Norm modifications in defeasible logic

This paper proposes a framework based on Defeasible Logic (DL) to reason about normative modifications. We show how to express them in DL and how the logic deals with conflicts between temporalised normative modifications. Some comments will be given with regard to the phenomenon of retroactivity.

Free radical reactions in atherosclerosis; An EPR spectrometry study

The copper catalysed oxidation of homocysteine has been studied by electron paramagnetic resonance (EPR) spectroscopy and spin trapping techniques to determine the nature of free radical species formed under varying experimental conditions. Three radicals; thiyl, alkyl and hydroxyl were detected with hydroxyl being predominant. A reaction mechanism is proposed involving Fenton chemistry. Inclusion of catalase to test for intermediate generation of hydrogen peroxide showed a marked reduction in amount of hydroxyl radical generated. In contrast, the addition of superoxide dismutase showed no significant effect on the level of hydroxyl radical formed. Enhanced radical formation was observed at higher levels of oxygen, an effect which has consequences for differential oxygen levels in arterial and venous systems. Implications are drawn for a higher incidence of atherosclerotic plaque formation in arteries versus veins. © 2006 - IOS Press and the authors. All rights reserved.

Transition of legacy systems to semantically enabled applications:TAO method and tools

Despite expectations being high, the industrial take-up of Semantic Web technologies in developing services and applications has been slower than expected. One of the main reasons is that many legacy systems have been developed without considering the potential of theWeb in integrating services and sharing resources.Without a systematic methodology and proper tool support, the migration from legacy systems to SemanticWeb Service-based systems can be a tedious and expensive process, which carries a significant risk of failure. There is an urgent need to provide strategies, allowing the migration of legacy systems to Semantic Web Services platforms, and also tools to support such strategies. In this paper we propose a methodology and its tool support for transitioning these applications to Semantic Web Services, which allow users to migrate their applications to Semantic Web Services platforms automatically or semi-automatically. The transition of the GATE system is used as a case study. © 2009 - IOS Press and the authors. All rights reserved.

Decentralised supply chain formation:a belief propagation-based approach

Decentralised supply chain formation involves determining the set of producers within a network able to supply goods to one or more consumers at the lowest cost. This problem is frequently tackled using auctions and negotiations. In this paper we show how it can be cast as an optimisation of a pairwise cost function. Optimising this class of functions is NP-hard but good approximations to the global minimum can be obtained using Loopy Belief Propagation (LBP). Here we detail a LBP-based approach to the supply chain formation problem, involving decentralised message-passing between potential participants. Our approach is evaluated against a well-known double-auction method and an optimal centralised technique, showing several improvements: it obtains better solutions for most networks that admit a competitive equilibrium Competitive equilibrium as defined in [3] is used as a means of classifying results on certain networks to allow for minor inefficiencies in their auction protocol and agent bidding strategies. while also solving problems where no competitive equilibrium exists, for which the double-auction method frequently produces inefficient solutions.

The Gilles de la Tourette Syndrome-Quality of Life Scale for children and adolescents (C&A-GTS-QOL):development and validation of the Italian version

BACKGROUND: Gilles de la Tourette syndrome (GTS) is a chronic childhood-onset neuropsychiatric disorder with a significant impact on patients' health-related quality of life (HR-QOL). Cavanna et al. (Neurology 2008; 71: 1410-1416) developed and validated the first disease-specific HR-QOL assessment tool for adults with GTS (Gilles de la Tourette Syndrome-Quality of Life Scale, GTS-QOL). This paper presents the translation, adaptation and validation of the GTS-QOL for young Italian patients with GTS. METHODS: A three-stage process involving 75 patients with GTS recruited through three Departments of Child and Adolescent Neuropsychiatry in Italy led to the development of a 27-item instrument (Gilles de la Tourette Syndrome-Quality of Life Scale in children and adolescents, C&A-GTS-QOL) for the assessment of HR-QOL through a clinician-rated interview for 6-12 year-olds and a self-report questionnaire for 13-18 year-olds. RESULTS: The C&A-GTS-QOL demonstrated satisfactory scaling assumptions and acceptability. Internal consistency reliability was high (Cronbach's alpha > 0.7) and validity was supported by interscale correlations (range 0.4-0.7), principal-component factor analysis and correlations with other rating scales and clinical variables. CONCLUSIONS: The present version of the C&A-GTS-QOL is the first disease-specific HR-QOL tool for Italian young patients with GTS, satisfying criteria for acceptability, reliability and validity. © 2013 - IOS Press and the authors. All rights reserved.

