Analysis of a multi-wavelength time-resolved observation of a coronal loop

Several items on the diagnostics and interpretation of coronal loop observations are under debate. In this work, we analyze a well-defined loop system detected in a time-resolved observation in several spectral bands. The dataset includes simultaneous images in the TRACE 171 A, 195 A and 284 A bands, and Yohkoh/SXT, and two rasters taken with SoHO/CDS in twelve relevant lines. The loop is initially best visible in the TRACE 195 A filter band, and later in the 171 A filter band, with correspondence with the CDS raster images at log T \~ 6.0-6.1. We have taken as pixel-by-pixel background the latest TRACE, Yohkoh and CDS images where the loop has faded out. We examine the loop morphology evolution, the light curves, the TRACE filter ratio distribution and evolution, the images and emission measure from the CDS spectral lines. Our analysis detects that, after background subtraction, the emission along the loop and its evolution are non-uniform, especially in the 171 A filter band, and that the TRACE 195/171 filter ratio has a moderately non-uniform distribution along the loop and evolves in time. Both the light curves and the filter ratio evolution indicate a globally cooling loop. Relatively hot plasma may be present at the beginning while, during the first CDS raster, the data indicate a rather moderate thermal structuring of the loop. Our data analysis supports a coherent scenario across the different bands and instruments, points out difficulties in diagnostic methods and puts quantitative basis for detailed forward modeling.Comment: 20 pages, 13 figs, refereed, in pres

Final results of Borexino Phase-I on low energy solar neutrino spectroscopy

Borexino has been running since May 2007 at the LNGS with the primary goal of detecting solar neutrinos. The detector, a large, unsegmented liquid scintillator calorimeter characterized by unprecedented low levels of intrinsic radioactivity, is optimized for the study of the lower energy part of the spectrum. During the Phase-I (2007-2010) Borexino first detected and then precisely measured the flux of the 7Be solar neutrinos, ruled out any significant day-night asymmetry of their interaction rate, made the first direct observation of the pep neutrinos, and set the tightest upper limit on the flux of CNO neutrinos. In this paper we discuss the signal signature and provide a comprehensive description of the backgrounds, quantify their event rates, describe the methods for their identification, selection or subtraction, and describe data analysis. Key features are an extensive in situ calibration program using radioactive sources, the detailed modeling of the detector response, the ability to define an innermost fiducial volume with extremely low background via software cuts, and the excellent pulse-shape discrimination capability of the scintillator that allows particle identification. We report a measurement of the annual modulation of the 7 Be neutrino interaction rate. The period, the amplitude, and the phase of the observed modulation are consistent with the solar origin of these events, and the absence of their annual modulation is rejected with higher than 99% C.L. The physics implications of phase-I results in the context of the neutrino oscillation physics and solar models are presented

PET Studies of Cerebral Levodopa Metabolism: A Review of Clinical Findings and Modeling Approaches

[18F]Fluoro-3,4-dihydroxyphenyl-l-alanine (FDOPA) was one of the first successful tracers for molecular imaging by positron emission tomography (PET), and has proven immensely valuable for studies of Parkinson’s disease. Following intravenous FDOPA injection, the decarboxylated metabolite [18F] fluorodopamine is formed and trapped within terminals of the nigrostriatal dopamine neurons; reduction in the simple ratio between striatum and cerebellum is indicative of nigrostriatal degeneration. However, the kinetic analysis of dynamic FDOPA-PET recordings is formidably complex due to the entry into brain of the plasma metabolite O-methyl-FDOPA and due to the eventual washout of decarboxylated metabolites. Linear graphical analysis relative to a reference tissue input function is popular and convenient for routine clinical studies in which serial arterial blood samples are unavailable. This simplified approach has facilitated longitudinal studies in large patient cohorts. Linear graphical analysis relative to the metabolite-corrected arterial FDOPA input yields a more physiological index of FDOPA utilization, the net blood-brain clearance. Using a constrained compartmental model, FDOPA-PET recordings can be used to calculate the relative activity of the enzyme DOPA decarboxylase in living brain. We have extended this approach so as to obtain an index of steady-state trapping of [18F]fluorodopamine in synaptic vesicles. Although simple methods of image analysis are sufficient for the purposes of routine clinical studies, the more complex approaches have revealed hidden aspects of brain dopamine in personality, healthy aging, and in the pathophysiologies of Parkinson’s disease and schizophrenia

Constraints on the assembly and dynamics of galaxies. II. Properties of kiloparsec-scale clumps in rest-frame optical emission of z ~ 2 star-forming galaxies

