15,756 research outputs found

    UV spectroscopy of the blue supergiant SBW1: the remarkably weak wind of a SN 1987A analog

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    The Galactic blue supergiant SBW1 with its circumstellar ring nebula represents the best known analog of the progenitor of SN 1987A. High-resolution imaging has shown H-alpha and IR structures arising in an ionized flow that partly fills the ring's interior. To constrain the influence of the stellar wind on this structure, we obtained an ultraviolet (UV) spectrum of the central star of SBW1 with the HST Cosmic Origins Spectrograph (COS). The UV spectrum shows none of the typical wind signatures, indicating a very low mass-loss rate. Radiative transfer models suggest an extremely low rate below 10−10^{-10} Msun/yr, although we find that cooling timescales probably become comparable to or longer than the flow time below 10−8^{-8} Msun/yr. We therefore adopt this latter value as a conservative upper limit. For the central star, the model yields TeffT_{\rm eff}=21,000±\pm1000 K, L≃L\simeq5×\times104^4 L⊙L_{\odot}, and roughly Solar composition except for enhanced N abundance. SBW1's very low mass-loss rate may hinder the wind's ability to shape the surrounding nebula. The very low mass-loss rate also impairs the wind's ability to shed angular momentum; the spin-down timescale for magnetic breaking is more than 500 times longer than the age of the ring. This, combined with the star's slow rotation rate, constrain merger scenarios to form ring nebulae. The mass-loss rate is at least 10 times lower than expected from mass-loss recipes, without any account of clumping. The physical explanation for why SBW1's wind is so weak presents an interesting mystery.Comment: 12 pages, 6 figs. submitted to MNRAS. comments welom

    Probabilistic lower bounds on maximal determinants of binary matrices

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    Let D(n){\mathcal D}(n) be the maximal determinant for n×nn \times n {±1}\{\pm 1\}-matrices, and R(n)=D(n)/nn/2\mathcal R(n) = {\mathcal D}(n)/n^{n/2} be the ratio of D(n){\mathcal D}(n) to the Hadamard upper bound. Using the probabilistic method, we prove new lower bounds on D(n){\mathcal D}(n) and R(n)\mathcal R(n) in terms of d=n−hd = n-h, where hh is the order of a Hadamard matrix and hh is maximal subject to h≤nh \le n. For example, R(n)>(πe/2)−d/2\mathcal R(n) > (\pi e/2)^{-d/2} if 1≤d≤31 \le d \le 3, and R(n)>(πe/2)−d/2(1−d2(π/(2h))1/2)\mathcal R(n) > (\pi e/2)^{-d/2}(1 - d^2(\pi/(2h))^{1/2}) if d>3d > 3. By a recent result of Livinskyi, d2/h1/2→0d^2/h^{1/2} \to 0 as n→∞n \to \infty, so the second bound is close to (πe/2)−d/2(\pi e/2)^{-d/2} for large nn. Previous lower bounds tended to zero as n→∞n \to \infty with dd fixed, except in the cases d∈{0,1}d \in \{0,1\}. For d≥2d \ge 2, our bounds are better for all sufficiently large nn. If the Hadamard conjecture is true, then d≤3d \le 3, so the first bound above shows that R(n)\mathcal R(n) is bounded below by a positive constant (πe/2)−3/2>0.1133(\pi e/2)^{-3/2} > 0.1133.Comment: 17 pages, 2 tables, 24 references. Shorter version of arXiv:1402.6817v4. Typos corrected in v2 and v3, new Lemma 7 in v4, updated references in v5, added Remark 2.8 and a reference in v6, updated references in v

    An application of multiattribute decision analysis to the Space Station Freedom program. Case study: Automation and robotics technology evaluation

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    The results are described of an application of multiattribute analysis to the evaluation of high leverage prototyping technologies in the automation and robotics (A and R) areas that might contribute to the Space Station (SS) Freedom baseline design. An implication is that high leverage prototyping is beneficial to the SS Freedom Program as a means for transferring technology from the advanced development program to the baseline program. The process also highlights the tradeoffs to be made between subsidizing high value, low risk technology development versus high value, high risk technology developments. Twenty one A and R Technology tasks spanning a diverse array of technical concepts were evaluated using multiattribute decision analysis. Because of large uncertainties associated with characterizing the technologies, the methodology was modified to incorporate uncertainty. Eight attributes affected the rankings: initial cost, operation cost, crew productivity, safety, resource requirements, growth potential, and spinoff potential. The four attributes of initial cost, operations cost, crew productivity, and safety affected the rankings the most

    Recent developments in the application of risk analysis to waste technologies.

