Mesoporous materials constitute a promising class of nanomaterials for a number of applications due to their tunable pore structure. The synthesis of most mesoporous materials involves a surfactant liquid crystal structure to form the pores. As well as the many advantages associated with this method of synthesis, there are disadvantages such as high production costs and a substantial environmental impact which limit the possibilities for large scale production. Therefore there is a need for other synthesis routes. The aim of the work described herein was to contribute to this field by developing a synthesis route that does not rely on surfactants for pore formation. A mesoporous magnesium carbonate material was therefore formed by self-assemblage of the particles around carbon dioxide gas bubbles, which functioned as pore templates. It was also possible to vary the pore diameter between 3 and 20 nm. The biocompatibility of the formed magnesium carbonate material was evaluated in terms of in vitro cytotoxicity and hemocompatibility, in vivo skin irritation and acute systemic toxicity. The results from the in vitro cytotoxicity, in vivo skin irritation and acute systemic toxicity test using a polar extraction vehicle showed that the material was non-toxic. While signs of toxicity were observed in the acute systemic toxicity test using a non-polar solvent, this was attributed to injection of particles rather than toxic leachables. In the in vitro hemocompatibility test, no hemolytic activity was found with material concentrations of up to 1 mg/ml. It was further shown that the material had anticoagulant properties and induced moderate activation of the complement system. The anticoagulant properties were ascribed to uptake of Ca2+. Finally, the ability of the material to increase the dissolution rate of the poorly soluble drug itraconazole was analyzed.  Itraconazole was dissolved up to 23 times faster from the magnesium carbonate pores than when the free drug was used. The release rate from the delivery vehicle was dependent on the pore diameter. The work presented herein is expected to be useful for the development of alternative synthesis routes for mesoporous materials and also for encouraging the development of biomedical applications for these materials.

Neste trabalho desenvolvemos um procedimento simples para a separação de nanoesferas ocas de carbono (do inglês Carbon Spherical Shells ou CSS) em diâmetros entre 400 e 500 nm utilizando centrifugação corroborado pelas análises realizadas na microscopia eletrônica de varredura e de transmissão. A análise de sua composição química, realizada através da técnica de fotoelétrons excitados por raios X, indicou que as CSS são constituídas de 79% de carbono e 21% de oxigênio em sua superfície, apresentando grupos funcionais carbonila e hidroxila. Plataformas sensoriais distintas foram obtidas formando filmes homogêneos das CSS sobre o eletrodo de carbonno vítreo GCE (do inglês glassy carbon electrode ou GCE). Como resultado dos experimentos eletroanalíticos, observou-se o aumento da sensitividade do eletrodo GCE/CSS de acordo com a diminuição do diâmetro (500 até 400 nm) das CSS. As plataformas sensoriais GCE/CSS com 400 nm de diâmetro apresentaram maior sensitividade (0.02 μA µmol L-1) com um limite detecção de 0.2 μmol L-1. Os eletrodos GCE/CSS foram estáveis, apresentando pequena interferência de espécies concomitantes presentes na amostra e seu desempenho na quantificação de paracetamol em suor mostrou-se estatisticamente equivalente ao método padrão baseado em cromatografia líquida. / We applied a simple strategy, based upon centrifugation, to separate carbon spherical shells (CSS), in sizes varying from 400 to 500 nm, which is shown by the micrographs obtained in the Scanning and Transmission Electron microscopy analysis. In their surface, carbonyl and hydroxyl groups were present, constituting a composition of 21% of oxygen and 79% of carbon. The CSS were casted on a glassy carbon electrode\'s (GCE) surface, forming a thin film, and the resulting platform was used as a sensor. A trend was observed in the results obtained by the electroanalytical experiments: as the size of the CSS were reduced, the sensibility of the GCE/CSS platform towards paracetamol detection increased. The best attained result, namely the platform with the GCE and the 400 nm diameter CSS, have shown promising results, achieving sensitivity\'s value of 0.02 μA μmol-1 L. The proposed sensors were stable, displaying little interference from another species coexisting in the samples, and its performance towards paracetamol detection were statistically identical to the standard method for paracetamol detection based upon liquid chromatography.

