Analyse de signaux sonores par les lois de Zipf et Zipf Inverse

- Nous présentons dans cet article un ensemble de codages de signaux sonores que nous avons développés afin d'adapter à ce type de signaux, l'analyse par les lois de Zipf et Zipf Inverse. L'efficacité de ces lois à décrire les phénomènes physiques n'est plus à démontrer, et à motiver nos investigations concernant le problème de la caractérisation de signaux sonores. Afin de valider notre approche, la méthode a été évaluée sur des signaux sonores médicaux, correspondant à des bruits xiphoïdiens

Segmentation et suivi de l'endocarde dans des séquences IRM 3D par surface active

Nous proposons un modèle de surface active 3D+T pour la segmentation et le suivi de la paroi endocardique du ventricule gauche dans des séquences cardiaques 3D. Pour réunir les étapes de segmentation et de suivi, la surface est dotée d'une structure divisée à la fois dans l'espace et le temps. Elle se modélise sous la forme d'une matrice de contours actifs planaires, connectés d'une coupe et d'une phase à l'autre, ce qui permet de maintenir une cohérence temporelle et spatiale. Dans une phase donnée, l'empilement des contours constitue un maillage triangulaire 3D de topologie cylindrique. La paroi ventriculaire est extraite par minimisation d'une énergie qui combine un terme contour et un nouveau terme basé région, exprimé selon le principe de la bande étroite

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Contribution de la loi de Zipf à l'analyse d'images

Notre travail concerne l'application à l'analyse d'images d'un modèle statistique issu de l'analyse linguistique : la loi de Zipf. Nous présentons d'abord les principaux modèles de loi puissance, les différentes interprétations de ces modèles ainsi que leurs principales applications. Nous montrons ensuite l'application de ces modèles aux images, leurs propriétés et les caractéristiques de l'image pouvant être mises en évidence. Ensuite nous présentons une application de la loi de Zipf pour l'évaluation de la qualité des images compressées. La dernière application présente l'utilisation des lois de Zipf et de Zipf inverse pour la détection d'objets et de zones d'intérêt dans les images. Les différents résultats obtenus montrent l'intérêt de ce modèle. Par toutes ces applications nous montrons que notre approche peut contribuer à la résolution de problèmes encore ouverts dans le domaine de l'analyse d'images.Our work concerns the application to image analysis of a statistical model adapted from linguistic analysis known as Zipf law. First we present the main power law models, their different interpretations and their main applications. Then we present their application to images, their properties and the characteristics of images they can put into evidence. We also present an application of Zipf law for quality evaluation of compressed images. Another application is the use of Zipf law and inverse Zipf law for object and region of interest detection in images. The different results obtained show the interest of this model. By all these applications we show that our approach can contribute to the resolution of image analysis problems which are still open.TOURS-BU Sciences Pharmacie (372612104) / SudocTOURS-Polytech'Informat.Product. (372612209) / SudocSudocFranceF

Use of power law models in detecting region of interest

International audienceIn this paper, we shall address the issue of semantic extraction of different regions of interest. The proposed approach is based on statistical methods and models inspired from linguistic analysis. Here, the models used are Zipf law and inverse Zipf law. They are used to model the frequency of appearance of the patterns contained in images as power law distributions. The use of these models allows to characterize the structural complexity of image textures. This complexity measure indicates a perceptually salient region in the image. The image is first partitioned into sub-images that are to be compared in some sense. Zipf or inverse Zipf law are applied to these sub-images and they are classified according to the characteristics of the power law models involved. The classification method consists in representing the characteristics of the Zipf and inverse Zipf model of each sub-image by a point in a representation space in which a clustering process is performed. Our method allows detection of regions of interest which are consistent with human perception, inverse Zipf law is particularly significant. This method has good performances compared to more classical detection methods. Alternatively, a neural network can be used for the classification phase

Zipf Analysis of Audio Signals

International audienceThis paper deals with several of the possible uses of Zipf and inverse Zipf laws in the field of audio signal analysis. We show that these laws are powerful analysis tools allowing the extraction of information not available by standard methods. The adaptation of Zipf and inverse Zipf laws to audio signals requires a coding of these signals into text-like data, considered as sequences of patterns. Because these codings are of first importance since they have to bring to the fore relevant information within signals, three types of codings have been developed, depending on the representation of the audio signal it is based on: temporal, frequential and time-scale representations. Once audio signal has been coded, features linked to Zipf and inverse Zipf approaches are computed. Finally, the classification step aims at the identification of signals. Four classification methods have been considered as well as a fusion method that combines these classifiers. In order to evaluate our method, we apply it on medical acoustical signals. They occur when swallowing and contain xiphoidal sounds. The problem is to extract and characterize xiphoidal sounds according to the gastro-oesophageal reflux pathological state. The aim is to help medical doctors to characterize and diagnose this pathology, and to give, in the end, a decision help tool as efficient as possible

Inner structure computation for audio signal analysis

International audienceWe present in this paper an audio signal classification method based on Zipf and inverse Zipf laws. These laws are powerful analysis tools allowing the extraction of information not available by the way of standard methods. The adaptation of Zipf and Inverse Zipf laws to audio signals requires a coding of these signals into literary texts, considered as sequences of patterns. Because these codings are of first importance since they have to bring to the fore relevant information in signals, three types of codings have been developed, depending on the representation of the audio signal it is based on: temporal, frequential and time-scale representations. Once audio signals have been coded, features linked to Zipf and inverse Zipf laws are computed. Finally, the classification step aims at the identification of signals. Four classification methods have been considered as well as a fusion method used to combine these classifiers. In order to evaluate our method, we have analysed medical signals corresponding to swallowing signals containing xiphoidal sounds. The problem is to characterize them according to the gastro-oesophageal reflux pathological state

Analyse de signaux vidéos et sonores (application à l'étude de signaux médicaux)

The work deals with the study of multimedia sequences containing images and sounds. The analysis of images sequences consists in the tracking of moving objects in order to allow the study of their properties. The investigations have to enable the understanding of sounds when correlated to events in the image sequence. One generic method, based on the combination of regions and contours tracking, and one method adapted to homogeneous objects, based on level set theory, are proposed. The analysis of audio data consists in the development of an identification system based on the study of the structure of signals thanks to their coding and Zipf laws modeling. These methods have been evaluated on medical sequences within the framework of the gastro-oesophageal reflux pathology study, in collaboration with the Acoustique et Motricité Digestive research team of the University of Tours.La problématique considérée concerne l'étude de séquences multimédia constituées d'images et de sons dont il s'agit d'étudier les corrélations de manière à aider à la compréhension de l'origine des bruits. L'analyse des séquences d'images consiste à suivre les objets en mouvement de manière à permettre leur étude. Une méthode générique, reposant sur une combinaison de suivi de régions et de contours, et une méthode adaptée aux objets homogènes, reposant sur la théorie des ensembles de niveaux, sont proposées. L'analyse des données sonores consiste en l'élaboration d'un système d'identification reposant sur des données sonores consiste en l'élaboration d'un système d'identification reposant sur l'étude de la structure des signaux grâce à des codages adaptés et à leur modélisation par les lois de Zipf. Ces méthodes ont été évaluées sur des séquences acoustico-radiologiques dans le cadre de l'étude de la pathologie du reflux gastro-oesophagien, en collaboration avec l'équipe Acoustique et Motricité Digestive de l'Université de Tours.TOURS-BU Sciences Pharmacie (372612104) / SudocTOURS-Polytech'Informat.Product. (372612209) / SudocPARIS-BIUP (751062107) / SudocSudocFranceF