11,655 research outputs found
Protein Secondary Structure Prediction Using Cascaded Convolutional and Recurrent Neural Networks
Protein secondary structure prediction is an important problem in
bioinformatics. Inspired by the recent successes of deep neural networks, in
this paper, we propose an end-to-end deep network that predicts protein
secondary structures from integrated local and global contextual features. Our
deep architecture leverages convolutional neural networks with different kernel
sizes to extract multiscale local contextual features. In addition, considering
long-range dependencies existing in amino acid sequences, we set up a
bidirectional neural network consisting of gated recurrent unit to capture
global contextual features. Furthermore, multi-task learning is utilized to
predict secondary structure labels and amino-acid solvent accessibility
simultaneously. Our proposed deep network demonstrates its effectiveness by
achieving state-of-the-art performance, i.e., 69.7% Q8 accuracy on the public
benchmark CB513, 76.9% Q8 accuracy on CASP10 and 73.1% Q8 accuracy on CASP11.
Our model and results are publicly available.Comment: 8 pages, 3 figures, Accepted by International Joint Conferences on
Artificial Intelligence (IJCAI
Note on neutron star equation of state in the light of GW170817
From the very first multimessenger event of GW170817, clean robust
constraints can be obtained for the tidal deformabilities of the two stars
involved in the merger, which provides us unique opportunity to study the
equation of states (EOSs) of dense stellar matter. In this contribution, we
employ a model from the quark level, describing consistently a nucleon and
many-body nucleonic system from a quark potential. We check that our sets of
EOSs are consistent with available experimental and observational constraints
at both sub-nuclear saturation densities and higher densities. The agreements
with ab-initio calculations are also good. Especially, we tune the density
dependence of the symmetry energy (characterized by its slope at nuclear
saturation ) and study its influence on the tidal deformability. The
so-called EOS is named after the case of , and it gives
and , for a
star. The tidal signals are demonstrated to be insensitive to
the uncertain crust-core matching, despite the good correlation between the
symmetry energy slope and the radius of the star.Comment: 8 pages, 6 figures, Submitted to the AIP Proceedings of the
Xiamen-CUSTIPEN Workshop on the EOS of Dense Neutron-Rich Matter in the Era
of Gravitational Wave Astronomy, Jan. 3-7, Xiamen, Chin
Graph state basis for Pauli Channels
We introduce graph state basis diagonalization to calculate the coherent
information of a quantum code passing through a Pauli channel. The scheme is
5000 times faster than the best known one for some concatenated repetition
codes, providing us a practical constructive way of approaching the quantum
capacity of a Pauli channel. The calculation of the coherent information of
non-additive quantum code can also be greatly simplified in graph state basis.Comment: 5 page
The analysis of the charmonium-like states ,, , and according to its strong decay behaviors
Inspired by the newly observed state , we analyze the strong
decay behaviors of some charmonium-like states ,,
, and by the model. We carry out our
work based on the hypothesis that these states are all being the charmonium
systems. Our analysis indicates that charmonium state can be a good
candidate for and state is the possible assignment for
. Considering as the state, the decay behavior of
is inconsistent with the experimental data. So, we can not assign
as the charmonium state by present work. Besides, our
analysis imply that it is reasonable to assign and to be
the same state, . However, combining our analysis with that of
Zhou~\cite{ZhouZY}, we speculate that / might not be a pure
systems
Analysis of the strong coupling form factors of and in QCD sum rules
In this article, we study the strong interaction of the vertexes
and using the three-point QCD sum rules under two different dirac
structures. Considering the contributions of the vacuum condensates up to
dimension in the operation product expansion, the form factors of these
vertexes are calculated. Then, we fit the form factors into analytical
functions and extrapolate them into time-like regions, which giving the
coupling constant. Our analysis indicates that the coupling constant for these
two vertexes are and
.Comment: 6 figure
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