Thesis (B.S.)--Butler University, 2007. / Includes bibliographical references (leaf 52).

abstract: Counterfeiting of goods is a widespread epidemic that is affecting the world economy. The conventional labeling techniques are proving inadequate to thwart determined counterfeiters equipped with sophisticated technologies. There is a growing need of a secure labeling that is easy to manufacture and analyze but extremely difficult to copy. Programmable metallization cell technology operates on a principle of controllable reduction of a metal ions to an electrodeposit in a solid electrolyte by application of bias. The nature of metallic electrodeposit is unique for each instance of growth, moreover it has a treelike, bifurcating fractal structure with high information capacity. These qualities of the electrodeposit can be exploited to use it as a physical unclonable function. The secure labels made from the electrodeposits grown in radial structure can provide enhanced authentication and protection from counterfeiting and tampering. So far only microscale radial structures and electrodeposits have been fabricated which limits their use to labeling only high value items due to high cost associated with their fabrication and analysis. Therefore, there is a need for a simple recipe for fabrication of macroscale structure that does not need sophisticated lithography tools and cleanroom environment. Moreover, the growth kinetics and material characteristics of such macroscale electrodeposits need to be investigated. In this thesis, a recipe for fabrication of centimeter scale radial structure for growing Ag electrodeposits using simple fabrication techniques was proposed. Fractal analysis of an electrodeposit suggested information capacity of 1.27 x 1019. The kinetics of growth were investigated by electrical characterization of the full cell and only solid electrolyte at different temperatures. It was found that mass transport of ions is the rate limiting process in the growth. Materials and optical characterization techniques revealed that the subtle relief like structure and consequently distinct optical response of the electrodeposit provides an added layer of security. Thus, the enormous information capacity, ease of fabrication and simplicity of analysis make macroscale fractal electrodeposits grown in radial programmable metallization cells excellent candidates for application as physical unclonable functions. / Dissertation/Thesis / Masters Thesis Materials Science and Engineering 2017

In everyday situations individuals make decisions. For example, a tourist usually chooses a crowded or recommended restaurant to have dinner. Perhaps it is an individual decision, but the observed pattern of decision-making is a collective phenomenon. Collective behaviour emerges from the local interactions that give rise to a complex pattern at the group level. In our example, the recommendations or simple copying the choices of others make a crowded restaurant even more crowded. The rules of interaction between individuals are important to study. Such studies should be complemented by biological experiments. Recent studies of collective phenomena in animal groups help us to understand these rules and develop mathematical models of collective behaviour. The most important communication mechanism is positive feedback between group members, which we observe in our example. In this thesis, we use a generic experimentally validated model of positive feedback to study collective decision-making. The first part of the thesis is based on the modelling of decision-making associated to the selection of feeding sites. This has been extensively studied for ants and slime moulds. The main contribution of our research is to demonstrate how such aspects as "irrationality", speed and quality of decisions can be modelled using differential equations. We study bifurcation phenomena and describe collective patterns above critical values of a bifurcation points in mathematical and biological terms. In the second part, we demonstrate how the primitive unicellular slime mould Physarum Polycephalum provides an easy test-bed for theoretical assumptions and model predictions about decision-making. We study its searching strategies and model decision-making associated to the selection of food options. We also consider the aggregation model to investigate the fractal structure of Physarum Polycephalum plasmodia. / <p>Fel serie i tryckt bok /Wrong series in the printed book</p>

Príons são patógenos infecciosos que causam um grupo de doenças neurodegenerativas fatais. A proteína normal, PrP celular, denominada PrPC, é convertida em PrPSc, isoforma anormal e patogênica de PrP, através de um processo no qual uma porção de -hélice da estrutura é reenovelada em folhas . A conversão de PrPC em PrPSc ocorre por um mecanismo auto-catalítico. Para um melhor entendimento do mecanismo de propagação dos príons, têm sido propostos vários modelos matemáticos. Nesse trabalho, estudamos o tempo de incubação de algumas doenças causadas por príons: Encefalopatia Espongiforme Bovina (BSE), ou mal da vaca louca; doença variante de Creutzfeldt-Jakob (vCJD), que afeta humanos, através da exposição ao agente de BSE; e Scrapie murina, uma infecção priônica experimental em camundongos. A distribuição de probabilidades da duração do período de incubação foi suposta ser lognormal, modelo este extensamente aceito em doenças infecciosas. Os objetivos desse trabalho foram esclarecer aspectos obscuros sobre a cinética de