A eletrooxidação de etanol foi investigada sobre catalisadores bi e trimetálicos constituídos de Pt-M1 e Pt-M-M1 M = Sn, Mo, W, Ru, Os e Ir). Os eletrodos foram preparados em três diferentes configurações: eletrodos lisos (preparados em forno a arco voltaico), filmes depositados em placas de Ti (Pt-M/Ti) e nanopartículas metálicas dispersas em carbono (Pt-M-M1/C), ambos preparados pelo método Pechini. Os resultados eletroquímicos mostraram que a adição dos diferentes metais à platina aumentou a atividade catalítica dos eletrodos. Este efeito se mostrou dependente da composição do eletrodo e para os eletrodos lisos apresentou resultados mais acentuados nas composições Pt-Os e Pt-Sn-W. Os intermediários e produtos de reação da oxidação de etanol os eletrodos lisos foram determinados pelas técnicas de FTIR in situ de SPAIRS e SNIFTIRS. Os resultados sugerem que a presença dos elementos modificadores da platina aumentam a velocidade da reação de oxidação de etanol pela dessorção de intemediários com dois átomos de carbono (como CH3CHOads) a potenciais mais baixos do que a Pt levando conseqüentemente a liberação dos sítios ativos para nova adsorção de etanol. Constatou-se contudo, que a presença desses elementos não favorece a quebra da ligação C-C para formação de CO2 em quantidades apreciáveis. As composições de catalisadores Pt-M/Ti (M = Sn, Ru, Ir e Mo) preparados pelo método Pechini que apresentaram os melhores resultados em densidades de corrente foram os eletrodos de Pt-Sn/Ti. As análise por HPLC mostraram o produto majoritariamente formado foi o acetaldeído independente da composição do catalisador, mas os catalisadores Pt-Sn/Ti tiveram a maior seletividade na formação de ácido acético. Os testes em célula unitária foram realizados para os catalisadores trimetálicos Pt-Sn-W/C em diferentes composições. A presença de Sn e W aumentou significativamente o desempenho da célula com relação à Pt pura. O melhor catalisador testado (Pt-Sn-W/C (85:8:7)) apresentou OCV de 777 mV contra 345 mV da Pt a 90oC. A densidade de potência máxima alcançada para essa composição foi de 33 mW cm-2. A análise de produtos ao final de 5 horas de reação a 90oC aplicando 30 mA cm-2 de corrente mostrou que os produtos principalmente formados foram ácido acético e acetaldeído. / Ethanol oxidation on Pt-M1 e Pt/M/M1 (M = Sn, Mo, W, Ru, Os e Ir) catalysts prepared by arc melting furnace process and Pechini method was investigated. The electrochemical data showed that the addition of these elements to Pt gives a highest current densities at lower potentials. The best composition of electrodes prepared by arc melting process based on current densities values was Pt-Os and Pt-Sn-W. The intemediates and reaction products for ethanol oxidation were detected by SPAIRS and SNIFTIRS. The results sugest that adding a foreign metal to Pt leads an increase of the reaction rate for ethanol oxidation because desorption of two carbon atoms intermediates (as CH3 CHOads) at lower potentials comparing to pure Pt. The active site become then available for the new ethanol adsorption. However, the presence of these metals doesn\'t increase the selectivity to CO2 generation. Pt-M/Ti (M = Sn, Ru, Ir e Mo) catalysts were prepared by Pechini method. The products of the ethanol oxidation on these electrodes were evaluated by HPLC. The results showed that acetaldehyde was the main product obtained for all compositions. DEFCs tests were carry on with Pt-Sn-W/C ternary catalysts in different compositions. It was obtained particles size about 3.9 to 11 nm, depending on the catalyst composition. The addition of Sn and W increased significantly the DEFC performance. The best result was obtained by Pt-Sn-W/C (85:8:7) catalyst. It presents OCV about 777 mV against 345 mV to Pt at 90oC. The maximum of power density for this catalyst was 33 mW cm-2. Acetaldehyde was the major product formed when applying a fixed current of 30 mA cm-2 at 90oC.