Neste trabalho desenvolvemos um procedimento simples para a separação de nanoesferas ocas de carbono (do inglês Carbon Spherical Shells ou CSS) em diâmetros entre 400 e 500 nm utilizando centrifugação corroborado pelas análises realizadas na microscopia eletrônica de varredura e de transmissão. A análise de sua composição química, realizada através da técnica de fotoelétrons excitados por raios X, indicou que as CSS são constituídas de 79% de carbono e 21% de oxigênio em sua superfície, apresentando grupos funcionais carbonila e hidroxila. Plataformas sensoriais distintas foram obtidas formando filmes homogêneos das CSS sobre o eletrodo de carbonno vítreo GCE (do inglês glassy carbon electrode ou GCE). Como resultado dos experimentos eletroanalíticos, observou-se o aumento da sensitividade do eletrodo GCE/CSS de acordo com a diminuição do diâmetro (500 até 400 nm) das CSS. As plataformas sensoriais GCE/CSS com 400 nm de diâmetro apresentaram maior sensitividade (0.02 μA µmol L-1) com um limite detecção de 0.2 μmol L-1. Os eletrodos GCE/CSS foram estáveis, apresentando pequena interferência de espécies concomitantes presentes na amostra e seu desempenho na quantificação de paracetamol em suor mostrou-se estatisticamente equivalente ao método padrão baseado em cromatografia líquida. / We applied a simple strategy, based upon centrifugation, to separate carbon spherical shells (CSS), in sizes varying from 400 to 500 nm, which is shown by the micrographs obtained in the Scanning and Transmission Electron microscopy analysis. In their surface, carbonyl and hydroxyl groups were present, constituting a composition of 21% of oxygen and 79% of carbon. The CSS were casted on a glassy carbon electrode\'s (GCE) surface, forming a thin film, and the resulting platform was used as a sensor. A trend was observed in the results obtained by the electroanalytical experiments: as the size of the CSS were reduced, the sensibility of the GCE/CSS platform towards paracetamol detection increased. The best attained result, namely the platform with the GCE and the 400 nm diameter CSS, have shown promising results, achieving sensitivity\'s value of 0.02 μA μmol-1 L. The proposed sensors were stable, displaying little interference from another species coexisting in the samples, and its performance towards paracetamol detection were statistically identical to the standard method for paracetamol detection based upon liquid chromatography.

During this study, the correlation between the evolution of the prior austenitic grain size and of the precipitation state during thermal treatment performed on steels is presented. To do this, the precipitation state has been finely characterized. Precipitate volume fractions were measured by plasma spectroscopy. Transmission Electron Microscopy (TEM) was used to determine the precipitate size distributions (HAADF images) and the precipitate chemical composition (EDX, EELS for carbon and nitrogen). In order to treat ELLS spectra obtained on complex carbonitrides (V,Nb,Ti)(C,N), a routine based on the Least Mean square Fitting have been developed. Results obtained with this method are in gopd agreement with those obtained by EDX analysis for metallic elements (Nb, V, Ti, ...). Then, grain size distributions were determined using a special etching called "Bechet-Beaujard", which reveals the prior austenite grain boundaries. Two alloys have been characterized in this study. (i) A model alloy, the FeVNbCN, which presents two precipitate types, NbC and VCN. This alloy was chosen to study the role of nitrogen on the precipitation state during reversion treatments. A model predicting the precipitation kinetics, coupled with a model for grain growth, give a good agreement with experimental results on grain sizes, precipitate sizes and on precipitate volume fraction. (ii) An industrial steel, the 16MnCr5+Nb was also studied. This alloy exhibits the presence of AlN and NbC precipitates. The correlation obtained between the Prior Austenite Grain Size and the evolution of the precipitation state shows that a large volume fraction of small precipitates allows a great pinning of grain boundaries. Finally, during thermo-mechanical treatments performed in the industry, some large grains may grow faster than smaller grains, leading to the so-called abnormal grain growth. This kind of growth can lead to undesirable mechanical instabilities. We have developed a criterium for abnormal grain growth which predicts the risk of such growth for a given precipitation state. This model presents a good agreement with all experimental results for both studied alloys.

