Origin of layer number dependent linear and nonlinear optical properties of two-dimensional graphene-like SiC

We theoretically discuss the physical origin of the dielectric constants [{\epsilon}({\omega})] and second harmonic generation coefficients [\{chi}(2)({\omega})] of the ABA-stacked two-dimensional graphene-like silicon carbide (2D-SiC) with the number of layers up to 5. It is found that the intensities of the pronounced peaks of both {\epsilon}({\omega}) and \{chi}(2)({\omega}) exhibit a clear layer number dependence. For the light polarization parallel to the 2DSiC plane, the monolayer SiC (ML-SiC) and multilayer SiC (MuL-SiC) have very similar pronounced peak positions of {\epsilon}({\omega}), which are attributed to the {\pi}->{\pi}* and {\sigma}->{\sigma}* transitions. However, for the light polarization perpendicular to the 2D-SiC plane, a characteristic peak is found for the MuL-SiC at about 4.0 eV, except that the allowed {\pi}->{\sigma}* and {\sigma}->{\pi}* transition peaks are found for both ML-SiC and MuL-SiC in the high-energy region (> 8 eV). This characteristic peak is attributed to the interlayer {\pi}->{\pi}* transition which does not exist for the ML-SiC, and at this peak position, the ML-SiC has a weak dark exciton based on the mBJ calculation within the Bethe-Salpeter equation framework. For \{chi}(2)({\omega}), the single-particle transition channels based on the three-band terms dominate the second harmonic generation process of both ML-SiC and MuL-SiC and determine the size and sign of \{chi}(2)({\omega}). In the ultraviolet visible region, the purely interband motion and intraband motion of electrons competitively determine the size and sign of \{chi}(2)({\omega}). For the light polarization perpendicular to the 2D-SiC plane, the intraband motion of electrons modulated more dramatically the interband motion than for that parallel to the 2D-SiC plane.Comment: 34 pages, 10 figures, 3 table

Zb/Zb′→ΥπZ_b/Z_b^\prime \to \Upsilon\pi and hbπh_b \pi decays in intermediate meson loops model

With the recent measurement of $Z_b(10610)$ and $Z_b(10650)\to B\bar{B}^*+c.c.$ and $B^*\bar{B}^*$, we investigate the transitions from the $Z_b(10610)$ and $Z_b(10650)$ to bottomonium states with emission of a pion via intermediate $B \ {B}^*$ meson loops. The experimental data can be reproduced in this approach with a commonly accepted range of values for the form factor cutoff parameter $\alpha$. The $\Upsilon(3S)\pi$ decay channels appear to experience obvious threshold effects which can be understood by the property of the loop integrals. By investigating the $\alpha$-dependence of partial decay widths and ratios between different decay channels, we show that the intermediate $B \ {B}^*$ meson loops are crucial for driving the transitions of $Z_b/Z_b'\to \Upsilon(nS)\pi$ with $n = 1, 2, 3$, and $h_b(mP)\pi$ with $m = 1$ and 2.Comment: 9 pages, 5 figure

Cardiac stem cells: A promising treatment option for heart failure.

Cardiovascular diseases are the most common cause of death in the world. The development of heart failure is mainly due to the loss of cardiomyocytes following myocardial infarction and the absence of endogenous myocardial repair. Numerous studies have focused on cardiac stem cells (CSCs) due to their therapeutic benefit, particularly in the treatment of heart failure. It has previously been demonstrated that CSCs are able to promote the regeneration of cardiomyocytes in animals following myocardial infarction. However, the underlying mechanism(s) remain unclear. This review mainly discusses the cardioprotective effect of CSCs and the effect of CSCs on the function of cardiomyocytes, and compares the efficacies of CSCs from rats, mice and humans, thereby contributing to an improved understanding of CSCs as a promising treatment option for heart failure

Dirichlet belief networks for topic structure learning

Recently, considerable research effort has been devoted to developing deep architectures for topic models to learn topic structures. Although several deep models have been proposed to learn better topic proportions of documents, how to leverage the benefits of deep structures for learning word distributions of topics has not yet been rigorously studied. Here we propose a new multi-layer generative process on word distributions of topics, where each layer consists of a set of topics and each topic is drawn from a mixture of the topics of the layer above. As the topics in all layers can be directly interpreted by words, the proposed model is able to discover interpretable topic hierarchies. As a self-contained module, our model can be flexibly adapted to different kinds of topic models to improve their modelling accuracy and interpretability. Extensive experiments on text corpora demonstrate the advantages of the proposed model.Comment: accepted in NIPS 201

The Demand for Vice: Inter-Commodity Interactions with Uncertainty

This paper introduces a simulation procedure in the context of a demand system for vice -- marijuana, tobacco and alcohol -- to formally account for the inherent uncertainty in marijuanarelated data and parameters. This entails using existing econometric estimates pertaining to the consumption of alcohol and tobacco, and the much more limited information on marijuana. As an illustrative application of the framework, we simulate the impact on the consumption of vice of a reduction in the price of marijuana; changes in pre-existing taxes on tobacco and alcohol; legalisation of marijuana, which is then subject to taxation; and a tax tradeoff involving the introduction of a revenue-neutral tax on marijuana that is offset by reduced alcohol taxation. The revenue-maximising tax rate of about 50 percent is estimated to yield additional revenue of about 15 percent of the pre-existing proceeds from vice taxation. The role of uncertainty surrounding preference interactions within vice, as well as the uncertainties regarding marijuana data, is highlighted by providing the whole distribution of each endogenous variable.