Over the past five decades, the Saudi government has adopted many agricultural policies aimed to: achieve self-sufficiency of food, increase the participation of the agricultural sector in the economy, and reduce the consumption of irrigation water. Due to conflicts among government objectives and the incompatibility of farmers' objectives with those of some agricultural policies, the government has not been able to fully achieve its objectives. To accomplish its goals the government, or decision maker needs to understand the farmer, or follower, reaction when s/he adopts a new decision. The dissertation aims to build a model that achieves government goals of minimizing the total irrigation water used while improving the total revenue from agricultural production, while incorporating farmers’ objective of maximizing their profit. To do this, linear programming and bi-level multi-objective multi-follower models are developed and applied to six regions of Saudi Arabia, which account for around 70 percent of cropland and consume about 13.131 BCM of irrigation water per year. The result of the linear programming model applied to the Riyadh region shows there is an unobserved factor effect on the farmers’ decisions, including irrigation water demand that comes from the presence of indirect subsidies. On the other hand, the bi-level multi-objective, multi-follower model shows there is the possibility to minimize irrigation water consumption while maintaining current total revenue from crop production through reallocating irrigation water among regions, while applying a variety of crop specific tax and subsidy policies among the regions to alter planting decisions.

Matching people to their preferences is an algorithmic topic with real world applications. One such application is the kidney exchange. The best "cure" for patients whose kidneys are failing is to replace it with a healthy one. Unfortunately, biological factors (e.g., blood type) constrain the number of possible replacements. Kidney exchanges seek to alleviate some of this pressure by allowing donors to give their kidney to a patient besides the one they most care about and in turn the donor for that patient gives her kidney to the patient that this first donor most cares about. Roth et al.~first discussed the classic kidney exchange problem. Freedman et al.~expanded upon this work by optimizing an additional objective in addition to maximal matching. In this work, I implement the traditional kidney exchange algorithm as well as expand upon more recent work by considering multi-objective optimization of the exchange. In addition I compare the use of 2-cycles to 3-cycles. I offer two hypotheses regarding the results of my implementation. I end with a summary and a discussion about potential future work.

The motivation of this study is to investigate the size dependent properties of Gadolinium silicide nanoparticles and their potential applications in Biomedicine. We use two approaches in our investigation - size dependence and possible exchange interaction in a core-shell structure. Past results showed Gd5Si4 NPs exhibit significantly reduced echo time compared to superparamagnetic iron oxide nanoparticles (SPION) when measured in a 7 T magnetic resonance imaging (MRI) system. This indicates potential use of Gd5Si4 ferromagnetic nanoparticles as T2 contrast agents for MRI. Until recently most contrast agents (CA) that are used in Magnetic Resonance Imaging (MRI) studies have been paramagnetic. However, ferromagnetic CAs are potentially more sensitive as T2 CAs than T1 paramagnetic compounds due to their large magnetic moments. Furthermore, the need for better MRI images without the need of upgrading to the higher magnetic field strength can be achieved using better CA such as Gd5Si4 NP. The quality of the image contrast in MRI is improved by shortening T1 and T2 relaxation times at the site or close proximity to the CA. In this study, effect of Gd5Si4 NP of varying sizes and with different concentrations are investigated on T1, T2 and T2* (effective/observed T2) relaxations times. Further study was carried out on possible exchange interaction between Fe3O4 and Gd5Si4 to enhance the magnetic properties of the Gd5Si4 which could be later used to synthesize core-shell structures. Exchange interaction / bias is a phenomena associated with the exchange anisotropy created at the interface between the two magnetic materials. Therefore, thin films of varying thickness was deposited and studied for their magnetic properties.

