Unique quantitative Symbiodiniaceae signature of coral colonies revealed through spatio-temporal survey in Moorea

One of the mechanisms of rapid adaptation or acclimatization to environmental changes in corals is through the dynamics of the composition of their associated endosymbiotic Symbiodiniaceae community. The various species of these dinoflagellates are characterized by different biological properties, some of which can confer stress tolerance to the coral host. Compelling evidence indicates that the corals' Symbiodiniaceae community can change via shuffling and/or switching but the ecological relevance and the governance of these processes remain elusive. Using a qPCR approach to follow the dynamics of Symbiodiniaceae genera in tagged colonies of three coral species over a 10-18 month period, we detected putative genus-level switching of algal symbionts, with coral species-specific rates of occurrence. However, the dynamics of the corals' Symbiodiniaceae community composition was not driven by environmental parameters. On the contrary, putative shuffling event were observed in two coral species during anomalous seawater temperatures and nutrient concentrations. Most notably, our results reveal that a suit of permanent Symbiodiniaceae genera is maintained in each colony in a specific range of quantities, giving a unique 'Symbiodiniaceae signature' to the host. This individual signature, together with sporadic symbiont switching may account for the intra-specific differences in resistance and resilience observed during environmental anomalies

Anti-viral RNA silencing: do we look like plants ?

The anti-viral function of RNA silencing was first discovered in plants as a natural manifestation of the artificial 'co-suppression', which refers to the extinction of endogenous gene induced by homologous transgene. Because silencing components are conserved among most, if not all, eukaryotes, the question rapidly arose as to determine whether this process fulfils anti-viral functions in animals, such as insects and mammals. It appears that, whereas the anti-viral process seems to be similarly conserved from plants to insects, even in worms, RNA silencing does influence the replication of mammalian viruses but in a particular mode: micro(mi)RNAs, endogenous small RNAs naturally implicated in translational control, rather than virus-derived small interfering (si)RNAs like in other organisms, are involved. In fact, these recent studies even suggest that RNA silencing may be beneficial for viral replication. Accordingly, several large DNA mammalian viruses have been shown to encode their own miRNAs. Here, we summarize the seminal studies that have implicated RNA silencing in viral infection and compare the different eukaryotic responses

Extraction et analyse de l'impact émotionnel des images

Session "Articles"National audienceCet article propose une méthode d'extraction de l'impact émotionnel des images à partir de descripteurs récents. Très souvent, on associe les émotions à l'expression du visage, mais nous avons décidé de ne pas faire de cette information la principale information émotionnelle des images naturelles, qui en général ne contiennent pas de visages. Nous avons ainsi effectué nos tests sur une base diversifiée, construite à partir d'images à faible contenu sémantique. La complexité des émotions a été prise en compte en intégrant, au processus de classification, les résultats de tests psycho-visuels que nous avons mis en place. Vingt cinq observateurs ont participé aux tests. Ils ont évalué la nature et la puissance des émotions ressenties. Nous avons choisi un réseau de neurones multicouches pour la classification. Le taux de réussite moyen obtenu lors de la classification est de 56,15% ; ce qui est encourageant au regard des résultats de la littérature

Extraction of emotional impact in colour images

International audienceThis paper proposes a method to extract the emotional impact of images. Emotions are often associated with facial expressions, but we decided consider other features as first emotional characteristic of natural images, which, in general, does not contain faces. For a seek of generally we have built a new image database composed of a large variety of low semantic images. We used colour images because often colours and emotions are supposed to be linked. For the modelling of the emotions, we considered colours features completed with other recent and efficient descriptors. We supposed that different features used could also implicitly encode high-level information about emotions. The concept of emotion is not easy to model. The perception of emotion is not only influenced by the content and the colour of the images. It is also modified by some personal experiences like cultural aspects and personal semantic associated to some colours or objects. The complexity of emotion modelling was considered in classification process through psycho-visual tests. The twenty-five observers assessed the nature and the power of emotions they felt. These tests allowed us to distinguish three classes of emotions, which are "Negative", "Neutral" and "Positive" emotions. We used a Support Vector Machine for classification and the average success rate is 51,75%; that is really relevant regarding the equivalent results in the literature

