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 $\mathbb{Z}_2$ 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 $\Delta$ there are families of hypersurfaces with the Newton polytopes $(\lambda\Delta)_{\lambda \in \mathbb{N}}$ that are asymptotically maximal when $\lambda$ 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$\Omega$ cm irradiated with neutrons showed a radiation hardness up to a fluence of $10^{15}$n$_{eq}$cm$^{-2}$ with a hit efficiency of about 99% and a noise occupancy lower than $10^{-6}$ 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