An efficient scheme for the evaluation of coding performance of high speed links incorporating joint error behaviour based on Monte Carlo Method

While channel coding is a standard method of improving a system’s energy efficiency in digital communications, its practice does not extend to high-speed links. Increasing demands in network speeds are placing a large burden on the energy efficiency of high-speed links and render the benefit of channel coding for these systems a timely subject. The low error rates of interest and the presence of residual intersymbol interference (ISI) caused by hardware constraints impede the analysis and simulation of coded high-speed links. Focusing on the residual ISI and combined noise as the dominant error mechanisms, this paper analyses error correlation through concepts of error region, channel signature, and correlation distance. This framework provides a deeper insight into joint error behaviours in high-speed links, extends the range of statistical simulation for coded high-speed links, and provides a case against the use of biased Monte Carlo methods in this setting

A Filter for Visual Tracking Based on a Stochastic Model for Driver Behaviour

A driver controls a car by turning the steering wheel or by pressing on the accelerator or the brake. These actions are modelled by Gaussian processes, leading to a stochastic model for the motion of the car. The stochastic model is the basis of a new filter for tracking and predicting the motion of the car, using measurements obtained by fitting a rigid 3D model to a monocular sequence of video images. Experiments show that the filter easily outperforms traditional filters.

Behaviour-based authentication in the built enviromnent

This paper proposes a novel method of authentication of users in secure buildings. The main objective is to investigate whether user actions in the built environment can produce consistent behavioural signatures upon which a building intrusion detection system could be based. In the process three behavioural expressions were discovered: time-invariant, co-dependent and idiosyncratic.

Effective elements of cognitive behaviour therapy for psychosis: results of a novel type of subgroup analysis based on principal stratification

Background. Meta-analyses show that cognitive behaviour therapy for psychosis (CBT-P) improves distressing positive symptoms. However, it is a complex intervention involving a range of techniques. No previous study has assessed the delivery of the different elements of treatment and their effect on outcome. Our aim was to assess the differential effect of type of treatment delivered on the effectiveness of CBT-P, using novel statistical methodology. Method. The Psychological Prevention of Relapse in Psychosis (PRP) trial was a multi-centre randomized controlled trial (RCT) that compared CBT-P with treatment as usual (TAU). Therapy was manualized, and detailed evaluations of therapy delivery and client engagement were made. Follow-up assessments were made at 12 and 24 months. In a planned analysis, we applied principal stratification (involving structural equation modelling with finite mixtures) to estimate intention-to-treat (ITT) effects for subgroups of participants, defined by qualitative and quantitative differences in receipt of therapy, while maintaining the constraints of randomization. Results. Consistent delivery of full therapy, including specific cognitive and behavioural techniques, was associated with clinically and statistically significant increases in months in remission, and decreases in psychotic and affective symptoms. Delivery of partial therapy involving engagement and assessment was not effective. Conclusions. Our analyses suggest that CBT-P is of significant benefit on multiple outcomes to patients able to engage in the full range of therapy procedures. The novel statistical methods illustrated in this report have general application to the evaluation of heterogeneity in the effects of treatment.

Synthesis and phase behaviour of a homologous series of polymethacrylate-based side-chain liquid crystal polymers

The homologous series of side chain liquid crystal polymers, the poly[x-(4-methoxyazobenzene- 40-oxy)alkyl methacrylate]s, has been prepared in which the length of the flexible alkyl spacer has been varied from 3 to 11 methylene units. All the polymers exhibit liquid crystalline behaviour. The propyl and butyl members show exclusively nematic behaviour. The pentyl, hexyl, octyl and decyl members show a nematic and a smectic A phase while the heptyl, nonyl and undecyl homologues exhibit only a smectic A phase. The smectic A phase has been studied using X-ray diffraction and assigned as a smectic A1 phase in which the side chains are fully overlapped and the backbones are confined to lie between the smectic layers. For the nonyl member an incommensurate smectic phase is observed. The dependence of the transition temperatures on the length of the flexible spacer is understood in terms of the average shapes of the side chains.

