A Monte-Carlo tree search in argumentation

Monte-Carlo Tree Search (MCTS) is a heuristic to search in large trees. We apply it to argumentative puzzles where MCTS pursues the best argumentation with respect to a set of arguments to be argued. To make our ideas as widely applicable as possible, we integrate MCTS to an abstract setting for argumentation where the content of arguments is left unspecified. Experimental results show the pertinence of this integration for learning argumentations by comparing it with a basic reinforcement learning.

Monte Carlo analysis of a puzzle game

When a puzzle game is created, its design parameters must be chosen to allow solvable and interesting challenges to be created for the player. We investigate the use of random sampling as a computationally inexpensive means of automated game analysis, to evaluate the BoxOff family of puzzle games. This analysis reveals useful insights into the game, such as the surprising fact that almost 100% of randomly generated challenges have a solution, but less than 10% will be solved using strictly random play, validating the inventor’s design choices. We show the 1D game to be trivial and the 3D game to be viable.

Clarification of the low-frequency modelling concept for marine craft

This article presents some remarks on models currently used in low speed manoeuvring and dynamic positioning problems. It discusses the relationship between the classical hydrodynamic equations for manoeuvring and seakeeping, and offers insight into the models used for simulation and control system design.

Bayesian model comparison in cosmology with Population Monte Carlo

We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo (PMC), a new adaptive sampling technique which was recently applied in a cosmological context. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulations and from data. For the cases we consider, the log-evidence is calculated with a precision of better than 0.08. Using a combined set of recent CMB, SNIa and BAO data, we find inconclusive evidence between flat LambdaCDM and simple dark-energy models. A curved Universe is moderately to strongly disfavoured with respect to a flat cosmology. Using physically well-motivated priors within the slow-roll approximation of inflation, we find a weak preference for a running spectral index. A Harrison-Zel'dovich spectrum is weakly disfavoured. With the current data, tensor modes are not detected; the large prior volume on the tensor-to-scalar ratio r results in moderate evidence in favour of r=0.

Prevalence of Staphylococcus aureus strains in an Australian cohort, 1989-2003 : evidence for the low prevalence of the toxic shock toxin and Panton-Valentine leukocidin genes

The purpose of this paper is to determine the prevalence of the toxic shock toxin gene (tst) and to enumerate the circulating strains of methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant S. aureus (MRSA) in Australian isolates collected over two decades. The aim was to subtype these strains using the binary genes pvl, cna, sdrE, pUB110 and pT181. Isolates were assayed using real-time polymerase chain reaction (PCR) for mecA, nuc, 16 S rRNA, eight single-nucleotide polymorphisms (SNPs) and for five binary genes. Two realtime PCR assays were developed for tst. The 90 MRSA isolates belonged to CC239 (39 in 1989, 38 in 1996 and ten in 2003), CC1 (two in 2003) and CC22 (one in 2003). The majority of the 210 MSSA isolates belonged to CC1 (26), CC5 (24) and CC78 (23). Only 18 isolates were tst-positive and only 15 were pvl-positive. Nine MSSA isolates belonged to five binary types of ST93, including two pvlpositive types. The proportion of tst-positive and pvl-positive isolates was low and no significant increase was demonstrated. Dominant MSSA clonal complexes were similar to those seen elsewhere, with the exception of CC78. CC239 MRSA (AUS-2/3) was the predominant MRSA but decreased significantly in prevalence, while CC22 (EMRSA-15) and CC1 (WA-1) emerged. Genetically diverse ST93 MSSA predated the emergence of ST93- MRSA (the Queensland clone).

Multivariate Markov Process Models for the transmission of methicillin-resistant Staphylococcus Aureus in a hospital ward

Methicillin-resistant Staphylococcus Aureus (MRSA) is a pathogen that continues to be of major concern in hospitals. We develop models and computational schemes based on observed weekly incidence data to estimate MRSA transmission parameters. We extend the deterministic model of McBryde, Pettitt, and McElwain (2007, Journal of Theoretical Biology 245, 470–481) involving an underlying population of MRSA colonized patients and health-care workers that describes, among other processes, transmission between uncolonized patients and colonized health-care workers and vice versa. We develop new bivariate and trivariate Markov models to include incidence so that estimated transmission rates can be based directly on new colonizations rather than indirectly on prevalence. Imperfect sensitivity of pathogen detection is modeled using a hidden Markov process. The advantages of our approach include (i) a discrete valued assumption for the number of colonized health-care workers, (ii) two transmission parameters can be incorporated into the likelihood, (iii) the likelihood depends on the number of new cases to improve precision of inference, (iv) individual patient records are not required, and (v) the possibility of imperfect detection of colonization is incorporated. We compare our approach with that used by McBryde et al. (2007) based on an approximation that eliminates the health-care workers from the model, uses Markov chain Monte Carlo and individual patient data. We apply these models to MRSA colonization data collected in a small intensive care unit at the Princess Alexandra Hospital, Brisbane, Australia.

