Localization and Mobility Gap in Topological Anderson Insulator

It has been proposed that disorder may lead to a new type of topological insulator, called topological Anderson insulator (TAI). Here we examine the physical origin of this phenomenon. We calculate the topological invariants and density of states of disordered model in a super-cell of 2-dimensional HgTe/CdTe quantum well. The topologically non-trivial phase is triggered by a band touching as the disorder strength increases. The TAI is protected by a mobility gap, in contrast to the band gap in conventional quantum spin Hall systems. The mobility gap in the TAI consists of a cluster of non-trivial subgaps separated by almost flat and localized bands.Comment: 8 pages, 7 figure

Elucidation of mechanisms of action of Wei-Sheng-Fang-Yi-Bao-Dan in the treatment of COVID-19 and depression using network pharmacology and molecular docking

Purpose: To investigate the mechanisms of action of Wei-Sheng-Fang-Yi-Bao-Dan (WSFYBD) in the treatment of COVID-19 and depression using network pharmacology and molecular docking. Methods: First, the bioactive components and target genes of WSFYBD were retrieved from TCMSP database. The relevant gene targets of depression and COVID-19 were obtained from databases. The core WSFYBD genes for treatment were separately obtained by determining gene intersection. Cytoscape 3.8.0 software was used to draw the visual interactive networks. STRING database was employed to construct protein-protein interaction networks, while Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were used to determine the function and pathway of target genes via a Bioconductor/R. Finally, AutoDockTools software was employed for molecular docking. Results: A total of 105 potential bio-active components and 35 target genes of WSFYBD for COVID-19 therapy were identified. Also, 1905 GO entries (p < 0.05) and 158 related signal pathways (p < 0.05) for COVID-19 were obtained. Similarly, 114 potential bio-active components of WSFYBD and 127 potential therapeutic targets of depression were identified. Moreover, 1948 GO entries (p < 0.05) and 177 related signal pathways for depression were retrieved (p < 0.05). Docking results showed the main bio-active components were closely bound to the core targets. Conclusion: The mechanisms for treating COVID-19 show that WSFYBD directly acts on SARS-CoV-2 virus to prevent it from entering the host cell, or inhibits virus replication. Secondly, WSFYBD ameliorates depression by acting on key targets that control over-activated cytokines. Therefore, WSFYBD has potentials for the management of COVID-19 and depression

Criticality of the O(N)O(N) universality via global solutions to nonperturbative fixed-point equations

Fixed-point equations in the functional renormalization group approach are integrated from large to vanishing field, where an asymptotic potential in the limit of large field is implemented as initial conditions. This approach allows us to obtain a global fixed-point potential with high numerical accuracy, that incorporates the correct asymptotic behavior in the limit of large field. Our calculated global potential is in good agreement with the Taylor expansion in the region of small field, and it also coincides with the Laurent expansion in the regime of large field. Laurent expansion of the potential in the limit of large field for general case, that the spatial dimension $d$ is a continuous variable in the range $2\leq d \leq 4$, is obtained. Eigenfunctions and eigenvalues of perturbations near the Wilson-Fisher fixed point are computed with the method of eigenperturbations. Critical exponents for different values of $d$ and $N$ of the $O(N)$ universality class are calculated.Comment: 10 pages, 4 figures, 1 table; v2: minor changes, discussions and references adde

DSCA: A Dual-Stream Network with Cross-Attention on Whole-Slide Image Pyramids for Cancer Prognosis

The cancer prognosis on gigapixel Whole-Slide Images (WSIs) has always been a challenging task. To further enhance WSI visual representations, existing methods have explored image pyramids, instead of single-resolution images, in WSIs. In spite of this, they still face two major problems: high computational cost and the unnoticed semantical gap in multi-resolution feature fusion. To tackle these problems, this paper proposes to efficiently exploit WSI pyramids from a new perspective, the dual-stream network with cross-attention (DSCA). Our key idea is to utilize two sub-streams to process the WSI patches with two resolutions, where a square pooling is devised in a high-resolution stream to significantly reduce computational costs, and a cross-attention-based method is proposed to properly handle the fusion of dual-stream features. We validate our DSCA on three publicly-available datasets with a total number of 3,101 WSIs from 1,911 patients. Our experiments and ablation studies verify that (i) the proposed DSCA could outperform existing state-of-the-art methods in cancer prognosis, by an average C-Index improvement of around 4.6%; (ii) our DSCA network is more efficient in computation -- it has more learnable parameters (6.31M vs. 860.18K) but less computational costs (2.51G vs. 4.94G), compared to a typical existing multi-resolution network. (iii) the key components of DSCA, dual-stream and cross-attention, indeed contribute to our model's performance, gaining an average C-Index rise of around 2.0% while maintaining a relatively-small computational load. Our DSCA could serve as an alternative and effective tool for WSI-based cancer prognosis.Comment: 12 pages, 6 figures, 7 table