80,456 research outputs found
The EM Algorithm and the Rise of Computational Biology
In the past decade computational biology has grown from a cottage industry
with a handful of researchers to an attractive interdisciplinary field,
catching the attention and imagination of many quantitatively-minded
scientists. Of interest to us is the key role played by the EM algorithm during
this transformation. We survey the use of the EM algorithm in a few important
computational biology problems surrounding the "central dogma"; of molecular
biology: from DNA to RNA and then to proteins. Topics of this article include
sequence motif discovery, protein sequence alignment, population genetics,
evolutionary models and mRNA expression microarray data analysis.Comment: Published in at http://dx.doi.org/10.1214/09-STS312 the Statistical
Science (http://www.imstat.org/sts/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Doping dependence of the electron-doped cuprate superconductors from the antiferromagnetic properties of the Hubbard model
Within the Kotliar-Ruckenstein slave-boson approach, we have studied the
antiferromagnetic (AF) properties for the --- model applied to
electron-doped cuprate superconductors. Due to inclusion of spin fluctuations
the AF order decreases with doping much faster than obtained in the
Hartree-Fock theory. Under an intermediate {\it constant} the calculated
doping evolution of the spectral intensity has satisfactorily reproduced the
experimental results, without need of a strongly doping-dependent as argued
earlier. This may reconcile a discrepancy suggested in recent studies on
photoemission and optical conductivity.Comment: 5 pages, 4 eps figures, minor improvement, references added, to
appear in Phys. Rev.
Study of gossamer superconductivity and antiferromagnetism in the t-J-U model
The d-wave superconductivity (dSC) and antiferromagnetism are analytically
studied in a renormalized mean field theory for a two dimensional t-J model
plus an on-site repulsive Hubbard interaction . The purpose of introducing
the term is to partially impose the no double occupancy constraint by
employing the Gutzwiller approximation. The phase diagrams as functions of
doping and are studied. Using the standard value of and
in the large limit, we show that the antiferromagnetic (AF) order emerges
and coexists with the dSC in the underdoped region below the doping
. The dSC order parameter increases from zero as the doping
increases and reaches a maximum near the optimal doping . In
the small limit, only the dSC order survives while the AF order disappears.
As increased to a critical value, the AF order shows up and coexists with
the dSC in the underdoped regime. At half filing, the system is in the dSC
state for small and becomes an AF insulator for large . Within the
present mean field approach, We show that the ground state energy of the
coexistent state is always lower than that of the pure dSC state.Comment: 7 pages, 8 figure
Effects of QCD Resummation on and Production at the Tevatron
The resummation of multiple soft gluon emission affects the production rate
and kinematic distributions of (where h is a Higgs boson) and
pairs at the Tevatron with TeV. Using the Collins-Soper-Sterman
resummation formalism, the production rate is enhanced over the
next-to-leading-order (NLO) prediction by 2-3% for the process, for
Higgs boson masses between 80-120 GeV, and over 3% for the process
for GeV. After resummation, the rate changes by 12-13% when
is varied by GeV. Various kinematic distributions are presented
for the individual final state particles and for the pair. The explicit
radiation of hard gluons in NLO QCD is included also for the final
state.Comment: 9 pages, 12 Postscript figures, in RevTeX format, uses epsf.te
Economic Sizing of Distributed Energy Resources for Reliable Community Microgrids
Community microgrids offer many advantages for power distribution systems.
When there is an extreme event happening, distribution systems can be
seamlessly partitioned into several community microgrids for uninterrupted
supply to the end-users. In order to guarantee the system reliability,
distributed energy resources (DERs) should be sized for ensuring generation
adequacy to cover unexpected events. This paper presents a comprehensive
methodology for DERs selection in community microgrids, and an economic
approach to meet the system reliability requirements. Algorithms of discrete
time Fourier transform (DTFT) and particle swarm optimization (PSO) are
employed to find the optimal solution. Uncertainties of load demand and
renewable generation are taken into consideration. As part of the case study, a
sensitivity analysis is carried out to show the renewable generation impact on
DERs' capacity planning.Comment: 5 pages, 6 figures, 1 table, 2017 IEEE Power & Energy Society General
Meeting. arXiv admin note: substantial text overlap with arXiv:1708.0102
Advection-dominated accretion, jets and the spectral energy distribution of LINERs
Low-luminosity active galactic nuclei (LLAGNs) represent the bulk of the AGN
population in the present-day universe and they trace low-level accreting
supermassive black holes. The observational properties of LLAGNs suggest that
their central engines are intrinsically different from those of more luminous
AGNs. It has been suggested that accretion in LLAGNs occurs via an
advection-dominated accretion flow (ADAF) associated with strong jets. In order
to probe the accretion physics in LLAGNs as a class, we model the
multiwavelength spectral energy distributions (SEDs) of 24 LINERs (taken from a
recent compilation by Eracleous et al.) with a coupled accretion-jet model. The
accretion flow is modeled as an inner ADAF outside of which there is a
truncated standard thin disk. These SEDs include radio, near-IR to near-UV HST
data, and Chandra X-ray data. We find that the radio emission is severely
underpredicted by ADAF models but can be explained by the relativistic jet. The
origin of the X-ray radiation in most sources can be explained by three
distinct scenarios: the X-rays can be dominated by emission from the ADAF, the
jet, or from both components contributing at similar levels. From the model
fits, we estimate important parameters of the central engine of LINERs, such as
the mass accretion rate -- relevant for studies of the feeding of AGNs -- and
the mass-loss rate in the jet and the jet power -- relevant for studies of the
kinetic feedback from jets.Comment: 6 pages, 3 figures, to be published in the Proceedings of the IAU
Symposium no. 267, "Co-Evolution of Central Black Holes and Galaxies: Feeding
and Feedback", eds. B.M. Peterson, R.S. Somerville and T. Storchi-Bergmann,
in pres
Statistical Mechanical Treatments of Protein Amyloid Formation
Protein aggregation is an important field of investigation because it is
closely related to the problem of neurodegenerative diseases, to the
development of biomaterials, and to the growth of cellular structures such as
cyto-skeleton. Self-aggregation of protein amyloids, for example, is a
complicated process involving many species and levels of structures. This
complexity, however, can be dealt with using statistical mechanical tools, such
as free energies, partition functions, and transfer matrices. In this article,
we review general strategies for studying protein aggregation using statistical
mechanical approaches and show that canonical and grand canonical ensembles can
be used in such approaches. The grand canonical approach is particularly
convenient since competing pathways of assembly and dis-assembly can be
considered simultaneously. Another advantage of using statistical mechanics is
that numerically exact solutions can be obtained for all of the thermodynamic
properties of fibrils, such as the amount of fibrils formed, as a function of
initial protein concentration. Furthermore, statistical mechanics models can be
used to fit experimental data when they are available for comparison.Comment: Accepted to IJM
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