The optical and chemical properties of the materials used in catalytic and sensing applications directly determine the characteristics of the resultant catalyst or sensor. It is well known that a catalyst needs to have high activity, selectivity, and stability to be viable in an industrial setting. The hydrogenation activity of palladium catalysts is known to be excellent, but the industrial applications are limited by the cost of obtaining catalyst in amounts large enough to make their use economical. As a result, alloying palladium with a cheaper, more widely available metal while maintaining the high catalytic activity seen in monometallic catalysts is, therefore, an attractive option. Similarly, the optical properties of nanoscale materials used for sensing must be attuned to their application. By adjusting the shape and composition of nanoparticles used in such applications, very fine changes can be made to the frequency of light that they absorb most efficiently. The design, synthesis, and characterization of (i) size controlled monometallic palladium nanoparticles for catalytic applications, (ii) nickel-palladium bimetallic nanoparticles and (iii) silver-palladium nanoparticles with applications in drug detection and biosensing through surface plasmon resonance, respectively, will be discussed. The composition, size, and shape of the nanoparticles formed were controlled through the use of wet chemistry techniques. After synthesis, the nanoparticles were analyzed using physical and chemical characterization techniques such as X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM), and Scanning Transmission Electron Microscopy- Energy-Dispersive Spectrometry (STEM-EDX). The Pd and Ni-Pd nanoparticles were then supported on silica for catalytic testing using mass spectrometry. The optical properties of the Ag-Pd nanoparticles in suspension were further investigated using ultraviolet-visible spectrometry (UV-Vis). Monometallic palladium particles have been synthesized and characterized to establish the effects of nanoparticle size on catalytic activity in methanol decomposition. The physicochemical properties of the synthesized palladium-nickel nanoparticles will be discussed, as a function of the synthesis parameters. The optical characteristics of the Ag and Pd nanoparticles will be determined, with a view toward tuning the response of the nanoparticles for incorporation in sensors. Analysis of the monometallic palladium particles revealed a dependence of syngas production on nanoparticle size. The peak and steady state TOFs increased roughly linearly with the average nanoparticle diameter. The amount of coke deposited on the particle surfaces was found to be independent on the size of the nanoparticles. Shape control of the nickel-palladium nanoparticles with a high selectivity for (100) and (110) facets (≤ 80%) has been demonstrated. The resulting alloy nanoparticles were found to have homogeneous composition throughout their volume and maintain FCC crystal structure. Substitution of Ni atoms in the Pd lattice at a 1:3 molar ratio was found to induce lattice strains of ~1%. The Ag nanocubes synthesized exhibited behavior very similar to literature values, when taken on their own, exhibiting a pair of distinct absorbance peaks at 350 nm and 455 nm. In physical mixtures with the Pd nanoparticles synthesized, their behavior showed that the peak position of the Ag nanocubes' absorbance in UV-Vis could be tuned based on the relative proportions of the Ag and Pd nanoparticles present in the suspension analysed. The Ag polyhedra synthesized for comparison showed a broad doublet peak throughout the majority of the visible range before testing as a component in a physical mixture with the Pd nanoparticles. The addition of Pd nanoparticles to form a physical mixture resulted in some damping of the doublet peak observed as well as a corresponding shift in the baseline absorbance proportional to the amount of Pd added to the mixture.

This paper studies Newton's method for solving the algebraic Riccati equation combined with an exact line search. Based on these considerations we present a Newton{like method for solving algebraic Riccati equations. This method can improve the sometimes erratic convergence behavior of Newton's method.

