Portail HAL de l'Université du Littoral Côte d'Opale
Not a member yet
11255 research outputs found
Sort by
Culture-driven neural plasticity and imprints of body-movement pace on musical rhythm processing
No full textNational audienceMoving the body on music can help individuals to internalise the temporal structure of music, making it easier to understand and appreciate the rhythmic complexities of a musical piece as it unfolds over time. This registered report aims at capturing direct neuroscientific evidence for the rhythmic, movement-related shaping of auditory information with a cross-cultural perspective. Specifically, West/Central African- and Western-enculturated individuals are tested in two distinct studies, to demonstrate the culture-driven neural plasticity in human rhythm processing, and how it is shaped by the pace of rhythmic body movement. Electroencephalography (EEG) and hand clapping are recorded in separate sessions in response to an auditory rhythm derived from West/Central African music repertoire. These recordings are conducted both before and after a body movement session where participants will engage in stepping and clapping to the rhythm following a specific metre (three- vs. four-beat metre). Data collection is ongoing, but we predict that the behavioural and neural representation of metre in the pre-movement session will be distinct in the African vs. Western-enculturated participant groups. Moreover, the representation of metre conveyed by prior movement will be selectively sharpened in the neural and behavioural responses obtained during the post-movement session. This movement effect is expected to be more pronounced for the metrical interpretation that is predominant according to the participant’s musical culture. Collectively, these findings are expected to elucidate how prior experience, shaped by long-term cultural background and short-term motor practice, imprint onto rhythm processing in humans
‘I’m here for the water’: sensory dimensions of slow sporting embodiment through seascapes in northern France
No full textInternational audienceIn this article, the authors explore the interconnections of aquatic embodiment and seascapes, drawing on phenomenological perspectives and the emergent concept of “slow” sports and physical cultures. Whilst many traditional aquatic sports and activities have sought the maximization of speed, strength, or skill, in recent times, the concept of “slow” has been taken up by those participating in recreational sea-based activities. This perspective valorizes “slowing down” in order to appreciate different kinds of aquatic embodiment and the sensory pleasures of deep engagement with the seascape. Drawing on a research project combining ethnographic and autoethnographic elements, the authors investigate slow aquatic “immersion” and some of the deep sensuosities of the mind–body–water connection, anchored in the seascapes of northern France. Their specific focus is on two slow sports: paddleboard yoga/yoga-paddle and aquatic hiking
L'artisanat et ses entreprises : regards croisés
No full textInternational audienceLongtemps, l’artisanat a été considéré comme un archaïsme sur le déclin, laminé par l’industrialisation. Pourtant, à un moment où il peut célébrer, en France, le centenaire de ses institutions représentatives, force est de constater au contraire sa vitalité. Or, longtemps également, l’histoire et les sciences économiques et sociales l’ont négligé. L’ambition de ce numéro thématique d’Entreprises et Histoire est de contribuer, d’une part, à combler cette lacune en croisant les approches disciplinaires et, d’autre part et plus précisément, à comprendre comment et pourquoi l’artisanat s’est maintenu en dépit de l’industrialisation des économies qui semblait devoir le faire disparaître. Cet éditorial dresse tout d’abord un état de l’art des travaux engagés sur le sujet, puis il en présente les enjeux et propose enfin de futures pistes d’étude
Control of the one-dimensional wave-equation with variable coefficients
No full textThe aim of this article is to theoretically and numerically study the controllability of the onedimensionalwave equation with variable coefficients. The coefficient appearing in the main part ofthe equation is of class C 1. A backstepping transformation is used to obtain the global finite-timestabilisation of the wave equation and thus its zero controllability. The kernel equations and thefinite-time stabilisation of the wave equation are solved numerically with first-order convergenceunder a CFL condition and numerical simulations are presented to validate them
Combining deep learning with physical parameters in POC and PIC inversion from spaceborne lidar CALIOP
