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The addition of coarse particles to a flocculating fine particle slurry increases the Bingham yield stress of the resulting mixture, which can drastically alter the laminar-to-turbulent transition velocity. The objective of this study is to quantify the effect of coarse particle size and volume concentration on mixture rheology. Fine particle (kaolin) mixtures of 10% to 22% (by volume) were prepared, to which sand particles were added to provide a coarse solid concentration of 5% to 20% (by volume). Sand particles of two different sizes – 90 and 190 microns – were added and these kaolin-sand-water mixtures tested with a concentric cylinder viscometer. At higher total solids concentrations, the Bingham yield stress of the bimodal mixture can increase by as much as 80% over that of a kaolin-only slurry. Coarse particle diameter had little effect. This study demonstrates that the use of existing correlations should be eschewed. System-specific high-quality measurements are necessary. / Chemical Engineering

Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (leaves 124-142).

Thesis (M.S.)--Oregon State University, 1989. / Typescript (photocopy). Includes bibliographical references. Also available on the World Wide Web.

Thesis (Ph. D.)--Oregon State University, 2006. / Printout. Includes bibliographical references (leaves 161-174). Also available on the World Wide Web.

Proteínas desempenham uma grande variedade de funções biológicas. O conhecimento da estrutura tridimensional proteica pode ajudar no entendimento da função desempenhada. De acordo com a hipótese de Anfisen, a estrutura terciária nativa de uma proteína pode ser determinada a partir da informação contida na sequência primária, o que permitiria que métodos computacionais poderiam ser usados para predizer estruturas terciárias quando a primária estiver disponível. No entanto, ainda não existe uma ferramenta computacional capaz de predizer a estrutura tridimensional para uma grande variedade de proteínas. Desse modo, o problema de Predição de Estruturas de Proteínas (PEP) permanece como um desafio para a Biologia Molecular. A conformação nativa de uma proteína é frequentemente a configuração termodinamicamente mais estável, ou seja, que possui menor energia livre. Assim, PEP pode ser vista como um problema de otimização, onde a estrutura com menor energia livre deve ser encontrada dentre todas as possíveis. Entretanto, este é um problema NP-completo, no qual métodos tradicionais de otimização, em geral, não apresentam um bom desempenho. Algoritmos Genéticos (AGs), devido às suas características, são interessantes para essa classe de problemas. O principal objetivo desse trabalho é verificar se a adição de informação pode ser útil aos AGs aplicados em PEP, valendo-se dede modelos moleculares simplificados. Cada indivíduo do AG representa uma solução que, neste caso, é uma possível conformação que será avaliada por um campo de força. Dessa forma, o indivíduo é codificado por um conjunto de ângulos de torção de cada aminoácido. Para auxiliar no processo de busca, bases de dados compostas de ângulos determinados por cristalografia e RNM são utilizadas. Com o objetivo de guiar o processo de busca e manter a diversidade nos AGs, duas estratégias são aqui testadas: Imigrantes Aleatórios e Imigrantes por Similaridade. A última delas foi criada baseando-se na similaridade da sequência primária. Além disso, é investigado neste trabalho o uso de um campo de força coarse grained, que utiliza os átomos de carbono- para representar a cadeia proteica, para avaliar os indivíduos do AG. / Proteins exhibit an enormous variety of biology functions. The knowledge of tertiary structures can help the understanding of the proteins function. According to Anfisen, the native tertiary structure of a protein can be determined by its primary structure information, what could allow that computational methods could be used to predict the tertiary structure when the primary structure is available. However, there is still not a computational tool to solve the structure prediction problem for a large range of proteins. In this way, Protein Structure Prediction (PSP) has been a challenge to Molecular Biology. The conformation of native protein is usually the thermodynamically most stable configuration, i.e., the one having the lowest free energy. Hence, PSP can be viewed as a problem of optimization, where the structure with the lowest free energy should be found among all possible structures. However, this is an NP-problem, where traditional optimization methods, in general, do not have good performance. Genetic algorithms (GAs), due to their characteristics, are interesting for this class of problems. In recent years, there is a growing interest in using GAs for the protein structure prediction problem. The main objective of this work is to verify the addition of useful information to GAs employed in PSP. Each individual of the GA represents a solution for the optimization problem which is, in this case, a possible conformation that will be evaluated by a force field function. Thus, an individual is encoded by a set of torsion angles of each amino acid. In order to reduce the search space, a database composed of angles, determined by crystallography and NMR, is used. With the aim to guide the final search process and maintain diversity in GAs, two strategies were employed here: Random Immigrants and Similarity-based Immigrants. The last strategy was based on similarity of primary amino acid sequence. Furthermore, in this work, a coarse-grained force field, which uses -carbon to represent the protein backbone was employed to evaluate the individuals of GA.