replicação priônica e o mecanismo de toxicidade das doenças priônicas, através de comparação dos resultados de simulações computacionais com os perfis de distribuição de tempos de incubação de BSE, vCJD e Scrapie murina. Foram realizadas simulações computacionais, utilizando o Método Monte Carlo Dinâmico (MCD) e o modelo Difusão Limitada à Agregação. Primeiramente, estudamos o modelo de Eigen (1996), através de simulações computacionais usando o MCD, para verificar quais termos são importantes para a cinética priônica. De posse desse resultado, partimos então para o estudo sobre a toxicidade das doenças priônicas, usando o modelo DLA e o método MCD: considerando que PrPC se converte em PrPSc quando existe contato (auto-catálise); e PrPCs são livres e podem se movimentar por uma rede, enquanto PrPScs, ou agregados de PrPScs são fixos. Confirmamos a suspeita de Eigen de que o termo mais importante nas equações de cinética priônica é o termo de Michaelis-Menten, ou termo auto-catalítico. Os resultados obtidos através das simulações MCD e modelo DLA foram comparados com os perfis de distribuições de tempos dessas doenças (BSE, vCJD e Scrapie murina). Conseguimos o ajuste de diferentes perfis de distribuição de tempos de incubação para algumas doenças priônicas, lognormal para BSE e vCJD, e lognormal com segundo pico para Scrapie murina. A auto-catálise é o mecanismo mais importante na cinética priônica, a conversão espontânea de PrPC em PrPSc pode ser negligenciada. A partir do modelo DLA, fica reforçada a hipótese de que para BSE e vCJD, doenças priônicas de ocorrência natural, a toxicidade é causada, principalmente, pela formação das placas amilóides. Para Scrapie murina, uma infecção experimentalmente induzida, a toxicidade é, possivelmente, causada por dois mecanismos: formação das placas amilóides e depleção de PrPC. Apenas com a mudança dos parâmetros iniciais e finais, conseguimos ajustar as distribuições de tempos de incubação das três doenças priônicas estudadas, apesar de o modelo ser bastante simples. A lognormalidade, de acordo com o modelo, é resultado do processo difusivo. As concentrações de PrPC devem ser baixas, menores que 1% e o número de PrPScs deve ser menor que 10 para que a lognormalidade ocorra sem a depleção de PrPC. / Prions are infectious agents responsible for a group of fatal neurodegenerative disorders. A pathogenic isoform of the prion protein (PrPSc) generated by a posttranslational process involving the conversion of alpha helices into beta sheets of the normal cellular prion protein (PrPC) is believed to be the main component of these infectious agents. The conversion of a normal PrPC into an abnormal isoform PrPSc, kinetically follows through an autocatalytic process. For better understanding of this kind of abnormal protein propagation, many analytical models have been proposed. Thus, we studied, using the Monte Carlo method, the distribution of the incubation periods in some of these neurodegenerative disorders, such as: bovine spongiform encephalopathy well known as mad cow disease (BSE), Variant Creutzfeldt Jakob disease (vCJD) and murine scrapie, an experimental murine prionic disease. The distribution of the incubation times of these diseases were considered lognormal. The aim of this study was to investigate some aspects of toxicity and replication of the prionic diseases, by comparing the results of computational simulations with the incubation times of BSE, vCJD and murine scrapie, previously established. Computational simulations, using a Dynamical Monte Carlo method (DMC) and the diffusion limited aggregation model (DLA), were worked out. At first, we evaluate the Eigen model through computational simulations using the DMC to verify the essential parameters in the kinetic of the prionic diseases. Following the results, we studied the toxicity of the prionic diseases using the DMC and the DLA model; by considering that PrPC converting in PrPSc just when exists contact (autocatalysis) and free PrPCs are allowed to diffuse randomly to their nearest neighbour sites in a square lattice, while isolated PrPScs or aggregate of PrPScs are fixed. Confirming the Eigen suspicion, the most important parameter in the equation of the prionic kinetic is the Michaelis Menten term (or the autocatalytic term). The results obtained through simulations using DMC and DLA model were compared with the time distribution profiles of the prionic diseases already established (BSE, vCJD and murine Scrapie). We get the fitting in different profiles of the distribution of the incubation periods (lognormal to BSE and vCJD and lognormal with a second peak to murine scrapie). It is concluded that autocatalysis is an essential mechanism for the prionic kinetics and the spontaneous conversion of PrPC in PrPSc can be neglected. Starting from the DLA model, is reinforced that the hypothesis for BSE and vCJD, prionic diseases of natural occurrence, the toxicity is caused, mainly, by the formation of amyloid plaques. For Scrapie murina, an experimentally induced infection, the toxicity is, possibly, caused by two mechanisms: formation of amyloid plaques and depletion of PrPC. Just with the change of the initial and final parameters, we fitted all studied prionic diseases, in spite of the model to be quite simple. The lognormality from the model, is resulting of a diffusive process. Concentrations of PrPC should be low, smaller than 1% and the number of PrPScs should be smaller than 10 for the lognormality take place without the depletion of PrPC.