Structural and morphological studies of the dipeptide based L-Pro-L-Val organocatalytic gels and their rheological behaviour

Organocatalytic gels based on the dipeptide sequence L-Pro-L-Val have been studied by two different FTIR techniques. This suggests a different arrangement of the gelator molecules in the self-assembled fibers depending on the organic solvent employed. In acetonitrile and nitromethane the structure of the supramolecular aggregates is similar and provides similar catalytic properties (supramolecularenhancement of basicity). In contrast, the self-assembled fibers obtained in toluene clearly presented a different molecular arrangement consistent with its different catalytic behaviour (enamine-based catalysis). In addition these gels have been studied by microscopy and rheology.

Incorporating technology buying behaviour into UK-based long term domestic stock energy models to provide improved policy analysis

The UK has a target for an 80% reduction in CO2 emissions by 2050 from a 1990 base. Domestic energy use accounts for around 30% of total emissions. This paper presents a comprehensive review of existing models and modelling techniques and indicates how they might be improved by considering individual buying behaviour. Macro (top-down) and micro (bottom-up) models have been reviewed and analysed. It is found that bottom-up models can project technology diffusion due to their higher resolution. The weakness of existing bottom-up models at capturing individual green technology buying behaviour has been identified. Consequently, Markov chains, neural networks and agent-based modelling are proposed as possible methods to incorporate buying behaviour within a domestic energy forecast model. Among the three methods, agent-based models are found to be the most promising, although a successful agent approach requires large amounts of input data. A prototype agent-based model has been developed and tested, which demonstrates the feasibility of an agent approach. This model shows that an agent-based approach is promising as a means to predict the effectiveness of various policy measures.

The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model

A process-based fire regime model (SPITFIRE) has been developed, coupled with ecosystem dynamics in the LPJ Dynamic Global Vegetation Model, and used to explore fire regimes and the current impact of fire on the terrestrial carbon cycle and associated emissions of trace atmospheric constituents. The model estimates an average release of 2.24 Pg C yr−1 as CO2 from biomass burning during the 1980s and 1990s. Comparison with observed active fire counts shows that the model reproduces where fire occurs and can mimic broad geographic patterns in the peak fire season, although the predicted peak is 1–2 months late in some regions. Modelled fire season length is generally overestimated by about one month, but shows a realistic pattern of differences among biomes. Comparisons with remotely sensed burnt-area products indicate that the model reproduces broad geographic patterns of annual fractional burnt area over most regions, including the boreal forest, although interannual variability in the boreal zone is underestimated.

Norm-based behaviour modification in BDI agents

While there has been much work on developing frameworks and models of norms and normative systems, consideration of the impact of norms on the practical reasoning of agents has attracted less attention. The problem is that traditional agent architectures and their associated languages provide no mechanism to adapt an agent at runtime to norms constraining their behaviour. This is important because if BDI-type agents are to operate in open environments, they need to adapt to changes in the norms that regulate such environments. In response, in this paper we provide a technique to extend BDI agent languages, by enabling them to enact behaviour modification at runtime in response to newly accepted norms. Our solution consists of creating new plans to comply with obligations and suppressing the execution of existing plans that violate prohibitions. We demonstrate the viability of our approach through an implementation of our solution in the AgentSpeak(L) language.

Electrochemical and spectroscopic characterization of screen-printed gold-based electrodes modified with self-assembled monolayers and Tc85 protein

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Disposable immunosensor for human cardiac troponin T based on streptavidin-microsphere modified screen-printed electrode

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

New label free CA125 detection based on gold nanostructured screen-printed electrode

This paper describes the optimisation and the analytical performances of a label-free impedimetric immunosensor for the detection of tumour marker CA125 based on gold nanoparticles modified screen-printed graphite electrode. Experimental conditions of each step for the developed immunosensor were studied and optimised. The immunosensor response varied linearly (r2 = 0.996) with antigen concentration between 0 and 100 U/mL. The estimated detection limit was 6.7 U/mL. The electrochemical immunosensor allowed unambiguous identification of CA125, while no significant non-specific signal was detected in the case of all negative controls. The analytical usefulness of the impedimetric immunosensor was finally demonstrated analysing serum samples. © 2012 Elsevier B.V. All rights reserved.