Many industrial applications require finding solutions to challenging combinatorial problems. Efficient elimination of symmetric solution candidates is one of the key enablers for high-performance solving. However, existing model-based approaches for symmetry breaking are limited to problems for which a set of representative and easily solvable instances is available, which is often not the case in practical applications. This work extends the learning framework and implementation of a model-based approach for Answer Set Programming to overcome these limitations and address challenging problems, such as the Partner Units Problem. In particular, we incorporate a new conflict analysis algorithm in the Inductive Logic Programming system ILASP, redefine the learning task, and suggest a new example generation method to scale up the approach. The experiments conducted for different kinds of Partner Units Problem instances demonstrate the applicability of our approach and the computational benefits due to the first-order constraints learned.

The goal of inductive logic programming (ILP) is to learn a program that explains a set of examples. Until recently, most research on ILP targeted learning Prolog programs. The ILASP system instead learns answer set programs (ASP). Learning such expressive programs widens the applicability of ILP considerably; for example, enabling preference learning, learning common-sense knowledge, including defaults and exceptions, and learning non-deterministic theories. Early versions of ILASP can be considered meta-level ILP approaches, which encode a learning task as a logic program and delegate the search to an ASP solver. More recently, ILASP has shifted towards a new method, inspired by conflict-driven SAT and ASP solvers. The fundamental idea of the approach, called Conflict-driven ILP (CDILP), is to iteratively interleave the search for a hypothesis with the generation of constraints which explain why the current hypothesis does not cover a particular example. These coverage constraints allow ILASP to rule out not just the current hypothesis, but an entire class of hypotheses that do not satisfy the coverage constraint. This article formalises the CDILP approach and presents the ILASP3 and ILASP4 systems for CDILP, which are demonstrated to be more scalable than previous ILASP systems, particularly in the presence of noise.

Cardiac Fibromas are primary cardiac tumours more common in children than in adults. Surgical intervention is often not required except in the case of limited cardiac output or significant arrhythmia burden. We present a symptomatic 3-month-old infant who had successful surgical intervention for a giant right ventricle fibroma found on prenatal imaging.

In this article, we present a case of a desaturated Fontan patient with an infra-diaphragmatic venous collateral to the pulmonary vein, which was too tortuous to attempt closure at the source. A trans-septal approach was successfully used to close the collateral in a retrograde manner.

In recent years, several frameworks and systems have been proposed that extend Inductive Logic Programming (ILP) to the Answer Set Programming (ASP) paradigm. In ILP, examples must all be explained by a hypothesis together with a given background knowledge. In existing systems, the background knowledge is the same for all examples; however, examples may be context-dependent. This means that some examples should be explained in the context of some information, whereas others should be explained in different contexts. In this paper, we capture this notion and present a context-dependent extension of the Learning from Ordered Answer Sets framework. In this extension, contexts can be used to further structure the background knowledge. We then propose a new iterative algorithm, ILASP2i, which exploits this feature to scale up the existing ILASP2 system to learning tasks with large numbers of examples. We demonstrate the gain in scalability by applying both algorithms to various learning tasks. Our results show that, compared to ILASP2, the newly proposed ILASP2i system can be two orders of magnitude faster and use two orders of magnitude less memory, whilst preserving the same average accuracy.

In the United States alone, ∼14,000 children are hospitalised annually with acute heart failure. The science and art of caring for these patients continues to evolve. The International Pediatric Heart Failure Summit of Johns Hopkins All Children’s Heart Institute was held on February 4 and 5, 2015. The 2015 International Pediatric Heart Failure Summit of Johns Hopkins All Children’s Heart Institute was funded through the Andrews/Daicoff Cardiovascular Program Endowment, a philanthropic collaboration between All Children’s Hospital and the Morsani College of Medicine at the University of South Florida (USF). Sponsored by All Children’s Hospital Andrews/Daicoff Cardiovascular Program, the International Pediatric Heart Failure Summit assembled leaders in clinical and scientific disciplines related to paediatric heart failure and created a multi-disciplinary “think-tank”. The purpose of this manuscript is to summarise the lessons from the 2015 International Pediatric Heart Failure Summit of Johns Hopkins All Children’s Heart Institute, to describe the “state of the art” of the treatment of paediatric cardiac failure, and to discuss future directions for research in the domain of paediatric cardiac failure.