A complex network of genes and proteins governs the robust progression through cell cycles in the presence of inevitable noise. Stochastic modeling is viewed as a key paradigm to study the effects of intrinsic and extrinsic noise on the dynamics of biochemical networks. A detailed quantitative description of such complex and multiscale networks via stochastic modeling poses several challenges. First, stochastic models generally require extensive computations, particularly when applied to large networks. Second, the accuracy of stochastic models is highly dependent on the quality of the parameter estimation based on experimental observations. The goal of this dissertation is to address these problems by developing new efficient methods for modeling and simulation of stochastic effects in biochemical systems. Particularly, a hybrid stochastic model is developed to represent a detailed molecular mechanism of cell cycle control in budding yeast cells. In a single multiscale model, the proposed hybrid approach combines the advantages of two regimes: 1) the computational efficiency of a deterministic approach, and 2) the accuracy of stochastic simulations. The results show that this hybrid stochastic model achieves high computational efficiency while generating simulation results that match very well with published experimental measurements. Furthermore, a new hierarchical deep classification (HDC) algorithm is developed to address the parameter estimation problem in a monomolecular system. The HDC algorithm adopts a neural network that, via multiple hierarchical search steps, finds reasonably accurate ranges for the model parameters. To train the neural network in the presence of experimental data scarcity, the proposed method leverages the domain knowledge from stochastic simulations to generate labeled training data. The results show that the proposed HDC algorithm yields accurate ranges for the model parameters and highlight the potentials of model-free learning for parameter estimation in stochastic modeling of complex biochemical networks. / Doctor of Philosophy / Cell cycle is a process in which a growing cell replicates its DNA and divides into two cells. Progression through the cell cycle is regulated by complex interactions between networks of genes, transcripts, and proteins. These interactions inside the confined volume of a cell are subject to inherent noise. To provide a quantitative description of the cell cycle, several deterministic and stochastic models have been developed. However, deterministic models cannot capture the intrinsic noise. In addition, stochastic modeling poses the following challenges. First, stochastic models generally require extensive computations, particularly when applied to large networks. Second, the accuracy of stochastic models is highly dependent on the accuracy of the estimated model parameters. The goal of this dissertation is to address these challenges by developing new efficient methods for modeling and simulation of stochastic effects in biochemical networks. The results show that the proposed hybrid model that combines stochastic and deterministic modeling approaches can achieve high computational efficiency while generating accurate simulation results. Moreover, a new machine learning-based method is developed to address the parameter estimation problem in biochemical systems. The results show that the proposed method yields accurate ranges for the model parameters and highlight the potentials of model-free learning for parameter estimation in stochastic modeling of complex biochemical networks.

Les liquides ioniques (LIs) à base d’imidazolium présentent une très grande organisation en réseaux 3D et sont constitués de microdomaines polaires et apolaires, dû à la présence des canaux ioniques et au regroupement des chaînes alkyles lipophiles. L’objectif de ce travail est d’utiliser leurs propriétés de solvatation, liées à cette organisation, pour générer et stabiliser in situ des nanoparticules métalliques (NPs) d’une taille contrôlée et prévisible. Cette approche a trouvé de nombreuses applications dans des domaines tels que la catalyse et la microélectronique. Le phénomène de croissance cristalline des NPs (ruthénium, nickel et tantale) générées in situ lors de la décomposition sous H2 des complexes organométalliques, est contrôlé i) par la taille des poches apolaires, dans lesquelles le complexe se dissout, ii) par les conditions expérimentales (température, agitation) et iii) par la nature du métal et du complexe précurseur. Le mécanisme de stabilisation des NPs, jusqu'alors mal compris, dépend du mécanisme de formation des NPs, qui pourrait entraîner la présence de ligands hydrures ou carbènes N-hétérocycliques (NHC) à leur surface. Cette présence a été démontrée par marquage isotopique et analysée en RMN ainsi qu’en spectrométrie de masse. Les LIs sont également des milieux intéressants en catalyse. Des études sur l’influence du LI sur l’activité des catalyseurs homogènes ont souligné l’importance cruciale des paramètres physico-chimiques des LIs, et particulièrement de la viscosité, qui intervient ainsi dans la loi cinétique. Enfin, une étude approfondie de l’effet de la taille des NPs sur l’activité catalytique et la sélectivité pour l’hydrogénation, réalisée en milieu LI, a confirmé l’importance du contrôle de la taille des NPs pour les applications catalytiques / Imidazolium based ionic liquids (ILs) consist of a continuous 3-D network of ionic channels, coexisting with non polar domains created by the grouping of lipophilic alkyl chains, forming dispersed or continuous microphases. The aim of this work is to use the specific solvation properties of ILs, related to this 3-D organisation, to generate and stabilise in situ metal nanoparticles (NPs) of a controlled and predictable size. This approach has found application in fields such as catalysis and microelectronics. The phenomenon of crystal growth of NPs (ruthenium, nickel, tantalum) generated in situ in ILs from the decomposition of organometallic complexes under molecular hydrogen, is found not only to be controlled by i) the size of non-polar domains, in which the complexes dissolve, but also by ii) the experimental conditions (temperature, stirring) and iii) the nature of the metal and its precursor complex. The previously unexplained stabilisation mechanism of NPs in ILs is found to depend on the mechanism of formation of NPs, which may lead to the presence of either hydrides or N-heterocyclic carbenes (NHC) at their surface. These have both been evidenced through isotopic labelling experiments analysed by NMR and mass spectrometry. Another advantage of ILs is that they provide an interesting medium for catalytic reactions. Studies on the influence of the IL on the catalytic performance in homogeneous catalysis have highlighted the crucial importance of the physical-chemical parameters of ILs, in particular the viscosity, for which a term must be included in the kinetic rate law. Using these findings, a thorough investigation of the effect of the NP size on catalytic activity and selectivity in hydrogenation in ILs was undertaken, confirming the importance of controlling NP size for catalytic applications.