Designing a successful adaptive agent for TAC Ad auction

This paper describes the design and evaluation of Aston-TAC, the runner-up in the Ad Auction Game of 2009 International Trading Agent Competition. In particular, we focus on how Aston-TAC generates adaptive bid prices according to the Market-based Value Per Click and how it selects a set of keyword queries to bid on to maximise the expected profit under limited conversion capacity. Through evaluation experiments, we show that AstonTAC performs well and stably not only in the competition but also across a broad range of environments. © 2010 The authors and IOS Press. All rights reserved.

A stepwise fuzzy linear programming model with possibility and necessity relations

Linear programming (LP) is the most widely used optimization technique for solving real-life problems because of its simplicity and efficiency. Although conventional LP models require precise data, managers and decision makers dealing with real-world optimization problems often do not have access to exact values. Fuzzy sets have been used in the fuzzy LP (FLP) problems to deal with the imprecise data in the decision variables, objective function and/or the constraints. The imprecisions in the FLP problems could be related to (1) the decision variables; (2) the coefficients of the decision variables in the objective function; (3) the coefficients of the decision variables in the constraints; (4) the right-hand-side of the constraints; or (5) all of these parameters. In this paper, we develop a new stepwise FLP model where fuzzy numbers are considered for the coefficients of the decision variables in the objective function, the coefficients of the decision variables in the constraints and the right-hand-side of the constraints. In the first step, we use the possibility and necessity relations for fuzzy constraints without considering the fuzzy objective function. In the subsequent step, we extend our method to the fuzzy objective function. We use two numerical examples from the FLP literature for comparison purposes and to demonstrate the applicability of the proposed method and the computational efficiency of the procedures and algorithms. © 2013-IOS Press and the authors. All rights reserved.

Handling varying amounts of missing data when classifying mental-health risk levels

One of the main challenges of classifying clinical data is determining how to handle missing features. Most research favours imputing of missing values or neglecting records that include missing data, both of which can degrade accuracy when missing values exceed a certain level. In this research we propose a methodology to handle data sets with a large percentage of missing values and with high variability in which particular data are missing. Feature selection is effected by picking variables sequentially in order of maximum correlation with the dependent variable and minimum correlation with variables already selected. Classification models are generated individually for each test case based on its particular feature set and the matching data values available in the training population. The method was applied to real patients' anonymous mental-health data where the task was to predict the suicide risk judgement clinicians would give for each patient's data, with eleven possible outcome classes: zero to ten, representing no risk to maximum risk. The results compare favourably with alternative methods and have the advantage of ensuring explanations of risk are based only on the data given, not imputed data. This is important for clinical decision support systems using human expertise for modelling and explaining predictions.

Understanding data collection behaviour of mental health practitioners

Failure to detect patients at risk of attempting suicide can result in tragic consequences. Identifying risks earlier and more accurately helps prevent serious incidents occurring and is the objective of the GRiST clinical decision support system (CDSS). One of the problems it faces is high variability in the type and quantity of data submitted for patients, who are assessed in multiple contexts along the care pathway. Although GRiST identifies up to 138 patient cues to collect, only about half of them are relevant for any one patient and their roles may not be for risk evaluation but more for risk management. This paper explores the data collection behaviour of clinicians using GRiST to see whether it can elucidate which variables are important for risk evaluations and when. The GRiST CDSS is based on a cognitive model of human expertise manifested by a sophisticated hierarchical knowledge structure or tree. This structure is used by the GRiST interface to provide top-down controlled access to the patient data. Our research explores relationships between the answers given to these higher-level 'branch' questions to see whether they can help direct assessors to the most important data, depending on the patient profile and assessment context. The outcome is a model for dynamic data collection driven by the knowledge hierarchy. It has potential for improving other clinical decision support systems operating in domains with high dimensional data that are only partially collected and in a variety of combinations.

Functional neuroanatomy and behavioural correlates of the basal ganglia:evidence from lesion studies

Introduction: The basal ganglia are interconnected with cortical areas involved in behavioural, cognitive and emotional processes, in addition to movement regulation. Little is known about which of these functions are associated with individual basal ganglia substructures. Methods: Pubmed was searched for literature related to behavioural, cognitive and emotional symptoms associated with focal lesions to basal ganglia structures in humans. Results: Six case-control studies and two case reports were identified as relevant. Lesion sites included the caudate nucleus, putamen and globus pallidus. These were associated with a spectrum of behavioural and cognitive symptoms, including abulia, poor working memory and deficits in emotional recognition. Discussion: It is often difficult to precisely map associations between cognitive, emotional or behavioural functions and particular basal ganglia substructures, due to the non-specific nature of the lesions. However, evidence from lesion studies shows that most symptoms correspond with established non-motor frontal-subcortical circuits. © 2013-IOS Press and the authors. All rights reserved.