Dans le noyau des cellules eucaryotes, l’ADN s’enroule autour d’histones pour former des nucléosomes, lesquels s’arrangent à leur tour en une fibre compacte et dynamique appelée chromatine. Les propriétés physiques de cette fibre aux différentes échelles, depuis la double-hélice de l’ADN jusqu’aux chromosomes micrométriques, sont essentielles aux mécanismes complexes de l’expression des gènes et sa régulation. La présente thèse est une contribution audéveloppement de modèles physiques capables de relier les différentes échelles, et d’interpréter et d’intégrer des données provenant d’une large gamme d’approches expérimentales et numériques. En premier lieu, nous utilisons des simulations de dynamique moléculaire d’oligomères d’ADN pour étudier l’ADN double-hélical à différentes températures. Nous estimons la contribution séquence-dépendante de l’entropie à l’élasticité de l’ADN, en lien avec des expériencesrécentes sur la longueur de persistence de l’ADN. En second lieu, nous modélisons les interactions ADN-histones au sein du Nucleosome Core Particle. Nous utilisons la nanomécanique de l’ADN afin d’extraire un champ de force d’un ensemble de structures cristallographiques du nucléosome et de données de dynamique moléculaire. En troisième lieu, nous étudions la partie plus molle du nucléosome, l’ADN linker entre les core particles, qui s’associe transitoirement à l’histone H1 pour former un “stem”. Nous combinons des informations structurales existantes avec des données expérimentales à deux résolutions différentes (DNA footprinting et électro-microscopie) afin de développer un modèle de stem à l’échelle nanométrique. / In the nucleus of eukaryotic cells, DNA wraps around histone proteins to form nucleosomes, which in turn associate in a compact and dynamic fiber called chromatin. The physical properties of this fiber at different lengthscales, from the DNA double-helix to micrometer-sized chromosomes, are essential to the complex mechanisms of gene expression and its regulation. The present thesis is a contribution to the development of physical models, which are able to link different scales and to interpret and integrate data from a wide range of experimental and computational approaches. In the first part, we use Molecular Dynamics simulations of DNA oligomers to study doublehelical DNA at different temperatures. We estimate the sequence-dependent contribution of entropy to DNA elasticity, in relation with recent experiments on DNA persistence length. In the second part, we model the DNA-histone interactions within the nucleosome core particle,using DNA nanomechanics to extract a force field from a set of crystallographic nucleosome structures and Molecular Dynamics snapshots. In the third part, we consider the softer part of the nucleosome, the linker DNA between coreparticles which transiently associates with the histone H1 to form a “stem”.We combine existing structural knowledge with experimental data at two different resolutions (DNA footprints and electro-micrographs) to develop a nanoscale model of the stem.

京都大学 / 新制・課程博士 / 博士(理学) / 甲第22978号 / 理博第4655号 / 新制||理||1669(附属図書館) / 京都大学大学院理学研究科数学・数理解析専攻 / (主査)准教授 照井 一成, 教授 長谷川 真人, 准教授 河村 彰星 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM

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