688,091 research outputs found
Mathematics at the eve of a historic transition in biology
A century ago physicists and mathematicians worked in tandem and established
quantum mechanism. Indeed, algebras, partial differential equations, group
theory, and functional analysis underpin the foundation of quantum mechanism.
Currently, biology is undergoing a historic transition from qualitative,
phenomenological and descriptive to quantitative, analytical and predictive.
Mathematics, again, becomes a driving force behind this new transition in
biology.Comment: 5 pages, 2 figure
Learning to Identify Ambiguous and Misleading News Headlines
Accuracy is one of the basic principles of journalism. However, it is
increasingly hard to manage due to the diversity of news media. Some editors of
online news tend to use catchy headlines which trick readers into clicking.
These headlines are either ambiguous or misleading, degrading the reading
experience of the audience. Thus, identifying inaccurate news headlines is a
task worth studying. Previous work names these headlines "clickbaits" and
mainly focus on the features extracted from the headlines, which limits the
performance since the consistency between headlines and news bodies is
underappreciated. In this paper, we clearly redefine the problem and identify
ambiguous and misleading headlines separately. We utilize class sequential
rules to exploit structure information when detecting ambiguous headlines. For
the identification of misleading headlines, we extract features based on the
congruence between headlines and bodies. To make use of the large unlabeled
data set, we apply a co-training method and gain an increase in performance.
The experiment results show the effectiveness of our methods. Then we use our
classifiers to detect inaccurate headlines crawled from different sources and
conduct a data analysis.Comment: Accepted by IJCAI 201
Determining the luminosity function of Swift long gamma-ray bursts with pseudo-redshifts
The determination of luminosity function (LF) of gamma-ray bursts (GRBs) is
of an important role for the cosmological applications of the GRBs, which is
however hindered seriously by some selection effects due to redshift
measurements. In order to avoid these selection effects, we suggest to
calculate pseudo-redshifts for Swift GRBs according to the empirical L-E_p
relationship. Here, such a relationship is determined by reconciling
the distributions of pseudo- and real redshifts of redshift-known GRBs. The
values of E_p taken from Butler's GRB catalog are estimated with Bayesian
statistics rather than observed. Using the GRB sample with pseudo-redshifts of
a relatively large number, we fit the redshift-resolved luminosity
distributions of the GRBs with a broken-power-law LF. The fitting results
suggest that the LF could evolve with redshift by a redshift-dependent break
luminosity, e.g., L_b=1.2\times10^{51}(1+z)^2\rm erg s^{-1}. The low- and
high-luminosity indices are constrained to 0.8 and 2.0, respectively. It is
found that the proportional coefficient between GRB event rate and star
formation rate should correspondingly decrease with increasing redshifts.Comment: 5 pages, 5 figures, accepted for publication in ApJ
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