Prediction- and simulation-error based perceptron training: Solution space analysis and a novel combined training scheme

Previous papers have noted the difficulty in obtaining neural models which are stable under simulation when trained using prediction-error-based methods. Here the differences between series-parallel and parallel identification structures for training neural models are investigated. The effect of the error surface shape on training convergence and simulation performance is analysed using a standard algorithm operating in both training modes. A combined series-parallel/parallel training scheme is proposed, aiming to provide a more effective means of obtaining accurate neural simulation models. Simulation examples show the combined scheme is advantageous in circumstances where the solution space is known or suspected to be complex. (c) 2006 Elsevier B.V. All rights reserved.

Improving the robustness of the iterative solver in state-space modelling of guitar distortion circuitry

Iterative solvers are required for the discrete-time simulation of nonlinear behaviour in analogue distortion circuits. Unfortunately,these methods are often computationally too expensive for realtime simulation. Two methods are presented which attempt to reduce the expense of iterative solvers. This is achieved by applying information that is derived from the specific form of the non linearity.The approach is first explained through the modelling of an asymmetrical diode clipper, and further exemplified by application to the Dallas Rangemaster Treble Booster guitar pedal, which provides an initial perspective of the performance on systems with multiple nonlinearities.

Dynamic Multivariate Statistical Process Control using Subspace Identification

This paper points out a serious flaw in dynamic multivariate statistical process control (MSPC). The principal component analysis of a linear time series model that is employed to capture auto- and cross-correlation in recorded data may produce a considerable number of variables to be analysed. To give a dynamic representation of the data (based on variable correlation) and circumvent the production of a large time-series structure, a linear state space model is used here instead. The paper demonstrates that incorporating a state space model, the number of variables to be analysed dynamically can be considerably reduced, compared to conventional dynamic MSPC techniques.

Double-electron above threshold ionization of helium

We present calculations of intense-field multiphoton ionization processes in helium at XUV wavelengths. The calculations are obtained from a full-dimensional integration of the two-electron time-dependent Schrödinger equation. A momentum-space analysis of the ionizing two-electron wavepacket reveals the existence of double-electron above threshold ionization (DATI). In momentum-space two distinct forms of DATI are resolved, namely non-sequential and sequential. In non-sequential DATI correlated electrons resonantly absorb and share energy in integer units of Ïlaser.

Identification of dynamic systems under closed-loop control

This paper introduces a novel modelling framework for identifying dynamic models of systems that are under feedback control. These models are identified under closed-loop conditions and produce a joint representation that includes both the plant and controller models in state space form. The joint plant/controller model is identified using subspace model identification (SMI), which is followed by the separation of the plant model from the identified one. Compared to previous research, this work (i) proposes a new modelling framework for identifying closed-loop systems, (ii) introduces a generic structure to represent the controller and (iii) explains how that the new framework gives rise to a simplified determination of the plant models. In contrast, the use of the conventional modelling approach renders the separation of the plant model a difficult task. The benefits of using the new model method are demonstrated using a number of application studies.

A hierarchical physical model-based approach to predictive control of a thermal power plant for efficient plant-wide disturbance rejection

Extending the work presented in Prasad et al. (IEEE Proceedings on Control Theory and Applications, 147, 523-37, 2000), this paper reports a hierarchical nonlinear physical model-based control strategy to account for the problems arising due to complex dynamics of drum level and governor valve, and demonstrates its effectiveness in plant-wide disturbance handling. The strategy incorporates a two-level control structure consisting of lower-level conventional PI regulators and a higher-level nonlinear physical model predictive controller (NPMPC) for mainly set-point manoeuvring. The lower-level PI loops help stabilise the unstable drum-boiler dynamics and allow faster governor valve action for power and grid-frequency regulation. The higher-level NPMPC provides an optimal load demand (or set-point) transition by effective handling of plant-wide interactions and system disturbances. The strategy has been tested in a simulation of a 200-MW oil-fired power plant at Ballylumford in Northern Ireland. A novel approach is devized to test the disturbance rejection capability in severe operating conditions. Low frequency disturbances were created by making random changes in radiation heat flow on the boiler-side, while condenser vacuum was fluctuating in a random fashion on the turbine side. In order to simulate high-frequency disturbances, pulse-type load disturbances were made to strike at instants which are not an integral multiple of the NPMPC sampling period. Impressive results have been obtained during both types of system disturbances and extremely high rates of load changes, right across the operating range, These results compared favourably with those from a conventional state-space generalized predictive control (GPC) method designed under similar conditions.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

From Rights to Compassion: The D Case and Contemporary Abortion Politics

This chapter is concerned with exploring the dynamics of contemporary debate on women’s reproductive choices and rights in the somewhat transformed social, political and economic context of the Republic of Ireland. News coverage of the events of April and May 2007 provide the focus of attention, as the case of ‘D’, a 17 year old in the temporary care of the state, seeking to terminate her pregnancy after a diagnosis of severe foetal abnormality, became yet again a focus of public debate on abortion access within the state. The analysis explores how the issues this case raised were framed in the public domain, in order to consider the shifting moral grammar shaping the debate. The paper explores the ways in which this case illustrates the ongoing tensions between changing characterisations of Irishness, and the social dynamics of access to reproductive rights, particularly for national minors in the care of the state.

