Effects of transverse electron dispersion on photo-emission spectra of quasi-one-dimensional systems

The random phase approximation (RPA) spectral function of the one-dimensional electron band with the three-dimensional long range Coulomb interaction shows a broad feature which is spread on the scale of the plasmon energy and vanishes at the chemical potential. The fact that there are no quasi-particle $\delta$-peaks is the direct consequence of the acoustic nature of the collective plasmon mode. This behaviour of the spectral function is in the qualitative agreement with the angle resolved photo-emission spectra of some Bechgaard salts. In the present work we consider the modifications in the spectral function due to finite transverse electron dispersion. The transverse bandwidth is responsible for the appearance of an optical gap in the long wavelength plasmon mode. The plasmon dispersion of such kind introduces the quasi-particle $\delta$-peak into the spectral function at the chemical potential. The cross-over from the Fermi liquid to the non-Fermi liquid regime by decreasing the transverse bandwidth takes place through the decrease of the quasi-particle weight as the optical gap in the long wavelength plasmon mode is closing.Comment: 2 pages, 2 figures, ISCOM'0

Photo-emission properties of quasi-one-dimensional conductors

We calculate the self-energy of one-dimensional electron band with the three-dimensional long range Coulomb interaction within the random phase approximation, paying particular attention to the contribution coming from the electron scatterings on the collective plasmon mode. It is shown that the spectral density has a form of wide feature at thr frequency scale of the plasmon frequency, without the presence of quasi-particle delta-peaks. The relevance of this result with respect to experimental findings and to the theory of Luttinger liquids is discussed.Comment: 4 pages, 2 figure

Domain-aware Evaluation of Named Entity Recognition Systems for Croatian

We provide an evaluation of the currently available named entity recognition systems for Croatian. The evaluation puts special emphasis on domain dependence. To this goal, we manually annotated a dataset of approximately 1 million tokens of Croatian text from various domains within the newspaper text genre. The dataset was annotated using a three-class named entity tagset – denoting personal names, locations and organizations. We give insight to feature selection, domain sensitivity and effects of increase in training set size for statistical named entity recognition using the state-of-the-art Stanford NER system. We also sketch a comparison of publicly available named entity recognition systems for Croatian considering domain dependence, regardless of their underlying paradigms. Our top-performing system achieved an F1-score of 0.884 in a mixed-domain testing scenario, scoring 0.925 and 0.843 in the two domains separated for the experiment. The system shows consistency in state-of-the-art scores for detecting names of persons, locations and organizations

Baselines and test data for cross-lingual inference

The recent years have seen a revival of interest in textual entailment, sparked by i) the emergence of powerful deep neural network learners for natural language processing and ii) the timely development of large-scale evaluation datasets such as SNLI. Recast as natural language inference, the problem now amounts to detecting the relation between pairs of statements: they either contradict or entail one another, or they are mutually neutral. Current research in natural language inference is effectively exclusive to English. In this paper, we propose to advance the research in SNLI-style natural language inference toward multilingual evaluation. To that end, we provide test data for four major languages: Arabic, French, Spanish, and Russian. We experiment with a set of baselines. Our systems are based on cross-lingual word embeddings and machine translation. While our best system scores an average accuracy of just over 75%, we focus largely on enabling further research in multilingual inference.Comment: To appear at LREC 201

Distant Supervision from Disparate Sources for Low-Resource Part-of-Speech Tagging

We introduce DsDs: a cross-lingual neural part-of-speech tagger that learns from disparate sources of distant supervision, and realistically scales to hundreds of low-resource languages. The model exploits annotation projection, instance selection, tag dictionaries, morphological lexicons, and distributed representations, all in a uniform framework. The approach is simple, yet surprisingly effective, resulting in a new state of the art without access to any gold annotated data.Comment: EMNLP 201

Motivation of the youth of Bosnia and Herzegovina to start a business: Examining aspects of education and social and political engagement

In the present study, several logit models were tested to identify the antecedents of entrepreneurial intention among the youth of Bosnia and Herzegovina (B&H). Specifically, we explore whether demographic and socio-economic characteristic or whether perceptions of education curriculum and social and political engagement as well as the perception of media influence have an impact on the intention to start one’s own business. Data analysis was done on a sample of 3,611 young people. Education level and perception of the standard of living have an impact on the attitude towards self-employment. In addition, the perception of education curriculum and parents support in education is linked with the entrepreneurial intention. Furthermore, some campaigns of social and political engagement are significant predictors of the propensity towards starting the business. Finally, the perception of media influence impacts entrepreneurial intention positively. The findings have important implications for policymakers and universities