Príons são patógenos infecciosos que causam um grupo de doenças neurodegenerativas fatais. A proteína normal, PrP celular, denominada PrPC, é convertida em PrPSc, isoforma anormal e patogênica de PrP, através de um processo no qual uma porção de -hélice da estrutura é reenovelada em folhas . A conversão de PrPC em PrPSc ocorre por um mecanismo auto-catalítico. Para um melhor entendimento do mecanismo de propagação dos príons, têm sido propostos vários modelos matemáticos. Nesse trabalho, estudamos o tempo de incubação de algumas doenças causadas por príons: Encefalopatia Espongiforme Bovina (BSE), ou mal da vaca louca; doença variante de Creutzfeldt-Jakob (vCJD), que afeta humanos, através da exposição ao agente de BSE; e Scrapie murina, uma infecção priônica experimental em camundongos. A distribuição de probabilidades da duração do período de incubação foi suposta ser lognormal, modelo este extensamente aceito em doenças infecciosas. Os objetivos desse trabalho foram esclarecer aspectos obscuros sobre a cinética de replicação priônica e o mecanismo de toxicidade das doenças priônicas, através de comparação dos resultados de simulações computacionais com os perfis de distribuição de tempos de incubação de BSE, vCJD e Scrapie murina. Foram realizadas simulações computacionais, utilizando o Método Monte Carlo Dinâmico (MCD) e o modelo Difusão Limitada à Agregação. Primeiramente, estudamos o modelo de Eigen (1996), através de simulações computacionais usando o MCD, para verificar quais termos são importantes para a cinética priônica. De posse desse resultado, partimos então para o estudo sobre a toxicidade das doenças priônicas, usando o modelo DLA e o método MCD: considerando que PrPC se converte em PrPSc quando existe contato (auto-catálise); e PrPCs são livres e podem se movimentar por uma rede, enquanto PrPScs, ou agregados de PrPScs são fixos. Confirmamos a suspeita de Eigen de que o termo mais importante nas equações de cinética priônica é o termo de Michaelis-Menten, ou termo auto-catalítico. Os resultados obtidos através das simulações MCD e modelo DLA foram comparados com os perfis de distribuições de tempos dessas doenças (BSE, vCJD e Scrapie murina). Conseguimos o ajuste de diferentes perfis de distribuição de tempos de incubação para algumas doenças priônicas, lognormal para BSE e vCJD, e lognormal com segundo pico para Scrapie murina. A auto-catálise é o mecanismo mais importante na cinética priônica, a conversão espontânea de PrPC em PrPSc pode ser negligenciada. A partir do modelo DLA, fica reforçada a hipótese de que para BSE e vCJD, doenças priônicas de ocorrência natural, a toxicidade é causada, principalmente, pela formação das placas amilóides. Para Scrapie murina, uma infecção experimentalmente induzida, a toxicidade é, possivelmente, causada por dois mecanismos: formação das placas amilóides e depleção de PrPC. Apenas com a mudança dos parâmetros iniciais e finais, conseguimos ajustar as distribuições de tempos de incubação das três doenças priônicas estudadas, apesar de o modelo ser bastante simples. A lognormalidade, de acordo com o modelo, é resultado do processo difusivo. As concentrações de PrPC devem ser baixas, menores que 1% e o número de PrPScs deve ser menor que 10 para que a lognormalidade ocorra sem a depleção de PrPC. / Prions are infectious agents responsible for a group of fatal neurodegenerative disorders. A pathogenic isoform of the prion protein (PrPSc) generated by a posttranslational process involving the conversion of alpha helices into beta sheets of the normal cellular prion protein (PrPC) is believed to be the main component of these infectious agents. The conversion of a normal PrPC into an abnormal isoform PrPSc, kinetically follows through an autocatalytic process. For better understanding of this kind of abnormal protein propagation, many analytical models have been proposed. Thus, we studied, using the Monte Carlo method, the distribution of the incubation periods in some of these neurodegenerative disorders, such as: bovine spongiform encephalopathy well known as mad cow disease (BSE), Variant Creutzfeldt Jakob disease (vCJD) and murine scrapie, an experimental murine prionic disease. The distribution of the incubation times of these diseases were considered lognormal. The aim of this study was to investigate some aspects of toxicity and replication of the prionic diseases, by comparing the results of computational simulations with the incubation times of BSE, vCJD and murine scrapie, previously established. Computational simulations, using a Dynamical Monte Carlo method (DMC) and the diffusion