One-loop Electroweak and QCD corrections to vector boson scattering into top pairs and application to ILC

We calculate the electroweak and QCD corrections to W-W+ -> tt and ZZ -> tt. We also consider the interplay of these corrections with the effect of anomalous interactions that affect the massive weak bosons and the top. The results at the VV level fusion are convoluted with the help of the effective vector boson approximation to give predictions for a high energy e+e- collider.Comment: 19 pages, 27 figure

Thoracocervicofacial Emphysema after Heimlich's Maneuvre.

We report an extremely rare example of a thoracocervicofacial subcutaneous emphysema after Heimlich maneuver case

Relationship Between Oxidative Stress and Anxiety: Emerging Role of Antioxidants Within Therapeutic or Preventive Approaches

International audienc

Dietary Derived Antioxidants: Implications on Health

International audienc

Oxidative stress and anxiety: Relationship and cellular pathways

High O2 consumption, modest antioxidant defenses and a lipid-rich constitution make the brain highly vulnerable to redox imbalances. Oxidative damage in the brain causes nervous system impairment. Recently, oxidative stress has also been implicated in depression, anxiety disorders and high anxiety levels. The findings which establish a link between oxidative stress and pathological anxiety have inspired a number of other recent studies focusing on the link between oxidative status and normal anxiety and also on a possible causal relationship between cellular oxidative stress and emotional stress. This review examines the recent discoveries made on the link between oxidative status and normal anxiety levels and the putative role of oxidative stress in genesis of anxiety. We discuss the different opinions and questions that exist in the field and review the methodological approaches that are being used to determine a causal relationship between oxidative and emotional stress

Le vêtement féminin dans la littérature Maghrébine, simple artifice ou révélation de soi ?

Women's Clothing in North African Literature, Simple Artifice or Self-Revelation? ABSTRACT: Contemporary literature has shown particular interest in the symbolism of being, object and clothing. It is built on symbols linked to culture to justify a form of ideology in search of a status and a political, cultural, social identity, etc. This is why the representation of the body and especially of women in contemporary North African novels of French expression are part of a thematic axis which converges towards this Ideology of the quest for Self and identity. Among the different literary genres, women writing has always been a quest for identity and a perpetual search for origins. In this article, it will be a question of seeing how women clothing becomes an indicator of identity and social representations through selected texts taken from female North African novels. RÉSUMÉ : La littérature contemporaine a porté un intérêt particulier pour la symbolique de l’être, de l’objet et du vêtement. Elle s’est bâtie sur des symboles liés à la culture pour justifier une forme d’idéologie en quête d’un statut et d’une identité, politique, culturelle, sociale, etc. C’est pourquoi, la représentation du corps et surtout de la femme dans les romans maghrébins contemporains d’expression française font partie d’un axe thématique qui converge vers cette Idéologie de la quête de Soi et de l’identité. Parmi les différents genres littéraires, l’écriture féminine a de tout temps été une quête de l’identité et une perpétuelle recherche d’origines. Il s’agira dans cet article, de voir comment le vêtement féminin devient un indicateur de représentations identitaires et sociales à travers des textes choisis pris de romans Maghrébins féminins.  

Sampling From Autoencoders' Latent Space via Quantization And Probability Mass Function Concepts

In this study, we focus on sampling from the latent space of generative models built upon autoencoders so as the reconstructed samples are lifelike images. To do to, we introduce a novel post-training sampling algorithm rooted in the concept of probability mass functions, coupled with a quantization process. Our proposed algorithm establishes a vicinity around each latent vector from the input data and then proceeds to draw samples from these defined neighborhoods. This strategic approach ensures that the sampled latent vectors predominantly inhabit high-probability regions, which, in turn, can be effectively transformed into authentic real-world images. A noteworthy point of comparison for our sampling algorithm is the sampling technique based on Gaussian mixture models (GMM), owing to its inherent capability to represent clusters. Remarkably, we manage to improve the time complexity from the previous $\mathcal{O}(n\times d \times k \times i)$ associated with GMM sampling to a much more streamlined $\mathcal{O}(n\times d)$, thereby resulting in substantial speedup during runtime. Moreover, our experimental results, gauged through the Fr\'echet inception distance (FID) for image generation, underscore the superior performance of our sampling algorithm across a diverse range of models and datasets. On the MNIST benchmark dataset, our approach outperforms GMM sampling by yielding a noteworthy improvement of up to $0.89$ in FID value. Furthermore, when it comes to generating images of faces and ocular images, our approach showcases substantial enhancements with FID improvements of $1.69$ and $0.87$ respectively, as compared to GMM sampling, as evidenced on the CelebA and MOBIUS datasets. Lastly, we substantiate our methodology's efficacy in estimating latent space distributions in contrast to GMM sampling, particularly through the lens of the Wasserstein distance