Traitement du cancer pulmonaire non à petites cellules par radiothérapie stéréotaxique d’ablation

Les néoplasies pulmonaires demeurent la première cause de décès par cancer au Québec représentant près de 6000 décès par année. Au cours des dernières années, la radiothérapie stéréotaxique d’ablation (SABR) s’est imposée comme un traitement alternatif à la résection anatomique pour les patients inopérables atteints d’un cancer pulmonaire non à petites cellules de stade précoce. Il s’agit d’une modalité de traitement qui permet d’administrer des doses élevées, typiquement 30-60 Gy en 1-8 fractions, dans le but de cibler précisément le volume de traitement tout en épargnant les tissus sains. Le Centre Hospitalier de l’Université de Montréal s’est muni en 2009 d’un appareil de SABR de fine pointe, le CyberKnife™ (CK), un accélérateur linéaire produisant un faisceau de photons de 6 MV dirigé par un bras robotisé, permettant d’administrer des traitements non-coplanaires avec une précision infra-millimétrique. Ce mémoire est dédié à la caractérisation de certains enjeux cliniques et physiques associés au traitement par CK. Il s’articule autour de deux articles scientifiques revus par les pairs. D’une part, une étude prospective clinique présentant les avantages de la SABR pulmonaire, une technique qui offre un excellent contrôle tumoral à long terme et aide au maintien de la qualité de vie et de la fonction pulmonaire. D’autre part, une étude de physique médicale illustrant les limites de l’acquisition d’images tomodensitométriques en auto-rétention respiratoire lors de la planification de traitement par CK.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Hierarchical control and optimisation of the Tennessee Eastman process

Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear - quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method is demonstrated using a simulation of the Tennessee Eastman benchmark chemical process.

Optimisation of the aqueous extraction conditions of phenols from meadowsweet (Filipendula ulmaria L.) for incorporation into beverages

Meadowsweet was extracted in water at a range of temperatures (60–100 °C), and the total phenols, tannins, quercetin, salicylic acid content and colour were analysed. The extraction of total phenols followed pseudo first-order kinetics, the rate constant (k) increased from 0.09 ± 0.02 min−1 to 0.44 ± 0.09 min−1, as the temperature increased from 60 to 100 °C. An increase in temperature from 60 to 100 °C increased the concentration of total phenols extracted from 39 ± 2 to 63 ± 3 mg g−1 gallic acid equivalents, although it did not significantly affect the proportion of tannin and non-tannin fractions. The extraction of quercetin and salicyclic acid from meadowsweet also followed pseudo first-order kinetics, the rate constant of both compounds increasing with an increase in temperature up until 90 °C. Therefore, the aqueous extraction of meadowsweet at temperatures at or above 90 °C for 15 min yields extracts high in phenols, which may be added to beverages.

Optimisation of oat milk formulation to obtain fermented derivatives by using probiotic Lactobacillus reuteri microorganisms

Functional advantages of probiotics combined with interesting composition of oat were considered as an alternative to dairy products. In this study, fermentation of oat milk with Lactobacillus reuteri and Streptococcus thermophilus was analysed to develop a new probiotic product. Central composite design with response surface methodology was used to analyse the effect of different factors (glucose, fructose, inulin and starters) on the probiotic population in the product. Optimised formulation was characterised throughout storage time at 4 ℃ in terms of pH, acidity, β-glucan and oligosaccharides contents, colour and rheological behaviour. All formulations studied were adequate to produce fermented foods and minimum dose of each factor was considered as optimum. The selected formulation allowed starters survival above 107/cfu ml to be considered as a functional food and was maintained during the 28 days controlled. β-glucans remained in the final product with a positive effect on viscosity. Therefore, a new probiotic non-dairy milk was successfully developed in which high probiotic survivals were assured throughout the typical yoghurt-like shelf life.