limited aggregation model (DLA), were worked out. At first, we evaluate the Eigen model through computational simulations using the DMC to verify the essential parameters in the kinetic of the prionic diseases. Following the results, we studied the toxicity of the prionic diseases using the DMC and the DLA model; by considering that PrPC converting in PrPSc just when exists contact (autocatalysis) and free PrPCs are allowed to diffuse randomly to their nearest neighbour sites in a square lattice, while isolated PrPScs or aggregate of PrPScs are fixed. Confirming the Eigen suspicion, the most important parameter in the equation of the prionic kinetic is the Michaelis Menten term (or the autocatalytic term). The results obtained through simulations using DMC and DLA model were compared with the time distribution profiles of the prionic diseases already established (BSE, vCJD and murine Scrapie). We get the fitting in different profiles of the distribution of the incubation periods (lognormal to BSE and vCJD and lognormal with a second peak to murine scrapie). It is concluded that autocatalysis is an essential mechanism for the prionic kinetics and the spontaneous conversion of PrPC in PrPSc can be neglected. Starting from the DLA model, is reinforced that the hypothesis for BSE and vCJD, prionic diseases of natural occurrence, the toxicity is caused, mainly, by the formation of amyloid plaques. For Scrapie murina, an experimentally induced infection, the toxicity is, possibly, caused by two mechanisms: formation of amyloid plaques and depletion of PrPC. Just with the change of the initial and final parameters, we fitted all studied prionic diseases, in spite of the model to be quite simple. The lognormality from the model, is resulting of a diffusive process. Concentrations of PrPC should be low, smaller than 1% and the number of PrPScs should be smaller than 10 for the lognormality take place without the depletion of PrPC.

La technique d’acquisition comprimée ou compressed sensing (CS) exploite la compressibilité de différents types d’images pour reconstruire des données sous-échantillonnées sans perte d’informations. Cette technique peut être appliquée à l’IRM pour réduire les temps d’acquisition. CS est basée sur trois composantes majeures : (1) la représentation parcimonieuse du signal dans un domaine de transformation, (2) des mesures incohérentes et (3) une méthode de reconstruction non-linéaire avec une contrainte de parcimonie. Dans la première résultats partie de cette thèse, nous proposons un nouveau modèle de sous-échantillonnage basé sur la théorie de l’agrégation limitée par la diffusion (DLA) et montrons qu’il est plus performant que la méthode de sous-échantillonnage aléatoire. Le modèle de sous-échantillonnage DLA a été utilisé pour implémenter la technique de CS pour l’imagerie haute résolution pondérée T2 et T1 sur un champ magnétique très intense (17.2T). Pour chacune des pondérations, le temps d’acquisition a été réduit de 50% tout en conservant la qualité des images en termes de résolution spatiale, rapport contraste sur bruit et quantification de l’intensité du signal. Les deux nouvelles séquences d’impulsions CS (csRARE et csFLASH) ont été implémentées sur le logiciel commercial ParaVision 5.1. La seconde résultats partie de la thèse est centrée sur l’étude de la dépendance en temps de la diffusivité dans le ganglion abdominal de l’Aplysia Californica. Le ganglion abdominal de l’aplysie a été choisi pour cette étude d’imagerie car l’IRM à haute résolution permet la description anatomique fine du réseau cellulaire (taille des neurones individuels et orientation des axones). Utiliser les tissus neuronaux de l’aplysie pour étudier la relation entre la structure cellulaire et le signal d’IRM de diffusion peut permettre de comprendre cette relation pour des organismes plus complexes. Le signal d’IRM de diffusion (IRMd) a été mesuré à différents temps de diffusion dans le ganglion abdominal et des simulations de la diffusion de l’eau dans des géométries obtenues à partir de la segmentation d’images haute résolution pondérées T2 et l’incorporation d’informations sur la structure cellulaire trouvées dans la littérature ont été réalisées. Pour comparer le signal d’IRMd dans des neurones composés d’une seule cellule avec le signal des simulations numériques, des cellules de grande taille ont été segmentées à partir d’images anatomiques pondérées T2. A l’intérieur des cellules, un noyau à forme irrégulière a été généré manuellement (environ 25-30% en fraction volumique). Les petites cellules ont été modélisées comme des petites