Ordinal response variables abound in scientific and quantitative analyses, whose outcomes comprise a few categorical values that admit a natural ordering, so that their values are often represented by non-negative integers, for instance, pain score (0-10) or disease severity (0-4) in medical research. Ordinal variables differ from rational variables in that its values delineate qualitative rather than quantitative differences. In this thesis, we develop new statistical methods for variable selection in a high-dimensional cumulative link regression model with an ordinal response. Our study is partly motivated by the needs for exploring the association structure between disease phenotype and high-dimensional medical covariates. The cumulative link regression model specifies that the ordinal response of interest results from an order-preserving quantization of some latent continuous variable that bears a linear regression relationship with a set of covariates. Commonly used error distributions in the latent regression include the normal distribution, the logistic distribution, the Cauchy distribution and the standard Gumbel distribution (minimum). The cumulative link model with normal (logit, Gumbel) errors is also known as the ordered probit (logit, complementary log-log) model. While the likelihood function has a closed-form solution for the aforementioned error distributions, its strong nonlinearity renders direct optimization of the likelihood to sometimes fail. To mitigate this problem and to facilitate extension to penalized likelihood estimation, we proposed specific minorization-maximization (MM) algorithms for maximum likelihood estimation of a cumulative link model for each of the preceding 4 error distributions. Penalized ordinal regression models play a role when variable selection needs to be performed. In some applications, covariates may often be grouped according to some meaningful way but some groups may be mixed in that they contain both relevant and irrelevant variables, i.e., whose coefficients are non-zero and zero, respectively. Thus, it is pertinent to develop a consistent method for simultaneously selecting relevant groups and the relevant variables within each selected group, which constitutes the so-called bi-level selection problem. We have proposed to use a penalized maximum likelihood approach with a composite bridge penalty to solve the bi-level selection problem in a cumulative link model. An MM algorithm was developed for implementing the proposed method, which is specific to each of the 4 error distributions. The proposed approach is shown to enjoy a number of desirable theoretical properties including bi-level selection consistency and oracle properties, under suitable regularity conditions. Simulations demonstrate that the proposed method enjoys good empirical performance. We illustrated the proposed methods with several real medical applications.

To many, high-frequency (HF) radio communications is obsolete in this age of long distance satellite communications and undersea optical fiber. Yet despite this, the HF band is used by defence agencies for backup communications and spectrum surveillance, and is monitored by spectrum management organizations to enforce licensing. Such activity usually requires systems capable of locating distant transmitters, separating valid signals from interference and noise, and recognizing signal modulation. Research presented here targets the latter issue. The ultimate aim is to develop robust algorithms for automatic modulation recognition of real HF signals, where real means signals propagating by multiple ionospheric modes with co-channel signals and non- Gaussian noise. However, many researchers adopt Gaussian noise models for signals for the sake of convenience at the cost of accuracy. Furthermore, literature describing the probability density function (PDF) of HF noise does not abound. So an additional aim of this research is measurement of the PDF of HF noise. A simple empirical technique, not found in the literature, is described that supports the hypothesis that HF noise is generally not Gaussian. In fact, the probability density function varies with the time of day, electromagnetic environment, and state of the ionosphere. Key contributions of this work relate to the statistics of HF noise and the discrimination of real HF signals via three signal features. Through two unique experiments, the density function of natural HF noise is found to closely follow a Bi-Kappa distribution. This distribution can model natural and man-made HF noise through a single control parameter. Regarding signal features, the coherence function is found to be a brute-force technique suitable only for hard (not soft) decisions. A novel application of an entropic distance measure proves able to separate four real HF signals based on their modulation types. And, an estimator for signal-to-noise (SNR) ratio is shown to provide reasonable measures of SNR for the same real HF signals. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1330848 / Thesis (Ph.D.) - University of Adelaide, School of Electrical and Electronic Engineering, 2008

Dans le premier chapitre on précise les définitions et notations utilisées par la suite et on rappelle certains résultats nécessaires ultérieurement. Dans le deuxième chapitre on définit à partir de deux ensembles convexes K1 et K2, le produit tensoriel direct note K1 cercle X K2 et polaire K1 d'Alemb. K2. Au troisième chapitre on étudie quelques propriétés faciales de K1 cercle x K2 et de K1d'alemb. K2. Au quatrième chapitre on étudie la relation entre K1 cercle X K2 et K1d'Alemb. K2. Enfin on étudie le produit tensoriel direct et le produit tensoriel polaire dans les cas suivants : K1 et k2 sont des hypersphères, K1 et K2 sont des polaires d'hypercubes, K1 et K2 sont des hypercubes.

