This research investigated the ethical and legal issues that impact on the urgent implementation of Nurse Initiated and Managed Anti-Retroviral Treatment (NIMART) in South Africa, which is part of the task-shifting strategy recommended by the World Health Organization (WHO) to deal with the human resource shortage that has negatively impacted access to Anti-Retroviral Treatment (ART) in developing countries (WHO;2006). The objectives were to review and analyse the existing legal framework and provisions for NIMART in South Africa; and to identify ethical issues and implications of NIMART within the current legal framework. It analysed the legal issues that impact on the implementation of NIMART within the public health service in South Africa, as well as the ethical basis and implications of NIMART on the practice of nurses in the scale-up of Anti-Retroviral Treatment in Primary Health Care (PHC). A comparative analysis was done with case studies of task-shifting in other developing countries and evidence-based recommendations for an enabling and long-term sustainable ethico-legal approach to task-shifting were established. The research concluded that despite the existing legal framework for NIMART in South Africa being firmly founded in the Constitution and further enabled by health policy, challenges exist in implementation of certain critical aspects of the enabling legislation relating to nurse training and accreditation required for full authorization to practice NIMART and that these technical challenges if not attended to could threaten the long-term sustainability of NIMART.

MPH, Faculty of Health Sciences, University of the Witwatersrand / Background: The increase use of highly active antiretroviral therapy (HAART) among patients with HIV infection and AIDS has led to increasing reports of metabolic abnormalities such as diabetes mellitus, hypertension, dyslipidaemia and obesity. Therefore, it is important to explore the burden of these diseases among HIV infected patients. Objectives: To determine the burden of metabolic diseases (hypertension, diabetes, obesity and dyslipidaemia) in patients attending HIV clinic at the Charlotte Maxeke Johannesburg Academic Hospital (JHBH). Methodology: It was a cross-sectional study. The study population included patients attending JHBH HIV clinic and on HAART for more than one year. A sample size of 304 patients, including 237 females and 67 males partook in this study. Anthropometric measurements were taken from patients and blood samples of these patients were sent to laboratory for lipograms, HbA1c, random glucose, CD4 lymphocytes counts as well as HIV viral load testing. The data was analysed with standard statistical software Epi-info version 6.0. Both descriptive and analytical statistics was used. Results: The prevalence of metabolic syndrome according to the IDF was 20.4 %; obesity (BMI 30 kg/m2) was 16.8% and patients that were overweight (BMI > 25 kg/m2 and BMI < 29.9 kg/m2) was 28.6%; hypercholesterolemia (TC 5.0 mmol/l) = 35.5%; HDL< 1.29 mmol\L in females was 58% and HDL <1.04 mmol/l in males was 36%; elevated triglycerides 1.7 mmol/l was 30% and only 16% was classified as being hypertensive (BP 140/90 mmHg and / or on Hypertensive medication). The majority of the patients (86.2%) had a CD4 lymphocyte count 200 X 106 cells/l and 84% of patients had less than detectable limits for viral loads (VL< 40 copies / μl), which has been reported as optimum levels for metabolic diseases in HAART recipients. Conclusion: These results clearly indicate that there is a growing burden of metabolic diseases among HIV patients on HAART attending the Johannesburg hospital HIV clinic. The current study also indicates that the metabolic disturbances are more frequent in women than in men, except for hypertension.

En kvalitativ studie har gjorts där personer med en högre känslighet än genomsnittetintervjuats. Fokus för studien har varit att undersöka hur dessa så kallat högkänsliga individer möter de krav och utmaningar som arbetslivet ställer, samt hur de kan använda sin högkänslighet som ett verktyg i sitt arbete. Syftet med studien var att få en djupare förståelse för, samt öka medvetenheten kring egenskapen högkänslighet och hur den kan påverka individen i arbetslivet.Vi var även intresserade av hur självbilden hos dessa individer ser - och har sett ut.Detta ville vi göra genom att gå ut och möta människor som har egenskapen och sedan skildra deras berättelser. Tematisk analys användes för att behandla data. Undersökningens resultat visade att högkänslighet många gånger är en tillgång i yrket, samtidigt som det kan vara svårtför högkänsliga att hitta rätt i arbetslivet. Genom rätt resurser och en ökad medvetenhet kring egenskapen, skulle högkänsliga ges större möjligheter att nå framgång och bidra med sin kompetens. / Program: Organisations- och personalutvecklare i samhället

