Entanglement entropy of (3+1)D topological orders with excitations

Excitations in (3+1)D topologically ordered phases have very rich structures. (3+1)D topological phases support both point-like and string-like excitations, and in particular the loop (closed string) excitations may admit knotted and linked structures. In this work, we ask the question how different types of topological excitations contribute to the entanglement entropy, or alternatively, can we use the entanglement entropy to detect the structure of excitations, and further obtain the information of the underlying topological orders? We are mainly interested in (3+1)D topological orders that can be realized in Dijkgraaf-Witten gauge theories, which are labeled by a finite group $G$ and its group 4-cocycle $\omega\in\mathcal{H}^4[G;U(1)]$ up to group automorphisms. We find that each topological excitation contributes a universal constant $\ln d_i$ to the entanglement entropy, where $d_i$ is the quantum dimension that depends on both the structure of the excitation and the data $(G,\,\omega)$. The entanglement entropy of the excitations of the linked/unlinked topology can capture different information of the DW theory $(G,\,\omega)$. In particular, the entanglement entropy introduced by Hopf-link loop excitations can distinguish certain group 4-cocycles $\omega$ from the others.Comment: 12 pages, 4 figures; v2: minor changes, published versio

Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

Detection transformers have recently shown promising object detection results and attracted increasing attention. However, how to develop effective domain adaptation techniques to improve its cross-domain performance remains unexplored and unclear. In this paper, we delve into this topic and empirically find that direct feature distribution alignment on the CNN backbone only brings limited improvements, as it does not guarantee domain-invariant sequence features in the transformer for prediction. To address this issue, we propose a novel Sequence Feature Alignment (SFA) method that is specially designed for the adaptation of detection transformers. Technically, SFA consists of a domain query-based feature alignment (DQFA) module and a token-wise feature alignment (TDA) module. In DQFA, a novel domain query is used to aggregate and align global context from the token sequence of both domains. DQFA reduces the domain discrepancy in global feature representations and object relations when deploying in the transformer encoder and decoder, respectively. Meanwhile, TDA aligns token features in the sequence from both domains, which reduces the domain gaps in local and instance-level feature representations in the transformer encoder and decoder, respectively. Besides, a novel bipartite matching consistency loss is proposed to enhance the feature discriminability for robust object detection. Experiments on three challenging benchmarks show that SFA outperforms state-of-the-art domain adaptive object detection methods. Code has been made available at: https://github.com/encounter1997/SFA.Comment: Fix a typo in Eq. 1

Inhibition of USP7 activity selectively eliminates senescent cells in part via restoration of p53 activity.

The accumulation of senescent cells (SnCs) is a causal factor of various age-related diseases as well as some of the side effects of chemotherapy. Pharmacological elimination of SnCs (senolysis) has the potential to be developed into novel therapeutic strategies to treat these diseases and pathological conditions. Here we show that ubiquitin-specific peptidase 7 (USP7) is a novel target for senolysis because inhibition of USP7 with an inhibitor or genetic depletion of USP7 by RNA interference induces apoptosis selectively in SnCs. The senolytic activity of USP7 inhibitors is likely attributable in part to the promotion of the human homolog of mouse double minute 2 (MDM2) ubiquitination and degradation by the ubiquitin-proteasome system. This degradation increases the levels of p53, which in turn induces the pro-apoptotic proteins PUMA, NOXA, and FAS and inhibits the interaction of BCL-XL and BAK to selectively induce apoptosis in SnCs. Further, we show that treatment with a USP7 inhibitor can effectively eliminate SnCs and suppress the senescence-associated secretory phenotype (SASP) induced by doxorubicin in mice. These findings suggest that small molecule USP7 inhibitors are novel senolytics that can be exploited to reduce chemotherapy-induced toxicities and treat age-related diseases

Strain Induced One-Dimensional Landau-Level Quantization in Corrugated Graphene

Theoretical research has predicted that ripples of graphene generates effective gauge field on its low energy electronic structure and could lead to zero-energy flat bands, which are the analog of Landau levels in real magnetic fields. Here we demonstrate, using a combination of scanning tunneling microscopy and tight-binding approximation, that the zero-energy Landau levels with vanishing Fermi velocities will form when the effective pseudomagnetic flux per ripple is larger than the flux quantum. Our analysis indicates that the effective gauge field of the ripples results in zero-energy flat bands in one direction but not in another. The Fermi velocities in the perpendicular direction of the ripples are not renormalized at all. The condition to generate the ripples is also discussed according to classical thin-film elasticity theory.Comment: 4 figures, Phys. Rev.

Research progress in ultrasound use for the diagnosis and treatment of cerebrovascular diseases

Cerebrovascular diseases pose a serious threat to human survival and quality of life and represent a major cause of human death and disability. Recently, the incidence of cerebrovascular diseases has increased yearly. Rapid and accurate diagnosis and evaluation of cerebrovascular diseases are of great importance to reduce the incidence, morbidity and mortality of cerebrovascular diseases. With the rapid development of medical ultrasound, the clinical relationship between ultrasound imaging technology and the diagnosis and treatment of cerebrovascular diseases has become increasingly close. Ultrasound techniques such as transcranial acoustic angiography, doppler energy imaging, three-dimensional craniocerebral imaging and ultrasound thrombolysis are novel and valuable techniques in the study of cerebrovascular diseases. In this review, we introduce some of the new ultrasound techniques from both published studies and ongoing trials that have been confirmed to be convenient and effective methods. However, additional evidence from future studies will be required before some of these techniques can be widely applied or recommended as alternatives