976 resultados para Computational modeling
Memory-Based Attentional Guidance: A Window to the Relationship between Working Memory and Attention
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Attention, the cognitive means by which we prioritize the processing of a subset of information, is necessary for operating efficiently and effectively in the world. Thus, a critical theoretical question is how information is selected. In the visual domain, working memory (WM)—which refers to the short-term maintenance and manipulation of information that is no longer accessible by the senses—has been highlighted as an important determinant of what is selected by visual attention. Furthermore, although WM and attention have traditionally been conceived as separate cognitive constructs, an abundance of behavioral and neural evidence indicates that these two domains are in fact intertwined and overlapping. The aim of this dissertation is to better understand the nature of WM and attention, primarily through the phenomenon of memory-based attentional guidance, whereby the active maintenance of items in visual WM reliably biases the deployment of attention to memory-matching items in the visual environment. The research presented here employs a combination of behavioral, functional imaging, and computational modeling techniques that address: (1) WM guidance effects with respect to the traditional dichotomy of top-down versus bottom-up attentional control; (2) under what circumstances the contents of WM impact visual attention; and (3) the broader hypothesis of a predictive and competitive interaction between WM and attention. Collectively, these empirical findings reveal the importance of WM as a distinct factor in attentional control and support current models of multiple-state WM, which may have broader implications for how we select and maintain information.
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Polarization is important for the function and morphology of many different cell types. The keys regulators of polarity in eukaryotes are the Rho-family GTPases. In the budding yeast Saccharomyces cerevisiae, which must polarize in order to bud and to mate, the master regulator is the highly conserved Rho GTPase, Cdc42. During polarity establishment, active Cdc42 accumulates at a site on the plasma membrane characterizing the “front” of the cell where the bud will emerge. The orientation of polarization is guided by upstream cues that dictate the site of Cdc42 clustering. However, in the absence of upstream cues, yeast can still polarize in a random direction during symmetry breaking. Symmetry breaking suggests cells possess an autocatalytic polarization mechanism that can amplify stochastic fluctuations of polarity proteins through a positive feedback mechanism.
Two different positive feedback mechanisms have been proposed to polarize Cdc42 in budding yeast. One model posits that Cdc42 activation must be localized to a site at the plasma membrane. Another model posits that Cdc42 delivery must be localized to a particular site at the plasma membrane. Although both mechanisms could work in parallel to polarize Cdc42, it is unclear which mechanism is critical to polarity establishment. We directly tested the predictions of the two positive feedback models using genetics and live microscopy. We found that localized Cdc42 activation is necessary for polarity establishment.
While this explains how active Cdc42 localizes to a particular site at the plasma membrane, it does not address how Cdc42 concentrates at that site. Several different mechanisms have been proposed to concentrate Cdc42. The GDI can extract Cdc42 from membranes and selective mobilize GDP-Cdc42 in the cytoplasm. It was proposed that selectively mobilizing GDP-Cdc42 in combination with local activation could locally concentrate total Cdc42 at the polarity site. Although the GDI is important for rapid Cdc42 accumulation at the polarity site, it is not essential to Cdc42 concentration. It was proposed that delivery of Cdc42 by actin-mediated vesicle can act as a backup pathway to concentrate Cdc42. However, we found no evidence for an actin-dependent concentrating pathway. Live microscopy experiments reveal that prenylated proteins are not restricted to membranes, and can enter the cytoplasm. We found that the GDI-independent concentrating pathway still requires Cdc42 to exchange between the plasma membrane and the cytoplasm, which is supported by computational modeling. In the absence of the GDI, we found that Cdc42 GAP became essential for polarization. We propose that the GAP limits GTP-Cdc42 leak into the cytoplasm, which would be prohibitive to Cdc42 polarization.
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Transcription factors (TFs) control the temporal and spatial expression of target genes by interacting with DNA in a sequence-specific manner. Recent advances in high throughput experiments that measure TF-DNA interactions in vitro and in vivo have facilitated the identification of DNA binding sites for thousands of TFs. However, it remains unclear how each individual TF achieves its specificity, especially in the case of paralogous TFs that recognize distinct target genomic sites despite sharing very similar DNA binding motifs. In my work, I used a combination of high throughput in vitro protein-DNA binding assays and machine-learning algorithms to characterize and model the binding specificity of 11 paralogous TFs from 4 distinct structural families. My work proves that even very closely related paralogous TFs, with indistinguishable DNA binding motifs, oftentimes exhibit differential binding specificity for their genomic target sites, especially for sites with moderate binding affinity. Importantly, the differences I identify in vitro and through computational modeling help explain, at least in part, the differential in vivo genomic targeting by paralogous TFs. Future work will focus on in vivo factors that might also be important for specificity differences between paralogous TFs, such as DNA methylation, interactions with protein cofactors, or the chromatin environment. In this larger context, my work emphasizes the importance of intrinsic DNA binding specificity in targeting of paralogous TFs to the genome.
