1,907 research outputs found

    The evolution of planetary nebulae. VIII. True expansion rates and visibility times

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    The visibility time of planetary nebulae (PNe) in stellar systems is an essential quantity for estimating the size of a PN population in the context of general population studies. For instance, it enters directly into the PN death rate determination. The basic ingredient for determining visibility times is the typical nebular expansion velocity, as a suited average over all PN sizes of a PN population within a certain volume or stellar system. The true expansion speed of the outer nebular edge of a PN is, however, not accessible by spectroscopy -- a difficulty that we surmount by radiation-hydrodynamics modelling. We find a mean true expansion velocity of 42 km/s, i.e. nearly twice as high as the commonly adopted value to date. Accordingly, the time for a PN to expand to a radius of, say 0.9 pc, is only 21000 +/- 5000 years. This visibility time of a PN holds for all central star masses since a nebula does not become extinct as the central star fades. There is, however, a dependence on metallicity in the sense that the visibility time becomes shorter for lower nebular metal content. With the higher expansion rate of PNe derived here we determined their local death-rate density as (1.4 +/- 0.5) x E-12 PN pc^{-3} yr^{-1}, using the local PN density advocated by Frew (2008).Comment: 20 pages, 10 Figures; accepted for publication in Astronomy & Astrophysics / Note added in proo

    Modeling the diffuse X-ray emission of Planetary Nebulae with different chemical composition

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    Based on time-dependent radiation-hydrodynamics simulations of the evolution of Planetary Nebulae (PNe), we have carried out a systematic parameter study to address the non-trivial question of how the diffuse X-ray emission of PNe with closed central cavities is expected to depend on the evolutionary state of the nebula, the mass of the central star, and the metallicity of stellar wind and circumstellar matter. We have also investigated how the model predictions depend on the treatment of thermal conduction at the interface between the central `hot bubble' and the `cool' inner nebula, and compare the results with recent X-ray observations. Our study includes models whose properties resemble the extreme case of PNe with Wolf-Rayet type central stars. Indeed, such models are found to produce the highest X-ray luminosities.Comment: 5 pages, 2 figures, to appear in proceedings of the IAU Symposium 283: "Planetary Nebulae: An Eye to the Future", Eds.: A. Manchado, L. Stanghellini and D. Schoenberne

    The evolution of planetary nebulae VII. Modelling planetary nebulae of distant stellar systems

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    By means of hydrodynamical models we do the first investigations of how the properties of planetary nebulae are affected by their metal content and what can be learned from spatially unresolved spectrograms of planetary nebulae in distant stellar systems. We computed a new series of 1D radiation-hydrodynamics planetary nebulae model sequences with central stars of 0.595 M_sun surrounded by initial envelope structures that differ only by their metal content. At selected phases along the evolutionary path, the hydrodynamic terms were switched off, allowing the models to relax for fixed radial structure and radiation field into their equilibrium state with respect to energy and ionisation. The analyses of the line spectra emitted from both the dynamical and static models enabled us to systematically study the influence of hydrodynamics as a function of metallicity and evolution. We also recomputed selected sequences already used in previous publications, but now with different metal abundances. These sequences were used to study the expansion properties of planetary nebulae close to the bright cut-off of the planetary nebula luminosity function. Our simulations show that the metal content strongly influences the expansion of planetary nebulae: the lower the metal content, the weaker the pressure of the stellar wind bubble, but the faster the expansion of the outer shell because of the higher electron temperature. This is in variance with the predictions of the interacting-stellar-winds model (or its variants) according to which only the central-star wind is thought to be responsible for driving the expansion of a planetary nebula. Metal-poor objects around slowly evolving central stars become very dilute and are prone to depart from thermal equilibrium because then adiabatic expansion contributes to gas cooling. ...abridged abstract.Comment: 35 pages, 43 figures, accepted for publication by A&

    Hot bubbles of planetary nebulae with hydrogen-deficient winds - II. Analytical approximations with application to BD+30∘^\circ3639

