21,042 research outputs found

    A new small satellite sunspot triggering recurrent standard- and blowout-coronal jets

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    In this paper,we report a detailed analysis of recurrent jets originated from a location with emerging, canceling and converging negative magnetic field at the east edge of NOAA active region AR11166 from 2011 March 09 to 10. The event presented several interesting features. First, a satellite sunspot appeared and collided with a pre-existing opposite polarity magnetic field and caused a recurrent solar jet event. Second, the evolution of the jets showed blowout-like nature and standard characteristics. Third, the satellite sunspot exhibited a motion toward southeast of AR11166 and merged with the emerging flux near the opposite polarity sunspot penumbra, which afterward, due to flux convergence and cancellation episodes, caused recurrent jets. Fourth, three of the blowout jets associated with coronal mass ejections (CMEs), were observed from field of view of the Solar Terrestrial Relations Observatory. Fifth, almost all the blowout jet eruptions were accompanied with flares or with more intense brightening in the jet base region, while almost standard jets did not manifest such obvious feature during eruptions. The most important, the blowout jets were inclined to faster and larger scale than the standard jets. The standard jets instead were inclined to relative longer-lasting. The obvious shearing and twisting motions of the magnetic field may be interpreted as due to the shearing and twisting motions for a blowout jet eruption. From the statistical results, about 30% blowout jets directly developed into CMEs. It suggests that the blowout jets and CMEs should have a tight relationship.Comment: ApJ 18 pages, 7 figure

    Microstructure and Fe-vacancy ordering in the KFexSe2 superconducting system

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    Structural investigations by means of transmission electron microscopy (TEM) on KFexSe2 with 1.5 \leq x \leq 1.8 have revealed a rich variety of microstructure phenomena, the KFe1.5Se2 crystal often shows a superstructure modulation along the [310] zone-axis direction, this superstructure can be well interpreted by the Fe-vacancy order within the a-b plane. Increase of Fe-concentration in the KFexSe2 materials could not only result in the appearance of superconductivity but also yield clear alternations of microstructure. Structural inhomogeneity, the complex superstructures and defect structures in the superconducting KFe1.8Se2 sample have been investigated based on the high-resolution TEM.Comment: 13 pages, 4 figure

    NMF-Based Comprehensive Latent Factor Learning with Multiview da

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    Multiview representations reveal the latent information of the data from different perspectives, consistency and complementarity. Unlike most multiview learning approaches, which focus only one perspective, in this paper, we propose a novel unsupervised multiview learning algorithm, called comprehensive latent factor learning (CLFL), which jointly exploits both consistent and complementary information among multiple views. CLFL adopts a non-negative matrix factorization based formulation to learn the latent factors. It learns the weights of different views automatically which makes the representation more accurate. Experiment results on a synthetic and several real datasets demonstrate the effectiveness of our approach

    Reversible Embedding to Covers Full of Boundaries

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    In reversible data embedding, to avoid overflow and underflow problem, before data embedding, boundary pixels are recorded as side information, which may be losslessly compressed. The existing algorithms often assume that a natural image has little boundary pixels so that the size of side information is small. Accordingly, a relatively high pure payload could be achieved. However, there actually may exist a lot of boundary pixels in a natural image, implying that, the size of side information could be very large. Therefore, when to directly use the existing algorithms, the pure embedding capacity may be not sufficient. In order to address this problem, in this paper, we present a new and efficient framework to reversible data embedding in images that have lots of boundary pixels. The core idea is to losslessly preprocess boundary pixels so that it can significantly reduce the side information. Experimental results have shown the superiority and applicability of our work
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