Vigorous atmospheric motion in the red supergiant star Antares

Red supergiant stars represent a late stage of the evolution of stars more massive than about nine solar masses, in which they develop complex, multi-component atmospheres. Bright spots have been detected in the atmosphere of red supergiants using interferometric imaging. Above the photosphere of a red supergiant, the molecular outer atmosphere extends up to about two stellar radii. Furthermore, the hot chromosphere (5,000 to 8,000 kelvin) and cool gas (less than 3,500 kelvin) of a red supergiant coexist at about three stellar radii. The dynamics of such complex atmospheres has been probed by ultraviolet and optical spectroscopy. The most direct approach, however, is to measure the velocity of gas at each position over the image of stars as in observations of the Sun. Here we report the mapping of the velocity field over the surface and atmosphere of the nearby red supergiant Antares. The two-dimensional velocity field map obtained from our near-infrared spectro-interferometric imaging reveals vigorous upwelling and downdrafting motions of several huge gas clumps at velocities ranging from about -20 to +20 kilometres per second in the atmosphere, which extends out to about 1.7 stellar radii. Convection alone cannot explain the observed turbulent motions and atmospheric extension, suggesting that an unidentified process is operating in the extended atmosphere.Comment: 27 pages, 8 figures, published in Natur

Fast and reliable online learning to rank for information retrieval

The amount of digital data we produce every day far surpasses our ability to process this data, and finding useful information in this constant flow of data has become one of the major challenges of the 21st century. Search engines are one way of accessing large data collections. Their algorithms have evolved far beyond simply matching search queries to sets of documents. Today’s most sophisticated search engines combine hundreds of relevance signals to provide the best possible results for each searcher. Current approaches for tuning the parameters of search engines can be highly effective. However, they typically require considerable expertise and manual effort. They rely on supervised learning to rank, meaning that they learn from manually annotated examples of relevant documents for given queries. Obtaining large quantities of sufficiently accurate manual annotations is becoming increasingly difficult, especially for personalized search, access to sensitive data, or search in settings that change over time. In this thesis, I develop new online learning to rank techniques, based on insights from reinforcement learning. In contrast to supervised approaches, these methods allow search engines to learn directly from users’ interactions. User interactions can typically be observed easily and cheaply, and reflect the preferences of real users. Interpreting user interactions and learning from them is challenging, because they can be biased and noisy. The contributions of this thesis include a novel interleaved comparison method, called probabilistic interleave, that allows unbiased comparisons of search engine result rankings, and methods for learning quickly and effectively from the resulting relative feedback. The obtained analytical and experimental results show how search engines can effectively learn from user interactions. In the future, these and similar techniques can open up new ways for gaining useful information from ever larger amounts of data

From extinction learning to anxiety treatment: mind the gap

Laboratory models of extinction learning in animals and humans have the potential to illuminate methods for improving clinical treatment of fear-based clinical disorders. However, such translational research often neglects important differences between threat responses in animals and fear learning in humans, particularly as it relates to the treatment of clinical disorders. Specifically, the conscious experience of fear and anxiety, along with the capacity to deliberately engage top-down cognitive processes to modulate that experience, involves distinct brain circuitry and is measured and manipulated using different methods than typically used in laboratory research. This paper will identify how translational research that investigates methods of enhancing extinction learning can more effectively model such elements of human fear learning, and how doing so will enhance the relevance of this research to the treatment of fear-based psychological disorders.Published versio

Interpersonal Emotion Regulation Questionnaire (IERQ): scale development and psychometric characteristics

Despite the popularity of emotion regulation in the contemporary literature, research has almost exclusively focused on only intrapersonal processes, whereas much less attention has been placed in interpersonal emotion regulation processes. In order to encourage research on interpersonal emotion regulation, we present a series of 4 studies to develop the Interpersonal Emotion Regulation Questionnaire (IERQ). The final scale consists of 20 items with 4 factors containing 5 items each. The 4 factors are: Enhancing Positive Affect; Perspective Taking; Soothing; and Social Modeling. The scale shows excellent psychometric characteristics. Implications for future research are discussed.R01 MH078308 - NIMH NIH HHS; R34 MH086668 - NIMH NIH HHS; R01 AT007257 - NCCIH NIH HHS; R21 MH101567 - NIMH NIH HHS; R34 MH099311 - NIMH NIH HHS; R21 MH102646 - NIMH NIH HHS; K23 MH100259 - NIMH NIH HHS; R01 MH099021 - NIMH NIH HH

Evidence for bipolar jets in late stages of AGB winds

Bipolar expansion at various stages of evolution has been recently observed in a number of AGB stars. The expansion is driven by bipolar jets that emerge late in the evolution of AGB winds. The wind traps the jets, resulting in an expanding, elongated cocoon. Eventually the jets break-out from the confining spherical wind, as recently observed in W43A. This source displays the most advanced evolutionary stage of jets in AGB winds. The earliest example is IRC+10011, where the asymmetry is revealed in high-resolution near-IR imaging. In this source the jets turned on only ~200 years ago, while the spherical wind is ~4000 years old.Comment: 6 pages, to appear in "Asymmetrical Planetary Nebulae III" editors M. Meixner, J. Kastner, N. Soker, & B. Balick (ASP Conf. Series

GdRh2_2Si2_2: An exemplary tetragonal system for antiferromagnetic order with weak in-plane anisotropy

The anisotropy of magnetic properties commonly is introduced in textbooks using the case of an antiferromagnetic system with Ising type anisotropy. This model presents huge anisotropic magnetization and a pronounced metamagnetic transition and is well-known and well-documented both, in experiments and theory. In contrast, the case of an antiferromagnetic $X$-$Y$ system with weak in-plane anisotropy is only poorly documented. We studied the anisotropic magnetization of the compound GdRh$_2$Si$_2$ and found that it is a perfect model system for such a weak-anisotropy setting because the Gd$^{3+}$ ions in GdRh$_2$Si$_2$ have a pure spin moment of S=7/2 which orders in a simple AFM structure with ${\bf Q} = (001)$. We observed experimentally in $M(B)$ a continuous spin-flop transition and domain effects for field applied along the $[100]$- and the $[110]$-direction, respectively. We applied a mean field model for the free energy to describe our data and combine it with an Ising chain model to account for domain effects. Our calculations reproduce the experimental data very well. In addition, we performed magnetic X-ray scattering and X-ray magnetic circular dichroism measurements, which confirm the AFM propagation vector to be ${\bf Q} = (001)$ and indicate the absence of polarization on the rhodium atoms