12,149 research outputs found
Learning a Mixture of Deep Networks for Single Image Super-Resolution
Single image super-resolution (SR) is an ill-posed problem which aims to
recover high-resolution (HR) images from their low-resolution (LR)
observations. The crux of this problem lies in learning the complex mapping
between low-resolution patches and the corresponding high-resolution patches.
Prior arts have used either a mixture of simple regression models or a single
non-linear neural network for this propose. This paper proposes the method of
learning a mixture of SR inference modules in a unified framework to tackle
this problem. Specifically, a number of SR inference modules specialized in
different image local patterns are first independently applied on the LR image
to obtain various HR estimates, and the resultant HR estimates are adaptively
aggregated to form the final HR image. By selecting neural networks as the SR
inference module, the whole procedure can be incorporated into a unified
network and be optimized jointly. Extensive experiments are conducted to
investigate the relation between restoration performance and different network
architectures. Compared with other current image SR approaches, our proposed
method achieves state-of-the-arts restoration results on a wide range of images
consistently while allowing more flexible design choices. The source codes are
available in http://www.ifp.illinois.edu/~dingliu2/accv2016
Collider Phenomenology with Split-UED
We investigate the collider implications of Split Universal Extra Dimensions.
The non-vanishing fermion mass in the bulk, which is consistent with the
KK-parity, largely modifies the phenomenology of Minimal Universal Exta
Dimensions. We scrutinize the behavior of couplings and study the discovery
reach of the Tevatron and the LHC for level-2 Kaluza-Klein modes in the
dilepton channel, which would indicates the presence of the extra dimensions.
Observation of large event rates for dilepton resonances can result from a
nontrivial fermion mass profile along the extra dimensions, which, in turn, may
corroborate extra dimensional explanation for the observation of the positron
excess in cosmic rays.Comment: 23 pages, 15 figure
Early (and Later) LHC Search Strategies for Broad Dimuon Resonances
Resonance searches generally focus on narrow states that would produce a
sharp peak rising over background. Early LHC running will, however, be
sensitive primarily to broad resonances. In this paper we demonstrate that
statistical methods should suffice to find broad resonances and distinguish
them from both background and contact interactions over a large range of
previously unexplored parameter space. We furthermore introduce an angular
measure we call ellipticity, which measures how forward (or backward) the muon
is in eta, and allows for discrimination between models with different parity
violation early in the LHC running. We contrast this with existing angular
observables and demonstrate that ellipticity is superior for discrimination
based on parity violation, while others are better at spin determination.Comment: 31 pages, 19 figures. References added, minor modifications made to
section
Brain activation during face perception: evidence of a developmental change.
Behavioral studies suggest that children under age 10 process faces using a piecemeal strategy based on individual distinctive facial features, whereas older children use a configural strategy based on the spatial relations among the face's features. The purpose of this study was to determine whether activation of the fusiform gyrus, which is involved in face processing in adults, is greater during face processing in older children (12-14 years) than in younger children (8-10 years). Functional MRI scans were obtained while children viewed faces and houses. A developmental change was observed: Older children, but not younger children, showed significantly more activation in bilateral fusiform gyri for faces than for houses. Activation in the fusiform gyrus correlated significantly with age and with a behavioral measure of configural face processing. Regions believed to be involved in processing basic facial features were activated in both younger and older children. Some evidence was also observed for greater activation for houses versus faces for the older children than for the younger children, suggesting that processing of these two stimulus types becomes more differentiated as children age. The current results provide biological insight into changes in visual processing of faces that occur with normal development
5D UED: Flat and Flavorless
5D UED is not automatically minimally flavor violating. This is due to flavor
asymmetric counter-terms required on the branes. Additionally, there are likely
to be higher dimensional operators which directly contribute to flavor
observables. We document a mostly unsuccessful attempt at utilizing
localization in a flat extra dimension to resolve these flavor constraints
while maintaining KK-parity as a good quantum number. It is unsuccessful
insofar as we seem to be forced to add brane operators in such a way as to
precisely mimic the effects of a double throat warped extra dimension. In the
