3,695 research outputs found

    Universal entanglement signatures of foliated fracton phases

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    Fracton models exhibit a variety of exotic properties and lie beyond the conventional framework of gapped topological order. In a previous work, we generalized the notion of gapped phase to one of foliated fracton phase by allowing the addition of layers of gapped two-dimensional resources in the adiabatic evolution between gapped three-dimensional models. Moreover, we showed that the X-cube model is a fixed point of one such phase. In this paper, according to this definition, we look for universal properties of such phases which remain invariant throughout the entire phase. We propose multi-partite entanglement quantities, generalizing the proposal of topological entanglement entropy designed for conventional topological phases. We present arguments for the universality of these quantities and show that they attain non-zero constant value in non-trivial foliated fracton phases.Comment: 17 pages, 7 figure

    Foliated fracton order in the checkerboard model

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    In this work, we show that the checkerboard model exhibits the phenomenon of foliated fracton order. We introduce a renormalization group transformation for the model that utilizes toric code bilayers as an entanglement resource, and show how to extend the model to general three-dimensional manifolds. Furthermore, we use universal properties distilled from the structure of fractional excitations and ground-state entanglement to characterize the foliated fracton phase and find that it is the same as two copies of the X-cube model. Indeed, we demonstrate that the checkerboard model can be transformed into two copies of the X-cube model via an adiabatic deformation.Comment: 8 pages, 9 figure

    Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification

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    Despite the steady progress in video analysis led by the adoption of convolutional neural networks (CNNs), the relative improvement has been less drastic as that in 2D static image classification. Three main challenges exist including spatial (image) feature representation, temporal information representation, and model/computation complexity. It was recently shown by Carreira and Zisserman that 3D CNNs, inflated from 2D networks and pretrained on ImageNet, could be a promising way for spatial and temporal representation learning. However, as for model/computation complexity, 3D CNNs are much more expensive than 2D CNNs and prone to overfit. We seek a balance between speed and accuracy by building an effective and efficient video classification system through systematic exploration of critical network design choices. In particular, we show that it is possible to replace many of the 3D convolutions by low-cost 2D convolutions. Rather surprisingly, best result (in both speed and accuracy) is achieved when replacing the 3D convolutions at the bottom of the network, suggesting that temporal representation learning on high-level semantic features is more useful. Our conclusion generalizes to datasets with very different properties. When combined with several other cost-effective designs including separable spatial/temporal convolution and feature gating, our system results in an effective video classification system that that produces very competitive results on several action classification benchmarks (Kinetics, Something-something, UCF101 and HMDB), as well as two action detection (localization) benchmarks (JHMDB and UCF101-24).Comment: ECCV 2018 camera read

    Pharmacokinetic study of thymol after intravenous injection and high-dose inhalation in mouse model.

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    Thymol is generally recognized as a safe substance by the FDA and has been widely used in the pharmaceutical, food, and cosmetic industries. Pharmacokinetic (PK) studies of thymol have been previously conducted for oral administration, but there has been no PK study for inhalation administration or intravenous (IV) injection. This study aims at exploring and comparing the inhalation and IV PK profile of thymol in a mouse model. The inhalation PK for mouse model was corrected with fur/skin absorption. Thirty-two male CD-1 mice were randomized into two study arms, Arm-A for intravenous (n = 16) and Arm-B for inhalation (n = 16). The amount of thymol in the mouse serum was measured for Arm-A and for Arm-B at the highest dose. Furthermore, 48 mice were utilized for fur/skin absorption of thymol. In total, 320 mouse serum samples for thymol were analyzed by LC/MS method. After inhalation, the peak concentration of thymol in mouse serum was 42.3 ng/mL (Cmax ) and occurred at 2 minutes (tmax ). The AUC of the inhaled thymol at 0-60 minutes (AUC0-60) was 464 ng/mL/min. From 10-60 minutes post-dose, the PK inhalation curve appeared to be higher than that for the IV injection. This is likely attributed to the effect of absorption of thymol through the fur/skin of mice. After an adjustment by fur/skin absorption, the PK profile for net inhalation closely matched the two-compartment model. In fact, the bioavailability for the net inhalation of thymol was 74% and 77% relative to that for IV injection per AUC0-60min and AUC0-infinite, respectively

    Handling racism in a radio phone-in programme:Telling it like it is

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    It is widely acknowledged that broadcast programmes are produced to serve the public’s interest. Presenting the programmes in a neutral and objective fashion, and engaging the audience in forming opinions, are common ways of achieving this. However, studies have suggested that there is a departure from these practices when the object of broadcast becomes societal problems such as racism. This case study examines how a presenter responds to a caller’s abuse in two live radio shows, and how she sets out a programme - and a new conversation - using her personal experience of racism/xenophobia. Using conversation analysis and discursive psychology, we studied the situated use of language and the actions being brought about. We found that the presenter assesses the caller’s abuse by rudeness on the spot, formulating the call as disruptive to an ongoing conversation. On the following day, the presenter revisits, and topicalises, this call as xenophobia and racism. Our analysis revealed that the presenter’s shift in evaluating this call is grounded in, and licensed by, her drawing on and cultivating a sympathetic listenership, characterising the call as race-driven, and formulating her personal experience as of public’s concern. Our findings spotlight the presenter’s orientation to her moral accountability in talking about racism, and the potential of broadcast in leading conversations on anti-racism
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