Strain-engineered magnetic order in (LaMnO3_{3})n_n/(SrMnO3_{3})2n_{2n} superlattices

Using first-principles calculations based on the density functional theory, we show a strong strain dependence of magnetic order in (LaMnO$_{3}$)$_n$/(SrMnO$_{3}$)$_{2n}$ (001) superlattices with $n=1,2$. The epitaxial strain lifts the degeneracy of Mn $e_{g}$ orbitals, thus inducing an inherent orbital order, which in turn strongly affects the ferromagnetic double exchange of itinerant $e_{g}$ electrons, competing with the antiferromagnetic superexchange of localized $t_{2g}$ electrons. For the case of tensile strain induced by SrTiO$_3$ (001) substrate, we find that the ground state is A-type antiferromagnetic and $d_{x^2-y^2}$ orbital ordered, which is in excellent agreement with recent experiments [S. J. May {\it et al.}, Nature Materials {\bf 8}, 892 (2009)]. Instead, for the case of compressive strain induced by LaAlO$_3$ (001) substrate, we predict that the ground state is C-type antiferromagnetic and $d_{3z^2-r^2}$ orbital ordered.Comment: The paper is accepted for publication in Phys. Rev.

Word Embedding based Correlation Model for Question/Answer Matching

With the development of community based question answering (Q&A) services, a large scale of Q&A archives have been accumulated and are an important information and knowledge resource on the web. Question and answer matching has been attached much importance to for its ability to reuse knowledge stored in these systems: it can be useful in enhancing user experience with recurrent questions. In this paper, we try to improve the matching accuracy by overcoming the lexical gap between question and answer pairs. A Word Embedding based Correlation (WEC) model is proposed by integrating advantages of both the translation model and word embedding, given a random pair of words, WEC can score their co-occurrence probability in Q&A pairs and it can also leverage the continuity and smoothness of continuous space word representation to deal with new pairs of words that are rare in the training parallel text. An experimental study on Yahoo! Answers dataset and Baidu Zhidao dataset shows this new method's promising potential.Comment: 8 pages, 2 figure

Solar Radio Bursts with Spectral Fine Structures in Preflares

A good observation of preflare activities is important for us to understand the origin and triggering mechanism of solar flares, and to predict the occurrence of solar flares. This work presents the characteristics of microwave spectral fine structures as preflare activities of four solar flares observed by Ond\v{r}ejov radio spectrograph in the frequency range of 0.8--2.0 GHz. We found that these microwave bursts which occurred 1--4 minutes before the onset of flares have spectral fine structures with relatively weak intensities and very short timescales. They include microwave quasi-periodic pulsations (QPP) with very short period of 0.1-0.3 s and dot bursts with millisecond timescales and narrow frequency bandwidths. Accompanying these microwave bursts, there are filament motions, plasma ejection or loop brightening on the EUV imaging observations and non-thermal hard X-ray emission enhancements observed by RHESSI. These facts may reveal certain independent non-thermal energy releasing processes and particle acceleration before the onset of solar flares. They may be conducive to understand the nature of solar flares and predict their occurrence

First-principles studies on the structural and electronic properties of as clusters

Based on the genetic algorithm (GA) incorporated with density functional theory (DFT) calculations, the structural and electronic properties of neutral and charged arsenic clusters Asn (n = 2-24) are investigated. The size-dependent physical properties of neutral clusters, such as the binding energy, HOMO-LUMO gap, and second difference of cluster energies, are discussed. The supercluster structures based on the As8 unit and As2 bridge are found to be dominant for the larger cluster Asn (n ≥ 8). Furthermore, the possible geometric structures of As28, As38, and As180 are predicted based on the growth pattern