7,348 research outputs found
A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping
The method described here performs blind deconvolution of the beamforming
output in the frequency domain. To provide accurate blind deconvolution,
sparsity priors are introduced with a smooth \ell_1/\ell_2 regularization term.
As the mean of the noise in the power spectrum domain is dependent on its
variance in the time domain, the proposed method includes a variance estimation
step, which allows more robust blind deconvolution. Validation of the method on
both simulated and real data, and of its performance, are compared with two
well-known methods from the literature: the deconvolution approach for the
mapping of acoustic sources, and sound density modeling
Asymptotically maximal families of hypersurfaces in toric varieties
A real algebraic variety is maximal (with respect to the Smith-Thom
inequality) if the sum of the Betti numbers (with coefficients)
of the real part of the variety is equal to the sum of Betti numbers of its
complex part. We prove that there exist polytopes that are not Newton polytopes
of any maximal hypersurface in the corresponding toric variety. On the other
hand we show that for any polytope there are families of hypersurfaces
with the Newton polytopes that are
asymptotically maximal when tends to infinity. We also show that
these results generalize to complete intersections.Comment: 18 pages, 1 figur
Decomposition of fractional quantum Hall states: New symmetries and approximations
We provide a detailed description of a new symmetry structure of the monomial
(Slater) expansion coefficients of bosonic (fermionic) fractional quantum Hall
states first obtained in Ref. 1, which we now extend to spin-singlet states. We
show that the Haldane-Rezayi spin-singlet state can be obtained without exact
diagonalization through a differential equation method that we conjecture to be
generic to other FQH model states. The symmetry rules in Ref. 1 as well as the
ones we obtain for the spin singlet states allow us to build approximations of
FQH states that exhibit increasing overlap with the exact state (as a function
of system size). We show that these overlaps reach unity in the thermodynamic
limit even though our approximation omits more than half of the Hilbert space.
We show that the product rule is valid for any FQH state which can be written
as an expectation value of parafermionic operators.Comment: 22 pages, 8 figure
Severe tremor due to vancomycin therapy: a case report and literature review
SummaryVancomycin is a popular antimicrobial used to treat a variety of Gram-positive infections. Its side effect profile has been well defined due to its high global utilization as a result of the emergence of antimicrobial-resistant organisms in recent decades. Despite its widespread use, however, various idiosyncratic reactions may occur without adequate or universal reporting. We present a case of severe tremor due to vancomycin that has not been previously reported in the literature. Our patient might have been prone to this adverse effect given an underlying essential tremor. Causality is presumed based on the temporal association, while the pathophysiological link remains elusive
Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters
We present several methods towards construction of precursors, which show
great promise towards early predictions, of solar flare events in this paper. A
data pre-processing pipeline is built to extract useful data from multiple
sources, Geostationary Operational Environmental Satellites (GOES) and Solar
Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI), to prepare
inputs for machine learning algorithms. Two classification models are
presented: classification of flares from quiet times for active regions and
classification of strong versus weak flare events. We adopt deep learning
algorithms to capture both the spatial and temporal information from HMI
magnetogram data. Effective feature extraction and feature selection with raw
magnetogram data using deep learning and statistical algorithms enable us to
train classification models to achieve almost as good performance as using
active region parameters provided in HMI/Space-Weather HMI-Active Region Patch
(SHARP) data files. Case studies show a significant increase in the prediction
score around 20 hours before strong solar flare events
Plane-wave based electronic structure calculations for correlated materials using dynamical mean-field theory and projected local orbitals
The description of realistic strongly correlated systems has recently
advanced through the combination of density functional theory in the local
density approximation (LDA) and dynamical mean field theory (DMFT). This
LDA+DMFT method is able to treat both strongly correlated insulators and
metals. Several interfaces between LDA and DMFT have been used, such as (N-th
order) Linear Muffin Tin Orbitals or Maximally localized Wannier Functions.
