Adaptive networks for robotics and the emergence of reward anticipatory circuits

Currently the central challenge facing evolutionary robotics is to determine how best to extend the range and complexity of behaviour supported by evolved neural systems. Implicit in the work described in this thesis is the idea that this might best be achieved through devising neural circuits (tractable to evolutionary exploration) that exhibit complementary functional characteristics. We concentrate on two problem domains; locomotion and sequence learning. For locomotion we compare the use of GasNets and other adaptive networks. For sequence learning we introduce a novel connectionist model inspired by the role of dopamine in the basal ganglia (commonly interpreted as a form of reinforcement learning). This connectionist approach relies upon a new neuron model inspired by notions of energy efficient signalling. Two reward adaptive circuit variants were investigated. These were applied respectively to two learning problems; where action sequences are required to take place in a strict order, and secondly, where action sequences are robust to intermediate arbitrary states. We conclude the thesis by proposing a formal model of functional integration, encompassing locomotion and sequence learning, extending ideas proposed by W. Ross Ashby. A general model of the adaptive replicator is presented, incoporating subsystems that are tuned to continuous variation and discrete or conditional events. Comparisons are made with Ross W. Ashby's model of ultrastability and his ideas on adaptive behaviour. This model is intended to support our assertion that, GasNets (and similar networks) and reward adaptive circuits of the type presented here, are intrinsically complementary. In conclusion we present some ideas on how the co-evolution of GasNet and reward adaptive circuits might lead us to significant improvements in the synthesis of agents capable of exhibiting complex adaptive behaviour

Engineering Transcriptional Control and Synthetic Gene Circuits in Cell Free systems

Engineering gene networks offers an opportunity to harness biological function for biotechnological and biomedical applications. In contrast to cell-based systems, cell free extracts offer a flexible and well-characterized context in which to implement predictable gene circuits. Critical to these efforts is the availability of a library of ligand sensitive gene regulatory systems. Here, I describe efforts to develop molecular tools to control gene expression and implement a negative feedback circuit in E.coli cell extracts. First, a strategy to regulate T7 RNA polymerase using DNA aptamers is detailed. I test the hypothesis that a DNA aptamer, when placed near the transcription start site, interferes with transcription in the presence of the target molecule. A DNA aptamer that binds thrombin is used as a model system for demonstrating feasibility of the approach. I show that for the hybrid T7-aptamer promoter, thrombin addition results in up to a 5-fold reduction in gene expression. I further demonstrate that gene expression be tuned by altering the position of the aptamer relative to the transcription start site. I then devised a mechanism to engineer dual regulation of T7 promoters using LacI and TetR repressor proteins. To achieve this, a LacI binding site (lacO) was positioned 92bp upstream from a T7lacO promoter, which resulted in an increased repression from T7lacO promoters presumably by a looping based mechanism. TetR binding sites were introduced into this framework to disrupt the DNA looping to create T7 promoters that respond to both LacI and TetR. I show that positioning a tetO operator between the upstream lacO and the T7lacO promoter results in relieving lacO mediated repression by TetR. Finally, a negative feedback circuit was realized using T7lacO promoters. To this end, mono-cistronic and bi-cistronic system assembly approaches for system assembly are examined leading to the realization of an inducible negative feedback circuit in cell free systems. Collectively, the tools developed in this work pave the way for expanding the library of ligands that can be used for regulating gene expression, enabling signal integration at T7 promoters and facilitating engineering of gene networks in cell free systems

