Clinical evaluation of radioactive stents

Restenosis, the major problem after stent implantation, is caused by in-stent neointimal hyperplasia. A number of metbods and techniques have been studied during the last ten years to address tbis issue, but in-stent restenosis has remained at a rate of 15-25% in most of tbe clinical trials. Several experimental and clinical trials showed that brachytherapy, following a balloon angioplasty or stent implantation, reduced restenosis by inhibiting neointimal hype

Systematic study of effect of cross-drafts and nozzle diameter on shield gas coverage

A shield gas flow rate of 15–20 L min21 is typically specified in metal inert gas welding, but is often adjusted to as high as 36 L min21 by welders in practice. Not only is this overuse of shield gas wasteful, but uncontrolled high gas flows can lead to significant turbulence induced porosity in the final weld. There is therefore a need to understand and control the minimum shield gas flow rate used in practical welding where cross-drafts may affect the coverage. Very low gas coverage or no shielding leads to porosity and spatter development in the weld region. A systematic study is reported of the weld quality achieved for a range of shield gas flow rates, cross-draft speeds and nozzle diameters using optical visualisation and numerical modelling to determine the shield gas coverage. As a consequence of the study, the shield gas flow has been reduced to 12 L min21 in production welding, representing a significant process cost saving and reduced environmental impact with no compromise to the final weld quality

MIG gas shielding : Economic savings without detriment to quality

Over the years a number of claims have been made related to potential savings of the shielding gas used in the MIG process. A number of work streams have been set up to consider such areas from a technical and economic standpoint. The use of small helium additions has particular benefits and despite an increase in unit cost, the overriding benefits are achieved in reduced manhour cost. A similar situation has been established when using a high frequency process to switch shielding gases during welding. The outcome from this was very similar to that already described. Overlaid on these has been the increasing use of a technique that visualises actual gas flow during welding by the use of laser backlighting. Some preliminary work in this area is described particularly related to the effect of drafts on the gas distribution. A recent development on the market place is a piece of equipment, which regulates the gas flow automatically and synchronously with the welding current. Gas savings in the region of 50-60% have been obtained. Data has been produced to illustrate these benefits. The potential benefit of developing a computational fluid dynamic model of the gas flow is also described, and early development stages of the model shown. However, there will always exist the very basic management need to minimise leaks from the gas delivery systems

Scale invariance in coarsening of binary and ternary fluids

Phase separation in binary and ternary fluids is studied using a two dimensional Lattice Gas Automata. The lengths, given by the the first zero crossing point of the correlation function and the total interface length is shown to exhibit power law dependence on time. In binary mixtures, our data clearly indicate the existence of a regime having more than one length scale where the coarsening process proceeds through the rupture and reassociation of domains. In ternary fluids; in the case of symmetric mixtures there exists a regime with a single length scale having dynamic exponent 1/2, while in asymmetric mixtures our data establish the break down of scale invariance.Comment: 20 pages, 13 figure

SYSTEMS-2: a randomised phase II study of radiotherapy dose escalation for pain control in malignant pleural mesothelioma

SYSTEMS-2 is a randomised study of radiotherapy dose escalation for pain control in 112 patients with malignant pleural mesothelioma (MPM). Standard palliative (20Gy/5#) or dose escalated treatment (36Gy/6#) will be delivered using advanced radiotherapy techniques and pain responses will be compared at week 5. Data will guide optimal palliative radiotherapy in MPM

Quantifying model uncertainty to improve watershed-level ecosystem service quantification: a global sensitivity analysis of the RUSLE

Ecosystem service-support tools are commonly used to guide natural resource management. Often, empirically based models are preferred due to low data requirements, simplicity and clarity. Yet, uncertainty produced by local context or parameter estimation remains poorly quantified and documented. We assessed model uncertainty of the Revised Universal Soil Loss Equation – RUSLE developed mainly from US data. RUSLE is the most commonly applied model to assess watershed-level soil loss. We performed a global sensitivity analysis (GSA) on RUSLE with four dissimilar datasets to understand uncertainty and to provide recommendations for data collection and model parameterization. The datasets cover varying spatial levels (plot, watershed and continental) and environmental conditions (temperate and tropical). We found cover management and topography create the most uncertainty regardless of environmental conditions or data parameterization techniques. The importance of other RUSLE factors varies across contexts. We argue that model uncertainty could be reduced through better parameterization of cover management and topography factors while avoiding severe soil losses by targeting soil conservation practices in areas where both factors interact and enhance soil loss. We recommend incorporating GSA to assess empirical models’ uncertainty, to guide model parameterization and to target soil conservation efforts

