University of Mons

About: University of Mons is a education organization based out in Mons, Belgium. It is known for research contribution in the topics: Large Hadron Collider & Standard Model. The organization has 3073 authors who have published 9465 publications receiving 294776 citations.

Free radical scavenging by natural polyphenols: atom versus electron transfer.

Abstract: Polyphenols (synthetically modified or directly provided by human diet) scavenge free radicals by H-atom transfer and may thus decrease noxious effects due to oxidative stress. Free radical scavenging by polyphenols has been widely theoretically studied from the thermodynamic point of view whereas the kinetic point of view has been much less addressed. The present study describes kinetic-based structure–activity relationship for quercetin. This compound is very characteristic of the wide flavonoid subclass of polyphenols. H-atom transfer is a mechanism based on either atom or electron transfer. This is analyzed here by quantum chemical calculations, which support the knowledge acquired from experimental studies. The competition between the different processes is discussed in terms of the nature of the prereaction complexes, the pH, the formation of activated-deprotonated forms, and the atom- and electron-transfer efficiency. The role of the catechol moiety and the 3-OH group of quercetin as scavengers of ...

Redox States of Long Oligothiophenes: Two Polarons on a Single Chain

Abstract: Can two isolated radical cations (polarons) exist simultaneously on a π-conjugated chain or do they coalesce into a single, doubly charged spinless (bipolaron) deformation? This long-standing question, fundamental to charge transport in conducting polymers, is now resolved by an investigation of the redox states of long oligothiophenes (below) in solution. In contrast to short oligothiophenes, for long oligothiophene dications two individual polarons prevail because of the decrease in Coulomb repulsion energy obtained by moving the two charges apart.

The impact of molecular data on our understanding of bee phylogeny and evolution.

Abstract: Our understanding of bee phylogeny has improved over the past fifteen years as a result of new data, primarily nucleotide sequence data, and new methods, primarily model-based methods of phylogeny reconstruction. Phylogenetic studies based on single or, more commonly, multilocus data sets have helped resolve the placement of bees within the superfamily Apoidea; the relationships among the seven families of bees; and the relationships among bee subfamilies, tribes, genera, and species. In addition, molecular phylogenies have played an important role in inferring evolutionary patterns and processes in bees. Phylogenies have provided the comparative framework for understanding the evolution of host-plant associations and pollen specialization, the evolution of social behavior, and the evolution of parasitism. In this paper, we present an overview of significant discoveries in bee phylogeny based primarily on the application of molecular data. We review the phylogenetic hypotheses family-by-family and then describe how the new phylogenetic insights have altered our understanding of bee biology.

Measurement of the differential cross section for top quark pair production in pp collisions at √s=8 TeV

Abstract: The normalized differential cross section for top quark pair (tt) production is measured in pp collisions at a centre-of-mass energy of 8TeV at the CERN LHC using the CMS detector in data corresponding to an integrated luminosity of 19.7fb^(−1). The measurements are performed in the lepton+jets (e/μ +jets) and in the dilepton (e^+e^−, μ^+μ^−, and e^±μ^∓) decay channels. The tt cross section is measured as a function of the kinematic properties of the charged leptons, the jets associated to b quarks, the top quarks, and the tt system. The data are compared with several predictions from perturbative quantum chromodynamic up to approximate next-to-next-to-leading-order precision. No significant deviations are observed relative to the standard model predictions.