Dans cette thèse on étudie quelques modèles macroscopiques pour des milieux conducteurs ou élastiques fortement hétérogènes et anisotropes obtenus par homogénéisation. Nous considérons le cas de l’homogénéisation périodique. En particulier pour le système de l’élasticité linéarisée modélisant les petites déformations d’un matériau fibré, nous étudions l’effet de l’anisotropie du matériau sur le modèle macroscopique et nous montrons que sous l’effet conjugué des conditions aux limites et de l’anisotropie des fibres, le système modélisant les déplacements à l’échelle macroscopique fait intervenir des termes non standard. Nous considérons plusieurs scalings et deux situations géométriques : dans la première le rayon des fibres cylindriques est du même ordre de grandeur que la taille de la période du milieu et dans la seconde la rayon est petit devant la période. Les résultats obtenus dans les deux cas, indépendants d’hypothèses de symétrie sur le matériau, permettent de retrouver les résultats déjà connus dans le cas de matériaux isotropes. / In this thesis we study some macroscopic models for drivers or elastic media highly heterogeneous and anisotropic obtained by homogenization. We consider the case of periodic homogenization. In particular the system of linearized elasticity modeling small deformations of a fiber material, we study the effect of material anisotropy on the macroscopic model and show that the combined effect of the boundary conditions and the anisotropy of the fiber system modeling movement at the macroscopic scale involves non-standard terms. We consider several scalings and two geometric situations: in the first radius of cylindrical fibers is of the same order of magnitude as the size of the middle period and in the second the radius is small compared to the period. The results obtained in both cases, independent of symmetry assumptions on the material used to find the results already known in the case of isotropic materials.

Following several terrorist attacks that have occurred during this decade, there is an urgent need to develop new technologies for the detection of highly energetic materials that can represent an explosive hazard. In an effort to contribute to the development of these new technologies, this work presents the design aspects of a chip-scale calorimeter that can be used to detect an explosive material by calorimetric methods. The aim of this work is to apply what has been done in the area of chip-scale calorimetry to the screening of highly energetic materials. The prototypes presented here were designed using computer assisted design and finite element analysis tools. The design parameters were set to satisfy the requirements of a sensor that can be integrated into a portable system (handheld) for field applications. The design approach consisted of developing a sensor with thick silicon membranes that can hold micro-size samples and that can operate at high temperatures, while keeping the cost of the sensor low. Contrary to other high resolution systems based on thin-film membranes, our prototypes exhibit a contribution from addenda that is comparable to that from the sample, and hence they have lower sensitivity. However, using thick membranes offers the advantage of producing sensors strong enough for this application and that have significantly lower cost. Once the prototypes were designed, the fabrication was performed using standard microfabrication techniques. Finally, the operation of our prototypes was demonstrated by conducting thermal analysis of different liquid and solid samples.

There are a number of techniques that are used to solve reinforcement learning problems, but very few that have been developed for and tested on highly reconfigurable systems cast as reinforcement learning problems. Reconfigurable systems refers to a vehicle (air, ground, or water) or collection of vehicles that can change its geometrical features, i.e. shape or formation, to perform tasks that the vehicle could not otherwise accomplish. These systems tend to be optimized for several operating conditions, and then controllers are designed to reconfigure the system from one operating condition to another. Q-learning, an unsupervised episodic learning technique that solves the reinforcement learning problem, is an attractive control methodology for reconfigurable systems. It has been successfully applied to a myriad of control problems, and there are a number of variations that were developed to avoid or alleviate some limitations in earlier version of this approach. This dissertation describes the development of three modular enhancements to the Q-learning algorithm that solve some of the unique problems that arise when working with this class of systems, such as the complex interaction of reconfigurable parameters and computationally intensive models of the systems. A multi-resolution state-space discretization method is developed that adaptively rediscretizes the state-space by progressively finer grids around one or more distinct Regions Of Interest within the state or learning space. A genetic algorithm that autonomously selects the basis functions to be used in the approximation of the action-value function is applied periodically throughout the learning process. Policy comparison is added to monitor the state of the policy encoded in the action-value function to prevent unnecessary episodes at each level of discretization. This approach is validated on several problems including an inverted pendulum, reconfigurable airfoil, and reconfigurable wing. Results show that the multi-resolution state-space discretization method reduces the number of state-action pairs, often by an order of magnitude, required to achieve a specific goal and the policy comparison prevents unnecessary episodes once the policy has converged to a usable policy. Results also show that the genetic algorithm is a promising candidate for the selection of basis functions for function approximation of the action-value function.

Since the speedy popularity of Internet infrastructure and explosive increasing of World Wide Web services, a lot of traditional companies had web-enabled their business over Internet and used WWW as their application platform. Those web services, such as the on-line search, e-learning, e-commence, multimedia, network service, e-government etc., need a stable and powerful web server to support the huge capability. The web hosting service becomes increasingly important in which the service providers offer system resources to store and to provide Web access to contents from individuals, institutions, and companies, who lack resources or expertise to maintain their Web site. Web server cluster is a popular architecture used by the hosting service providers as a way to create scalable and highly available solutions. However, hosting a variety of contents from different customers on such a distributed server system faces new design and management problems. This dissertation describes the work pursuing for constructing a system to address the challenges of hosting Web content on a server cluster environment. Based on the achievement of the software-based content-aware distributor, some high repetition and fixity tasks originally treated by software module are delivered to hardware module for speeding up the packet processes and for sharing the loads on the software module. Our software-based distributor is implemented in Linux kernel as a loadable module. A few system calls in user level are built to support the integration of resource management.

