The Adaptive Priority Queue with Elimination and Combining

Priority queues are fundamental abstract data structures, often used to manage limited resources in parallel programming. Several proposed parallel priority queue implementations are based on skiplists, harnessing the potential for parallelism of the add() operations. In addition, methods such as Flat Combining have been proposed to reduce contention by batching together multiple operations to be executed by a single thread. While this technique can decrease lock-switching overhead and the number of pointer changes required by the removeMin() operations in the priority queue, it can also create a sequential bottleneck and limit parallelism, especially for non-conflicting add() operations. In this paper, we describe a novel priority queue design, harnessing the scalability of parallel insertions in conjunction with the efficiency of batched removals. Moreover, we present a new elimination algorithm suitable for a priority queue, which further increases concurrency on balanced workloads with similar numbers of add() and removeMin() operations. We implement and evaluate our design using a variety of techniques including locking, atomic operations, hardware transactional memory, as well as employing adaptive heuristics given the workload.Comment: Accepted at DISC'14 - this is the full version with appendices, including more algorithm

Using Electronic Documents for Knowledge Acquisition and Model Maintenance

Knowledge acquisition and model maintenance are key problems in knowledge engineering to improve the productivity in the development of intelligent systems. Although historically a number of technical solutions have been proposed in this area, the recent experience shows that there is still an important gap between the way end-users describe their expertise and the way intelligent systems represent knowledge. In this paper we propose an original way to cope with this problem based on electronic documents. We propose the concept of intelligent document processor as a tool that allows the end-user to read/write a document explaining how an intelligent system operates in such a way that, if the user changes the content of the document, the intelligent system will react to these changes. The paper presents the structure of such a document based on knowledge categories derived from the modern knowledge modeling methodologies together with a number of requirements to be understandable by end-users and problem solvers

Mentalizing and motivation neural function during social interactions in autism spectrum disorders

AbstractAutism Spectrum Disorders (ASDs) are characterized by core deficits in social functions. Two theories have been suggested to explain these deficits: mind-blindness theory posits impaired mentalizing processes (i.e. decreased ability for establishing a representation of others' state of mind), while social motivation theory proposes that diminished reward value for social information leads to reduced social attention, social interactions, and social learning. Mentalizing and motivation are integral to typical social interactions, and neuroimaging evidence points to independent brain networks that support these processes in healthy individuals. However, the simultaneous function of these networks has not been explored in individuals with ASDs. We used a social, interactive fMRI task, the Domino game, to explore mentalizing- and motivation-related brain activation during a well-defined interval where participants respond to rewards or punishments (i.e. motivation) and concurrently process information about their opponent's potential next actions (i.e. mentalizing). Thirteen individuals with high-functioning ASDs, ages 12–24, and 14 healthy controls played fMRI Domino games against a computer-opponent and separately, what they were led to believe was a human-opponent. Results showed that while individuals with ASDs understood the game rules and played similarly to controls, they showed diminished neural activity during the human-opponent runs only (i.e. in a social context) in bilateral middle temporal gyrus (MTG) during mentalizing and right Nucleus Accumbens (NAcc) during reward-related motivation (Pcluster<0.05 FWE). Importantly, deficits were not observed in these areas when playing against a computer-opponent or in areas related to motor and visual processes. These results demonstrate that while MTG and NAcc, which are critical structures in the mentalizing and motivation networks, respectively, activate normally in a non-social context, they fail to respond in an otherwise identical social context in ASD compared to controls. We discuss implications to both the mind-blindness and social motivation theories of ASD and the importance of social context in research and treatment protocols

A likely planet-induced gap in the disc around T Cha

We present high-resolution (0.11 × 0.06 arcsec2) 3 mm ALMA observations of the highly inclined transition disc around the star T Cha. Our continuum image reveals multiple dust structures: an inner disc, a spatially resolved dust gap, and an outer ring. When fitting sky-brightness models to the real component of the 3 mm visibilities, we infer that the inner emission is compact (≤1 au in radius), the gap width is between 18 and 28 au, and the emission from the outer ring peaks at ∼36 au. We compare our ALMA image with previously published 1.6 μm VLT/SPHERE imagery. This comparison reveals that the location of the outer ring is wavelength dependent. More specifically, the peak emission of the 3 mm ring is at a larger radial distance than that of the 1.6 μm ring, suggesting that millimeter-sized grains in the outer disc are located farther away from the central star than micron-sized grains. We discuss different scenarios to explain our findings, including dead zones, star-driven photoevaporation, and planet-disc interactions. We find that the most likely origin of the dust gap is from an embedded planet, and estimate – for a single planet scenario – that T Cha's gap is carved by a 1.2MJup planet