Such schemes are however either complex in use or additional simplifications
are often performed (i.e., the atomic sphere approximation). We present an
alternative implementation of LDA+DMFT, which keeps the precision of the
Wannier implementation, but which is lighter. It relies on the projection of
localized orbitals onto a restricted set of Kohn-Sham states to define the
correlated subspace. The method is implemented within the Projector Augmented
Wave (PAW) and within the Mixed Basis Pseudopotential (MBPP) frameworks. This
opens the way to electronic structure calculations within LDA+DMFT for more
complex structures with the precision of an all-electron method. We present an
application to two correlated systems, namely SrVO3 and beta-NiS (a
charge-transfer material), including ligand states in the basis-set. The
results are compared to calculations done with Maximally Localized Wannier
functions, and the physical features appearing in the orbitally resolved
spectral functions are discussed.Comment: 15 pages, 17 figure
Searching for the Annual Modulation of Dark Matter signal with the GENIUS-TF experiment
The annual modulation of the recoil spectrum observed in an underground
detector is well known as the main signature of a possible WIMP signal. The
GENIUS-TF experiment, under construction in the Gran Sasso National Laboratory,
can search for the annual modulation of the Dark Matter signal using 40 kg of
naked-Ge detectors in liquid nitrogen. Starting from a set of data simulated
under the hypothesis of modulation and using different methods, we show the
potential of GENIUS-TF for extracting the modulated signal and the expected
WIMP mass and WIMP cross section.Comment: In press, Nuclear Instruments and Methods in Physics Research Section
A: Accelerators, Spectrometers, Detectors and Associated Equipment (2003) and
in Proc. of IDM2002, York Minster, England, 2-6 September, 2002, World
Scientific 200
Characterisation of AMS H35 HV-CMOS monolithic active pixel sensor prototypes for HEP applications
Monolithic active pixel sensors produced in High Voltage CMOS (HV-CMOS)
technology are being considered for High Energy Physics applications due to the
ease of production and the reduced costs. Such technology is especially
appealing when large areas to be covered and material budget are concerned.
This is the case of the outermost pixel layers of the future ATLAS tracking
detector for the HL-LHC. For experiments at hadron colliders, radiation
hardness is a key requirement which is not fulfilled by standard CMOS sensor
designs that collect charge by diffusion. This issue has been addressed by
depleted active pixel sensors in which electronics are embedded into a large
deep implantation ensuring uniform charge collection by drift. Very first small
prototypes of hybrid depleted active pixel sensors have already shown a
radiation hardness compatible with the ATLAS requirements. Nevertheless, to
compete with the present hybrid solutions a further reduction in costs
achievable by a fully monolithic design is desirable. The H35DEMO is a large
electrode full reticle demonstrator chip produced in AMS 350 nm HV-CMOS
technology by the collaboration of Karlsruher Institut f\"ur Technologie (KIT),
Institut de F\'isica d'Altes Energies (IFAE), University of Liverpool and
University of Geneva. It includes two large monolithic pixel matrices which can
be operated standalone. One of these two matrices has been characterised at
beam test before and after irradiation with protons and neutrons. Results
demonstrated the feasibility of producing radiation hard large area fully
monolithic pixel sensors in HV-CMOS technology. H35DEMO chips with a substrate
resistivity of 200 cm irradiated with neutrons showed a radiation
hardness up to a fluence of ncm with a hit efficiency of
about 99% and a noise occupancy lower than hits in a LHC bunch
crossing of 25ns at 150V
Influence of Amazonian deforestation on the future evolution of regional surface fluxes, circulation, surface temperature and precipitation
The extent of the Amazon rainforest is projected to drastically decrease in future decades because of land-use changes. Previous climate modelling studies have found that the biogeophysical effects of future Amazonian deforestation will likely increase surface temperatures and reduce precipitation locally. However, the magnitude of these changes and the potential existence of tipping points in the underlying relationships is still highly uncertain. Using a regional climate model at a resolution of about 50 km over the South American continent, we perform four ERA-interim-driven simulations with prescribed land cover maps corresponding to present-day vegetation, two deforestation scenarios for the twenty-first century, and a totally-deforested Amazon case. In response to projected land cover changes for 2100, we find an annual mean surface temperature increase of 0.5∘C over the Amazonian region and an annual mean decrease in rainfall of 0.17 mm/day compared to present-day conditions. These estimates reach 0.8∘C and 0.22 mm/day in the total-deforestation case. We also compare our results to those from 28 previous (regional and global) climate modelling experiments. We show that the historical development of climate models did not modify the median estimate of the Amazonian climate sensitivity to deforestation, but led to a reduction of its uncertainty. Our results suggest that the biogeophysical effects of deforestation alone are unlikely to lead to a tipping point in the evolution of the regional climate under present-day climate conditions. However, the conducted synthesis of the literature reveals that this behaviour may be model-dependent, and the greenhouse gas-induced climate forcing and biogeochemical feedbacks should also be taken into account to fully assess the future climate of this region
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