Determining Energy Balance in the Flaring Chromosphere from Oxygen V Line Ratios

The impulsive phase of solar flares is a time of rapid energy deposition and heating in the lower solar atmosphere, leading to changes in the temperature and density structure of the region. We use an O V density diagnostic formed of the 192 to 248 line ratio, provided by Hinode EIS, to determine the density of flare footpoint plasma, at O V formation temperatures of 250,000 K, giving a constraint on the properties of the heated transition region. Hinode EIS rasters from 2 small flare events in December 2007 were used. Raster images were co-aligned to identify and establish the footpoint pixels, multiple-component Gaussian line fitting of the spectra was carried out to isolate the diagnostic pair, and the density was calculated for several footpoint areas. The assumptions of equilibrium ionization and optically thin radiation for the O V lines were found to be acceptable. Properties of the electron distribution, for one event, were deduced from earlier RHESSI hard X-ray observations and used to calculate the plasma heating rate, delivered by an electron beam adopting collisional thick-target assumptions, for 2 model atmospheres. Electron number densities of at least log n = 12.3 cm-3 were measured during the flare impulsive phase, far higher than previously expected. For one footpoint, the radiative loss rate for this plasma was found to exceed that which can be delivered by an electron beam implied by the RHESSI data. However, when assuming a completely ionised target atmosphere the heating rate exceeded the losses. A chromospheric thickness of 70-700 km was found to be required to balance a conductive input to the O V-emitting region with radiative losses. The analysis shows that for heating by collisional electrons, it is difficult, or impossible to raise the temperature of the chromosphere to explain the observed densities without assuming a completely ionised atmosphere.Comment: Accepted to A&A 14th September 201

Impulsive Heating of Solar Flare Ribbons Above 10 MK

The chromospheric response to the input of flare energy is marked by extended extreme ultraviolet (EUV) ribbons and hard X-ray (HXR) footpoints. These are usually explained as the result of heating and bremsstrahlung emission from accelerated electrons colliding in the dense chromospheric plasma. We present evidence of impulsive heating of flare ribbons above 10 MK in a two-ribbon flare. We analyse the impulsive phase of SOL2013-11-09T06:38, a C2.6 class event using data from Atmospheric Imaging Assembly (AIA) on board of Solar Dynamics Observatory (SDO) and the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) to derive the temperature, emission measure and differential emission measure of the flaring regions and investigate the evolution of the plasma in the flaring ribbons. The ribbons were visible at all SDO/AIA EUV/UV wavelengths, in particular, at 94 and 131 \AA\ filters, sensitive to temperatures of 8 MK and 12 MK. Time evolution of the emission measure of the plasma above 10 MK at the ribbons has a peak near the HXR peak time. The presence of hot plasma in the lower atmosphere is further confirmed by RHESSI imaging spectroscopy analysis, which shows resolved sources at 11-13 MK associated with at least one ribbon. We found that collisional beam heating can only marginally explain the necessary power to heat the 10 MK plasma at the ribbons.Comment: 21 pages, 15 figure

Generalized Wilson Chain for solving multichannel quantum impurity problems

The Numerical Renormalization Group is used to solve quantum impurity problems, which describe magnetic impurities in metals, nanodevices, and correlated materials within DMFT. Here we present a simple generalization of the Wilson Chain, which improves the scaling of computational cost with the number of channels/bands, bringing new problems within reach. The method is applied to calculate the t-matrix of the three-channel Kondo model at T=0, which shows universal crossovers near non-Fermi liquid critical points. A non-integrable three-impurity problem with three bands is also studied, revealing a rich phase diagram and novel screening/overscreening mechanisms.Comment: 5 pages + 5 pages supplementary materia

Investigating the Magnetospheres of Rapidly Rotating B-type Stars

Recent spectropolarimetric surveys of bright, hot stars have found that ~10% of OB-type stars contain strong (mostly dipolar) surface magnetic fields (~kG). The prominent paradigm describing the interaction between the stellar winds and the surface magnetic field is the magnetically confined wind shock (MCWS) model. In this model, the stellar wind plasma is forced to move along the closed field loops of the magnetic field, colliding at the magnetic equator, and creating a shock. As the shocked material cools radiatively it will emit X-rays. Therefore, X-ray spectroscopy is a key tool in detecting and characterizing the hot wind material confined by the magnetic fields of these stars. Some B-type stars are found to have very short rotational periods. The effects of the rapid rotation on the X-ray production within the magnetosphere have yet to be explored in detail. The added centrifugal force due to rapid rotation is predicted to cause faster wind outflows along the field lines, leading to higher shock temperatures and harder X-rays. However, this is not observed in all rapidly rotating magnetic B-type stars. In order to address this from a theoretical point of view, we use the X-ray Analytical Dynamical Magnetosphere (XADM) model, originally developed for slow rotators, with an implementation of new rapid rotational physics. Using X-ray spectroscopy from ESA's XMM-Newton space telescope, we observed 5 rapidly rotating B-type stars to add to the previous list of observations. Comparing the observed X-ray luminosity and hardness ratio to that predicted by the XADM allows us to determine the role the added centrifugal force plays in the magnetospheric X-ray emission of these stars.Comment: IAUS Conference Proceeding

