3,781 research outputs found

    Thermodynamics in the universe described by the emergence of the space and the energy balance relation

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    It has previously been shown that it is more general to describe the evolution of the universe based on the emergence of the space and the energy balance relation. Here we investigate the thermodynamic properties of the universe described by such a model. We show that the first law of thermodynamics and the generalized second law of thermodynamics (GSLT) are both satisfied and the weak energy condition are also fulfilled for two typical examples. Finally we examine the physical consistency for the present model.Comment: 9 pages, 2 figure

    Social Network Analysis for Online Knowledge Exchange Platform: Evidence from Zhihu

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    The knowledge exchange platform is an innovative way that empowers online learning for the Internet users to utilize their spare time slots for knowledge sharing and seeking. Many researchers have conducted research on the user interaction and content of the knowledge payment platform. This paper analyzes the user interaction and user comments by analyzing the data of Zhihu live, a major online knowledge exchange platform in China. We employ social network analysis and deep learning method to explore the users’ interaction structure in Zhihu live platform and their emotional tendency for knowledge exchange. Particularly, we use social network analysis theory supplemented by social analysis tools Gephi and neural network algorithm, LSTM to achieve our goals. We propose a set of hypotheses from the perspective of a small world phenomenon and users’ social engagement in the platform. Our results show that there is a small world phenomenon on core topics and the more frequent users interaction is, the more positive the users’ comments are. Theoretically, this study explores the users’ knowledge seeking and sharing behavior from the perspective of user interaction and user emotion. Also, our research offers implications to practice that enhancing sociality can be an effective strategy to motivate the desirable users’ paid knowledge sharing behaviors in the platform

    Rotation-invariant features for multi-oriented text detection in natural images.

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    Texts in natural scenes carry rich semantic information, which can be used to assist a wide range of applications, such as object recognition, image/video retrieval, mapping/navigation, and human computer interaction. However, most existing systems are designed to detect and recognize horizontal (or near-horizontal) texts. Due to the increasing popularity of mobile-computing devices and applications, detecting texts of varying orientations from natural images under less controlled conditions has become an important but challenging task. In this paper, we propose a new algorithm to detect texts of varying orientations. Our algorithm is based on a two-level classification scheme and two sets of features specially designed for capturing the intrinsic characteristics of texts. To better evaluate the proposed method and compare it with the competing algorithms, we generate a comprehensive dataset with various types of texts in diverse real-world scenes. We also propose a new evaluation protocol, which is more suitable for benchmarking algorithms for detecting texts in varying orientations. Experiments on benchmark datasets demonstrate that our system compares favorably with the state-of-the-art algorithms when handling horizontal texts and achieves significantly enhanced performance on variant texts in complex natural scenes

    Topology and Criticality in Resonating Affleck-Kennedy-Lieb-Tasaki loop Spin Liquid States

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    We exploit a natural Projected Entangled-Pair State (PEPS) representation for the resonating Affleck-Kennedy-Lieb-Tasaki loop (RAL) state. By taking advantage of PEPS-based analytical and numerical methods, we characterize the RAL states on various two-dimensional lattices. On square and honeycomb lattices, these states are critical since the dimer-dimer correlations decay as a power law. On kagome lattice, the RAL state has exponentially decaying correlation functions, supporting the scenario of a gapped spin liquid. We provide further evidence that the RAL state on the kagome lattice is a Z2\mathbb{Z}_2 spin liquid, by identifying the four topological sectors and computing the topological entropy. Furthermore, we construct a one-parameter family of PEPS states interpolating between the RAL state and a short-range Resonating Valence Bond state and find a critical point, consistent with the fact that the two states belong to two different phases. We also perform a variational study of the spin-1 kagome Heisenberg model using this one-parameter PEPS.Comment: 10 pages, 14 figures, published versio
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