266 research outputs found
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
-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 -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
How (not) to train a dependency parser: The curious case of jackknifing part-of-speech taggers
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
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