grainy head (grh) genes encode a family of transcription factors conserved from fly to human. Drosophila grh is the founding member of this gene family and has multiple functions, including tracheal tube size control, epidermal barrier formation and reconstruction after wounding. To understand the underlying molecular mechanism of grh functions, we tried to isolate its direct targets and analyze their function. We identified ten grh targets by combining bioinformatics and genetics. Grh directly controls the expression of stitcher (stit), which encodes a Ret family receptor tyrosine kinase (RTK), during both development and wound healing. Stit promotes actin cable assembly and induces extracellular signal-regulated kinase (ERK) phosphorylation around the wound edges upon injury. Stit also activates barrier repair genes and its own expression at the wound sites in a Grh-dependent manner. This positive feedback loop ensures efficient epidermal wound repair. In addition, Grh regulates the expression of multiple genes involved in chitin biosynthesis or modification. Most of the genes are required for tracheal tube size control. Two of them, verm and serp, encode related putative luminal chitin deacetylases. The functional analysis of verm and serp identifies an important role of luminal chitin matrix modification in limiting tracheal tube elongation. Therefore, it is very likely that Grh controls tracheal tube size through regulating multiple targets involved in the assembly or modification of luminal chitin matrix. Grh also directly activates the epidermal expression of Peptidoglycan recognition protein LC (PGRP-LC) gene that is required for the induction of antimicrobial peptides (AMPs) upon infection. Furthermore, ectopically expressing Grh is sufficient to induce AMP Cecropin A lacZ reporter (CecA-LacZ) in the embryonic epidermis. These results suggest a new function of Grh in the local immune responses in Drosophila barrier epithelia. / At the time of the doctoral defense, the following papers was unpublished and had a status as follows: Paper 1: Manuscript.

The objective of this research is to presents new acoustic echo cancellation design methods that can effectively work in the nonlinear environment. Acoustic echo is an annoying issue for voice communication systems. Because of room acoustics and delay in the transmission path, echoes affect the sound quality and may hamper communications. Acoustic echo cancellers (AECs) are employed to remove the acoustic echo while keeping full-duplex communications. AEC designs face a variety of challenges, including long room impulse response, acoustic path nonlinearity, ambient noise, and double-talk situation. We investigate two parts of echo canceller design: echo cancellation algorithm design and control logic algorithm design. In the first part, our work focuses on the nonlinear adaptive and fast-convergence algorithms. We investigate three different structures: predistortion linearization, cascade structure, and nonlinear residual echo suppressor. Specifically, we are interested in the coherence function, since it provides a means for quantifying linear association between two stationary random processes. By using the coherence as a criterion to design the nonlinear echo canceller in the system, our method guarantees the algorithm stability and leads to a faster convergence rate. In the second part, our work focuses on the robustness of AECs in the presence of interference. With regard to the near-end speech, we investigate the double-talk detector (DTD) design in conjunction with nonlinear AECs. Specifically, we propose to design a DTD based on the mutual information (MI). We show that the advantage of the MI-based method, when compared with the existing methods, is that it is applicable to both the linear and nonlinear scenarios. With respect to the background noise, we propose a variable step-size and variable tap-length least mean square (LMS) algorithm. Based on the fact that the room impulse response usually exhibits an exponential decay power profile in acoustic echo cancellation applications, the proposed method finds optimal step size and tap length at each iteration. Thus, it achieves faster convergence rate and better steady-state performance. We show a number of experimental results to illustrate the performance of the proposed algorithms.