Preduals of semigroup algebras

For a locally compact group G, the measure convolution algebra M(G) carries a natural coproduct. In previous work, we showed that the canonical predual C 0(G) of M(G) is the unique predual which makes both the product and the coproduct on M(G) weak*-continuous. Given a discrete semigroup S, the convolution algebra ℓ 1(S) also carries a coproduct. In this paper we examine preduals for ℓ 1(S) making both the product and the coproduct weak*-continuous. Under certain conditions on S, we show that ℓ 1(S) has a unique such predual. Such S include the free semigroup on finitely many generators. In general, however, this need not be the case even for quite simple semigroups and we construct uncountably many such preduals on ℓ 1(S) when S is either ℤ+×ℤ or (ℕ,⋅)

Modelling Timeouts without Timelocks

We address the issue of modelling a simple timeout in timed automata. We argue that expression of the timeout in the UPPAAL timed automata model is unsatisfactory since when composed with a component behaviour, the timeout can generate timelocks. In response we consider an alternative timed automata framework - timed automata with deadlines. This framework has the property that timelocks cannot be created when composing automata in parallel. We explore a number of different options for reformulating the timeout in this framework and then we relate them

White matter tract integrity in treatment-resistant gambling disorder

Background Gambling disorder is a relatively common psychiatric disorder recently re-classified within the DSM-5 under the category of ‘substance-related and addictive disorders’. Aims To compare white matter integrity in patients with gambling disorder with healthy controls; to explore relationships between white matter integrity and disease severity in gambling disorder. Method In total, 16 participants with treatment-resistant gambling disorder and 15 healthy controls underwent magnetic resonance imaging (MRI). White matter integrity was analysed using tract-based spatial statistics. Results Gambling disorder was associated with reduced fractional anisotropy in the corpus callosum and superior longitudinal fasciculus. Fractional anisotropy in distributed white matter tracts elsewhere correlated positively with disease severity. Conclusions Reduced corpus callosum fractional anisotropy is suggestive of disorganised/damaged tracts in patients with gambling disorder, and this may represent a trait/vulnerability marker for the disorder. Future research should explore these measures in a larger sample, ideally incorporating a range of imaging markers (for example functional MRI) and enrolling unaffected first-degree relatives of patients.This research was supported by a grant from the National Center for Responsible Gaming to Dr. Grant, and by a grant from the Academy of Medical Sciences to Dr. Chamberlain (UK). Dr. Grant has received research grants from NIMH, National Center for Responsible Gaming, and Forest and Roche Pharmaceuticals Dr. Grant receives yearly compensation from Springer Publishing for acting as Editor-in-Chief of the Journal of Gambling Studies and has received royalties from Oxford University Press, American Psychiatric Publishing, Inc., Norton Press, and McGraw Hill. Dr. Chamberlain consults for Cambridge Cognition. Mr. Odlaug has received a research grant from the Trichotillomania Learning Center, consults for H. Lundbeck A/S, and has received royalties from Oxford University Press. Mr. Leppink and Ms. Derbyshire report no conflicts of interest.This is the author accepted manuscript. The final version is available from the Royal College of Psychiatrists via http://dx.doi.org/10.1192/bjp.bp.115.16550

White matter tract integrity in treatment-resistant gambling disorder.

BACKGROUND: Gambling disorder is a relatively common psychiatric disorder recently re-classified within the DSM-5 under the category of 'substance-related and addictive disorders'. AIMS: To compare white matter integrity in patients with gambling disorder with healthy controls; to explore relationships between white matter integrity and disease severity in gambling disorder. METHOD: In total, 16 participants with treatment-resistant gambling disorder and 15 healthy controls underwent magnetic resonance imaging (MRI). White matter integrity was analysed using tract-based spatial statistics. RESULTS: Gambling disorder was associated with reduced fractional anisotropy in the corpus callosum and superior longitudinal fasciculus. Fractional anisotropy in distributed white matter tracts elsewhere correlated positively with disease severity. CONCLUSIONS: Reduced corpus callosum fractional anisotropy is suggestive of disorganised/damaged tracts in patients with gambling disorder, and this may represent a trait/vulnerability marker for the disorder. Future research should explore these measures in a larger sample, ideally incorporating a range of imaging markers (for example functional MRI) and enrolling unaffected first-degree relatives of patients.This research was supported by a grant from the National Center for Responsible Gaming to Dr. Grant, and by a grant from the Academy of Medical Sciences to Dr. Chamberlain (UK). Dr. Grant has received research grants from NIMH, National Center for Responsible Gaming, and Forest and Roche Pharmaceuticals Dr. Grant receives yearly compensation from Springer Publishing for acting as Editor-in-Chief of the Journal of Gambling Studies and has received royalties from Oxford University Press, American Psychiatric Publishing, Inc., Norton Press, and McGraw Hill. Dr. Chamberlain consults for Cambridge Cognition. Mr. Odlaug has received a research grant from the Trichotillomania Learning Center, consults for H. Lundbeck A/S, and has received royalties from Oxford University Press. Mr. Leppink and Ms. Derbyshire report no conflicts of interest.This is the author accepted manuscript. The final version is available from the Royal College of Psychiatrists via http://dx.doi.org/10.1192/bjp.bp.115.16550

Spontaneous alloying in binary metal microclusters - A molecular dynamics study -

Microcanonical molecular dynamics study of the spontaneous alloying(SA), which is a manifestation of fast atomic diffusion in a nano-sized metal cluster, is done in terms of a simple two dimensional binary Morse model. Important features observed by Yasuda and Mori are well reproduced in our simulation. The temperature dependence and size dependence of the SA phenomena are extensively explored by examining long time dynamics. The dominant role of negative heat of solution in completing the SA is also discussed. We point out that a presence of melting surface induces the diffusion of core atoms even if they are solid-like. In other words, the {\it surface melting} at substantially low temperature plays a key role in attaining the SA.Comment: 15 pages, 12 fgures, Submitted to Phys.Rev.