This dissertation presents a hybrid quadrature polar modulator (HQPM) to drive the power amplifier (PA) highly efficiently in a wireless RF transmitter with good potential for multi-mode operation. For enhancing the efficiency, a Class-E PA is used in the transmitter. The HQPM consists of a quadrature modulator for processing the RF modulated carrier and a Class-S modulator for processing the supply-voltage signal. The quadrature modulator and the Class-S modulator deliver the output signals with envelope variation before being inserted into the RF-input terminal and the supply-voltage terminal of Class-E PA, respectively, causing the double envelope modulation to distort the modulated RF signal at the PA output. Therefore, a digital predistorter is proposed to be embedded in the HQPM for compensation. The use of such predistorted HQPM techniques can help reducing the average DC and RF input powers and the output feed-through levels so as to enhance power added efficiency and adjacent channel power rejection quite remarkably.

In a wireless communication system, the RF signal integrity is often deteriorated by power amplifier (PA) nonlinearity and local oscillator (LO) pulling. This dissertation attempts to study power amplifier and local oscillator with the deliberate input distortion or interference for understanding, and hence improving, the resultant RF signal integrity issues. Furthermore, the scope of this study is extended to explore novel wireless applications. Based on the above thoughts, this dissertation includes three topics. The first topic is devoted to a baseband digital predistortion technique for enhancing the power amplifier linearity in a wireless RF transmitter. A digital predistorter has been designed to compensate the amplitude and phase distortion due to the nature of PAs, and the predistortion can enhance the linearity of linear PAs as well as switching-mode PAs. The second topic proceeds with a rigorous analysis of a local oscillator subject to injection signal. A phase-locked loop (PLL) under injection is analyzed in frequency domain to account for the inherent band-pass filtering on an injection signal. Such analysis can further predict the effect of co-frequency or co-channel interference on the PLL phase noise. A discrete-time analysis is also provided to predict output spectra of the LO pulled by a sinusoidal and modulated injection signal. The final topic presents a novel RF sensing circuit for a cognitive radio to sense spectral environment using injection locking and frequency demodulation techniques. The proposed RF sensing circuit can fast and reliably detect frequency and power for analog and digital modulation signals. In addition, the sensing principle and circuit architecture are delivered on theoretical basis developed in this dissertation. A discrete time approach is also investigated to compute the sensed output signal.

The main aim of this thesis is to design efficient and novel numerical algorithms for a class of deterministic and stochastic dynamical systems with multiple time scales. Classical numerical methods for such problems need temporal resolution to resolve the finest scale and become, therefore, inefficient when the much longer time intervals are of interest. In order to accelerate computations and improve the long time accuracy of numerical schemes, we take advantage of various multiscale structures established from a separation of time scales. This dissertation is organized into four chapters: an introduction followed by three chapters, each based on one of three different papers. The framework of the heterogeneous multiscale method (HMM) is considered as a general strategy both for the design and the analysis of multiscale methods. In Chapter 2, we consider a new class of multiscale methods that use a technique related to the construction of a Poincaré map. The main idea is to construct effective paths in the state space whose projection onto the slow subspace shows the correct dynamics. More precisely, we trace the evolution of the invariant manifold M(t), identified by the level sets of slow variables, by introducing a slowly evolving effective path which crosses M(t). The path is locally constructed through interpolation of neighboring points generated from our developed map. This map is qualitatively similar to a Poincaré map, but its construction is based on the procedure which solves two split equations successively backward and forward in time only over a short period. This algorithm does not require an explicit form of any slow variables. In Chapter 3, we present efficient techniques for numerical averaging over the invariant torus defined by ergodic dynamical systems which may not be mixing. These techniques are necessary, for example, in the numerical approximation of the effective slow behavior of highly oscillatory ordinary differential equations in weak near-resonance. In this case, the torus is embedded in a higher dimensional space and is given implicitly as the intersection of level sets of some slow variables, e.g. action variables. In particular, a parametrization of the torus may not be available. Our method constructs an appropriate coordinate system on lifted copies of the torus and uses an iterated convolution with respect to one-dimensional averaging kernels. Non-uniform invariant measures are approximated using a discretization of the Frobenius-Perron operator. These two numerical averaging strategies play a central role in designing multiscale algorithms for dynamical systems, whose fast dynamics is restricted not to a circle, but to the tori. The efficiency of these methods is illustrated by numerical examples. In Chapter 4, we generalize the classical two-scale averaging theory to multiple time scale problems. When more than two time scales are considered, the effective behavior may be described by the new type of slow variables which do not have formally bounded derivatives. Therefore, it is necessary to develop a theory to understand them. Such theory should be applied in the design of multiscale algorithms. In this context, we develop an iterated averaging theory for highly oscillatory dynamical systems involving three separated time scales. The relevant multiscale algorithm is constructed as a family of multilevel solvers which resolve the different time scales and efficiently computes the effective behavior of the slowest time scale. / text