Optimal Policies Search for Sensor Management

International audienceThis paper introduces a new approach to solve sensor management problems. Classically sensor management problems can be well formalized as Partially-Observed Markov Decision Processes (POMPD). The original approach developped here consists in deriving the optimal parameterized policy based on a stochastic gradient estimation. We assume in this work that it is possible to learn the optimal policy off-line (in simulation ) using models of the environement and of the sensor(s). The learned policy can then be used to manage the sensor(s). In order to approximate the gradient in a stochastic context, we introduce a new method to approximate the gradient, based on Infinitesimal Perturbation Approximation (IPA). The effectiveness of this general framework is illustrated by the managing of an Electronically Scanned Array Radar. First simulations results are finally proposed

Discovery of molecular subtypes in leiomyosarcoma through integrative molecular profiling.

Leiomyosarcoma (LMS) is a soft tissue tumor with a significant degree of morphologic and molecular heterogeneity. We used integrative molecular profiling to discover and characterize molecular subtypes of LMS. Gene expression profiling was performed on 51 LMS samples. Unsupervised clustering showed three reproducible LMS clusters. Array comparative genomic hybridization (aCGH) was performed on 20 LMS samples and showed that the molecular subtypes defined by gene expression showed distinct genomic changes. Tumors from the muscle-enriched cluster showed significantly increased copy number changes (P=0.04). A majority of the muscle-enriched cases showed loss at 16q24, which contains Fanconi anemia, complementation group A, known to have an important role in DNA repair, and loss at 1p36, which contains PRDM16, of which loss promotes muscle differentiation. Immunohistochemistry (IHC) was performed on LMS tissue microarrays (n=377) for five markers with high levels of messenger RNA in the muscle-enriched cluster (ACTG2, CASQ2, SLMAP, CFL2 and MYLK) and showed significantly correlated expression of the five proteins (all pairwise P<0.005). Expression of the five markers was associated with improved disease-specific survival in a multivariate Cox regression analysis (P<0.04). In this analysis that combined gene expression profiling, aCGH and IHC, we characterized distinct molecular LMS subtypes, provided insight into their pathogenesis, and identified prognostic biomarkers

Preliminary Efforts Directed Toward the Detection of Craving of Illicit Substances: The iHeal Project

Many behavioral interventions, whether for the management of chronic pain, overeating, medication adherence, or substance abuse, are ineffective outside of the clinic or office environments in which they are taught. This lack of utility has spawned interest in enabling technologies that are capable of detecting changes in affective state that potentially herald a transition to risky behaviors. We have therefore undertaken the preliminary development of “iHeal”, an innovative constellation of technologies that incorporates artificial intelligence, continuous biophysical monitoring, wireless connectivity, and smartphone computation. In its fully realized form, iHeal can detect developing drug cravings; as a multimedia device, it can also intervene as the cravings develop to prevent drug use. This manuscript describes preliminary data related to the iHeal Project and our experience with its use.United States. American Recovery and Reinvestment Act of 2009National Institutes of Health (U.S.

How should we measure psychological resilience in sport performers?

Psychological resilience is important in sport because athletes must constantly withstand a wide range of pressures to attain and sustain high performance. To advance psychologists’ understanding of this area, there exists an urgent need to develop a sport-specific measure of resilience. The purpose of this paper is to review psychometric issues in resilience research and to discuss the implications for sport psychology. Drawing on the wider general psychology literature to inform the discussion, the narrative is divided into three main sections relating to resilience and its assessment: adversity, positive adaptation, and protective factors. The first section reviews the different ways that adversity has been measured and considers the potential problems of using items with varying degrees of controllability and risk. The second section discusses the different approaches to assessing positive adaptation and examines the issue of circularity pervasive in resilience research. The final section explores the various issues related to the assessment of protective factors drawing directly from current measures of resilience in other psychology sub-disciplines. The commentary concludes with key recommendations for sport psychology researchers seeking to develop a measure of psychological resilience in athletes