Differential negative reinforcement of other behavior to increase compliance with wearing an anti-strip suit

Using a changing-criterion design, we replicated and extended a study (Cook, Rapp, & Schulze, 2015) on differential negative reinforcement of other behavior (DNRO). More specifically, educational assistants implemented DNRO to teach a 12-year-old boy with autism spectrum disorder to comply with wearing an anti-strip suit to prevent inappropriate fecal behavior in a school setting. The duration for which the participant wore the suit systematically increased from 2 s at the start of treatment to the entire duration of the school day at the termination of the study. Moreover, these effects were generalized to a new school with novel staff and persisted for more than a year. These findings replicate prior research on DNRO and further support the use of the intervention to increase compliance with wearing protective items, or medical devices, in practical settings

The Distance to Nova V959 Mon from VLA Imaging

Determining reliable distances to classical novae is a challenging but crucial step in deriving their ejected masses and explosion energetics. Here we combine radio expansion measurements from the Karl G. Jansky Very Large Array with velocities derived from optical spectra to estimate an expansion parallax for nova V959 Mon, the first nova discovered through its gamma-ray emission. We spatially resolve the nova at frequencies of 4.5-36.5 GHz in nine different imaging epochs. The first five epochs cover the expansion of the ejecta from 2012 October to 2013 January, while the final four epochs span 2014 February to 2014 May. These observations correspond to days 126 through 199 and days 615 through 703 after the first detection of the nova. The images clearly show a non-spherical ejecta geometry. Utilizing ejecta velocities derived from 3D modelling of optical spectroscopy, the radio expansion implies a distance between 0.9 +/- 0.2 and 2.2 +/- 0.4 kpc, with a most probable distance of 1.4 +/- 0.4 kpc. This distance implies a gamma-ray luminosity much less than the prototype gamma-ray-detected nova, V407 Cyg, possibly due to the lack of a red giant companion in the V959 Mon system. V959 Mon also has a much lower gamma-ray luminosity than other classical novae detected in gamma-rays to date, indicating a range of at least a factor of 10 in the gamma-ray luminosities for these explosions.Comment: 11 pages, 8 figures, 3 tables, submitted to ApJ 2015-01-21, under revie

The Peculiar Multi-Wavelength Evolution Of V1535 Sco

We present multi-wavelength observations of the unusual nova V1535 Sco throughout its outburst in 2015. Early radio observations were consistent with synchrotron emission, and early X-ray observations revealed the presence of high-energy (>1 keV) photons. These indicated that strong shocks were present during the first ~2 weeks of the nova's evolution. The radio spectral energy distribution was consistent with thermal emission from week 2 to week 6. Starting in week 7, the radio emission again showed evidence of synchrotron emission and there was an increase in X-ray emission, indicating a second shock event. The optical spectra show evidence for at least two separate outflows, with the faster outflow possibly having a bipolar morphology. The optical and near infrared light curves and the X-ray measurements of the hydrogen column density indicated that the companion star is likely a K giant.Comment: 20 pages, 13 figures, under review at ApJ, updated to match the most recent version submitted to the refere

Repetition and difference: Lefebvre, Le Corbusier and modernity's (im)moral landscape: a commentary

This article engages with the relationship between social theory, architectural theory and material culture. The article is a reply to an article in a previous volume of the journal in question (Smith, M. (2001) ‘Repetition and difference: Lefebvre, Le Corbusier and modernity’s (im)moral landscape’, Ethics, Place and Environment, 4(1), 31-34) and, consequently, is also a direct engagement with another academic's scholarship. It represents a critique of their work as well as a recasting of their ideas, arguing that the matter in question went beyond interpretative issues to a direct critique of another author's scholarship on both Le Corbusier and Lefebvre. A reply to my article from the author of the original article was carried in a later issue of the journal (Smith, M. (2002) ‘Ethical Difference(s): a Response to Maycroft on Le Corbusier and Lefebvre’, Ethics, Place and Environment, 5(3), 260-269)

Neural Networks for Information Retrieval

Machine learning plays a role in many aspects of modern IR systems, and deep learning is applied in all of them. The fast pace of modern-day research has given rise to many different approaches for many different IR problems. The amount of information available can be overwhelming both for junior students and for experienced researchers looking for new research topics and directions. Additionally, it is interesting to see what key insights into IR problems the new technologies are able to give us. The aim of this full-day tutorial is to give a clear overview of current tried-and-trusted neural methods in IR and how they benefit IR research. It covers key architectures, as well as the most promising future directions.Comment: Overview of full-day tutorial at SIGIR 201