LTL Parameter Synthesis of Parametric Timed Automata

The parameter synthesis problem for parametric timed automata is undecidable in general even for very simple reachability properties. In this paper we introduce restrictions on parameter valuations under which the parameter synthesis problem is decidable for LTL properties. The investigated bounded integer parameter synthesis problem could be solved using an explicit enumeration of all possible parameter valuations. We propose an alternative symbolic zone-based method for this problem which results in a faster computation. Our technique extends the ideas of the automata-based approach to LTL model checking of timed automata. To justify the usefulness of our approach, we provide experimental evaluation and compare our method with explicit enumeration technique.Comment: 23 pages, extended versio

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker.

OBJECTIVE: Huntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real-life clinical diagnosis in HD. METHOD: A multivariate machine learning approach was applied to resting-state and structural magnetic resonance imaging scans from 19 premanifest HD gene carriers (preHD, 8 of whom developed clinical disease in the 5 years postscanning) and 21 healthy controls. A classification model was developed using cross-group comparisons between preHD and controls, and within the preHD group in relation to "estimated" and "actual" proximity to disease onset. Imaging measures were modeled individually, and combined, and permutation modeling robustly tested classification accuracy. RESULTS: Classification performance for preHDs versus controls was greatest when all measures were combined. The resulting polymarker predicted converters with high accuracy, including those who were not expected to manifest in that time scale based on the currently adopted statistical models. INTERPRETATION: We propose that a holistic multivariate machine learning treatment of brain abnormalities in the premanifest phase can be used to accurately identify those patients within 5 years of developing motor features of HD, with implications for prognostication and preclinical trials. Ann Neurol 2018;83:532-543.SLM is funded by a National Institute for Health Research (NIHR) Translational Research Collaboration for Rare Diseases fellowship. This research has been funded/supported by the National Institute for Health Research Rare Diseases Translational Research Collaboration (NIHR RD-TRC). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. RAB is funded by the NIHR Cambridge Biomedical Research Centre and the Cambridge University NHS Foundation Trust. RED is employed on an EC Marie-Curie CIG, awarded to AH, SJT, EJ and RS receive funding from a Wellcome Collaborative Award (200181/Z/15/Z

The determinants of election to the United Nations Security Council

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s11127-013-0096-4.The United Nations Security Council (UNSC) is the foremost international body responsible for the maintenance of international peace and security. Members vote on issues of global importance and consequently receive perks—election to the UNSC predicts, for instance, World Bank and IMF loans. But who gets elected to the UNSC? Addressing this question empirically is not straightforward as it requires a model that allows for discrete choices at the regional and international levels; the former nominates candidates while the latter ratifies them. Using an original multiple discrete choice model to analyze a dataset of 180 elections from 1970 to 2005, we find that UNSC election appears to derive from a compromise between the demands of populous countries to win election more frequently and a norm of giving each country its turn. We also find evidence that richer countries from the developing world win election more often, while involvement in warfare lowers election probability. By contrast, development aid does not predict election

Probabilistic Verification at Runtime for Self-Adaptive Systems

An effective design of effective and efficient self-adaptive systems may rely on several existing approaches. Software models and model checking techniques at run time represent one of them since they support automatic reasoning about such changes, detect harmful configurations, and potentially enable appropriate (self-)reactions. However, traditional model checking techniques and tools may not be applied as they are at run time, since they hardly meet the constraints imposed by on-the-fly analysis, in terms of execution time and memory occupation. For this reason, efficient run-time model checking represents a crucial research challenge. This paper precisely addresses this issue and focuses on probabilistic run-time model checking in which reliability models are given in terms of Discrete Time Markov Chains which are verified at run-time against a set of requirements expressed as logical formulae. In particular, the paper discusses the use of probabilistic model checking at run-time for self-adaptive systems by surveying and comparing the existing approaches divided in two categories: state-elimination algorithms and algebra-based algorithms. The discussion is supported by a realistic example and by empirical experiments

Accelerated Model Checking of Parametric Markov Chains

Parametric Markov chains occur quite naturally in various applications: they can be used for a conservative analysis of probabilistic systems (no matter how the parameter is chosen, the system works to specification); they can be used to find optimal settings for a parameter; they can be used to visualise the influence of system parameters; and they can be used to make it easy to adjust the analysis for the case that parameters change. Unfortunately, these advancements come at a cost: parametric model checking is---or rather was---often slow. To make the analysis of parametric Markov models scale, we need three ingredients: clever algorithms, the right data structure, and good engineering. Clever algorithms are often the main (or sole) selling point; and we face the trouble that this paper focuses on -- the latter ingredients to efficient model checking. Consequently, our easiest claim to fame is in the speed-up we have often realised when comparing to the state of the art