Scene Graph Generation with External Knowledge and Image Reconstruction

Scene graph generation has received growing attention with the advancements in image understanding tasks such as object detection, attributes and relationship prediction,~\etc. However, existing datasets are biased in terms of object and relationship labels, or often come with noisy and missing annotations, which makes the development of a reliable scene graph prediction model very challenging. In this paper, we propose a novel scene graph generation algorithm with external knowledge and image reconstruction loss to overcome these dataset issues. In particular, we extract commonsense knowledge from the external knowledge base to refine object and phrase features for improving generalizability in scene graph generation. To address the bias of noisy object annotations, we introduce an auxiliary image reconstruction path to regularize the scene graph generation network. Extensive experiments show that our framework can generate better scene graphs, achieving the state-of-the-art performance on two benchmark datasets: Visual Relationship Detection and Visual Genome datasets.Comment: 10 pages, 5 figures, Accepted in CVPR 201

Terahertz Atmospheric Windows for High Angular Resolution Terahertz Astronomy from Dome A

Atmospheric transmission from Dome A, Antarctica, presents new possibilities in the field of terahertz astronomy, where space telescopes have been the only observational tools until now. Using atmospheric transmission measurements from Dome A with a Fourier transform spectrometer, transmission spectra and long-term stabilities have been analyzed at 1.461 THz, 3.393 THz, 5.786 THz and 7.1 THz, which show that important atmospheric windows for terahertz astronomy open for a reasonable length of time in the winter season. With large aperture terahertz telescopes and interferometers at Dome A, high angular resolution terahertz observations are foreseen of atomic fine-structure lines from ionized gas and a water ice feature from protoplanetary disks.Comment: 6 pages, 3 figures, to appear in Advances in Polar Scienc

Sound speed resonance of the stochastic gravitational wave background

We propose a novel mechanism to test time variation of the propagation speed of gravitational waves (GWs) in light of GWs astronomy. As the stochastic GWs experience the whole history of cosmic expansion, they encode potential observational evidence of such variation. We report that, one feature of a varying GWs speed is that the energy spectrum of GWs will present resonantly-enhanced peaks if the GWs speed oscillates in time at high-energy scales. Such oscillatory behaviour arises in a wide class of modified gravity theories. The amplitude of these peaks can be at reach by current and forthcoming GWs instruments, hence making the underlying theories falsifiable. This mechanism reveals that probing the variation of GWs speed can be a promising way to search for new physics beyond general relativity.Comment: 6 pages, 2 figure

AMPK and TOR:the Yin and Yang of cellular nutrient sensing and growth control

The AMPK (AMP-activated protein kinase) and TOR (target-of-rapamycin) pathways are interlinked, opposing signaling pathways involved in sensing availability of nutrients and energy and regulation of cell growth. AMPK (Yin, or the "dark side") is switched on by lack of energy or nutrients and inhibits cell growth, while TOR (Yang, or the "bright side") is switched on by nutrient availability and promotes cell growth. Genes encoding the AMPK and TOR complexes are found in almost all eukaryotes, suggesting that these pathways arose very early during eukaryotic evolution. During the development of multicellularity, an additional tier of cell-extrinsic growth control arose that is mediated by growth factors, but these often act by modulating nutrient uptake so that AMPK and TOR remain the underlying regulators of cellular growth control. In this review, we discuss the evolution, structure, and regulation of the AMPK and TOR pathways and the complex mechanisms by which they interact

Delayed response to the photovoltaic performance in a double quantum dot photocell with spatially correlated fluctuation

A viable strategy for enhancing photovoltaic performance in a double quantum dot (DQD) photocell is to comprehend the underlying quantum physical regime of charge transfer. This work explores the photovoltaic performance dependent spatially correlated fluctuation in a DQD photocell. A suggested DQD photocell model was used to examine the effects of spatially correlated variation on charge transfer and output photovoltaic efficiency. The charge transfer process and the process of reaching peak solar efficiency were both significantly delayed as a result of the spatially correlated fluctuation, and the anti-spatial correlation fluctuation also resulted in lower output photovoltaic efficiency. Further results revealed that some structural parameters, such as gap difference and tunneling coefficient within two dots, could suppress the delayed response, and a natural adjustment feature was demonstrated on the delayed response in this DQD photocell model. Subsequent investigation verified that the delayed response was caused by the spatial correlation fluctuation, which slowed the generative process of noise-induced coherence, which had previously been proven to improve quantum photovoltaic performance in quantum photocells. While anti-spatial correlation fluctuation and a hotter thermal ambient environment could diminish the condition for noise-induced coherence, as demonstrated by the reduced photovoltaic capabilities in this suggested DQD photocell model. As a result, we expect that regulated noise-induced coherence, via spatially correlated fluctuation, will have a major impact on photovoltaic qualities in a DQD photocell system. The discovery of its underlying physical regime of quantum fluctuation will broaden and deepen understanding of quantum features of electron transfer, as well as provide some indications concerning quantum techniques for high efficiency DQD solar cells.Comment: 16 pages, 5 figure

The Viscoelasticity Model of Corn Straw under the Different Moisture Contents

Viscoelastic model of corn straw, based on different moisture contents, is set up to characterise the deformation through three-point bending test. The model contains a linear elastic element, a damping element, and a nonlinear elastic element. The parameters of the model are determined according to the features of three-point bending test curve and characteristic of the model. The relationships between mechanical properties, energy absorption behavior of corn stalk, and moisture content have been, respectively, analysed. And regression analysis and curve fitting have been conducted based on various parameters and moisture contents with Matlab. These parameters provide the basis for straw crushing equipment design

3,3′-Dimethyl-1,1′-[(1,3-dihy­droxy­propane-2,2-di­yl)dimethyl­idene]diimidazolium bis­(hexa­fluoro­phosphate)

The title compound, C13H22N4O2 2+·2PF6 −, was prepared by the anion exchange of the dibromide ionic liquid with potassium hexa­fluoro­phosphate. The two imidazole rings are each planar (r.m.s. deviations = 0.0016 and 0.0060 Å) and make a dihedral angle of 45.3 (18)°. Intra­molecular O—H⋯F hydrogen bonds occur. Inter­molecular C—H⋯F, O—H⋯O and C—H⋯O hydrogen bonds stabilize the crystal structure