Atomically phase-matched second-harmonic generation in a 2D crystal.

Second-harmonic generation (SHG) has found extensive applications from hand-held laser pointers to spectroscopic and microscopic techniques. Recently, some cleavable van der Waals (vdW) crystals have shown SHG arising from a single atomic layer, where the SH light elucidated important information such as the grain boundaries and electronic structure in these ultra-thin materials. However, despite the inversion asymmetry of the single layer, the typical crystal stacking restores inversion symmetry for even numbers of layers leading to an oscillatory SH response, drastically reducing the applicability of vdW crystals such as molybdenum disulfide (MoS2). Here, we probe the SHG generated from the noncentrosymmetric 3R crystal phase of MoS2. We experimentally observed quadratic dependence of second-harmonic intensity on layer number as a result of atomically phase-matched nonlinear dipoles in layers of the 3R crystal that constructively interfere. By studying the layer evolution of the A and B excitonic transitions in 3R-MoS2 using SHG spectroscopy, we also found distinct electronic structure differences arising from the crystal structure and the dramatic effect of symmetry and layer stacking on the nonlinear properties of these atomic crystals. The constructive nature of the SHG in this 2D crystal provides a platform to reliably develop atomically flat and controllably thin nonlinear media

Literature Review of Cross-border M&A Performance Test and Path Selection by Chinese Banks

In the course of the development of the international banks, cross-border M&A has become one of the main methods of its realization of international operation. With the opening of China's financial industry on Dec.11th in 2006, international financial service trade has entered a new era. Faced with the competition of the large commercial banks around the world, China’s banks also shift their strategy. In the process of international operation, it is an economic proposition of strong practical significance that how to expand the business area and business scope and improve bank performance through international mergers and acquisitions, thus on the competition of the international finance, we can compete for more financial resources and strengthen the financial strength. This thesis starts from the research on motivation and performance of bank M&A, and discusses the evaluation method and the path of bank M&A

Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks

Factorization Machines (FMs) are a supervised learning approach that enhances the linear regression model by incorporating the second-order feature interactions. Despite effectiveness, FM can be hindered by its modelling of all feature interactions with the same weight, as not all feature interactions are equally useful and predictive. For example, the interactions with useless features may even introduce noises and adversely degrade the performance. In this work, we improve FM by discriminating the importance of different feature interactions. We propose a novel model named Attentional Factorization Machine (AFM), which learns the importance of each feature interaction from data via a neural attention network. Extensive experiments on two real-world datasets demonstrate the effectiveness of AFM. Empirically, it is shown on regression task AFM betters FM with a $8.6\%$ relative improvement, and consistently outperforms the state-of-the-art deep learning methods Wide&Deep and DeepCross with a much simpler structure and fewer model parameters. Our implementation of AFM is publicly available at: https://github.com/hexiangnan/attentional_factorization_machineComment: 7 pages, 5 figure