Composite multi-vortex diffraction-free beams and van Hove singularities in honeycomb lattices

We find diffraction-free beams for graphene and MoS$_2$-type honeycomb optical lattices. The resulting composite solutions have the form of multi-vortices, with spinor topological charges ($n$, $n\pm1$). Exact solutions for the spinor components are obtained in the Dirac limit. The effects of the valley degree of freedom and the mass are analyzed. Passing through the van-Hove singularity the topological structure of the solutions is modified. Exactly at the singularity the diffraction-free beams take the form of strongly localized one-dimensional stripes.Comment: 4 pages, 6 figures, accepted for publication in Optics Letter

Closed-form expressions for nonparaxial accelerating beams with pre-engineered trajectories

In this letter, we propose a general real-space method for the generation of nonparaxial accelerating beams with arbitrary predefined convex trajectories. Our results lead to closed-form expressions for the required phase at the input plane. We present such closed-form results for a variety of caustic curves: besides circular, elliptic, and parabolic, we find for the first time general power-law and exponential trajectories. Furthermore, by changing the initial amplitude we can design different intensity profiles along the caustic.Comment: Accepted for publication in Optics Letter

Statistical analysis of emotions and opinions at Digg website

We performed statistical analysis on data from the Digg.com website, which enables its users to express their opinion on news stories by taking part in forum-like discussions as well as directly evaluate previous posts and stories by assigning so called "diggs". Owing to fact that the content of each post has been annotated with its emotional value, apart from the strictly structural properties, the study also includes an analysis of the average emotional response of the posts commenting the main story. While analysing correlations at the story level, an interesting relationship between the number of diggs and the number of comments received by a story was found. The correlation between the two quantities is high for data where small threads dominate and consistently decreases for longer threads. However, while the correlation of the number of diggs and the average emotional response tends to grow for longer threads, correlations between numbers of comments and the average emotional response are almost zero. We also show that the initial set of comments given to a story has a substantial impact on the further "life" of the discussion: high negative average emotions in the first 10 comments lead to longer threads while the opposite situation results in shorter discussions. We also suggest presence of two different mechanisms governing the evolution of the discussion and, consequently, its length.Comment: 26 pages, 16 figures, 6 table

Strain-induced interface reconstruction in epitaxial heterostructures

We investigate in the framework of Landau theory the distortion of the strain fields at the interface of two dissimilar ferroelastic oxides that undergo a structural cubic-to-tetragonal phase transition. Simple analytical solutions are derived for the dilatational and the order parameter strains that are globally valid over the whole of the heterostructure. The solutions reveal that the dilatational strain exhibits compression close to the interface which may in turn affect the electronic properties in that region.Comment: 7 pages, 5 figures, to be published in Physical Review

Quantitative Analysis of Bloggers Collective Behavior Powered by Emotions

Large-scale data resulting from users online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms involving emotions expressed in the posted text play a role. Here we combine approaches of statistical physics with machine-learning methods of text analysis to study emergence of the emotional behavior among Web users. Mapping the high-resolution data from digg.com onto bipartite network of users and their comments onto posted stories, we identify user communities centered around certain popular posts and determine emotional contents of the related comments by the emotion-classifier developed for this type of texts. Applied over different time periods, this framework reveals strong correlations between the excess of negative emotions and the evolution of communities. We observe avalanches of emotional comments exhibiting significant self-organized critical behavior and temporal correlations. To explore robustness of these critical states, we design a network automaton model on realistic network connections and several control parameters, which can be inferred from the dataset. Dissemination of emotions by a small fraction of very active users appears to critically tune the collective states

The Gradients in the 47 Tuc Red Giant Branch Bump and Horizontal Branch are Consistent With a Centrally-Concentrated, Helium-Enriched Second Stellar Generation

We combine ground and space-based photometry of the Galactic globular cluster 47 Tuc to measure four independent lines of evidence for a helium gradient in the cluster, whereby stars in the cluster outskirts would have a lower initial helium abundance than stars in and near the cluster core. First and second, we show that the red giant branch bump (RGBB) stars exhibit gradients in their number counts and brightness. With increased separation from the cluster center, they become more numerous relative to the other red giant (RG) stars. They also become fainter. For our third and fourth lines of evidence, we show that the horizontal branch (HB) of the cluster becomes both fainter and redder for sightlines farther from the cluster center. These four results are respectively detected at the 2.3$\sigma$, 3.6$\sigma$, 7.7$\sigma$ and 4.1$\sigma$ levels. Each of these independent lines of evidence is found to be significant in the cluster-outskirts; closer in, the data are more compatible with uniform mixing. Our radial profile is qualitatively consistent with but quantitatively tighter than previous results based on CN absorption. These observations are qualitatively consistent with a scenario wherein a second generation of stars with modestly enhanced helium and CNO abundance formed deep within the gravitational potential of a cluster of previous generation stars having more canonical abundances.Comment: 20 pages, 6 figures, 1 table, submitted to The Astrophysical Journa

From sentence to emotion: a real-time three-dimensional graphics metaphor of emotions extracted from text

This paper presents a novel concept: a graphical representation of human emotion extracted from text sentences. The major contributions of this paper are the following. First, we present a pipeline that extracts, processes, and renders emotion of 3D virtual human (VH). The extraction of emotion is based on data mining statistic of large cyberspace databases. Second, we propose methods to optimize this computational pipeline so that real-time virtual reality rendering can be achieved on common PCs. Third, we use the Poisson distribution to transfer database extracted lexical and language parameters into coherent intensities of valence and arousal—parameters of Russell's circumplex model of emotion. The last contribution is a practical color interpretation of emotion that influences the emotional aspect of rendered VHs. To test our method's efficiency, computational statistics related to classical or untypical cases of emotion are provided. In order to evaluate our approach, we applied our method to diverse areas such as cyberspace forums, comics, and theater dialog

Collective emotions online and their influence on community life

E-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information - how participants feel about the subject discussed or other group members. Emotions are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. It is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities. We show the collective character of affective phenomena on a large scale as observed in 4 million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions. Our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.Comment: 23 pages including Supporting Information, accepted to PLoS ON

Negative emotions boost users activity at BBC Forum

We present an empirical study of user activity in online BBC discussion forums, measured by the number of posts written by individual debaters and the average sentiment of these posts. Nearly 2.5 million posts from over 18 thousand users were investigated. Scale free distributions were observed for activity in individual discussion threads as well as for overall activity. The number of unique users in a thread normalized by the thread length decays with thread length, suggesting that thread life is sustained by mutual discussions rather than by independent comments. Automatic sentiment analysis shows that most posts contain negative emotions and the most active users in individual threads express predominantly negative sentiments. It follows that the average emotion of longer threads is more negative and that threads can be sustained by negative comments. An agent based computer simulation model has been used to reproduce several essential characteristics of the analyzed system. The model stresses the role of discussions between users, especially emotionally laden quarrels between supporters of opposite opinions, and represents many observed statistics of the forum.Comment: 29 pages, 6 figure