13,538 research outputs found

    Constructive role of dissipation for driven coupled bosonic modes

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    We describe four cases of childhood B-cell progenitor acute lymphoblastic leukaemia (BCP-ALL) and one of T-cell (T-ALL) with unexpected numbers of interphase signals for ETV6 with an ETV6-RUNX1 fusion probe. Three fusion negative cases each had a telomeric part of 12p terminating within intron 2 of ETV6, attached to sequences from 5q, 7p and 7q, respectively. Two fusion positive cases, with partial insertions of ETV6 into chromosome 21, also had a breakpoint in intron 2. Fluorescence in situ hybridisation ( FISH), array comparative genomic hybridization (aCGH) and Molecular Copy-Number Counting (MCC) results were concordant for the T-cell case. Sequences downstream of TLX3 on chromosome 5 were deleted, leaving the intact gene closely apposed to the first two exons of ETV6 and its upstream promoter. qRT-PCR showed a significant upregulation of TLX3. In this study we provide the first incontrovertible evidence that the upstream promoter of ETV6 attached to the first two exons of the gene was responsible for the ectopic expression of a proto-oncogene that became abnormally close as the result of deletion and translocation. We have also shown breakpoints in intron 2 of ETV6 in two cases of insertion with ETV6-RUNX1 fusion

    Snow spectral albedo at Summit, Greenland: measurements and numerical simulations based on physical and chemical properties of the snowpack

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    The broadband albedo of surface snow is determined both by the near-surface profile of the physical and chemical properties of the snowpack and by the spectral and angular characteristics of the incident solar radiation. Simultaneous measurements of the physical and chemical properties of snow were carried out at Summit Camp, Greenland (72°36´ N, 38°25´ W, 3210 m a.s.l.) in May and June 2011, along with spectral albedo measurements. One of the main objectives of the field campaign was to test our ability to predict snow spectral albedo by comparing the measured albedo to the albedo calculated with a radiative transfer model, using measured snow physical and chemical properties. To achieve this goal, we made daily measurements of the snow spectral albedo in the range 350–2200 nm and recorded snow stratigraphic information down to roughly 80 cm. The snow specific surface area (SSA) was measured using the DUFISSS instrument (DUal Frequency Integrating Sphere for Snow SSA measurement, Gallet et al., 2009). Samples were also collected for chemical analyses including black carbon (BC) and dust, to evaluate the impact of light absorbing particulate matter in snow. This is one of the most comprehensive albedo-related data sets combining chemical analysis, snow physical properties and spectral albedo measurements obtained in a polar environment. The surface albedo was calculated from density, SSA, BC and dust profiles using the DISORT model (DIScrete Ordinate Radiative Transfer, Stamnes et al., 1988) and compared to the measured values. Results indicate that the energy absorbed by the snowpack through the whole spectrum considered can be inferred within 1.10%. This accuracy is only slightly better than that which can be obtained considering pure snow, meaning that the impact of impurities on the snow albedo is small at Summit. In the near infrared, minor deviations in albedo up to 0.014 can be due to the accuracy of radiation and SSA measurements and to the surface roughness, whereas deviations up to 0.05 can be explained by the spatial heterogeneity of the snowpack at small scales, the assumption of spherical snow grains made for DISORT simulations and the vertical resolution of measurements of surface layer physical properties. At 1430 and around 1800 nm the discrepancies are larger and independent of the snow properties; we propose that they are due to errors in the ice refractive index at these wavelengths. This work contributes to the development of physically based albedo schemes in detailed snowpack models, and to the improvement of retrieval algorithms for estimating snow properties from remote sensing data

    Optical detection and spectroscopic confirmation of supernova remnant G213.0-0.6 (now re-designated as G213.3-0.4)

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    During a detailed search for optical counterparts of known Galactic supernova remnants (SNRs) using the Anglo Australian Observatory/United Kingdom Schmidt Telescope (AAO/UKST) HAlpha survey of the southern Galactic plane we have found characteristic optical HAlpha filaments and associated emission in the area of SNR G213.0-0.6. Although this remnant was previously detected in the radio as a non-thermal source, we also confirm emission at 4850 MHz in the Parkes-MIT-NRAO (PMN) survey and at 1400 MHz in the NRAO/VLA Sky Survey (NVSS). There is an excellent match in morphological structure between the optical (HAlpha) and radio emission. We subsequently obtained optical spectroscopy of selected HAlpha filaments using the South African Astronomical Observatory 1.9-m telescope which confirmed shock excitation typical of supernova remnants. Our discovery of HAlpha emission and the positional match with several radio frequency maps led us to reassign G213.0-0.6 as G213.3-0.4 as these co-ordinates more accurately reflect the actual centre of the SNR shell and hence the most probable place of the original supernova explosion. Support for this new SNR ID comes from the fact that the X-ray source 1RXS J065049.7-003220 is situated in the centre of this new remnant and could be connected with the supernova explosion.Comment: 9 pages, 8 figures, Accepted for publishing in MNRA

    Lyapunov exponents for products of complex Gaussian random matrices

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    The exact value of the Lyapunov exponents for the random matrix product PN=ANAN−1...A1P_N = A_N A_{N-1}...A_1 with each Ai=Σ1/2GicA_i = \Sigma^{1/2} G_i^{\rm c}, where Σ\Sigma is a fixed d×dd \times d positive definite matrix and GicG_i^{\rm c} a d×dd \times d complex Gaussian matrix with entries standard complex normals, are calculated. Also obtained is an exact expression for the sum of the Lyapunov exponents in both the complex and real cases, and the Lyapunov exponents for diffusing complex matrices.Comment: 15 page
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