The EU's 'transnational power over' Central Asia:Developing and applying a structurally integrative approach to the study of the EU's power over Central Asia

This thesis challenges the consensual scholarly expectation of low EU impact in Central Asia. In particular, it claims that by focusing predominantly on narrow, micro-level factors, the prevailing theoretical perspectives risk overlooking less obvious aspects of the EU?s power, including structural aspects, and thus tend to underestimate the EU?s leverage in the region. Therefore, the thesis argues that a more structurally integrative and holistic approach is needed to understand the EU?s power in the region. In responding to this need, the thesis introduces a conceptual tool, which it terms „transnational power over? (TNPO). Inspired by debates in IPE, in particular new realist and critical IPE perspectives, and combining these views with insights from neorealist, neo-institutionalist and constructivist approaches to EU external relations, the concept of TNPO is an analytically eclectic notion, which helps to assess the degree to which, in today?s globalised and interdependent world, the EU?s power over third countries derives from its control over a combination of material, institutional and ideational structures, making it difficult for the EU?s partners to resist the EU?s initiatives or to reject its offers. In order to trace and assess the mechanisms of EU impact across these three structures, the thesis constructs a toolbox, which centres on four analytical distinctions: (i) EU-driven versus domestically driven mechanisms, (ii) mechanisms based on rationalist logics of action versus mechanisms following constructivist logics of action, (iii) agent-based versus purely structural mechanisms of TNPO, and (iv) transnational and intergovernmental mechanisms of EU impact. Using qualitative research methodology, the thesis then applies the conceptual model to the case of EU-Central Asia. It finds that the EU?s power over Central Asia effectively derives from its control over a combination of material, institutional and ideational structures, including its position as a leader in trade and investment in the region, its (geo)strategic and security-related capabilities vis-à-vis Central Asia, as well as the relatively dense level of institutionalisation of its relations with the five countries and the positive image of the EU in Central Asia as a more neutral actor.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

A simple remote sensing based information system for monitoring sites of conservation importance

Monitoring is essential for conservation of sites, but capacity to undertake it in the field is often limited. Data collected by remote sensing has been identified as a partial solution to this problem, and is becoming a feasible option, since increasing quantities of satellite data in particular are becoming available to conservationists. When suitably classified, satellite imagery can be used to delineate land cover types such as forest, and to identify any changes over time. However, the conservation community lacks (a) a simple tool appropriate to the needs for monitoring change in all types of land cover (e.g. not just forest), and (b) an easily accessible information system which allows for simple land cover change analysis and data sharing to reduce duplication of effort. To meet these needs, we developed a web-based information system which allows users to assess land cover dynamics in and around protected areas (or other sites of conservation importance) from multi-temporal medium resolution satellite imagery. The system is based around an open access toolbox that pre-processes and classifies Landsat-type imagery, and then allows users to interactively verify the classification. These data are then open for others to utilize through the online information system. We first explain imagery processing and data accessibility features, and then demonstrate the toolbox and the value of user verification using a case study on Nakuru National Park, Kenya. Monitoring and detection of disturbances can support implementation of effective protection, assist the work of park managers and conservation scientists, and thus contribute to conservation planning, priority assessment and potentially to meeting monitoring needs for Aichi target 11.

Physiologically based pharmacokinetic modelling in drug delivery

The application of pharmacokinetic modelling within the drug development field essentially allows one to develop a quantitative description of the temporal behaviour of a compound of interest at a tissue/organ level, by identifying and defining relationships between a dose of a drug and dependent variables. In order to understand and characterise the pharmacokinetics of a drug, it is often helpful to employ pharmacokinetic modelling using empirical or mechanistic approaches. Pharmacokinetic models can be developed within mathematical and statistical commercial software such as MATLAB using traditional mathematical and computation coding, or by using the Simbiology Toolbox available within MATLAB for a graphical user interface approach to developing pharmacokinetic (PBPK) models. For formulations dosed orally, a prerequisite for clinical activity is the entry of the drug into the systemic circulation.