Electrografting of poly (carbazole-co-acrylamide) onto highly oriented pyroltic graphite. A cyclovoltammetric, atomic force microscopic and ellipsometric study

The electrocopolymerization of carbazole and acrylamide on highly oriented pyrolytic graphite (HOPG) from ACN solutions via cyclovoltammetry (CV) was studied in order to evaluate the possibility to deposit uniform and thin but pinhole-free and still reactive coatings onto graphite-like substrates. The morphology of the coatings was investigated using atomic force microscopy and the coating thicknesses and optical parameters were measured using ellipsometry. It was found that under the chosen conditions thin (coating thickness hf>180 nm) and relatively smooth (root mean square surface roughness RMS<150 nm) P(Cz-co-AAm)-coatings exhibiting a uniform globuoidal morphology can be deposited onto graphite. From a certain coating thickness (hf>50 nm) no pinholes could be detected. It was found that the thickness of the deposited coatings increases almost linearly with increasing number of CV-cycles while keeping all other experimental parameters (scan rate and comonomer concentration ratio) constant. No influence of the comonomer concentration ratio on the film thickness and coating appearance could be observed, however, at quite low initial concentrations. However, the CV-scanning rate has quite a significant influence on the thickness of the deposited coatings. Higher scan rates (100 mV/s) result in thin (hf≈22 nm) coatings whereas at lower scan rates (<50 mV/s) coatings with thicknesses of approximately 50 nm were obtained. The optical coating parameters (the refractive index n and extinction coefficient k) seem to be independent of the deposition parameters and therefore averaged values of n̄=1.54±0.03 and k̄=0.08±0.03 were obtained.

Reduced metal transferrin binding in neurological diseases

By employing G75 gel-filtration chromotography, it has been demonstrated that human plasma gallium speciation (and by implication, Al speciation) is bimodal. Normally, gallium was predominantly bound to a high molecular weight fraction which was presumably transferrin. Literature reviews and experimental work throughout this thesis provided evidence to support this idea. An aluminium-transferrin species was assumed to be relatively non-toxic and a protective function for this complex has been suggested. A second, low molecular weight species of gallium was observed and its identity has been suggested to be citrate. The results of this thesis support the concept citrate was a gallium binding ligand present in the plasma, but there was another species (tentatively identified as phosphate) which bound gallium to a much greater degree than did citrate in the majority of samples studied. The consequence of a low molecular weight species of aluminium is the possibility that this leads to a more rapid, uncontrolled deposition of the metal in the brain compared to a transferrin mediated mechanism. Plasma speciation studies in Alzheimer's disease, Parkinson's disease, Down's syndrome, and neonates has revealed an altered ratio of the two gallium species found in control subjects. In all groups there was an increase in the potentially more neurotoxic low molecular weight species. These observations have led to a suggested mechanism of accumulation of metals in the brain, which is known to occur in the first three groups. Possible pathogenic mechanisms are described. The results can also offer an explanation to the reported increased sensitivity to the toxic effects of aluminium in the neonate. Speciation studies on normal plasma has shown the balance between high and low molecular weight species of gallium to be influenced by many physiological factors. There appears to be a fine equilibrium between both species which can be altered without any great difficulty. Therefore, in the diseased groups studied, it is possible that there are subtle biochemical changes within the circulatory system to affect the equilibrium which results in an increased low molecular weight species of aluminium. Furthermore, it has been demonstrated that there is a group of normal controls with no clinical signs of Alzheimer's or Parkinson's disease which have reduced transferrin binding. This indicates there is a population of healthy people who are at risk to the development of either disease.

Genetics and competing strategies in a threshold model for mail processing

Multi-agent algorithms inspired by the division of labour in social insects are applied to a problem of distributed mail retrieval in which agents must visit mail producing cities and choose between mail types under certain constraints.The efficiency (i.e. the average amount of mail retrieved per time step), and the flexibility (i.e. the capability of the agents to react to changes in the environment) are investigated both in static and dynamic environments. New rules for mail selection and specialisation are introduced and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a genetic algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation. From a more theoretical point of view, in order to avoid finite size effects, most results are obtained for large population sizes. However, we do analyse the influence of population size on the performance. Furthermore, we critically analyse the causes of efficiency loss, derive the exact dynamics of the model in the large system limit under certain conditions, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.

Agent Based Models of Competition and Collaboration

Swarm intelligence is a popular paradigm for algorithm design. Frequently drawing inspiration from natural systems, it assigns simple rules to a set of agents with the aim that, through local interactions, they collectively solve some global problem. Current variants of a popular swarm based optimization algorithm, particle swarm optimization (PSO), are investigated with a focus on premature convergence. A novel variant, dispersive PSO, is proposed to address this problem and is shown to lead to increased robustness and performance compared to current PSO algorithms. A nature inspired decentralised multi-agent algorithm is proposed to solve a constrained problem of distributed task allocation. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. New rules for specialisation are proposed and are shown to exhibit improved eciency and exibility compared to existing ones. These new rules are compared with a market based approach to agent control. The eciency (average number of tasks performed), the exibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved eciency and robustness. Evolutionary algorithms are employed, both to optimize parameters and to allow the various rules to evolve and compete. We also observe extinction and speciation. In order to interpret algorithm performance we analyse the causes of eciency loss, derive theoretical upper bounds for the eciency, as well as a complete theoretical description of a non-trivial case, and compare these with the experimental results. Motivated by this work we introduce agent "memory" (the possibility for agents to develop preferences for certain cities) and show that not only does it lead to emergent cooperation between agents, but also to a signicant increase in efficiency.