Mathematical practice, crowdsourcing, and social machines

The highest level of mathematics has traditionally been seen as a solitary endeavour, to produce a proof for review and acceptance by research peers. Mathematics is now at a remarkable inflexion point, with new technology radically extending the power and limits of individuals. Crowdsourcing pulls together diverse experts to solve problems; symbolic computation tackles huge routine calculations; and computers check proofs too long and complicated for humans to comprehend. Mathematical practice is an emerging interdisciplinary field which draws on philosophy and social science to understand how mathematics is produced. Online mathematical activity provides a novel and rich source of data for empirical investigation of mathematical practice - for example the community question answering system {\it mathoverflow} contains around 40,000 mathematical conversations, and {\it polymath} collaborations provide transcripts of the process of discovering proofs. Our preliminary investigations have demonstrated the importance of "soft" aspects such as analogy and creativity, alongside deduction and proof, in the production of mathematics, and have given us new ways to think about the roles of people and machines in creating new mathematical knowledge. We discuss further investigation of these resources and what it might reveal. Crowdsourced mathematical activity is an example of a "social machine", a new paradigm, identified by Berners-Lee, for viewing a combination of people and computers as a single problem-solving entity, and the subject of major international research endeavours. We outline a future research agenda for mathematics social machines, a combination of people, computers, and mathematical archives to create and apply mathematics, with the potential to change the way people do mathematics, and to transform the reach, pace, and impact of mathematics research.Comment: To appear, Springer LNCS, Proceedings of Conferences on Intelligent Computer Mathematics, CICM 2013, July 2013 Bath, U

Homogeneous Analysis of the Dust Morphology of Transition Disks Observed with ALMA: Investigating Dust Trapping and the Origin of the Cavities

We analyze the dust morphology of 29 transition disks (TDs) observed with ALMA at (sub-) millimeter-emission. We perform the analysis in the visibility plane to characterize the total flux, cavity size, and shape of the ring-like structure. First, we found that the $M_{\rm{dust}}-M_\star$ relation is much flatter for TDs than the observed trends from samples of class II sources in different star forming regions. This relation demonstrates that cavities open in high (dust) mass disks, independent of the stellar mass. The flatness of this relation contradicts the idea that TDs are a more evolved set of disks. Two potential reasons (not mutually exclusive) may explain this flat relation: the emission is optically thick or/and millimeter-sized particles are trapped in a pressure bump. Second, we discuss our results of the cavity size and ring width in the context of different physical processes for cavity formation. Photoevaporation is an unlikely leading mechanism for the origin of the cavity of any of the targets in the sample. Embedded giant planets or dead zones remain as potential explanations. Although both models predict correlations between the cavity size and the ring shape for different stellar and disk properties, we demonstrate that with the current resolution of the observations, it is difficult to obtain these correlations. Future observations with higher angular resolution observations of TDs with ALMA will help to discern between different potential origins of cavities in TDs

Experimental determination of the transient transport and of fluctuations relevant to transport in ASDEX

Particle transport was studied in ASDEZ with modulated puffing of the discharge gas and of impurities. The energy transport is investigated by numerical simulation of the heat pulse after the swatooth crash. Small scale density fluctuations are investigated in the confinement region with far infrared scattering and reflectometry and in the edge plasma with langmuir probes and Ha diagnostic. In addition to a diffuse component of the particle transport, a strong inward drift is observed in all discharges. In ohmic discharges the transport coefficients decrease and saturate like 1/TE with increasing density. They are smaller in deuterium that in hydrogen. In the improved ohmic confinement (IOC)regime mainly D in the outer region is reduced. D increases proportionally to the heating power in L-mode discharges. The improvement of particle confinement in the H-mode is explained by a increase of the inward drift at the edge rather than a decrease of D. The impurity diffusion coefficient is independent of the impurity mass and charge. In ohmic discharges, it varies with ne like the bulk diffusion coefficient, is independent of B or increases weakly with B and increases with Ip. In L-mode discharges, Dimp increases linearly with the heating power. The electron thermal condustivity determined by heat pulse propagation exceeds the stationary value by a factor of 3-4, assuming merely diffusive heat transport. Convection does not significantly reduce this factor. however, non-diagonal terms