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    The European waste sector is undergoing a period of unprecedented change driven by business consolidation, new legislation and heightened public and government scrutiny. One feature is the transition of the sector towards a process industry with increased pre-treatment of wastes prior to the disposal of residues and the co-location of technologies at single sites, often also for resource recovery and residuals management. Waste technologies such as in-vessel composting, the thermal treatment of clinical waste, the stabilisation of hazardous wastes, biomass gasification, sludge combustion and the use of wastes as fuel, present operators and regulators with new challenges as to their safe and environmentally responsible operation. A second feature of recent change is an increased regulatory emphasis on public and ecosystem health and the need for assessments of risk to and from waste installations. Public confidence in waste management, secured in part through enforcement of the planning and permitting regimes and sound operational performance, is central to establishing the infrastructure of new waste technologies. Well-informed risk management plays a critical role. We discuss recent developments in risk analysis within the sector and the future needs of risk analysis that are required to respond to the new waste and resource management agenda

    Development and application of a self-referencing glucose microsensor for the measurement of glucose consumption by pancreatic ?-cells

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    Glucose gradients generated by an artificial source and ?-cells were measured using an enzyme-based glucose microsensor, 8-?m tip diameter, as a self-referencing electrode. The technique is based on a difference measurement between two locations in a gradient and thus allows us to obtain real-time flux values with minimal impact of sensor drift or noise. Flux values were derived by incorporation of the measured differential current into Fick's first equation. In an artificial glucose gradient, a flux detection limit of 8.2 ± 0.4 pmol·cm-2·s-1 (mean ± SEM, n = 7) with a sensor sensitivity of 7.0 ± 0.4 pA/mM (mean ± SEM, n = 16) was demonstrated. Under biological conditions, the glucose sensor showed no oxygen dependence with 5 mM glucose in the bulk medium. The addition of catalase to the bulk medium was shown to ameliorate surface-dependent flux distortion close to specimens, suggesting an underlying local accumulation of hydrogen peroxide. Glucose flux from ?-cell clusters, measured in the presence of 5 mM glucose, was 61.7 ± 9.5 fmol·nL-1·s-1 (mean ± SEM, n = 9) and could be pharmacologically modulated. Glucose consumption in response to FCCP (1 ?M) transiently increased, subsequently decreasing to below basal by 93 ± 16 and 56 ± 6%, respectively (mean ± SEM, n = 5). Consumption was decreased after the application of 10 ?M rotenone by 74 ± 5% (mean ± SEM, n = 4). These results demonstrate that an enzyme-based amperometric microsensor can be applied in the self-referencing mode. Further, in obtaining glucose flux measurements from small clusters of cells, these are the first recordings of the real-time dynamic of glucose movements in a biological microenvironment. <br/

    Cycle Bases of Reduced Powers of Graphs

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    We define what appears to be a new construction. Given a graph G and a positive integer k, the reduced kth power of G, denoted G(k), is the configuration space in which k indistinguishable tokens are placed on the vertices of G, so that any vertex can hold up to k tokens. Two configurations are adjacent if one can be transformed to the other by moving a single token along an edge to an adjacent vertex. We present propositions related to the structural properties of reduced graph powers and, most significantly, provide a construction of minimum cycle bases of G(k). The minimum cycle basis construction is an interesting combinatorial problem that is also useful in applications involving configuration spaces. For example, if G is the state-transition graph of a Markov chain model of a stochastic automaton, the reduced power G(k) is the state-transition graph for k identical (but not necessarily independent) automata. We show how the minimum cycle basis construction of G(k) may be used to confirm that state-dependent coupling of automata does not violate the principle of microscopic reversibility, as required in physical and chemical applications
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