course of our efforts, we encounter and present solutions to a problem common
to many extra dimensional models in which fields are "doubly localized:"
ultra-light modes. Under scrutiny, this issue seems tied to an intrinsic
tension between maintaining Kaluza-Klein parity and resolving mass hierarchies
via localization.Comment: 27 pages, 6 figure
Measuring productivity and efficiency: a Kalman filter approach
In the Kalman filter setting, one can model the inefficiency term of the standard stochastic frontier composed error as an unobserved state. In this study a panel data version of the local level model is used for estimating time-varying efficiencies of firms. We apply the Kalman filter to estimate average efficiencies of U.S. airlines and find that the technical efficiency of these carriers did not improve during the period 1999-2009. During this period the industry incurred substantial losses, and the efficiency gains from reorganized networks, code-sharing arrangements, and other best business practices apparently had already been realized
Spin Discrimination in Three-Body Decays
The identification of the correct model for physics beyond the Standard Model
requires the determination of the spin of new particles. We investigate to
which extent the spin of a new particle can be identified in scenarios
where it decays dominantly in three-body decays . Here we
assume that is a candidate for dark matter and escapes direct detection at
a high energy collider such as the LHC. We show that in the case that all
intermediate particles are heavy, one can get information on the spins of
and at the LHC by exploiting the invariant mass distribution of the two
standard model fermions. We develop a model-independent strategy to determine
the spins without prior knowledge of the unknown couplings and test it in a
series of Monte Carlo studies.Comment: 31+1 pages, 4 figures, 8 tables, JHEP.cls include
Leukocyte-specific protein 1 regulates T-cell migration in rheumatoid arthritis
Copy number variations (CNVs) have been implicated in human diseases. However, it remains unclear how they affect immune dysfunction and autoimmune diseases, including rheumatoid arthritis (RA). Here, we identified a novel leukocyte-specific protein 1 (LSP1) deletion variant for RA susceptibility located in 11p15.5. We replicated that the copy number of LSP1 gene is significantly lower in patients with RA, which correlates positively with LSP1 protein expression levels. Differentially expressed genes in Lsp1-deficient primary T cells represent cell motility and immune and cytokine responses. Functional assays demonstrated that LSP1, induced by T-cell receptor activation, negatively regulates T-cell migration by reducing ERK activation in vitro. In mice with T-cell-dependent chronic inflammation, loss of Lsp1 promotes migration of T cells into the target tissues as well as draining lymph nodes, exacerbating disease severity. Moreover, patients with RA show diminished expression of LSP1 in peripheral T cells with increased migratory capacity, suggesting that the defect in LSP1 signaling lowers the threshold for T-cell activation. To our knowledge, our work is the first to demonstrate how CNVs result in immune dysfunction and a disease phenotype. Particularly, our data highlight the importance of LSP1 CNVs and LSP1 insufficiency in the pathogenesis of RA and provide previously unidentified insights into the mechanisms underlying T-cell migration toward the inflamed synovium in RA.1187Ysciescopu
Tailoring force sensitivity and selectivity by microstructure engineering of multidirectional electronic skins
Electronic skins (e-skins) with high sensitivity to multidirectional mechanical stimuli are crucial for healthcare monitoring devices, robotics, and wearable sensors. In this study, we present piezoresistive e-skins with tunable force sensitivity and selectivity to multidirectional forces through the engineered microstructure geometries (i.e., dome, pyramid, and pillar). Depending on the microstructure geometry, distinct variations in contact area and localized stress distribution are observed under different mechanical forces (i.e., normal, shear, stretching, and bending), which critically affect the force sensitivity, selectivity, response/relaxation time, and mechanical stability of e-skins. Microdome structures present the best force sensitivities for normal, tensile, and bending stresses. In particular, microdome structures exhibit extremely high pressure sensitivities over broad pressure ranges (47,062 kPa(-1) in the range of < 1 kPa, 90,657 kPa(-1) in the range of 1-10 kPa, and 30,214 kPa(-1) in the range of 10-26 kPa). On the other hand, for shear stress, micropillar structures exhibit the highest sensitivity. As proof-of-concept applications in healthcare monitoring devices, we show that our e-skins can precisely monitor acoustic waves, breathing, and human artery/carotid pulse pressures. Unveiling the relationship between the microstructure geometry of e-skins and their sensing capability would provide a platform for future development of high-performance microstructured e-skins
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