward, related to the fc of RAC, and the parameters of the concrete formulation
Frictional dissipation of incident waves over a spatially varying rough barrier reef in Mayotte, Indian Ocean
No full textInternational audienceCoral reefs serve as a highly effective natural barrier against incom ing ocean waves. However, climate change and human induced degradations are threatening reefs, reducing their capacity to protect coastal populations by di minishing the frictional processes that dissipate wave energy. The most common approach to represent wave energy dissipation through bottom friction relies on the estimation of a representative roughness length, whose definition on coral environments remains to be elucidated. As a consequence, a generic parametrization for friction processes on coral reef systems is still lacking. In this study, high resolution hydrodynamical and topographical data collected at the South West barrier reef of Mayotte, Indian Ocean, were used to perform an estimation of wave friction. The hydraulic roughness estimated across the reef varies spatially, and attempts are made to connect this information with the diverse bed morphologies observed in the field
Le jugement des cons - Édition, traduction et notes d'après le manuscrit BnF 837
No full textÉdition, traduction et notes du Jugement des cons d'après le manuscrit BnF fr. 83
Le fevre de Creeil - Édition, traduction et notes d'après le manuscrit BnF fr. 837
No full textÉdition, traduction et notes du Fevre de Creeil d'après le ms. BnF fr. 83
La dame escoillee - Édition et notes d'après le ms. BnF fr. 1593
No full textÉdition et notes de La dame escoillee d'après le ms. BnF fr. 159