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In this paper we consider a simple syntactic extension of Answer Set Programming (ASP) for dealing with (nested) existential quantifiers and double negation in the rule bodies, in a close way to the recent proposal RASPL-1. The semantics for this extension just resorts to Equilibrium Logic (or, equivalently, to the General Theory of Stable Models), which provides a logic-programming interpretation for any arbitrary theory in the syntax of Predicate Calculus. We present a translation of this syntactic class into standard logic programs with variables (either disjunctive or normal, depending on the input rule heads), as those allowed by current ASP solvers. The translation relies on the introduction of auxiliary predicates and the main result shows that it preserves strong equivalence modulo the original signature.
The paper aims to bring the experience of playing videogames closer to objective knowledge, where the experience can be assessed and falsified via an operational concept. The theory focuses on explaining the basic elements that form the core of the process of the experience. The name of puppetry is introduced after discussing the similarities in the importance of experience for both videogames and theatrical puppetry. Puppetry, then, operationalizes the gaming experience into a concept that can be assessed.
We summarize Chandra observations of the emission line profiles from 17 OB stars. The lines tend to be broad and unshifted. The forbidden/intercombination line ratios arising from Helium-like ions provide radial distance information for the X-ray emission sources, while the H-like to He-like line ratios provide X-ray temperatures, and thus also source temperature versus radius distributions. OB stars usually show power law differential emission measure distributions versus temperature. In models of bow shocks, we find a power law differential emission measure, a wide range of ion stages, and the bow shock flow around the clumps provides transverse velocities comparable to HWHM values. We find that the bow shock results for the line profile properties, consistent with the observations of X-ray line emission for a broad range of OB star properties.
We study the time variability of emission lines in three WNE stars : WR 2 (WN2), WR 3 (WN3ha) and WR152 (WN3). While WR 2 shows no variability above the noise level, the other stars do show variation, which are like other WR stars in WR 152 but very fast in WR 3. From these motions, we deduce a value of β ∼1 for WR 3 that is like that seen in O stars and β ∼2–3 for WR 152, that is intermediate between other WR stars and WR 3.
Artificial intelligence (AI)-based technologies can increasingly perform knowledge work tasks, such as medical diagnosis. Thereby, it is expected that humans will not be replaced by AI but work closely with AI-based technology (“augmentation”). Augmentation has ethical implications for humans (e.g., impact on autonomy, opportunities to flourish through work), thus, developers and managers of AI-based technology have a responsibility to anticipate and mitigate risks to human workers. However, doing so can be difficult as AI encompasses a wide range of technologies, some of which enable fundamentally new forms of interaction. In this research-in-progress paper, we propose the development of a taxonomy to categorize unique characteristics of AI-based technology that influence the interaction and have ethical implications for human workers. The completed taxonomy will support researchers in forming cumulative knowledge on the ethical implications of augmentation and assist practitioners in the ethical design and management of AI-based technology in knowledge work.
By quantitatively fitting simple emission line profile models that include both atomic opacity and porosity to the Chandra X-ray spectrum of ζ Pup, we are able to explore the trade-offs between reduced mass-loss rates and wind porosity. We find that reducing the mass-loss rate of ζ Pup by roughly a factor of four, to 1.5 × 10−6 M⊙ yr−1, enables simple non-porous wind models to provide good fits to the data. If, on the other hand, we take the literature mass-loss rate of 6×10−6 M⊙ yr−1, then to produce X-ray line profiles that fit the data, extreme porosity lengths – of h∞ ≈ 3 R∗ – are required. Moreover, these porous models do not provide better fits to the data than the non-porous, low optical depth models. Additionally, such huge porosity lengths do not seem realistic in light of 2-D numerical simulations of the wind instability.