4,817 research outputs found

    Could the 21-cm absorption be explained by the dark matter suggested by 8^8Be transitions?

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    The stronger than expected 21-cm absorption was observed by EDGES recently, and another anomaly of 8^8Be transitions would be signatures of new interactions. These two issues may be related to each other, e.g., pseudoscalar AA mediated fermionic millicharged dark matter (DM), and the 21-cm absorption could be induced by photon mediated scattering between MeV millicharged DM and hydrogen. This will be explored in this paper. For fermionic millicharged DM χˉχ\bar{\chi} \chi with masses in a range of 2mA<2mχ<3mA2 m_A < 2 m_{\chi} < 3 m_A, the p-wave annihilation χˉχ→AA\bar{\chi} \chi \to A A would be dominant during DM freeze-out. The s-wave annihilation χˉχ\bar{\chi} \chi →A,γ\to A, \gamma →e+e−\to e^+ e^- is tolerant by constraints from CMB and the 21-cm absorption. The millicharged DM can evade constraints from direct detection experiments. The process of K+→π+π0K^+ \to \pi^+ \pi^0 with the invisible decay π0→χˉχ\pi^0 \to \bar{\chi} \chi could be employed to search for the millicharged DM, and future high intensity K+K^+ sources, such as NA62, will do the job.Comment: 6 pages, 2 figures, the accepted version, EPJ

    Multifractal analysis of weighted networks by a modified sandbox algorithm

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    Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks.First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): "Sierpinski" WFNs and "Cantor dust" WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply the SBw algorithm to study multifractal properties of some real weighted networks ---collaboration networks. It is found that the multifractality exists in these weighted networks, and is affected by their edge-weights.Comment: 15 pages, 6 figures. Accepted for publication by Scientific Report

    Numerical study on the effect of welding and heating treatments on strength of high strength steel column

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    [EN] High strength steel box columns are usually fabricated from steel slab by applying welding. The welding process can introduce residual stresses and geometric imperfections into the columns and influence the column strength. In this study, a numerical investigation on the behavior of high strength steel thin-walled box columns under the compression force was carried out. The welding processes were firstly simulated with commercial package ABAQUS in this study to find out the residual stress distributions in high strength steel box column. After that, the column behaviors under the compression were modelled with predefined field from the previous step. The effect of the welding process (including flux-core arc welding and submerged arc welding), heating treatment (including preheating and post-weld heat treatment) and geometrical imperfection on the residual stress field and box column strength was investigated and discussed.Jin, J.; Bao, W.; Liu, J.; Peng, Z. (2018). Numerical study on the effect of welding and heating treatments on strength of high strength steel column. En Proceedings of the 12th International Conference on Advances in Steel-Concrete Composite Structures. ASCCS 2018. Editorial Universitat Politècnica de València. 667-673. https://doi.org/10.4995/ASCCS2018.2018.8370OCS66767
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