959 research outputs found
Finite mixtures of matrix-variate Poisson-log normal distributions for three-way count data
Three-way data structures, characterized by three entities, the units, the
variables and the occasions, are frequent in biological studies. In RNA
sequencing, three-way data structures are obtained when high-throughput
transcriptome sequencing data are collected for n genes across p conditions at
r occasions. Matrix-variate distributions offer a natural way to model
three-way data and mixtures of matrix-variate distributions can be used to
cluster three-way data. Clustering of gene expression data is carried out as
means to discovering gene co-expression networks. In this work, a mixture of
matrix-variate Poisson-log normal distributions is proposed for clustering read
counts from RNA sequencing. By considering the matrix-variate structure, full
information on the conditions and occasions of the RNA sequencing dataset is
simultaneously considered, and the number of covariance parameters to be
estimated is reduced. A Markov chain Monte Carlo expectation-maximization
algorithm is used for parameter estimation and information criteria are used
for model selection. The models are applied to both real and simulated data,
giving favourable clustering results
Structural origins of electronic conduction in amorphous copper-doped alumina
We perform an {\it ab initio} modeling of amorphous copper-doped alumina
(a-AlO:Cu), a prospective memory material based on resistance
switching, and study the structural origin of electronic conduction in this
material. We generate molecular dynamics based models of a-AlO:Cu at
various Cu-concentrations and study the structural, electronic and vibrational
properties as a function of Cu-concentration. Cu atoms show a strong tendency
to cluster in the alumina host, and metallize the system by filling the band
gap uniformly for higher Cu-concentrations. We also study thermal fluctuations
of the HOMO-LUMO energy splitting and observe the time evolution of the size of
the band gap, which can be expected to have an important impact on the
conductivity. We perform a numerical computation of conduction pathways, and
show its explicit dependence on Cu connectivity in the host. We present an
analysis of ion dynamics and structural aspects of localization of classical
normal modes in our models
Density functional study of FeS, FeSe and FeTe: Electronic structure, magnetism, phonons and superconductivity
We report density functional calculations of the electronic structure, Fermi
surface, phonon spectrum, magnetism and electron-phonon coupling for the
superconducting phase FeSe, as well as the related compounds FeS and FeTe. We
find that the Fermi surface structure of these compounds is very similar to
that of the Fe-As based superconductors, with cylindrical electron sections at
the zone corner, cylindrical hole surface sections, and depending on the
compound, other small hole sections at the zone center. As in the Fe-As based
materials, these surfaces are separated by a 2D nesting vector at
(,). The density of states, nesting and Fermi surface size increase
going from FeSe to FeTe. Both FeSe and FeTe show spin density wave ground
states, while FeS is close to an instability. In a scenario where
superconductivity is mediated by spin fluctuations at the SDW nesting vector,
the strongest superconductor in this series would be doped FeTe.Comment: Added note regarding recent experimental observations of
superconductivity under pressure. Some additional discussio
- …