La biomasse représente l'une des principales alternatives à l'utilisation du pétrole dans la plasturgie. Grâce à leurs propriétés fonctionnelles, les caséinates sont une matière première prometteuse pour la fabrication de films plastiques pour des applications dans l'emballage biodégradable et hydrosoluble. La transformation du caséinate de sodium par les techniques habituellement utilisées dans la plasturgie a été démontrée. Des extrudats de caséinate plastifié au glycérol ont été obtenus au moyen d'une extrudeuse bi-vis corotative. La caractérisation physico-chimique du matériau obtenu a confirmé la thermostabilité de cette protéine et a montré la dépendance du comportement du matériau vis-à-vis de l'humidité ambiante. Pour une variation du taux d'Humidité Relative, de 40 à 90% et une augmentation de la concentration du glycérol, plastifiant hygroscopique, le matériau passe d'un état vitreux (rigide) à un état caoutchouteux (mou). Des films fins ont été ensuite réalisés, à partir des extrudats thermoplastiques, par extrusion gonflage. La perméabilité à la vapeur d'eau des films de caséinate de sodium a été étudiée et a montré que ces matériaux sont de mauvaises barrières à l'humidité. La deuxième partie a été consacré à l'étude de mélanges caséinate de sodium/caséinate de calcium d'un côté et caséinate de sodium/PBAT de l'autre. Le mélange des deux caséinates a permis d'augmenter la tenue mécanique du mélange, à partir de 50% de caséinate de calcium, et de retarder le transfert hydrique à travers le film. Dans le même sens, l'ajout du PBAT, a augmenté jusqu'à deux fois plus, le module d'Young des mélanges mais a baissé la résistance au transfert d'humidité du film à cause de l'incompatibilité des deux polymères.

Les Quantum Dots (QDs) sont des nanocristaux de semiconducteurs qui possèdent des propriétés optiques hors du commun. Leur utilisation comme sondes en biologie nécessite leur solubilisation dans l'eau, grâce à une chimie de surface adaptée, qui influence la taille finale du QD, ses propriétés optiques et son interaction avec l'environnement biologique. Nous avons développé un nouveau ligand, l'acide dihydrolipoïque-sulfobétaïne (DHLA-SB), qui permet d'obtenir des QDs à la fois petits, stables dans une vaste gamme de pH, dans des solutions saturées en sel et dans le temps, et avec une très faible adsorption non spécifique sur les cellules. Nous avons observé et caractérisé le comportement intracellulaire des QDs DHLA-SB au cours du temps et nous l'avons comparé à celui de deux autres classes de QDs : cette étude a clairement montré l'influence de la chimie de surface sur le devenir intracellulaire des nanoparticules et a révélé une stabilité accrue des QDs DHLA-SB. Nous nous sommes également intéressés à la fonctionnalisation des QDs avec la streptavidine (SA) ou la biotine afin de marquer spécifiquement des cellules vivantes ou fixées. Les QDs-SA DHLA-SB obtenus ont permis de suivre un récepteur membranaire ou encore de marquer de façon spécifique une protéine biotinylée à l'intérieur de cellules vivantes, bien plus efficacement qu'avec les QDs-SA commerciaux (Invitrogen). Enfin, nous avons proposé d'utiliser les QDs DHLA-SB pour améliorer une technique de microscopie à illumination structurée, la microscopie HiLo bicouleur, et obtenir une coupe optique (type image confocale) d'échantillons biologiques épais en une seule image.

Les conditions de circulation sur un réseau routier subissent souvent de la congestion. Selon ses sources, la congestion routière peut être classée en deux catégories : la congestion récurrente déterminée par les lois de trafic et la congestion non-récurrente due aux incidents, accidents ou autres aléas sur la route. Grâce à l'avancement des technologies, notamment en informatique, communication et techniques de traitement des données, l'exploitant est devenu capable de détecter les perturbations, de mesurer les effets et même d'anticiper l'état du trafic afin de mieux adapter ses actions d'exploitation. L'information dynamique concernant les conditions de trafic permet aux usagers de réduire l'inconfort et d'effectuer leur choix d'itinéraire de manière plus raisonnable. Pour l'exploitant, le service d'information aux usagers peut servir à la gestion du trafic. Nous avons étudié la contribution potentielle de l'information dynamique au profit individuel des usagers et à la performance collective du système en prenant en compte : i) la congestion récurrente et non-récurrente ; ii) des différents comportements de choix d'itinéraire en fonction de l'accessibilité à l'information ; iii) d'autres actions de gestion du trafic menées par l'exploitant. Un modèle théorique avec une application analytique sur un réseau élémentaire de deux routes parallèles, une paire origine-destination et deux classes d'usagers respectivement informée ou non-informée nous a permis de retirer de nombreuses indications : i) la diffusion excessive de l'information avec un contenu " neutre " dégrade à la fois le profit individuel et la performance du système ; ii) l'information dynamique avec certain contenu " coopératif " peut contribuer l'optimisation du système sans causer le problème d'acceptabilité ; iii) l'information dynamique et d'autres mesures de gestion dynamique s'interagissent de manière complémentaire à l'optimisation du trafic