A note on the resolution of the entropy discrepancy

It was found by Hung, Myers and Smolkin that there is entropy discrepancy for the CFTs in 6-dimensional space-time, between the field theoretical and the holographic analysis. Recently, two different resolutions to this puzzle have been proposed. One of them suggests to utilize the anomaly-like entropy and the generalized Wald entropy to resolve the HMS puzzle, while the other one initiates to use the entanglement entropy which arises from total derivative terms in the Weyl anomaly to explain the HMS mismatch. We investigate these two proposals carefully in this note. By studying the CFTs dual to Einstein gravity, we find that the second proposal can not solve the HMS puzzle. Moreover, the Wald entropy formula is not well-defined on horizon with extrinsic curvatures, in the sense that, in general, it gives different results for equivalent actions.Comment: 12 pages, no figures, accepted by PL

Dark Energy and Normalization of the Cosmological Wave Function

Dark energy is investigated from the perspective of quantum cosmology. It is found that, together with an appropriate normal ordering factor $q$, only when there is dark energy then can the cosmological wave function be normalized. This interesting observation may require further attention.Comment: Title changed, match the published versio

Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation

Automatic parsing of anatomical objects in X-ray images is critical to many clinical applications in particular towards image-guided invention and workflow automation. Existing deep network models require a large amount of labeled data. However, obtaining accurate pixel-wise labeling in X-ray images relies heavily on skilled clinicians due to the large overlaps of anatomy and the complex texture patterns. On the other hand, organs in 3D CT scans preserve clearer structures as well as sharper boundaries and thus can be easily delineated. In this paper, we propose a novel model framework for learning automatic X-ray image parsing from labeled CT scans. Specifically, a Dense Image-to-Image network (DI2I) for multi-organ segmentation is first trained on X-ray like Digitally Reconstructed Radiographs (DRRs) rendered from 3D CT volumes. Then we introduce a Task Driven Generative Adversarial Network (TD-GAN) architecture to achieve simultaneous style transfer and parsing for unseen real X-ray images. TD-GAN consists of a modified cycle-GAN substructure for pixel-to-pixel translation between DRRs and X-ray images and an added module leveraging the pre-trained DI2I to enforce segmentation consistency. The TD-GAN framework is general and can be easily adapted to other learning tasks. In the numerical experiments, we validate the proposed model on 815 DRRs and 153 topograms. While the vanilla DI2I without any adaptation fails completely on segmenting the topograms, the proposed model does not require any topogram labels and is able to provide a promising average dice of 85% which achieves the same level accuracy of supervised training (88%)

Scares and Stocks: Evidence from Twitter Sentiments During Covid-19

This paper examines the investor reaction of firm-specific pessimistic sentiment extracted from Twitter messages during the pandemic period due to the Covid-19. We find that Twitter sentiment predicts stock returns without subsequent reversals. This finding is consistent with the view that tweets provide information not already reflected in stock prices during the pandemic period. We investigate possible sources of return predictability with a Twitter sentiment. The results show that Twitter\u27s pessimistic sentiment towards the Covid-19 provides new information about the investor. This information explains about onethird of the predictive ability of Twitter sentiment for stock returns. Our findings shed new light on the predictive value of social media content for stock returns

EFormer: Enhanced Transformer towards Semantic-Contour Features of Foreground for Portraits Matting

The portrait matting task aims to extract an alpha matte with complete semantics and finely-detailed contours. In comparison to CNN-based approaches, transformers with self-attention allow a larger receptive field, enabling it to better capture long-range dependencies and low-frequency semantic information of a portrait. However, the recent research shows that self-attention mechanism struggle with modeling high-frequency information and capturing fine contour details, which can lead to bias while predicting the portrait's contours. To address the problem, we propose EFormer to enhance the model's attention towards semantic and contour features. Especially the latter, which is surrounded by a large amount of high-frequency details. We build a semantic and contour detector (SCD) to accurately capture the distribution of semantic and contour features. And we further design contour-edge extraction branch and semantic extraction branch for refining contour features and complete semantic information. Finally, we fuse the two kinds of features and leverage the segmentation head to generate the predicted portrait matte. Remarkably, EFormer is an end-to-end trimap-free method and boasts a simple structure. Experiments conducted on VideoMatte240K-JPEGSD and AIM datasets demonstrate that EFormer outperforms previous portrait matte methods.Comment: 17 pages, 6 figure

Erosion-induced CO2 flux of small watersheds

Soil erosion not only results in severe ecological damage, but also interferes with soil organic carbon formation and decomposition, influencing the global green-house effect. However, there is controversy as to whether a typical small watershed presumed as the basic unit of sediment yield acts as a CO2 sink or source. This paper proposes a discriminant equation for the direction of CO2 flux in small watersheds, basing on the concept of Sediment Delivery Ratio (SDR). Using this equation, watersheds can be classified as Sink Watersheds, Source Watersheds, or Transition Watersheds, noting that small watersheds can act either as a CO2 sink or as a CO2 source. A mathematical model for calculating the two discriminant coefficients in the equation is set up to analyze the conditions under which each type of watershed would occur. After assigning the model parameter values at three levels (low, medium, and high), and considering 486 scenarios in total, the influences are examined for turnover rate of the carbon pool, erosion rate, deposition rate, cultivation depth and period. The effect of adopting conservation measures like residue return, contour farming, terracing, and conservation tillage is also analyzed. The results show that Sink Watersheds are more likely to result in conditions of high erosion rate, long cultivation period, high deposition rate, fast carbon pool turnover rate, and small depth of cultivation; otherwise, Source Watersheds would possibly occur. The results also indicate that residue return and conservation tillage are beneficial for CO2 sequestration. (C) 2012 Elsevier B.V. All rights reserved.Geography, PhysicalGeosciences, MultidisciplinarySCI(E)EI0ARTICLE101-11094-9

Effects of laser fluence on silicon modification by four-beam laser interference

This paper discusses the effects of laser fluence on silicon modification by four-beam laser interference. In this work, four-beam laser interference was used to pattern single crystal silicon wafers for the fabrication of surface structures, and the number of laser pulses was applied to the process in air. By controlling the parameters of laser irradiation, different shapes of silicon structures were fabricated. The results were obtained with the single laser fluence of 354 mJ/cm, 495 mJ/cm, and 637 mJ/cm, the pulse repetition rate of 10 Hz, the laser exposure pulses of 30, 100, and 300, the laser wavelength of 1064 nm, and the pulse duration of 7-9 ns. The effects of the heat transfer and the radiation of laser interference plasma on silicon wafer surfaces were investigated. The equations of heat flow and radiation effects of laser plasma of interfering patterns in a four-beam laser interference distribution were proposed to describe their impacts on silicon wafer surfaces. The experimental results have shown that the laser fluence has to be properly selected for the fabrication of well-defined surface structures in a four-beam laser interference process. Laser interference patterns can directly fabricate different shape structures for their corresponding applications

Symmetry restoring bifurcations and quasiperiodic chaos induced by a new intermittency in a vibro-impact system

This work was supported by National Natural Science Foundation of China (11272268, 11572263, and 11672249).Peer reviewedPublisher PD

Stability and Bautin bifurcation of four-wheel-steering vehicle system with driver steering control

Acknowledgments This work is supported by the National Natural Science Foundation of China (Nos. 12202168, 12072291,12172306).Peer reviewedPostprin