288 research outputs found

    Intelligent optical performance monitor using multi-task learning based artificial neural network

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    An intelligent optical performance monitor using multi-task learning based artificial neural network (MTL-ANN) is designed for simultaneous OSNR monitoring and modulation format identification (MFI). Signals' amplitude histograms (AHs) after constant module algorithm are selected as the input features for MTL-ANN. The experimental results of 20-Gbaud NRZ-OOK, PAM4 and PAM8 signals demonstrate that MTL-ANN could achieve OSNR monitoring and MFI simultaneously with higher accuracy and stability compared with single-task learning based ANNs (STL-ANNs). The results show an MFI accuracy of 100% and OSNR monitoring root-mean-square error of 0.63 dB for the three modulation formats under consideration. Furthermore, the number of neuron needed for the single MTL-ANN is almost the half of STL-ANN, which enables reduced-complexity optical performance monitoring devices for real-time performance monitoring

    The K1,2K_{1,2}-structure-connectivity of graphs

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    In this paper, we mainly investigate K1,2K_{1,2}-structure-connectivity for any connected graph. Let GG be a connected graph with nn vertices, we show that κ(G;K1,2)\kappa(G; K_{1,2}) is well-defined if diam(G)≥4diam(G)\geq 4, or n≡1(mod3)n\equiv 1\pmod 3, or G∉{C5,Kn}G\notin \{C_{5},K_{n}\} when n≡2(mod3)n\equiv 2\pmod 3, or there exist three vertices u,v,wu,v,w such that NG(u)∩(NG(v,w)∪{v,w})=∅N_{G}(u)\cap (N_{G}(v,w)\cup\{v,w\})=\emptyset when n≡0(mod3)n\equiv 0\pmod 3. Furthermore, if GG has K1,2K_{1,2}-structure-cut, we prove κ(G)/3≤κ(G;K1,2)≤κ(G)\kappa(G)/3\leq\kappa(G; K_{1,2})\leq\kappa(G).Comment: 18 pages,15 figure

    Modulation of Androgen Receptor by FOXA1 and FOXO1 Factors in Prostate Cancer

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    © Ivyspring International Publisher. This is an open-access article distributed under the terms of the Creative Commons Licens

    New Chinese Facilities for Short-Range Correlation Physics

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    This article explores the significant advancements in Short-Range Correlation (SRC) research enabled by the latest Chinese nuclear physics facilities- CSR at HIRFL, HIAF, SHINE, and the upcoming EicC. These facilities introduce cutting-edge technologies and methodologies, addressing existing challenges and broadening the scope for SRC studies. By providing detailed insights into the capabilities and expected contributions of each facility, the paper highlights China's emerging role in the global nuclear physics landscape. The collaborative potential, alongside complementary global efforts, positions these facilities to deeply influence our understanding of nuclear matter's fundamental properties and interactions.Comment: 16 pages, 14 figures, to be submitted to EPJA Topical Collection: Short-Range Correlations and the EMC Effec
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