Indirect impact of landslide hazards on transportation infrastructure

This thesis examines the indirect impact of natural hazards on infrastructure networks. It addresses several key themes and issues for hazard assessment, network modelling and risk assessment using the case study of landslides impacting the national road network in Scotland, United Kingdom. The research follows four distinct stages. First, a landslide susceptibility model is developed using a database of landslide occurrences, spatial data sets and logistic regression. The model outputs indicate the terrain characteristics that are associated with increased landslide potential, including critical slope angles and south westerly aspects associated with increased rates of solar irradiance and precipitation. The results identify the hillslopes and road segments that are most prone to disruption by landslides and these indicate that 40 % (1,700 / 4,300 km) of Scotland s motorways and arterial roads (i.e. strategic road network) are susceptible to landslides and this is above previous assessments. Second, a novel user-equilibrium traffic model is developed using UK Census origin-destination tables. The traffic model calculates the additional travel time and cost (i.e. indirect impacts) caused by network disruptions due to landslide events. The model is applied to calculate the impact of historic scenarios and for sets of plausible landslide events generated using the landslide susceptibility model. Impact assessments for historic scenarios are 29 to 83 % greater than previous, including £1.2 million of indirect impacts over 15 days of disruption at the A83 Rest and Be Thankful landslide October 2007. The model results indicate that the average impact of landslides is £64 k per day of disruption, and up to £130 k per day on the most critical road segments in Scotland. In addition to identifying critical road segments with both high impact and high susceptibility to landslides, the study indicates that the impact of landslides is concentrated away from urban centres to the central and north-west regions of Scotland that are heavily reliant on road and haulage-based industries such as seasonal tourism, agriculture and craft distilling. The third research element is the development of landslide initiation thresholds using weather radar data. The thresholds classify the rainfall conditions that are most commonly associated with landslide occurrence in Scotland, improving knowledge of the physical initiation processes and their likelihood. The thresholds are developed using a novel optimal-point threshold selection technique, high resolution radar and new rain variables that provide spatio-temporally normalised thresholds. The thresholds highlight the role of the 12-day antecedent hydrological condition of soils as a precursory factor in controlling the rain conditions that trigger landslides. The new results also support the observation that landslides occur more frequently in the UK during the early autumn and winter seasons when sequences or clustering of multiple cyclonic-storm systems is common in periods lasting 5 to 15 days. Fourth, the three previous elements are combined to evaluate the landslide hazard of the strategic road segments and a prototype risk assessment model is produced - a catastrophe model. The catastrophe model calculates the annual average loss and aggregated exceedance probability of losses due to the indirect impact of landslides in Scotland. Beyond application to cost-benefit analyses for landslide mitigation efforts, the catastrophe model framework is applicable to the study of other natural hazards (e.g. flooding), combinations of hazards, and other infrastructure networks

Application of Advanced Early Warning Systems with Adaptive Protection

This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers

New experimental and theoretical tools for studying protein systems with elements of structural disorder

Disordered proteins are one class of proteins which do not possess well-folded three-dimensional structures as their native conformations. Many eukaryotic proteins have been found to be fully disordered or contain certain disordered regions. Disordered proteins usually display several characteristic properties, such as increased motional freedom and the conformational heterogeneity caused by that. The elements of structural disorder are commonly involved in many important biological functions and are implicated in many diseases. Therefore, the study of disordered proteins has become one of the most important research topics in recent years. This thesis presents results from three different research projects; the common feature is that all systems being studied contain varying amount of structural disorder. Most results have been obtained based on experimental nuclear magnetic resonance (NMR) studies and molecular dynamics (MD) simulations. Both are among the most popular biophysical techniques for studying molecular dynamics. The first project investigates the relationship between domain cooperativity and residual dipolar coupling (RDC) parameters based on a series of two-domain chimera proteins with disordered linkers. Many eukaryotic proteins contain multiple domains and their biological functions are closely related to the property of domain cooperativity, which is often regulated by the linker region. Therefore it is necessary to develop suitable tools to characterize linker region properties in order to better understand biological functions of multidomain proteins. The second project is about the development of NMR pulse sequences for studying disordered proteins. Two new NMR pulse sequences, PD-CPMG and CP-HISQC, have been developed. Both experiments are well suited for studying intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs) under physiological conditions. These two experiments produce higher precision for 15N R2 rates measurement or higher sensitivity in 1H– 15N HSQC spectra respectively. Besides, they also show many advantages over most other existing experiments for studying IDPs. The last project is about protein-peptide encounter complex study based on Crk-Sos model system. The ten-residue Sos peptide serves as a minimal model for disordered proteins. Encounter complex is an important type of intermediate state formed during many protein interactions. Such complexes are usually characterized by a large amount of motional freedom and conformational heterogeneity. Therefore their properties are considerably different from tight-binding complexes which are more commonly studied. Although it is usually quite difficult to study encounter complexes using standard biophysical techniques, in this project we have successfully characterized structural and dynamic properties of Crk-Sos electrostatic encounter complex with a combination of MD simulations and experimental NMR approaches. It can be directly seen from the structural model based on MD trajectories that Sos peptide in the encounter complex remains highly dynamic, sampling large area on the surface of Crk N-SH3 domain. Such strategy can also be utilized for studying many other encounter complexes involving disordered proteins or peptide