Robust control of nonlinear stochastic systems by modelling conditional distributions of control signals

We introduce a novel inversion-based neuro-controller for solving control problems involving uncertain nonlinear systems that could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. In this work a novel robust inverse control approach is obtained based on importance sampling from these distributions. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The performance of the new algorithm is illustrated through simulations with example systems.

Conditional distribution modeling for estimating and exploiting uncertainty in control systems

This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non Gaussian distributions of control signal as well as processes with hysteresis.

Targeted delivery of a novel group of site-directed transglutaminase inhibitors to the liver using liposomes:a new approach for the potential treatment of liver fibrosis

Liver fibrosis and its end-stage disease cirrhosis are a main cause of mortality and morbidity worldwide. Thus far, there is no efficient pharmaceutical intervention for the treatment of liver fibrosis. Liver fibrosis is characterized by excessive accumulation of the extracellular matrix (ECM) proteins. Transglutaminase (TG)-mediated covalent cross-linking has been implicated in the stabilization and accumulation of ECM in a number of fibrotic diseases. Thus, the use of tissue TG2 inhibitors has potential in the treatment of liver fibrosis. Recently, we introduced a novel group of site-directed irreversible specific inhibitors of TGs. Here, we describe the development of a liposome-based drug-delivery system for the site-specific delivery of these TG inhibitors into the liver. By using anionic or neutral-based DSPC liposomes, the TG inhibitor can be successfully incorporated into these liposomes and delivered specifically to the liver. Liposomes can therefore be used as a potential carrier system for site-specific delivery of the TG2 inhibitors into the liver, opening up a potential new avenue for the treatment of liver fibrosis and its end-stage disease cirrhosis.

Using monthly returns to model conditional heteroscedasticity

This empirical study examines the extent of non-linearity in a multivariate model of monthly financial series. To capture the conditional heteroscedasticity in the series, both the GARCH(1,1) and GARCH(1,1)-in-mean models are employed. The conditional errors are assumed to follow the normal and Student-t distributions. The non-linearity in the residuals of a standard OLS regression are also assessed. It is found that the OLS residuals as well as conditional errors of the GARCH models exhibit strong non-linearity. Under the Student density, the extent of non-linearity in the GARCH conditional errors was generally similar to those of the standard OLS. The GARCH-in-mean regression generated the worse out-of-sample forecasts.

Conditional volatility and firm size:an empirical analysis of UK equity portfolios

The techniques and insights from two distinct areas of financial economic modelling are combined to provide evidence of the influence of firm size on the volatility of stock portfolio returns. Portfolio returns are characterized by positive serial correlation induced by the varying levels of non-synchronous trading among the component stocks. This serial correlation is greatest for portfolios of small firms. The conditional volatility of stock returns has been shown to be well represented by the GARCH family of statistical processes. Using a GARCH model of the variance of capitalization-based portfolio returns, conditioned on the autocorrelation structure in the conditional mean, striking differences related to firm size are uncovered.

Incorporation of N-heterocyclic cations into proteins with a highly directed chemical modification

N-Heterocyclic cations are incorporated into proteins using 5-(2-bromoethyl)phenanthridinium bromide, which selectively reacts with either cysteine or lysine residues, resulting in ethylphenanthridinium (Phen) or highly stable cyclised dihydro-imidazo-phenanthridinium (DIP) adducts respectively; these modifications have been found to manipulate the observed structure of lysozyme and bovine serum albumin by AFM.

Typical case behaviour of spin systems in random graph and composite ensembles

This thesis includes analysis of disordered spin ensembles corresponding to Exact Cover, a multi-access channel problem, and composite models combining sparse and dense interactions. The satisfiability problem in Exact Cover is addressed using a statistical analysis of a simple branch and bound algorithm. The algorithm can be formulated in the large system limit as a branching process, for which critical properties can be analysed. Far from the critical point a set of differential equations may be used to model the process, and these are solved by numerical integration and exact bounding methods. The multi-access channel problem is formulated as an equilibrium statistical physics problem for the case of bit transmission on a channel with power control and synchronisation. A sparse code division multiple access method is considered and the optimal detection properties are examined in typical case by use of the replica method, and compared to detection performance achieved by interactive decoding methods. These codes are found to have phenomena closely resembling the well-understood dense codes. The composite model is introduced as an abstraction of canonical sparse and dense disordered spin models. The model includes couplings due to both dense and sparse topologies simultaneously. The new type of codes are shown to outperform sparse and dense codes in some regimes both in optimal performance, and in performance achieved by iterative detection methods in finite systems.

The use of site-directed mutagenesis to study GPCRs

G protein coupled receptors (GPCRs) are highly flexible and dynamic proteins, which are able to interact with diverse ligands, effectors, and regulatory proteins. Site-directed mutagenesis (SDM) is a powerful tool for providing insight into how these proteins actually work, both in its own right and when used in conjunction with information provided by other techniques such as crystallography or molecular modelling. Mutagenesis has been used to identify and characterise a myriad of functionally important residues, motifs and domains within the GPCR architecture, and to identify aspects of similarity and differences between the major families of GPCRs. This chapter presents the necessary information for undertaking informative SDM of these proteins. Whilst this is relevant to protein structure/function studies in -general, specific pitfalls and protocols suited to investigating GPCRs in particular will be highlighted.