A Phase transition in acoustic propagation in 2D random liquid media

Acoustic wave propagation in liquid media containing many parallel air-filled cylinders is considered. A self-consistent method is used to compute rigorously the propagation, incorporating all orders of multiple scattering. It is shown that under proper conditions, multiple scattering leads to a peculiar phase transition in acoustic propagation. When the phase transition occurs, a collective behavior of the cylinders appears and the acoustic waves are confined in a region of space in the neighborhood of the transmission source. A novel phase diagram is used to describe such phase transition. Originally submitted on April 6, 99.Comment: 5 pages, 5 color figure

Active repression by unliganded retinoid receptors in development: less is sometimes more

The retinoid receptors have major roles throughout development, even in the absence of ligand. Here, we summarize an emerging theme whereby gene repression, mediated by unliganded retinoid receptors, can dictate cell fate. In addition to activating transcription, retinoid receptors actively repress gene transcription by recruiting cofactors that promote chromatin compaction. Two developmental processes for which gene silencing by the retinoid receptors is essential are head formation in Xenopus and skeletal development in the mouse. Inappropriate repression, by oncogenic retinoic acid (RA)* receptor (RAR) fusion proteins, blocks myeloid differentiation leading to a rare form of leukemia. Our current understanding of the developmental role of retinoid repression and future perspectives in this field are discussed

Dynamic Key-Value Memory Networks for Knowledge Tracing

Knowledge Tracing (KT) is a task of tracing evolving knowledge state of students with respect to one or more concepts as they engage in a sequence of learning activities. One important purpose of KT is to personalize the practice sequence to help students learn knowledge concepts efficiently. However, existing methods such as Bayesian Knowledge Tracing and Deep Knowledge Tracing either model knowledge state for each predefined concept separately or fail to pinpoint exactly which concepts a student is good at or unfamiliar with. To solve these problems, this work introduces a new model called Dynamic Key-Value Memory Networks (DKVMN) that can exploit the relationships between underlying concepts and directly output a student's mastery level of each concept. Unlike standard memory-augmented neural networks that facilitate a single memory matrix or two static memory matrices, our model has one static matrix called key, which stores the knowledge concepts and the other dynamic matrix called value, which stores and updates the mastery levels of corresponding concepts. Experiments show that our model consistently outperforms the state-of-the-art model in a range of KT datasets. Moreover, the DKVMN model can automatically discover underlying concepts of exercises typically performed by human annotations and depict the changing knowledge state of a student.Comment: To appear in 26th International Conference on World Wide Web (WWW), 201

The AUSTRAL VLBI Observing Program

The AUSTRAL observing program was started in 2011, performing geodetic and astrometric very long baseline interferometry (VLBI) sessions using the new Australian AuScope VLBI antennas at Hobart, Katherine, and Yarragadee, with contribution from the Warkworth (New Zealand) 12 m and Hartebeesthoek (South Africa) 15 m antennas to make a southern hemisphere array of telescopes with similar design and capability. Designed in the style of the next-generation VLBI system, these small and fast antennas allow for a new way of observing, comprising higher data rates and more observations than the standard observing sessions coordinated by the International VLBI Service for Geodesy and Astrometry (IVS). In this contribution, the continuous development of the AUSTRAL sessions is described, leading to an improvement of the results in terms of baseline length repeatabilities by a factor of two since the start of this program. The focus is on the scheduling strategy and increased number of observations, aspects of automated operation, and data logistics, as well as results of the 151 AUSTRAL sessions performed so far. The high number of the AUSTRAL sessions makes them an important contributor to VLBI end-products, such as the terrestrial and celestial reference frames and Earth orientation parameters. We compare AUSTRAL results with other IVS sessions and discuss their suitability for the determination of baselines, station coordinates, source coordinates, and Earth orientation parameters

Digging into acceptor splice site prediction : an iterative feature selection approach

Feature selection techniques are often used to reduce data dimensionality, increase classification performance, and gain insight into the processes that generated the data. In this paper, we describe an iterative procedure of feature selection and feature construction steps, improving the classification of acceptor splice sites, an important subtask of gene prediction. We show that acceptor prediction can benefit from feature selection, and describe how feature selection techniques can be used to gain new insights in the classification of acceptor sites. This is illustrated by the identification of a new, biologically motivated feature: the AG-scanning feature. The results described in this paper contribute both to the domain of gene prediction, and to research in feature selection techniques, describing a new wrapper based feature weighting method that aids in knowledge discovery when dealing with complex datasets