885 resultados para Radio and literature


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This paper analyses the relation between exile and literature in Angelina Muñiz-Huberman’s work El canto del peregrino. In this collection of essays, the Spanish-Mexican writer, member of the second generation of Spanish Republican exiles in Mexico, outlines a poetics of exile. From the outset, the relation between exile and literature is presented in terms of identity: while defining exile as “literary form”, the book tends to prefer a metaphorical concept of exile over ‘merely’ historical or referential approaches to it. More in particular, this paper will examine how the author constructs an identity of ‘exiled writer’ based on the close association between exile and literature on the one hand, and on the view of exile as ‘home’ or ‘dwelling’, on the other hand. A second point of interest concerns the discursive impact of this literary and metaphorical concept of exile and the author’s personal experience. A brief analysis of the essayist’s discursive voice and her writing practice shows how Muñiz-Huberman gives shape to an intrinsically complex and paradoxical view on exile.

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The performance of three conventional enzyme and radioimmunoassays routinely used to detect residues of anabolic steroids in cattle sera were compared with dissociation enhanced lanthanide fluorescence immunoassay (DELFIA) kits designed for the hospital market. Slight modifications to the kit reagents were required for the analysis of bovine sera. Owing to the large sample volumes used in conventional assays, detection limits were generally better than those obtained with DELFIA kits, however, assay reproducibility was enhanced using the DELFIA technology. Comparison of sera obtained from cattle implanted with anabolic steroids revealed a good correlation between alternate methods (r(2) from 0.91 to 0.97). The DELFIA kits offer a faster method for measuring estradiol, progesterone and testosterone with adequate sensitivity and in a safer environment than that encountered using radioimmunoassays.

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On 2011 August 24 (UT) the Palomar Transient Factory (PTF) discovered PTF11kly (SN 2011fe), the youngest and most nearby Type Ia supernova (SN Ia) in decades. We followed this event up in the radio (centimeter and millimeter bands) and X-ray bands, starting about a day after the estimated explosion time. We present our analysis of the radio and X-ray observations, yielding the tightest constraints yet placed on the pre-explosion mass-loss rate from the progenitor system of this supernova. We find a robust limit of from sensitive X-ray non-detections, as well as a similar limit from radio data, which depends, however, on assumptions about microphysical parameters. We discuss our results in the context of single-degenerate models for SNe Ia and find that our observations modestly disfavor symbiotic progenitor models involving a red giant donor, but cannot constrain systems accreting from main-sequence or sub-giant stars, including the popular supersoft channel. In view of the proximity of PTF11kly and the sensitivity of our prompt observations, we would have to wait for a long time (a decade or longer) in order to more meaningfully probe the circumstellar matter of SNe Ia.

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Perfect information is seldom available to man or machines due to uncertainties inherent in real world problems. Uncertainties in geographic information systems (GIS) stem from either vague/ambiguous or imprecise/inaccurate/incomplete information and it is necessary for GIS to develop tools and techniques to manage these uncertainties. There is a widespread agreement in the GIS community that although GIS has the potential to support a wide range of spatial data analysis problems, this potential is often hindered by the lack of consistency and uniformity. Uncertainties come in many shapes and forms, and processing uncertain spatial data requires a practical taxonomy to aid decision makers in choosing the most suitable data modeling and analysis method. In this paper, we: (1) review important developments in handling uncertainties when working with spatial data and GIS applications; (2) propose a taxonomy of models for dealing with uncertainties in GIS; and (3) identify current challenges and future research directions in spatial data analysis and GIS for managing uncertainties.

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