Extraction de l'impact émotionnel des images

International audienceCet article propose une méthode d'extraction de l'impact émotionnel des images à partir de descripteurs bas niveau. Nous avons émis l'hypothèse que la précision de ces derniers encoderait des informations haut niveau intéressantes voire discriminantes pour les émotions. Il n'existe à ce jour aucun descripteur particulièrement adapté à l'étude de l'impact émotionnel des images. Les émotions ressenties dépendent, en effet, de plusieurs informations dans l'image mais également de sa nature (très sémantique ou non) ou encore de la durée d'observation. Plus ce temps est long plus l'interprétation sémantique de l'image prend le dessus sur l'émotion " primaire ". À ces descripteurs nous avons associé deux classifieurs performants, particulièrement adaptés à des discriminations d'informations complexes. Il s'agit d'un réseau de neurones multicouche et d'un SVM dans son extension multiclasse basée sur la stratégie " un contre un ". Très souvent, on associe les émotions à l'expression du visage, mais nous avons décidé de ne pas faire de cette information la principale caractéristique émotionnelle des images naturelles, qui en général ne contiennent pas de visages. Nous avons, à cet effet, effectué nos tests sur une base diversifiée de 350 images, construite à partir d'images à faible contenu sémantique. Notre choix de descripteurs est basé sur des supposés liens entre les émotions et le contenu des images mais également sur la précision qu'offrent certains descripteurs de traitement d'images en indexation ou en catégorisation. La complexité des émotions a été prise en compte en intégrant, au processus de classification, les résultats de tests psychovisuels que nous avons mis en place. Nous avons défini trois classes d'émotions. Les taux de réussite moyens obtenus lors de la classification sont de 56,15 % pour le réseau de neurones et 55,25 % pour le SVM. Ces résultats sont encourageants au regard des résultats de la littérature. Ces tests confirment aussi l'hypothèse que les descripteurs choisis sont complémentaires dans notre processus d'extraction des émotions

Gender influences on subjective evaluations in images

International audienceThis paper proposes to study gender influences on subjective evaluations in images. Our goal is to verify if some common conclusions in psychology experiences are confirmed during the subjective evaluations we organized. Our database and our test strategy are the main originalities of this work. We built a new low semantic images database, composed of 350 natural images. The tests were accessible via the Internet and each participant rated 24 randomly selected images. 1741 participants, including 848 men (48.71%) and 893 women (51.29%) assessed our 350 images according to the nature and the power of the emotion. We also ask them to quick evaluate each image (under10 seconds) to have really their "primary" emotions. During the analysis of the results of the tests, we observed that women tend to associate more often positive or negative emotions to images than men who consider those images as neutral. The additional neutral ones scored by men are generally classified positive or negative by women. In fact, women scored positive with the low power some images men scored neutral. These results confirm potential differences in gender emotion evaluations and also the common conclusion that women express more emotions than men

Statistical region-based active contours for segmentation: an overview

International audienceIn this paper we propose a brief survey on geometric variational approaches and more precisely on statistical region-based active contours for medical image segmentation. In these approaches, image features are considered as random variables whose distribution may be either parametric, and belongs to the exponential family, or non-parametric estimated with a kernel density method. Statistical region-based terms are listed and reviewed showing that these terms can depict a wide spectrum of segmentation problems. A shape prior can also be incorporated to the previous statistical terms. A discussion of some optimization schemes available to solve the variational problem is also provided. Examples on real medical images are given to illustrate some of the given criteria

Statistical region-based active contours with exponential family observations

In this paper, we focus on statistical region-based active contour models where image features (e.g. intensity) are random variables whose distribution belongs to some parametric family (e.g. exponential) rather than confining ourselves to the special Gaussian case. Using shape derivation tools, our effort focuses on constructing a general expression for the derivative of the energy (with respect to a domain) and derive the corresponding evolution speed. A general result is stated within the framework of multi-parameter exponential family. More particularly, when using Maximum Likelihood estimators, the evolution speed has a closed-form expression that depends simply on the probability density function, while complicating additive terms appear when using other estimators, e.g. moments method. Experimental results on both synthesized and real images demonstrate the applicability of our approach.Comment: 4 pages, ICASSP 200

Statistical region-based active contours with exponential family observations

International audienceIn this paper, we focus on statistical region-based active contour models where image features (e.g. intensity) are random variables whose distribution belongs to some parametric family (e.g. exponential) rather than confining ourselves to the special Gaussian case. Using shape derivation tools, our effort focuses on constructing a general expression for the derivative of the energy (with respect to a domain) and derive the corresponding evolution speed. A general result is stated within the framework of multi-parameter exponential family. More particularly, when using Maximum Likelihood estimators, the evolution speed has a closed-form expression that depends simply on the probability density function, while complicating additive terms appear when using other estimators, e.g. momentsmethod. Experimental results on both synthesized and real images demonstrate the applicability of our approach