Six ways to leave unemployment

This paper uses a unique Portuguese dataset to examine the effect of access to unemployment benefits (UBs) and their maximum potential duration on escape rates from unemployment. In examining the time profile of transitions out of unemployment, the principal contributions of the paper are twofold. First, it provides a detailed state space of potential outcomes: open-ended employment, fixed-term contracts, part-time work, government-provided jobs, self employment, and labour force withdrawal. Second, it is able to exploit major exogenous discontinuities in the maximum duration of unemployment benefits to identify disincentive effects. While confirming strong disincentive effects, it is shown that use of an aggregate hazard function regression model compounds very different and even contradictory effects of the determinants of unemployment.

Double-Electron Above-Threshold Ionization Resonances as Interference Phenomena

We report calculations of double ionization energy spectra and momentum distributions of laser-driven helium due to few-cycle pulses of wavelength 195 nm. The results are obtained from full-dimensional numerical integration of the two electron time-dependent Schr¨odinger equation. A momentum-space analysis of doubly ionizing wavepackets shows that the concentric-ring structure of above-threshold double ionization, together with the associated structure of peaks in the total kinetic energy spectrum, may be attributed to wavepacket interference effects, where at least two doubly-ionizing wavepackets from different recollision events populate the same spatial hemisphere.

Role of environmental correlations in the non-Markovian dynamics of a spin system

We study the dynamics of a chain of interacting quantum particles affected by an individual or collective environment(s), focusing on the role played by the environmental quantum correlations over the evolution of the chain. The presence of entanglement in the state of the environment magnifies the non-Markovian nature of the chain's dynamics, giving rise to structures in figures of merit such as spin entanglement and purity that are not observed under a separable environmental state. Our analysis can be relevant to problems tackling the open-system dynamics of biological complexes of strong current interest.

Exploiting spatio-temporal constraints for robust 2D pose tracking

We present a Spatio-temporal 2D Models Framework (STMF) for 2D-Pose tracking. Space and time are discretized and a mixture of probabilistic "local models" is learnt associating 2D Shapes and 2D Stick Figures. Those spatio-temporal models generalize well for a particular viewpoint and state of the tracked action but some spatio-temporal discontinuities can appear along a sequence, as a direct consequence of the discretization. To overcome the problem, we propose to apply a Rao-Blackwellized Particle Filter (RBPF) in the 2D-Pose eigenspace, thus interpolating unseen data between view-based clusters. The fitness to the images of the predicted 2D-Poses is evaluated combining our STMF with spatio-temporal constraints. A robust, fast and smooth human motion tracker is obtained by tracking only the few most important dimensions of the state space and by refining deterministically with our STMF.

Structural and kinetic characterization of the LPS biosynthetic enzyme D-alpha,beta-D-heptose-1,7-bisphosphate phosphatase (GmhB) from Escherichia coli

Lipopolysaccharide is a major component of the outer membrane of gram-negative bacteria and provides a permeability barrier to many commonly used antibiotics. ADP-heptose residues are an integral part of the LPS inner core, and mutants deficient in heptose biosynthesis demonstrate increased membrane permeability. The heptose biosynthesis pathway involves phosphorylation and dephosphorylation steps not found in other pathways for the synthesis of nucleotide sugar precursors. Consequently, the heptose biosynthetic pathway has been marked as a novel target for antibiotic adjuvants, which are compounds that facilitate and potentiate antibiotic activity. D-alpha,beta-D-heptose-1,7-bisphosphate phosphatase (GmhB) catalyzes the third essential step of LPS heptose biosynthesis. This study describes the first crystal structure of GmhB and enzymatic analysis of the protein. Structure-guided mutations followed by steady state kinetic analysis, together with established precedent for HAD phosphatases, suggest that GmhB functions through a phosphoaspartate intermediate. This study provides insight into the structure-function relationship of GmhB, a new target for combatting gram-negative bacterial infection.

Burkholderia cenocepacia C5424 produces a pigment with antioxidant properties using a homogentisate intermediate

Burkholderia cenocepacia is a gram-negative opportunistic pathogen that belongs to the Burkholderia cepacia complex. B. cenocepacia can survive intracellularly within phagocytic cells, and some epidemic strains produce a brown melanin-like pigment that can scavenge free radicals, resulting in the attenuation of the host cell oxidative burst. In this work, we demonstrate that the brown pigment produced by B. cenocepacia C5424 is synthesized from a homogentisate (HGA) precursor. The disruption of BCAL0207 (hppD) by insertional inactivation resulted in loss of pigmentation. Steady-state kinetic analysis of the BCAL0207 gene product demonstrated that it has 4-hydroxyphenylpyruvic acid dioxygenase (HppD) activity. Pigmentation could be restored by complementation providing hppD in trans. The hppD mutant was resistant to paraquat challenge but sensitive to H2O2 and to extracellularly generated superoxide anions. Infection experiments in RAW 264.7 murine macrophages showed that the nonpigmented bacteria colocalized in a dextran-positive vacuole, suggesting that they are being trafficked to the lysosome. In contrast, the wild-type strain did not localize with dextran. Colocalization of the nonpigmented strain with dextran was reduced in the presence of the NADPH oxidase inhibitor diphenyleneiodonium, and also the inducible nitric oxide inhibitor aminoguanidine. Together, these observations suggest that the brown pigment produced by B. cenocepacia C5424 is a pyomelanin synthesized from an HGA intermediate that is capable of protecting the organism from in vitro and in vivo sources of oxidative stress.