Realization of Zero-Refractive-Index Lens with Ultralow Spherical Aberration

Optical complex materials offer unprecedented opportunity to engineer fundamental band dispersion which enables novel optoelectronic functionality and devices. Exploration of photonic Dirac cone at the center of momentum space has inspired an exceptional characteristic of zero-index, which is similar to zero effective mass in fermionic Dirac systems. Such all-dielectric zero-index photonic crystals provide an in-plane mechanism such that the energy of the propagating waves can be well confined along the chip direction. A straightforward example is to achieve the anomalous focusing effect without longitudinal spherical aberration, when the size of zero-index lens is large enough. Here, we designed and fabricated a prototype of zero-refractive-index lens by comprising large-area silicon nanopillar array with plane-concave profile. Near-zero refractive index was quantitatively measured near 1.55 um through anomalous focusing effect, predictable by effective medium theory. The zero-index lens was also demonstrated to perform ultralow longitudinal spherical aberration. Such IC compatible device provides a new route to integrate all-silicon zero-index materials into optical communication, sensing, and modulation, and to study fundamental physics on the emergent fields of topological photonics and valley photonics.Comment: 14 pages, 4 figure

The effect of transforming growth factor-β1 on nasopharyngeal carcinoma cells: insensitive to cell growth but functional to TGF-β/Smad pathway

<p>Abstract</p> <p>Objectives</p> <p>This study explored the response of nasopharyngeal carcinoma cells to TGF-β1-induced growth suppression and investigated the roles of the TGF-β/Smad signaling pathway in nasopharyngeal carcinoma cells.</p> <p>Methods</p> <p>The cells of nasopharyngeal carcinoma cell line CNE2 were treated with TGF-β1. The growth responses of CNE2 cells were analyzed by MTT assay. The mRNA expression and protein subcellular localization of the TGF-β/Smad signaling components in the CNE2 were determined by real time RT-PCR and immunocytochemical analysis.</p> <p>Results</p> <p>We found that the growth of CNE2 cells was not suppressed by TGF-β1. The signaling proteins TβRII, Smad 7 were expressed normally, while Smad2, Smad3, and Smad4 increased significantly at the mRNA level. TGF-β type II receptor and Smad7 had no change compared to the normal nasopharyngeal epithelial cells. In addition, Smad2 was phosphorylated to pSmad2, and the activated pSmad2 translocated into the nucleus from the cytoplasm, while the inhibitory Smad-Smad7 translocated from the nucleus to the cytoplasm after TGF-β1 stimulation.</p> <p>Conclusion</p> <p>The results suggested that CNE2 cells are not sensitive to growth suppression by TGF-β1, but the TGF-β/Smad signaling transduction is functional. Further work is needed to address a more detailed spectrum of the TGF-β/Smad signaling pathway in CNE2 cells.</p

DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System

In general, recommendation can be viewed as a matching problem, i.e., match proper items for proper users. However, due to the huge semantic gap between users and items, it's almost impossible to directly match users and items in their initial representation spaces. To solve this problem, many methods have been studied, which can be generally categorized into two types, i.e., representation learning-based CF methods and matching function learning-based CF methods. Representation learning-based CF methods try to map users and items into a common representation space. In this case, the higher similarity between a user and an item in that space implies they match better. Matching function learning-based CF methods try to directly learn the complex matching function that maps user-item pairs to matching scores. Although both methods are well developed, they suffer from two fundamental flaws, i.e., the limited expressiveness of dot product and the weakness in capturing low-rank relations respectively. To this end, we propose a general framework named DeepCF, short for Deep Collaborative Filtering, to combine the strengths of the two types of methods and overcome such flaws. Extensive experiments on four publicly available datasets demonstrate the effectiveness of the proposed DeepCF framework

The Leap of Comparative Advantage Trap in Guangzhou-Based on the Perspective of Global Value Chain

This paper analyzes the situation and reasons of the trap of comparative advantage in Guangzhou, and proposes some strategies on how to leap the trap of comparative advantage. Firstly, based on the perspective of global value chain, this paper analyzes the status of Guangzhou in the global value chain through RCA (revealed comparative advantage index) and RTV (revealed technology added value index), and illustrates the situation of Guangzhou in the trap of comparative advantage. Secondly, the reasons why Guangzhou is into comparative advantage trap are analyzed from three aspects, capital, labor force and technology. Thirdly, in view of the main reasons, we seek some effective strategies to leap the comparative advantage trap, promote the transformation and upgrading of enterprises in guangzhou into innovative enterprises, and lead to the promotion of the competitiveness of Guangzhou in the globalization division of labor