Reactive power dispatch and planning using a non-linear branch-and-bound algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genetic Algorithms (Binary and Real Codes) for the Optimisation of a Fermentation Process for Butanol Production

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Optimisation of a fermentation process for butanol production by particle swarm optimisation (PSO)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Traitement du cancer pulmonaire non à petites cellules par radiothérapie stéréotaxique d’ablation

Les néoplasies pulmonaires demeurent la première cause de décès par cancer au Québec représentant près de 6000 décès par année. Au cours des dernières années, la radiothérapie stéréotaxique d’ablation (SABR) s’est imposée comme un traitement alternatif à la résection anatomique pour les patients inopérables atteints d’un cancer pulmonaire non à petites cellules de stade précoce. Il s’agit d’une modalité de traitement qui permet d’administrer des doses élevées, typiquement 30-60 Gy en 1-8 fractions, dans le but de cibler précisément le volume de traitement tout en épargnant les tissus sains. Le Centre Hospitalier de l’Université de Montréal s’est muni en 2009 d’un appareil de SABR de fine pointe, le CyberKnife™ (CK), un accélérateur linéaire produisant un faisceau de photons de 6 MV dirigé par un bras robotisé, permettant d’administrer des traitements non-coplanaires avec une précision infra-millimétrique. Ce mémoire est dédié à la caractérisation de certains enjeux cliniques et physiques associés au traitement par CK. Il s’articule autour de deux articles scientifiques revus par les pairs. D’une part, une étude prospective clinique présentant les avantages de la SABR pulmonaire, une technique qui offre un excellent contrôle tumoral à long terme et aide au maintien de la qualité de vie et de la fonction pulmonaire. D’autre part, une étude de physique médicale illustrant les limites de l’acquisition d’images tomodensitométriques en auto-rétention respiratoire lors de la planification de traitement par CK.

PhotoVoltaic DC-DC module integrated converter for novel cascaded and bypass grid connection topologies - design and optimisation

Grid connected PhotoVoltaic (PV) inverters fall into three broad categories — Central, String and Module Integrated Converers (MICs). MICs offer any avantaes in performance and flexibility, but are at a cost disadvantage. Two alternative novel approaches proposed by the author — cascaded dc-dc MICs and bypass dc-dc MICs — integrate a simple non-isolated intelligent dc-dc converter with each PV module to provide the advantages of dc-ac MICs at a lower cost. A suitable universal 150W 5A dc-dc converter design is presented based on two interleaved MOSFET half bridges. Testing shows Zero Voltage Switching (ZVS) keeps losses under 1W for bi-directional power flows up to 15W between two adjacent 12V PV modules for the bypass application, and efficiencies over 94% for most of the operational power range for the cascaded converter application. Based on the experimental results, potential optimizations to further reduce losses are discussed.

Mathematical modelling and optimisation of a water heat pump

The purpose of the work described here has been to seek methods of narrowing the present gap between currently realised heat pump performance and the theoretical limit. The single most important pre-requisite to this objective is the identification and quantitative assessment of the various non-idealities and degradative phenomena responsible for the present shortfall. The use of availability analysis has been introduced as a diagnostic tool, and applied to a few very simple, highly idealised Rankine cycle optimisation problems. From this work, it has been demonstrated that the scope for improvement through optimisation is small in comparison with the extensive potential for improvement by reducing the compressor's losses. A fully instrumented heat pump was assembled and extensively tested. This furnished performance data, and led to an improved understanding of the systems behaviour. From a very simple analysis of the resulting compressor performance data, confirmation of the compressor's low efficiency was obtained. In addition, in order to obtain experimental data concerning specific details of the heat pump's operation, several novel experiments were performed. The experimental work was concluded with a set of tests which attempted to obtain definitive performance data for a small set of discrete operating conditions. These tests included an investigation of the effect of two compressor modifications. The resulting performance data was analysed by a sophisticated calculation which used that measurements to quantify each dagradative phenomenon occurring in that compressor, and so indicate where the greatest potential for improvement lies. Finally, in the light of everything that was learnt, specific technical suggestions have been made, to reduce the losses associated with both the refrigerant circuit and the compressor.