We study the properties of luminous stellar clumps identified in deep, high resolution HST/NIC2 F160W imaging at 1.6um of six z~2 star-forming galaxies with existing near-IR integral field spectroscopy from SINFONI at the VLT. Individual clumps contribute ~0.5%-15% of the galaxy-integrated rest-frame ~5000A emission, with median of about 2%; the total contribution of clump light ranges from 10%-25%. The median intrinsic clump size and stellar mass are ~1kpc and log(Mstar[Msun])~9, in the ranges for clumps identified in rest-UV or line emission in other studies. The clump sizes and masses in the subset of disks are broadly consistent with expectations for clump formation via gravitational instabilities in gas-rich, turbulent disks given the host galaxies' global properties. By combining the NIC2 data with ACS/F814W imaging available for one source, and AO-assisted SINFONI Halpha data for another, we infer modest color, M/L, and stellar age variations within each galaxy. In these two objects, sets of clumps identified at different wavelengths do not fully overlap; NIC2-identified clumps tend to be redder/older than ACS- or Halpha-identified clumps without rest-frame optical counterparts. There is evidence for a systematic trend of older ages at smaller galactocentric radii among the clumps, consistent with scenarios where inward migration of clumps transports material towards the central regions. From constraints on a bulge-like component at radii <1-3kpc, none of the five disks in our sample appears to contain a compact massive stellar core, and we do not discern a trend of bulge stellar mass fraction with stellar age of the galaxy. Further observations are necessary to probe the build-up of stellar bulges and the role of clumps in this process.Comment: 29 pages, 11 figures. Revised version accepted for publication in the Astrophysical Journa

Star-forming Clumps in Local Luminous Infrared Galaxies

We present HST narrowband near-infrared imaging of Paα and Paβ emission of 48 local luminous infrared galaxies (LIRGs) from the Great Observatories All-Sky LIRG Survey. These data allow us to measure the properties of 810 spatially resolved star-forming regions (59 nuclei and 751 extranuclear clumps) and directly compare their properties to those found in both local and high-redshift star-forming galaxies. We find that in LIRGs the star-forming clumps have radii ranging from ~90 to 900 pc and star formation rates (SFRs) of ~1 × 10⁻³ to 10 M⊙ yr⁻¹, with median values for extranuclear clumps of 170 pc and 0.03 M⊙ yr⁻¹. The detected star-forming clumps are young, with a median stellar age of 8.7 Myr, and have a median stellar mass of 5 × 10⁵ M ⊙. The SFRs span the range of those found in normal local star-forming galaxies to those found in high-redshift star-forming galaxies at z = 1–3. The luminosity function of the LIRG clumps has a flatter slope than found in lower-luminosity, star-forming galaxies, indicating a relative excess of luminous star-forming clumps. In order to predict the possible range of star-forming histories and gas fractions, we compare the star-forming clumps to those measured in the MassiveFIRE high-resolution cosmological simulation. The star-forming clumps in MassiveFIRE cover the same range of SFRs and sizes found in the local LIRGs and have total gas fractions that extend from 10% to 90%. If local LIRGs are similar to these simulated galaxies, we expect that future observations with ALMA will find a large range of gas fractions, and corresponding star formation efficiencies, among the star-forming clumps in LIRGs

Structural Health Monitoring With Emphasis On Computer Vision, Damage Indices, And Statistical Analysis

Structural Health Monitoring (SHM) is the sensing and analysis of a structure to detect abnormal behavior, damage and deterioration during regular operations as well as under extreme loadings. SHM is designed to provide objective information for decision-making on safety and serviceability. This research focuses on the SHM of bridges by developing and integrating novel methods and techniques using sensor networks, computer vision, modeling for damage indices and statistical approaches. Effective use of traffic video synchronized with sensor measurements for decision-making is demonstrated. First, some of the computer vision methods and how they can be used for bridge monitoring are presented along with the most common issues and some practical solutions. Second, a conceptual damage index (Unit Influence Line) is formulated using synchronized computer images and sensor data for tracking the structural response under various load conditions. Third, a new index, Nd , is formulated and demonstrated to more effectively identify, localize and quantify damage. Commonly observed damage conditions on real bridges are simulated on a laboratory model for the demonstration of the computer vision method, UIL and the new index. This new method and the index, which are based on outlier detection from the UIL population, can very effectively handle large sets of monitoring data. The methods and techniques are demonstrated on the laboratory model for damage detection and all damage scenarios are identified successfully. Finally, the application of the proposed methods on a real life structure, which has a monitoring system, is presented. It is shown that these methods can be used efficiently for applications such as damage detection and load rating for decision-making. The results from this monitoring project on a movable bridge are demonstrated and presented along with the conclusions and recommendations for future work