No full textInternational audiencePOC and PIC are indispensable components in the global ocean carbon cycle, their transport and space distribution being driven by the biological carbon pump and the carbonate pump. However, passive ocean color remote sensing, usually employed for POC and PIC research, experiences serious shortcomings in polar winter conditions due to its reliance on sunlight, leading to scarce data coverage in the polar regions. In contrast, CALIOP has shown considerable promise in high-latitude ocean observing. Past approaches to estimate POC from CALIOP data relied on bbp measurements obtained through the application of algorithms that presume an empirical linear correlation between bbp and the backscatter coefficient measured at 180°. This method does not account for any spatiotemporal variability in the conversion coefficient. Furthermore, the potential of CALIOP to provide estimates of PIC has not been explored yet. Here, we developed an innovative Two-Branch-Two-Step (TBTS) model to estimate POC and PIC from CALIOP data, which effectively expands the spatial coverage of the MODIS products. This method exploits the strength of deep learning while encapsulating the generalizability of physical parameters. This method consists of two branches: (1) a deep learning branch based on lidar attenuated backscatter waveform and (2) a branch focusing on physical parameters, including the total column-integrated depolarization ratio and the subsurface cross-polarized component of column-integrated backscatter. The model’s generalizability and accuracy are confirmed through the evaluation of a test dataset and validation using in-situ measurements. Our model outperforms several other prevalent machine learning models. We also dissected the importance of different parts of the input data using SHAP tools, thereby providing insights into the black-box nature of deep learning models. Using CALIOP products, we put forth the inaugural estimation of interannually resolved PIC and POC standing stocks in polar regions. The implementation of CALIOP in polar regions bridges the gap inherent in passive ocean color measurements. Lidar-derived total global PIC standing stock is estimated to be 8% higher than that from MODIS, while the POC standing stock is boosted by 17.2%. The carbon standing stock in polar regions exhibits significant inter-annual variability and apparent seasonal periodicity. Hence, results from this research effort clearly reveal that the exploitation of the CALIOP-derived POC and PIC measurements, in combination with the application of new approaches and algorithms to future space lidar data, will undeniably enhance our comprehension of the polar ocean carbon cycle. However, it is important to acknowledge that the CALIOP products may inherit biases from the MODIS data used for training. Hence, where MODIS data is available, it’s still the “better” product to use, but where there isn’t MODIS data, the CALIOP product is extremely useful, especially in the polar regions
Native arbuscular mycorrhizal inoculation enhances secondary metabolite contents in Tamarix gallica grown in saline soil
No full textInternational audienceTamarix gallica is a halophytic species of steppe regions. It contains a high concentration of bioactive compounds with potential health benefits. The use of arbuscular mycorrhizal fungi (AMF) has gained interest in mitigating abiotic stress and enhancing plant tolerance through the accumulation of secondary metabolites. Thus, the current study aims to evaluate the relevance of plant inoculation with native AMF in terms of optimizing the secondary metabolite production in T. gallica while cultivated in saline soils. Furthermore, the antimicrobial and antioxidant activities were investigated. The extraction of secondary metabolites was evaluated using three different methods after five years of plantation. The bioactive components were analysed and quantified. The most effective solvent for the extraction of secondary metabolites from T. gallica leaves was found to be pure methanol. AMF inoculation significantly increased the content of bioactive components, including phenolic, flavonoids, flavones, proanthocyanidins, anthocyanins, and saponins, in methanolic leave extracts by 13% compared to the non-inoculated plants. A positive correlation was revealed between the total mycorrhizal rate and T. gallica polyphenol contents. High antioxidant activity with an IC50 of 280 µg.ml− 1, and antibacterial activity against Klebsiella pneumoniae with 17 mm inhibition zone were pointed out. The current study highlighted the importance of AMF inoculation in the improvement of the quantity and quality of T. gallica bioactive compounds under saline soil conditions. Furthermore, it suggested the relevance of T. gallica mycorrhizal inoculation under salinity stress conditions, to produce bioactive molecules for pharmaceutical applications
Mieux appréhender et se représenter les risques et les enjeux par l'usage d'un jeu sérieux.