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    The first high-resolution X-ray spectroscopy of the planetary nebula BD+30∘^\circ3639 allowed to study X-ray emitting "hot bubbles" (HBs) of planetary nebulae in unprecedented detail. We investigate (i) how diagnostic line ratios are affected by the HB thermal structure and chemical profile, (ii) if the HB chemical composition of BD+30∘^\circ3639 is consistent with the H-poor (H for hydrogen) composition of the stellar photosphere, and (iii) if H-rich nebular matter has been added to this HB by evaporation. We apply an analytical, 1D model for wind-blown HBs with temperature and density profiles based on self-similar solutions including thermal conduction. We construct heat-conduction HBs with chemical stratification. The X-ray emission is computed using the CHIANTI code. Our HB models are used to re-analyse the high-resolution X-ray spectrum of BD+30∘^\circ3639. Our models reproduce the observed line ratios much better than plasmas with single electron temperatures. All the temperature- and abundance-sensitive line ratios are consistent with BD+30∘^\circ3639 X-ray observations for (i) an intervening column density of neutral H, NH=0.20−0.10+0.05× ⁣1022 cm−2N_{\rm H} = 0.20_{-0.10}^{+0.05}\times\!10^{22}\rm\ cm^{-2}, (ii) a characteristic HB X-ray temperature of TX=1.8±0.1 {T_{\rm X} = 1.8\pm 0.1~ }MK together with (iii) a very high neon mass fraction of about 0.05, virtually as high as that of oxygen. For lower values of NHN_{\rm H}, we cannot exclude that the HB of BD+30∘^\circ3639 contains a small amount of evaporated (or mixed) H-rich nebular matter. Given the possible range of NHN_{\rm H}, the fraction of evaporated H-rich matter cannot exceed 3% of the HB mass. The diffuse X-ray emission from BD+30∘^\circ3639 can well be explained by models of wind-blown HBs with thermal conduction and a chemical composition equal to that of the H-poor and carbon-, oxygen-, and neon-rich stellar surface.Comment: 24 pages, 19 figures (col and b/w), 4 tables, accepted for publication in A&A, Fig. 18 adapted to accepted versio

    Wearables as Augmentation Means: Conceptual Definition, Pathways, and Research Framework

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    Wearables pervade many facets of human endeavor, thanks to their integration into everyday artifacts and activities. From fitness bands to medical patches, to augmented reality glasses, wearables have demonstrated immense potential for intelligence augmentation (IA) through human-machine symbiosis. To advance an understanding of how wearables engender IA and to provide a solid foundation for grounding IS research on wearables and IA, this study draws from Engelbart’s framework for augmenting human intellect to: (1) develop a conceptual definition of wearable technology as a digitally enhanced body-borne device that can augment a human or non-human capability by affording context sensitivity, mobility, hands-free interaction, and constancy of operation, (2) extend Engelbart’s framework to the sociomaterial domain to account for the emergence of augmented capabilities that are neither wholly social nor wholly material, and (3) propose and elaborate four augmentation pathways —complementation, supplementation, mediation, and mutual constitution—to facilitate IA research

    Alienation and Digital Labour—A Depth-Hermeneutic Inquiry into Online Commodification and the Unconscious

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    At the core of this paper is a psychosocial inquiry into the Marxist concept of alienation and its applications to the field of digital labour. Following a brief review of different theoretical works on alienation, it looks into its recent conceptualisations and applications to the study of online social networking sites. Finally, the authors offer suggestions on how to extend and render more complex these recent approaches through in-depth analyses of Facebook posts that exemplify how alienation is experienced, articulated, and expressed online. For this perspective, the article draws on Rahel Jaeggi’s (2005) reassessment of alienation, as well as the depth-hermeneutic method of “scenic understanding” developed by Alfred Lorenzer (e.g. 1970; 1986)

    Sequential Recommendation with Self-Attentive Multi-Adversarial Network

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    Recently, deep learning has made significant progress in the task of sequential recommendation. Existing neural sequential recommenders typically adopt a generative way trained with Maximum Likelihood Estimation (MLE). When context information (called factor) is involved, it is difficult to analyze when and how each individual factor would affect the final recommendation performance. For this purpose, we take a new perspective and introduce adversarial learning to sequential recommendation. In this paper, we present a Multi-Factor Generative Adversarial Network (MFGAN) for explicitly modeling the effect of context information on sequential recommendation. Specifically, our proposed MFGAN has two kinds of modules: a Transformer-based generator taking user behavior sequences as input to recommend the possible next items, and multiple factor-specific discriminators to evaluate the generated sub-sequence from the perspectives of different factors. To learn the parameters, we adopt the classic policy gradient method, and utilize the reward signal of discriminators for guiding the learning of the generator. Our framework is flexible to incorporate multiple kinds of factor information, and is able to trace how each factor contributes to the recommendation decision over time. Extensive experiments conducted on three real-world datasets demonstrate the superiority of our proposed model over the state-of-the-art methods, in terms of effectiveness and interpretability
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