This paper contributes to the area of inductive logic programming by presenting a new learning framework that allows the learning of weak constraints in Answer Set Programming (ASP). The framework, called Learning from Ordered Answer Sets, generalises our previous work on learning ASP programs without weak constraints, by considering a new notion of examples as ordered pairs of partial answer sets that exemplify which answer sets of a learned hypothesis (together with a given background knowledge) are preferred to others. In this new learning task inductive solutions are searched within a hypothesis space of normal rules, choice rules, and hard and weak constraints. We propose a new algorithm, ILASP2, which is sound and complete with respect to our new learning framework. We investigate its applicability to learning preferences in an interview scheduling problem and also demonstrate that when restricted to the task of learning ASP programs without weak constraints, ILASP2 can be much more efficient than our previously proposed system.

This article focuses attention on research examining workplace discrimination against employees from marginalized groups. We particularly consider the experiences of seven different groups of marginalized individuals, some of which have legal protection and some of which do not but all of whom we feel have been overlooked by the field of industrial–organizational (I–O) psychology. We briefly describe the importance of studying each group and then delineate the brief amount of research that has been conducted. Finally, we make recommendations for I–O psychologists in terms of research and advocacy. Overall, we argue that I–O psychologists are missing an opportunity to be at the forefront of understanding and instigating changes that would result in maximizing the fairness and optimization of these often forgotten employees and their experiences in the workplace.

Buprenorphine is a partial μ-opioid receptor agonist that is being increasingly used in clinical practice in the treatment of opioid dependence in the UK, USA, and, elsewhere. Its unique pharmacological properties mean it is a relatively safe drug, it can be given by alternate day dispensing, and it is associated with relatively mild symptoms on withdrawal. The interpretation of the research literature on buprenorphine is however, complex, and often appears to be in conflict with how buprenorphine is used in clinical practice. This article describes these apparent contradictions, their likely explanations, and how these may further inform our clinical practice. The article also describes the clinically relevant pharmacological properties of buprenorphine, compares it to methadone, relates the evidence to clinical experience, and provides practical advice on how to manage the most common clinical techniques. The best quality evidence suggests that very rapid buprenorphine induction is not associated with a higher drop-out rate than methadone, that buprenorphine is probably as good as methadone for maintenance treatment, and is superior to methadone and α-2 adrenergic agonists for detoxification. However, buprenorphine cannot yet be considered the ‘gold standard’ treatment for opiate dependence because of the higher drop-out rates that may occur on induction using current techniques, its high-cost relative to methadone, and because the place of buprenorphine in treatment is still continuing to evolve.

The Australian Square Kilometre Array Pathfinder (ASKAP) will give us an unprecedented opportunity to investigate the transient sky at radio wavelengths. In this paper we present VAST, an ASKAP survey for Variables and Slow Transients. VAST will exploit the wide-field survey capabilities of ASKAP to enable the discovery and investigation of variable and transient phenomena from the local to the cosmological, including flare stars, intermittent pulsars, X-ray binaries, magnetars, extreme scattering events, interstellar scintillation, radio supernovae, and orphan afterglows of gamma-ray bursts. In addition, it will allow us to probe unexplored regions of parameter space where new classes of transient sources may be detected. In this paper we review the known radio transient and variable populations and the current results from blind radio surveys. We outline a comprehensive program based on a multi-tiered survey strategy to characterise the radio transient sky through detection and monitoring of transient and variable sources on the ASKAP imaging timescales of 5 s and greater. We also present an analysis of the expected source populations that we will be able to detect with VAST.

We investigated AlAs0.56Sb0.44 epitaxial layers lattice-matched to InP grown by molecular beam epitaxy (MBE). Silicon (Si) and tellurium (Te) were studied as n-type dopants in AlAs0.56Sb0.44 material. Similar to most Sb-based materials, AlAs0.56Sb0.44 demonstrates a maximum active carrier concentration around low-1018 cm-3 when using Te as a dopant. We propose the use of a heavily Si-doped InAlAs layer embedded in the AlAsSb barrier as a modulation-doped layer. The In0.53Ga0.47As/AlAs0.56Sb0.44 double heterostructures with a 10 nm InGaAs well show an electron mobility of about 9400 cm2/V・s at 295 K and 32000 cm2/V・s at 46 K. A thinner 5 nm InGaAs well has an electron mobility of about 4300 cm2/V・s at 295 K. This study demonstrates that AlAs0.56Sb0.44 is a promising barrier material for highly scaled InGaAs MOSFETs and HEMTs.

