40,571 research outputs found
Magnetism and Mott Transition: A Slave-rotor Study
Motivated by the debate of spin-density-wave (SDW) versus local-moment (LM)
picture in the iron-based superconducting (FeSC) materials, we consider a
two-band orbital-symmetric Hubbard model in which there is robust Fermi surface
nesting at . We obtain the phase diagram of such system by a
mean-field slave-rotor approach, in which the Fermi surface nesting and the SDW
order are explicitly taken into account via a natural separation of scale
between the Hund's coupling and the Coulomb interaction. We find that for a
sizable range of Hund's coupling the Mott transition acquires a strong
first-order character, but there also exists a small range of stronger Hund's
coupling in which an enhancement of magnetization can be observed on the SDW
side. We interpret the former scenario as one in which a sharp distinction can
be drawn between LM and the SDW picture, and the latter scenario as one in
which signs of LM physics begin to develop in the metallic phase. It is
tempting to suggest that some FeSC materials are in the vicinity of the latter
scenario.Comment: 7 pages, 5 figures; v2: Added discussions on anisotropy in
renormalized hopping, clarifications and discussions with regard to orbital
order, new inset in Fig. 3(d), expanded and revised bibliography, plus other
minor revisions. Accepted to PR
Gamma-ray Luminosity and Photon Index Evolution of FSRQ Blazars and Contribution to the Gamma-ray Background
We present the redshift evolutions and distributions of the gamma-ray
luminosity and photon spectral index of flat spectrum radio quasar (FSRQ) type
blazars, using non-parametric methods to obtain the evolutions and
distributions directly from the data. The sample we use for analysis consists
of almost all FSRQs observed with a greater than approximately 7 sigma
detection threshold in the first year catalog of the Fermi Gamma-ray Space
Telescope's Large Area Telescope, with redshfits as determined from optical
spectroscopy by Shaw et al. We find that FSQRs undergo rapid gamma-ray
luminosity evolution, but negligible photon index evolution, with redshift.
With these evolutions accounted for we determine the density evolution and
luminosity function of FSRQs, and calculate their total contribution to the
extragalactic gamma-ray background radiation, resolved and unresolved, which is
found to be 16(+10/-4)%, in agreement with previous studies.Comment: 9 pages, 10 figures, Accepted to Ap
Automatically Designing CNN Architectures for Medical Image Segmentation
Deep neural network architectures have traditionally been designed and
explored with human expertise in a long-lasting trial-and-error process. This
process requires huge amount of time, expertise, and resources. To address this
tedious problem, we propose a novel algorithm to optimally find hyperparameters
of a deep network architecture automatically. We specifically focus on
designing neural architectures for medical image segmentation task. Our
proposed method is based on a policy gradient reinforcement learning for which
the reward function is assigned a segmentation evaluation utility (i.e., dice
index). We show the efficacy of the proposed method with its low computational
cost in comparison with the state-of-the-art medical image segmentation
networks. We also present a new architecture design, a densely connected
encoder-decoder CNN, as a strong baseline architecture to apply the proposed
hyperparameter search algorithm. We apply the proposed algorithm to each layer
of the baseline architectures. As an application, we train the proposed system
on cine cardiac MR images from Automated Cardiac Diagnosis Challenge (ACDC)
MICCAI 2017. Starting from a baseline segmentation architecture, the resulting
network architecture obtains the state-of-the-art results in accuracy without
performing any trial-and-error based architecture design approaches or close
supervision of the hyperparameters changes.Comment: Accepted to Machine Learning in Medical Imaging (MLMI 2018
How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?
Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU)
systems. In particular, MUDiv allows for scheduling among users in order to
eliminate the negative effects of unfavorable channel fading conditions of some
users on the system performance. Scheduling, however, consumes energy (e.g.,
for making users' channel state information available to the scheduler). This
extra usage of energy, which could potentially be used for data transmission,
can be very wasteful, especially if the number of users is large. In this
paper, we answer the question of how much MUDiv is required for energy limited
MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling
algorithms which aim at maximizing the MUDiv gain. Toward this end, we
introduce a new realistic energy model which accounts for scheduling energy and
describes the distribution of the total energy between scheduling and data
transmission stages. Using the fact that such energy distribution can be
controlled by varying the number of active users, we optimize this number by
either (i) minimizing the overall system bit error rate (BER) for a fixed total
energy of all users in the system or (ii) minimizing the total energy of all
users for fixed BER requirements. We find that for a fixed number of available
users, the achievable MUDiv gain can be improved by activating only a subset of
users. Using asymptotic analysis and numerical simulations, we show that our
approach benefits from MUDiv gains higher than that achievable by generic
greedy access algorithm, which is the optimal scheduling method for energy
unlimited systems.Comment: 28 pages, 9 figures, submitted to IEEE Trans. Signal Processing in
Oct. 200
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OBOME - Ontology based opinion mining in UBIPOL
Ontologies have a special role in the UBIPOL system, they help to structure the policy related context, provide conceptualization for policy domain and use in the opinion mining process. In this work we presented a system called Ontology Based Opinion Mining Engine (OBOME) for analyzing a domain-specific opinion corpus by first assisting the user with the creation of a domain ontology from the corpus. We determined the polarity of opinion on the various domain aspects. In the former step, the policy domain aspect has are identified (namely which policy category is represented by the concept). This identification is supported by the policy modelling ontology, which describe the most important policy – related classes and structure. Then the most informative documents from the corpus are extracted and asked the user to create a set of aspects and related keywords using these documents. In the latter step, we used the corpus specific ontology to model the domain and extracted aspect-polarity associations using grammatical dependencies between words. Later, summarized results are shown to the user to analyze and store. Finally, in an offline process policy modeling ontology is updated
Contribution of through the QCD anomaly in exclusive decays and
We compute the decay rates for the exclusive decays and in a QCD-improved factorization framework by including the
contribution from the process through
the QCD anomaly. This method provides an alternative estimate of the
contribution to these decays as
compared to the one using the intrinsic charm content of the
and mesons determined through the decays . The resulting branching ratios are compared with the CLEO
data on and
and predictions are made for the rest.Comment: 16 pages including 4 postscript figures; uses epsfig. The most recent
branching ratios from CLEO, ref. [5], are taken into account. The theory part
is unchange
Methylation of CpG island is not a ubiquitous mechanism for the loss of oestrogen receptor in breast cancer cells.
Methylation has been shown to play an important role in the down-regulation of oestrogen receptors (ER) in breast cancer cells. One critical question that remains unclear is whether methylation can account for the loss of ER expression in cells derived from an ER-positive cell line. This laboratory has established an in vitro cell system using long-term growth of human ER-positive breast cancer cell line T47D in oestrogen-free medium. A clonal cell line, T47D:C4:2 (C4:2), has been characterized. Unlike T47D:A18 (A18), which is a T47D line maintained in oestrogen medium, C4:2 has lost the expression of ER and hormone responsiveness. DNA fingerprinting and restriction fragment length polymorphism (RFLP) analysis results confirmed that C4:2 was of the same lineage as A18. These cell lines provide an invaluable system to study the mechanism of ER expression and regulatory pathways leading to hormone-independent growth. The results here clearly demonstrate that the ER CpG island in C4:2 cells remains unmethylated. The loss of ER in the cell line must be due to mechanisms other than methylation. We also evaluated the ER CpG island in the MDA-MB-231:10A (10A) cell line, which is a clone from the MDA-MB-231 line obtained from ATCC and the DNA from the MDA-MB-231 cell line used in the original report. Unlike the cell line from the report, which showed a full methylation pattern in the island, the 10A line only showed a partial methylation pattern in the CpG island. Possible mechanisms pertaining to the heterogeneous methylation pattern of the ER CpG island in the breast cancer cells are discussed
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