sphères avec un petit noyau sphérique concentrique (environ 25% en fraction volumique). Le nerf a été modélisé en combinant des axones (cylindres) de différents diamètres en cohérence avec la littérature. Le signal numérique d’IRMd a été simulé en résolvant l’équation de Bloch-Torrey pour les domaines géométriques décris ci-dessus. En fittant le signal expérimental avec le signal simulé pour différents types de cellules comme les grandes cellules neuronales (diamètre entre 150 et 420 µm), des agrégats de petites cellules neuronales ayant la forme d’un sac (jusqu’à 400 cellule chez l’aplysie adulte dans chaque sac avec une taille cellulaire entre 40 et 100 µm de diamètre), des nerfs (groupes d’axones de forme cylindrique avec un diamètre de moins de 1 à 25 µm) pour une grande gamme de temps de diffusions, nous avons obtenu des estimations du coefficient de diffusion intrinsèque dans le noyau et le cytoplasme (pour les neurones) et le coefficient de diffusion intrinsèque dans les axones (pour les nerfs). Nous avons aussi évalué la pertinence d’utiliser une formule préexistante décrivant la dépendance en temps du coefficient de diffusion pour estimer la taille des cellules. / Compressed sensing (CS) exploits the compressibility of different types of images to reconstruct undersampled data without loss of information. The technique can be applied to MRI to reduce the acquisition times. The CS is based on three major components: (1) sparsity representation of the signal in some transform domain, (2) incoherent measurements, and (3) sparsity-constrained nonlinear reconstruction method. If the total number of points in the image is larger than four times the number of sparse coefficients, then the reconstruction of under sampled data is feasible. In the first results part of this thesis, we propose a new under sampling model based on the diffusion limited aggregation (DLA) theory and show that it performs better than the random variable under sampling method. The DLA under sampling model was used to implement the CS for T2-weighted and T1-weighted high resolution imaging at the ultra-high magnetic field (17.2T). In both cases, the acquisition time was reduced by 50% while maintaining the quality of the images in terms of spatial resolution, contrast to noise ratio, and signal intensity quantification. Both new CS pulse sequences (csRARE and csFLASH) were implemented in ParaVision 5.1 commercial software. The second results part of the thesis is focused on the study of the time-dependent diffusivity in the abdominal ganglion of Aplysia California. The Aplysia abdominal ganglion was chosen in this imaging study because high resolution MR imaging allows the fine anatomical description of the cellular network (size of individual neurons and orientation of axons). Using the Aplysia ganglia to study the relationship between the cellular structure and the diffusion MRI signal can shed light on this relationship for more complex organisms. We measured the dMRI signal at several diffusion times in the abdominal ganglion and performed simulations of water diffusion in geometries obtained after segmenting high resolution T2-weighted images and incorporating known information about the cellular structure from the literature. To match the dMRI signal in the single cell neurons with numerical simulations signal, the large cell outline was segmented from the anatomical T2 weighted image. Inside this cell shape, an irregularly shaped nucleus was manually generated (around 25-30% volume fraction). The small cells were modeled as small spheres with a smaller concentric spherical nucleus (around 25% volume fraction). The nerve was modeled by combining axons (cylinders) of different diameters consistent with the literature. The numerical dMRI signal can be simulated by solving Bloch-Torrey equation under the geometries domain described above. By fitting the experimental signal to the simulated signal for several types of cells such as: large cell neurons (diameter between 150 µm and 420 µm); cluster of small neuron cells gathered in the shape of a bag (up to 400 cells in adult Aplysia in each bag with cell size between 40 µm to 100 µm in diameter); and nerves (group of axons cylindrical shape diameter from less than 1 µm to 25 µm) at a wide range of diffusion times, we obtained estimates of the intrinsic diffusion coefficient in the nucleus and the cytoplasm (for cell neurons) and the intrinsic diffusion coefficient in the axons (for the nerves). We also evaluated the reliability of using an existing formula for the time-dependent diffusion coefficient to estimate cell size.