The low-affinity site of the β1-adrenoceptor and its relevance to cardiovascular pharmacology

β-Adrenoceptor blocking agents (β-blockers) that at low concentrations antagonize cardiostimulant effects of catecholamines, but at high concentrations also cause cardiostimulation, have been appearing since the late 1960s. These cardiostimulant β-blockers, coined non-conventional partial agonists, antagonize the effects of catecholamines through a high-affinity site (β1HAR), but cause cardiostimulation mainly through a low-affinity site (β1LAR) of the myocardial β1-adrenoceptor. The experimental non-conventional partial agonist (−)-CGP12177 increases cardiac L-type Ca2+ current density and Ca2+ transients, shortens action potential duration but augments action potential plateau, increases heart rate and force, as well as causes arrhythmic Ca2+ transients and arrhythmic cardiocyte contractions. Other β-blockers, which do not cause cardiostimulation, consistently have lower affinity for β1LAR than β1HAR. These sites were verified and the cardiac pharmacology of non-conventional partial agonists confirmed on recombinant β1-adrenoceptors and on β1-adrenoceptors overexpressed into the heart. A targeted mutation of Asp138 to Glu138 virtually abolished the pharmacology of β1HAR but left intact the pharmacology of β1LAR. Non-conventional partial agonists may be beneficial for the treatment of peripheral autonomic neuropathy but probably due to their arrhythmic propensities, may be harmful for the treatment of chronic heart failure.

The high road or the low road? Alternatives for Australia's future

The OECD suggests that countries now have a choice. They can focus on development based on either:  competition via investment in technology and innovation - which is important in high knowledge industries and high innovation economies, or  competition via exchange rates and wages - which is important in industries producing standardised, lower-tech goods and services. The first route will maximise higher-skilled, higher-paid employment growth and living standards. Given the lack of control over the exchange rate, the second route requires competition based on wages. It is essential to understand that markets themselves won’t shift a country from one path to the other. These conclusions arise from the OECD’s recognition that technical progress - the creation of new products or the adoption of more efficient methods of production - is the main source of economic growth and enhanced quality of life. Technological change is, the OECD suggests, ...also the engine for job creation as higher wages and profits resulting from technology-induced productivity gains and lower prices lead to increased demand for new products from existing as well as new industries (1997: 4).Further, Competitiveness in high-technology industries is mainly driven by technology factors and much less by wage and exchange rate movements, while the reverse is true in low-technology industries (OECD 1996e: 12). The OECD has shown that sound macroeconomic conditions, such as the low inflation and reduced public sector debt visible in almost all member countries in the 1990s, are not enough to deal with high levels of unemployment and the need to increase levels of income: If economic performance is to improve, additional structural reform, which can increase innovation and the diffusion of technologies within and among national economies, seems necessary (OECD 1997: 4 Emphasis added).

Summary report : the high road or the low road? Alternatives for Australia's future

This document is a summary of the findings of the inaugural study commissioned by the Australian Business Foundation Limited. It was conducted by Professor Jane Marceau, Pro-Vice Chancellor (Research) at the University of Western Sydney Macarthur, Dr Karen Manley, Visiting Research Fellow at the University of Western Sydney Macarthur and Mr Derek Sicklen, Managing Director of Australian Economic Analysis Pty Limited. The full report is available from the Australian Business Foundation. The Australian Business Foundation Limited is a recently formed independent economic and industry policy think-tank. It has been established and sponsored by Australian Business Limited, a pre-eminent and long-standing industry association and business services network. The report is in three parts. The first reviews the key findings of contemporary international economic and innovation-oriented analyses of the characteristics of high growth economies. The second assesses the shape, structure and dynamics of Australian industry as these compare with the characteristics for successful economic development suggested in the literature. Finally, the report indicates the nature of urgently required policy directions.

Bayesian models for the determination of resonant frequencies in a DI diesel engine

A time series method for the determination of combustion chamber resonant frequencies is outlined. This technique employs the use of Markov-chain Monte Carlo (MCMC) to infer parameters in a chosen model of the data. The development of the model is included and the resonant frequency is characterised as a function of time. Potential applications for cycle-by-cycle analysis are discussed and the bulk temperature of the gas and the trapped mass in the combustion chamber are evaluated as a function of time from resonant frequency information.

Towards the development of a gas sensor system for monitoring pollutant gases in the low troposphere using small unmanned aerial vehicles

The world is facing problems due to the effects of increased atmospheric pollution, climate change and global warming. Innovative technologies to identify, quantify and assess fluxes exchange of the pollutant gases between the Earth’s surface and atmosphere are required. This paper proposes the development of a gas sensor system for a small UAV to monitor pollutant gases, collect data and geo-locate where the sample was taken. The prototype has two principal systems: a light portable gas sensor and an optional electric–solar powered UAV. The prototype will be suitable to: operate in the lower troposphere (100-500m); collect samples; stamp time and geo-locate each sample. One of the limitations of a small UAV is the limited power available therefore a small and low power consumption payload is designed and built for this research. The specific gases targeted in this research are NO2, mostly produce by traffic, and NH3 from farming, with concentrations above 0.05 ppm and 35 ppm respectively which are harmful to human health. The developed prototype will be a useful tool for scientists to analyse the behaviour and tendencies of pollutant gases producing more realistic models of them.