2,581 research outputs found

    On the rise and fall of networked societies

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    We review recent results on the dynamics of social networks which suggest that the interplay between the network formation process and volatility may lead to the occurrence of discontinuous phase transitions and phase coexistence in a large class of models. We then investigate the effects of negative links -- links inhibiting local growth of the network -- and of a geographical distribution of the agents in such models. We show, by extensive numerical simulations, that both effects enhance this phenomenology, i.e. it increases the size of the coexistence region.Comment: 6 pages, 4 figures, Proceedings of Granada Workshop 200

    Absolute differential cross sections for electron-impact excitation of CO near threshold: II. The Rydberg states of CO

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    Absolute differential cross sections for electron-impact excitation of Rydberg states of CO have been measured from threshold to 3.7 eV above threshold and for scattering angles between 20° and 140°. Measured excitation functions for the b 3Σ+, B 1Σ+ and E 1π states are compared with cross sections calculated by the Schwinger multichannel method. The behaviour of the excitation functions for these states and for the j 3Σ+ and C 1Σ+ states is analysed in terms of negative-ion states. One of these resonances has not been previously reported

    Faster PET reconstruction with non-smooth priors by randomization and preconditioning

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    Uncompressed clinical data from modern positron emission tomography (PET) scanners are very large, exceeding 350 million data points (projection bins). The last decades have seen tremendous advancements in mathematical imaging tools many of which lead to non-smooth (i.e. non-differentiable) optimization problems which are much harder to solve than smooth optimization problems. Most of these tools have not been translated to clinical PET data, as the state-of-the-art algorithms for non-smooth problems do not scale well to large data. In this work, inspired by big data machine learning applications, we use advanced randomized optimization algorithms to solve the PET reconstruction problem for a very large class of non-smooth priors which includes for example total variation, total generalized variation, directional total variation and various different physical constraints. The proposed algorithm randomly uses subsets of the data and only updates the variables associated with these. While this idea often leads to divergent algorithms, we show that the proposed algorithm does indeed converge for any proper subset selection. Numerically, we show on real PET data (FDG and florbetapir) from a Siemens Biograph mMR that about ten projections and backprojections are sufficient to solve the MAP optimisation problem related to many popular non-smooth priors; thus showing that the proposed algorithm is fast enough to bring these models into routine clinical practice

    XPS Investigations of Ruthenium Deposited onto Representative Inner Surfaces of Nuclear Reactor Containment Buildings

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    International audienceIn the case of a hypothetical severe accident in a nuclear power plant, interactions of gaseous RuO4 with reactor containment building surfaces (stainless steel and epoxy paint) could possibly lead to a black Ru-containing deposit on these surfaces. Some scenarios include the possibility of formation of highly radiotoxic RuO4(g) by the interactions of these deposits with the oxidising medium induced by air radiolysis, in the reactor containment building, and consequently dispersion of this species. Therefore, the accurate determination of the chemical nature of ruthenium in the deposits is of the high importance for safety studies. An experiment was designed to model the interactions of RuO4(g) with samples of stainless steel and of steel covered with epoxy paint. Then, these deposits have been carefully characterised by scanning electron microscopy (SEM/EDS), electron probe microanalysis (EPMA) and X-ray photoelectron spectroscopy (XPS). The analysis by XPS of Ru deposits formed by interaction of RuO4(g), revealed that the ruthenium is likely to be in the IV oxidation state, as the shapes of the Ru3d core levels are very similar with those observed on the RuO2,xH2O reference powder sample. The analysis of O1s peaks indicates a large component attributed to the hydroxyl functional groups. From these results, it was concluded that Ru was present on the surface of the deposits as an oxyhydroxide of Ru(IV). It has also to be pointed out that the presence of “pure” RuO2, or of a thin layer of RuO3 or Ru2O5, coming from the decomposition of RuO4 on the surface of samples of stainless steel and epoxy paint, could be ruled out. These findings will be used for further investigations of the possible revolatilisation phenomena induced by ozone

    Genetic evidence that cellulose synthase activity influences microtubule cortical array organization

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    To identify factors that influence cytoskeletal organization we screened for Arabidopsis ( Arabidopsis thaliana) mutants that show hypersensitivity to the microtubule destabilizing drug oryzalin. We cloned the genes corresponding to two of the 131 mutant lines obtained. The genes encoded mutant alleles of PROCUSTE1 and KORRIGAN, which both encode proteins that have previously been implicated in cellulose synthesis. Analysis of microtubules in the mutants revealed that both mutants have altered orientation of root cortical microtubules. Similarly, isoxaben, an inhibitor of cellulose synthesis, also altered the orientation of cortical microtubules while exogenous cellulose degradation did not. Thus, our results substantiate that proteins involved in cell wall biosynthesis influence cytoskeletal organization and indicate that this influence on cortical microtubule stability and orientation is correlated with cellulose synthesis rather than the integrity of the cell wall

    Decrypting Integrins by Mixed-Solvent Molecular Dynamics Simulations

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    Integrins are a family of α/β heterodimeric cell surface adhesion receptors which are capable of transmitting signals bidirectionally across membranes. They are known for their therapeutic potential in a wide range of diseases. However, the development of integrin-targeting medications has been impacted by unexpected downstream effects including unwanted agonist-like effects. Allosteric modulation of integrins is a promising approach to potentially overcome these limitations. Applying mixed-solvent molecular dynamics (MD) simulations to integrins, the current study uncovers hitherto unknown allosteric sites within the integrin α I domains of LFA-1 (αLβ2; CD11a/CD18), VLA-1 (α1β1; CD49a/CD29), and Mac-1 (αMβ2, CD11b/CD18). We show that these pockets are putatively accessible to small-molecule modulators. The findings reported here may provide opportunities for the design of novel allosteric integrin inhibitors lacking the unwanted agonism observed with earlier as well as current integrin-targeting drugs.</p

    Deep learning as optimal control problems

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    We briefly review recent work where deep learning neural networks have been interpreted as discretisations of an optimal control problem subject to an ordinary differential equation constraint. We report here new preliminary experiments with implicit symplectic Runge-Kutta methods. In this paper, we discuss ongoing and future research in this area
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