Level set methods have been used for Solid phase epitaxial regrowth, etching and deposition.This study is to model the growth of nickel silicide accurately using the level set method. NiSi growth has been observed to follow a linear-parabolic law which takes into account both diffusion and interfacial reaction. This linear-parabolic system is very similar to the Deal and Grove model of SiO2 growth. This model uses similar diffusion transport and reaction rate equations. This simulation models the growth of silicide coupling diffusion solutions to level-set techniques. Dual level sets have been used for top and bottom interface propagation of silicide; velocities were estimated based on nickel concentrations at both interfaces as well as diffusivity and reaction rate of nickel. This is important to predict precise shape of silicide that will allow current crowding and field focusing effects to be modeled in transport out of the intrinsic device into the contacting layers. These simulation models can be used for latest technology nodes at 45, 32, 22nm and special devices such as FinFET’s etc. The level set method is successfully implemented and verified in Florida Object Oriented Process Simulator and growth shapes matches well with the literature Transmission Electron Microscopy data.

We present photometry and spectroscopy of the peculiar Type II supernova SN 2010jp, also named PTF10aaxi. The light curve exhibits a linear decline with a relatively low peak absolute magnitude of only −15.9 (unfiltered), and a low radioactive decay luminosity at late times that suggests a low synthesized nickel mass of about 0.003 M⊙ or less. Spectra of SN 2010jp display an unprecedented triple-peaked Hα line profile, showing: (1) a narrow central component that suggests shock interaction with a dense circumstellar medium (CSM); (2) high-velocity blue and red emission features centered at −12,600 and +15,400 km s−1; and (3) very broad wings extending from −22,000 to +25,000 km s−1. We propose that this line profile indicates a bipolar jet-driven explosion, with the central component produced by normal SN ejecta and CSM interaction at mid and low latitudes, while the high-velocity bumps and broad line wings arise in a nonrelativistic bipolar jet. Jet-driven SNe II are predicted for collapsars resulting from a wide range of initial masses above 25 M⊙, especially at the sub-solar metallicity consistent with the SN host environment. It also seems consistent with the apparently low 56Ni mass that may accompany black hole formation. We speculate that the jet survives to produce observable signatures because the star's H envelope was very low mass, having been mostly stripped away by the previous eruptive mass loss.

Flash-assist Rapid Thermal Processing (RTP) presents an opportunity to investigate annealing time and temperature regimes which were previously not accessible with conventional annealing techniques such as Rapid Thermal Annealing. This provides a unique opportunity to explore the early stages of the End of Range (EOR) damage evolution and also to examine how the damage evolves during the high temperature portion of the temperature profile. However, the nature of the Flash-assist RTP makes it is extremely difficult to reasonably compare it to alternative annealing techniques, largely because the annealing time at a given temperature is dictated by the FWHM of the radiation pulse. The FWHM for current flash tools vary between 0.85 and 1.38 milliseconds, which is three orders of magnitude smaller to that required for a RTA to achieve similar temperatures. Traditionally, the kinetics of the extended defects has been studied by time dependent studies utilizing isothermal anneals; in which specific defect structures could be isolated. The characteristics of Flash-assist RTP do not allow for such investigations in which the EOR defect evolution could be closely tracked with time. Since the annealing time at the target temperature for the Flash-assist RTP is essentially fixed to very small times on the order of milliseconds, isochronal anneals are a logical experimental approach to temperature dependent studies. This fact presents a challenge in the data analysis and comparison. Another feature of Flash-assist RTP which makes the analysis complex is the ramp time relative to the dwell time spent at the peak fRTP temperature. As the flash anneal temperature is increased the total ramp time can exceed the dwell time at the peak temperature, which may play a significantly larger role in dictating the final material properties. The inherent characteristics of Flash-assist RTP have consequently required the development of another approach to analyzing the attainable experimental data, such that a meaningful comparison could be made to past studies. The adopted analysis entails the selection of a reference anneal, from which the decay in the trapped interstitial density can be tracked with the flash anneal temperature, allowing for the kinetics of the interstitial decay to be extracted.