No full textInternational audienc
Partir aux Amériques. Les minorités religieuses et le peuplement du Nouveau Monde (XVe-XIXe siècles).
No full textInternational audienc
Prise en compte de l’esthétique dans la gestion des gammes de luminance des images
No full textAesthetic analysis of digital images enhances the visual content's aesthetic quality. By analyzing aesthetic features that influence visual perception through image data, computers can perform tasks like assisted image editing, aesthetic quality enhancement, and filtering for the best image. This thesis merges aesthetic image analysis with high dynamic range (HDR) imaging. We consider both the properties of HDR and the aesthetic characteristics of images during HDR image processing. The aim is to maximize the preservation of the original aesthetic features of images when adjusting HDR image display results, thereby achieving a pleasant visual experience. In this thesis, we propose a composition leading lines reconstruction method and two HDR image auto-adjustment methods. Regarding automatic adjustment of HDR images, we are developing a model based on a neural network to predict the adjustment curve of HDR images, and a model using a convolutional neural network to estimate the exposure adjustment value, by analyzing potential features of HDR images. Both methods automatically enhance the aesthetic quality perception of HDR images on HDR display devices by training neural networls to learn expert editing parameters from an HDR database. In order to analyze the aesthetics of image composition, we propose to reconstruct the leading lines of the image. Just like color, lighting, or the grain of the image, the leading lines among the aesthetic features that need to be analyzed. The proposed method identified implicit leading lines in the image through a line regrouping algorithm. We initially carried out an inter-expert consistency analysis to demonstrate the feasibility of our method. In addition, we propose a metric for comparing the two sets of leading lines.L'analyse des caractéristiques esthétiques d'images numériques permettent d'améliorer la qualité esthétique du contenu visuel. En analysant les caractéristiques esthétiques qui influencent la perception visuelle à travers les données de l'image, les ordinateurs peuvent effectuer des tâches telles que l'édition assistée d'image, l'amélioration de la qualité esthétique et le filtrage de la meilleure image. Cette thèse intègre l'analyse des caractéristiques esthétiques des images avec l'imagerie à haute gamme dynamique (HDR). Nous prenons en compte les propriétés du HDR et les caractéristiques esthétiques lors du traitement des images HDR. L'objectif est de maximiser la préservation des caractéristiques esthétiques originales des images lors de l'ajustement des effets d'affichage HDR, afin d'atteindre l'expérience visuelle plus agréable. Dans cette thèse, nous proposons deux approches d'auto-ajustement des images HDR et une méthode de reconstruction des lignes de force de la composition. Concernant l'auto-ajustement des images HDR, nous développons un modèle basé sur un réseau de neurones pour prédire la courbe d'ajustement des images HDR, et un modèle utilisant un réseau de neurones convolutifs pour estimer la valeur d'ajustement de l'exposition, en analysant les caractéristiques potentielles des images HDR. Ces deux méthodes consistent à améliorer automatiquement la perception de la qualité esthétique des images HDR sur des dispositifs d'affichage HDR. Elles le font en entraînant des réseaux de neurones à apprendre des paramètres d'édition d'experts à partir de jeux de données HDR. Afin d'analyser l'esthétique de la composition d'une image, nous proposons de reconstruire les lignes de force. Tout comme la couleur, les lumières ou le grain de l'image, les lignes de force font partie des caractéristiques esthétiques qui doivent être analysées. La méthode proposée identifie les lignes de force implicites dans l'image par un algorithme de regroupement des lignes. Nous avons initialement mené une analyse de cohérence entre experts pour démontrer la faisabilité de notre méthode. Par ailleurs, nous proposons une métrique pour comparer les deux ensembles de lignes de force