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Using Coulomb correlation parameters appropriate for -conjugated polymers ͑PCPs͒, and a nearest neighbor hopping integral that is arrived at by fitting the energy spectra of three zigzag semiconducting singlewalled carbon nanotubes ͑S-SWCNTs͒, we are able to determine quantitatively the exciton energies and exciton binding energies of 29 S-SWCNTs within a semiempirical -electron Hamiltonian that has been widely used for PCPs. Our work establishes the existence of a deep and fundamental relationship between PCPs and S-SWCNTs.

In this paper, we present Uformer, an effective and efficient Transformer-based architecture, in which we build a hierarchical encoder-decoder network using the Transformer block for image restoration. Uformer has two core designs to make it suitable for this task. The first key element is a local-enhanced window Transformer block, where we use non-overlapping window-based self-attention to reduce the computational requirement and employ the depth-wise convolution in the feedforward network to further improve its potential for capturing local context. The second key element is that we explore three skip-connection schemes to effectively deliver information from the encoder to the decoder. Powered by these two designs, Uformer enjoys a high capability for capturing useful dependencies for image restoration. Extensive experiments on several image restoration tasks demonstrate the superiority of Uformer, including image denoising, deraining, deblurring and demoireing. We expect that our work will encourage further research to explore Transformer-based architectures for low-level vision tasks. The code and models will be available at https://github.com/ZhendongWang6/Uformer.

The DEAD-box-protein DDX5 is an ATP-dependent RNA helicase that is frequently overexpressed in various cancers and acts as a transcriptional co-activator of several transcription factors, including β-catenin. DDX5 is reported to be involved in cancer progression by promoting cell proliferation and epithelial–mesenchymal transition. However, the clinical significance and biological role of DDX5 in non-small-cell lung cancer (NSCLC) remain largely unknown. In this study, we examined the expression of DDX5 in clinical NSCLC samples, investigated its role in regulating NSCLC cell proliferation and tumorigenesis, and explored the possible molecular mechanism. We found that DDX5 was significantly overexpressed in NSCLC tissues as compared with the matched normal adjacent tissues. In addition, overexpression of DDX5 was associated with advanced clinical stage, higher Ki67 index, and shorter overall survival in NSCLC patients. Upregulation of DDX5 promoted proliferation of NSCLC cells in vitro and growth of NSCLC xenografts in vivo, whereas downregulation of DDX5 showed the opposite effects. Furthermore, DDX5 directly interacted with β-catenin, promoted its nuclear translocation, and co-activated the expression of cyclin D1 and c-Myc. β-catenin silencing significantly abrogated DDX5-induced cyclin D1 and c-Myc expression and proliferation in NSCLC cells. Interestingly, DDX5 and cyclin D1 expression followed positive correlation in the same set of NSCLC samples. These findings indicated that DDX5 played an important role in the proliferation and tumorigenesis of NSCLC cells by activating the β-catenin signaling pathway. Therefore, DDX5 may serve as a novel prognostic marker and potential therapeutic target in the treatment of NSCLC.

We present fast algorithms to perform accurate CCD queries between triangulated models. Our formulation uses properties of the Bernstein basis and Bézier curves and reduces the problem to evaluating signs of polynomials. We present a geometrically exact CCD algorithm based on the exact geometric computation paradigm to perform reliable Boolean collision queries. Our algorithm is more than an order of magnitude faster than prior exact algorithms. We evaluate its performance for cloth and FEM simulations on CPUs and GPUs, and highlight the benefits.

Hierarchically ordered materials with core/shell structures were synthesized through a layer-by-layer approach. The novel microporous/mesoporous hybrid materials were composed of a TS-1 zeolite particle for the core and mesoporous silica for the shell. The as-synthesized TS-1 crystals were modified with polydiallyldimethylammonium chloride to make their external surface positively charged, which induced an oriented self-assembly of tetraethoxysilane (TEOS) with cetyltrimethyl ammonium bromide on the TS-1 particle surface to form a shell of mesophase silica. The thickness of the mesoporous silica shell was controlled to be in the range 30-55 nm by changing the amount of TEOS added in the synthesis. The mesoporous channels in the shell were perpendicular to the zeolite core, which made the micropores inside the core accessible from the outside through the mesopores. Taking advantage of the confining effect of the mesopores, Au nanoparticles were incorporated into the shell, resulting in bifunctional catalysts which were more selective than conventional Au/TS-1 catalysts in the direct epoxidation of propylene to propylene oxide with H 2 and O 2 .

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