In situ studies of phase separation and crystallization directed by Marangoni instabilities during spin-coating

Results of a pioneering study are presented in which for the first time, crystallization, phase separation and Marangoni instabilities occurring during the spin-coating of polymer blends are directly visualized, in real-space and real-time. The results provide exciting new insights into the process of self-assembly, taking place during spin-coating, paving the way for the rational design of processing conditions, to allow desired morphologies to be obtained. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A socio-economic approach to online vision graph generation and handover in distributed smart camera networks

In this paper we propose an approach based on self-interested autonomous cameras, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to grow the vision graph during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online which permits the addition and removal cameras to the network during runtime and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multi-camera calibration can be avoided. © 2011 IEEE.

Deficient inhibition of return in subclinical OCD only when attention is directed to the threatening aspects of a stimulus

Background - Inhibition of return (IOR) is thought to reflect inhibition of previously attended but irrelevant stimuli. Deficient IOR would increase the likelihood of revisiting previously searched locations or objects, thus leading to unproductive perseverations. Method - Therefore, using a novel IOR task, we investigated whether high scoring checkers attentional biases to threat would result in dysfunctional inhibitory functioning compared to low checkers. In two tasks, we compared 53 subclinical high and 49 low checkers regarding IOR effects for stimuli that were concordant with the concerns of high but not of low checkers (electrical kitchen appliances: e.g., toaster, kettle). The difference between the two tasks was the cueing procedure. In one task, an appliance was switched “ON” and “OFF” as an unpredictive cue, drawing attention to the functionality of the stimulus. Results - In this task, IOR was specifically attenuated in high checkers. In the other task, however, the cue was more abstract in form of a yellow outline that appeared around one of two appliances. Although the appliance was either “ON” or “OFF,” this did not seem to matter and high checkers revealed a typical IOR pattern similar to low checkers. Conclusions - We conclude that IOR mechanisms might not be generally deficient in high checkers; rather only when attention is drawn to the threatening aspects of ecologically valid stimuli, then disengagement of attention is deficient in high checkers. We make suggestions on how our task-specific findings may inform cognitive interventions that target attentional control in the treatment of checking/obsessive–compulsive disorder.

Investigating evoked and induced electroencephalogram activity in task-related alpha power increases during an internally directed attention task

This study sought to explore whether the so-called 'paradoxical' task-related increases in the alpha bandwidth of the human electroencephalogram result from increases in evoked (phase locked), as opposed to induced (non-phase locked), activity. The electroencephalograms of 18 participants were recorded while they engaged in both auditory sensory-intake tasks (listening to randomly generated 'tunes') and internally directed attention tasks (imagining the same randomly generated tunes) matched for auditory input. Measures of evoked (phase locked) and induced (non-phase locked) activity were compared between tasks. Increases in induced alpha power were found during internal attention. No experimental effects were observed for evoked activity. These results are not entirely consistent with proposals that 'paradoxical' alpha indexes the evoked inhibition of task irrelevant processing.

Conditional osmotic stress in yeast:a system to study transport through aquaglyceroporins and osmostress signaling

The accumulation and transport of solutes are hallmarks of osmoadaptation. In this study we have employed the inability of the Saccharomyces cerevisiae gpd1Δ gpd2Δ mutant both to produce glycerol and to adapt to high osmolarity to study solute transport through aquaglyceroporins and the control of osmostress-induced signaling. High levels of different polyols, including glycerol, inhibited growth of the gpd1Δ gpd2Δ mutant. This growth inhibition was suppressed by expression of the hyperactive allele Fps1-AΔ of the osmogated yeast aquaglyceroporin, Fps1. The degree of suppression correlated with the relative rate of transport of the different polyols tested. Transport studies in secretory vesicles confirmed that Fps1-Δ1 transports polyols at increased rates compared with wild type Fps1. Importantly, wild type Fps1 and Fps1-Δ1 showed similarly low permeability for water. The growth defect on polyols in the gpd1Δ gpd2Δ mutant was also suppressed by expression of a heterologous aquaglyceroporin, rat AQP9. We surmised that this suppression was due to polyol influx, causing the cells to passively adapt to the stress. Indeed, when aquaglyceroporin-expressing gpd1Δ gpd2Δ mutants were treated with glycerol, xylitol, or sorbitol, the osmosensing HOG pathway was activated, and the period of activation correlated with the apparent rate of polyol uptake. This observation supports the notion that deactivation of the HOG pathway is closely coupled to osmotic adaptation. Taken together, our "conditional" osmotic stress system facilitates studies on aquaglyceroporin function and reveals features of the osmosensing and signaling system. © 2005 by The American Society for Biochemistry and Molecular Biology, Inc.