A local network neighbourhood artificial immune system

As information is becoming more available online and will forevermore be part of any business, the true value of the large amounts of stored data is in the discovery of hidden and unknown relations and connections or traits in the data. The acquisition of these hidden relations can influence strategic decisions which have an impact on the success of a business. Data clustering is one of many methods to partition data into different groups in such a way that data patterns within the same group share some common trait compared to patterns across different groups. This thesis proposes a new artificial immune model for the problem of data clustering. The new model is inspired by the network theory of immunology and differs from its network based predecessor models in its formation of artificial lymphocyte networks. The proposed model is first applied to data clustering problems in stationary environments. Two different techniques are then proposed which enhances the proposed artificial immune model to dynamically determine the number of clusters in a data set with minimal to no user interference. A technique to generate synthetic data sets for data clustering of non-stationary environments is then proposed. Lastly, the original proposed artificial immune model and the enhanced version to dynamically determine the number of clusters are then applied to generated synthetic non-stationary data clustering problems. The influence of the parameters on the clustering performance is investigated for all versions of the proposed artificial immune model and supported by empirical results and statistical hypothesis tests. AFRIKAANS: Soos wat inligting meer aanlyn toeganglik raak en vir altyd meer deel vorm van enige besigheid, is die eintlike waarde van groot hoeveelhede data in die ontdekking van verskuilde en onbekende verwantskappe en konneksies of eienskappe in die data. Die verkryging van sulke verskuilde verwantskappe kan die strategiese besluitneming van ’n besigheid beinvloed, wat weer ’n impak het op die sukses van ’n besigheid. Data groepering is een van baie metodes om data op so ’n manier te groepeer dat data patrone wat deel vorm van dieselfde groep ’n gemeenskaplike eienskap deel in vergelyking met patrone wat verspreid is in ander groepe. Hierdie tesis stel ’n nuwe kunsmatige immuun model voor vir die probleem van data groepering. Die nuwe model is geinspireer deur die netwerk teorie in immunologie en verskil van vorige netwerk gebaseerde modelle deur die model se formasie van kunsmatige limfosiet netwerke. Die voorgestelde model word eers toegepas op data groeperingsprobleme in statiese omgewings. Twee verskillende tegnieke word dan voorgestel wat die voorgestelde kunsmatige immuun model op so ’n manier verbeter dat die model die aantal groepe in ’n data stel dinamies kan bepaal met minimum tot geen gebruiker invloed. ’n Tegniek om kunsmatige data stelle te genereer vir data groepering in dinamiese omgewings word dan voorgestel. Laastens word die oorspronklik voorgestelde model sowel as die verbeterde model wat dinamies die aantal groepe in ’n data stel kan bepaal toegepas op kunsmatig genereerde dinamiese data groeperingsprobleme. Die invloed van die parameters op die groepering prestasie is ondersoek vir alle weergawes van die voorgestelde kunsmatige immuun model en word toegelig deur empiriese resultate en statistiese hipotese toetse.Thesis (PhD)--University of Pretoria, 2011.Computer Scienceunrestricte

Loop formation mechanism in the air-jet texturing process

A brief introduction to the air-jet texturing process is given, with reference to similarities between air-jet textured yarns and spun yarns, differences between them and stretch yarns, and developments in texturing nozzles. Researches undertaken at various universities on the investigation of the loop formation mechanism are reviewed. An alternative explanation of the loop formation mechanism is offered by detailed reference to current research in the Department of Mechanical Engineering at Loughborough University of Technology, this being based on high-speed photography and flow measurement methods applied mainly to the standard core HemaJet produced by Heberlein of Switzerland. It is argued that the suggested mechanism applies generally to all texturing nozzles