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In this work I study the optical properties of helical particles and chiral sculptured thin films, using computational modeling (discrete dipole approximation, Berreman calculus), and experimental techniques (glancing angle deposition, ellipsometry, scatterometry, and non-linear optical measurements). The first part of this work focuses on linear optics, namely light scattering from helical microparticles. I study the influence of structural parameters and orientation on the optical properties of particles: circular dichroism (CD) and optical rotation (OR), and show that as a consequence of random orientation, CD and OR can have the opposite sign, compared to that of the oriented particle, potentially resulting in ambiguity of measurement interpretation. Additionally, particles in random orientation scatter light with circular and elliptical polarization states, which implies that in order to study multiple scattering from randomly oriented chiral particles, the polarization state of light cannot be disregarded. To perform experiments and attempt to produce particles, a newly constructed multi stage thin film coating chamber is calibrated. It enables the simultaneous fabrication of multiple sculptured thin film coatings, each with different structure. With it I successfully produce helical thin film coatings with Ti and TiO_{2}. The second part of this work focuses on non-linear optics, with special emphasis on second-harmonic generation. The scientific literature shows extensive experimental and theoretical work on second harmonic generation from chiral thin films. Such films are expected to always show this non-linear effect, due to their lack of inversion symmetry. However no experimental studies report non-linear response of chiral sculptured thin films. In this work I grow films suitable for a second harmonic generation experiment, and report the first measurements of non-linear response.
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Os oceanos representam um dos maiores recursos naturais, possuindo expressivo potencial energético, podendo suprir parte da demanda energética mundial. Nas últimas décadas, alguns dispositivos destinados à conversão da energia das ondas dos oceanos em energia elétrica têm sido estudados. No presente trabalho, o princípio de funcionamento do conversor do tipo Coluna de Água Oscilante, do inglês Oscillating Water Colum, (OWC) foi analisado numericamente. As ondas incidentes na câmara hidro-pneumática da OWC, causam um movimento alternado da coluna de água no interior da câmara, o qual produz um fluxo alternado de ar que passa pela chaminé. O ar passa e aciona uma turbina a qual transmite energia para um gerador elétrico. O objetivo do presente estudo foi investigar a influência de diferentes formas geométricas da câmara sobre o fluxo resultante de ar que passa pela turbina, que influencia no desempenho do dispositivo. Para isso, geometrias diferentes para o conversor foram analisadas empregando modelos computacionais 2D e 3D. Um modelo computacional desenvolvido nos softwares GAMBIT e FLUENT foi utilizado, em que o conversor OWC foi acoplado a um tanque de ondas. O método Volume of Fluid (VOF) e a teoria de 2ª ordem Stokes foram utilizados para gerar ondas regulares, permitindo uma interação mais realista entre o conversor, água, ar e OWC. O Método dos Volumes Finitos (MVF) foi utilizado para a discretização das equações governantes. Neste trabalho o Contructal Design (baseado na Teoria Constructal) foi aplicado pela primeira vez em estudos numéricos tridimensionais de OWC para fim de encontrar uma geometria que mais favorece o desempenho do dispositivo. A função objetivo foi a maximização da vazão mássica de ar que passa através da chaminé do dispositivo OWC, analisado através do método mínimos quadrados, do inglês Root Mean Square (RMS). Os resultados indicaram que a forma geométrica da câmara influencia na transformação da energia das ondas em energia elétrica. As geometrias das câmaras analisadas que apresentaram maior área da face de incidência das ondas (sendo altura constante), apresentaram também maior desempenho do conversor OWC. A melhor geometria, entre os casos desse estudo, ofereceu um ganho no desempenho do dispositivo em torno de 30% maior.
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Esta dissertação apresenta a modelagem de uma ferramenta baseada em SMA para a simulação da produção e gestão social de um ecossistema urbano, a organização social do Projeto da Horta San Jeronimo(SJVG), localizado no Parque San Jeronimo Sevilha, Espanha, que e coordenado pela confederação Ecologistas en Accion . Estes processos sociais observados no projeto do SJVG são caracterizados pela ocorrência de uma serie de interações e trocas sociais entre os participantes. Além disso, os comportamentos periódicos, interações e comunicações são regulados pelo Regimento de Normas Internas, estabelecidos pela comunidade em assembleia, sob a supervisão e coordenação da confederação EA. O SMA foi concebido como um sistema JaCaMo multidimensional, composto por cinco dimensões integradas: a população de agentes, os artefatos normativos (a organização), os artefatos físicos (o ambiente dos agentes), artefatos de comunicação (o conjunto de interações) e os artefatos normativos (política normativa interna). A ferramenta utilizada no projeto e o framework JaCaMo, uma vez que apresenta suporte de alto nível e modularidade para o desenvolvimento das três primeiras dimensões acima mencionadas. Mesmo tendo enfrentado alguns problemas importantes que surgiram adotando o framework JaCaMo para desenvolvimento do Projeto SJVG-SMA, como: (i) a impossibilidade de especificação da periodicidade no modelo MOISE, (II) a impossibilidade de definir normas, seus atributos básicos (nome, periodicidade, papel a que se aplica) e as sanções, e (III) a inexistência de uma infraestrutura modular para a definição de interações através da comunicação, foi possível adotar soluções modulares interessantes para manter a ideia de um SMA de 5 dimensões, desenvolvidos na plataforma JaCaMo. As soluções apresentadas neste trabalho são baseadas principalmente no âmbito do Cartago, apontando também para a integração de artefatos organizacionais, normativos, físicos e de comunicação.
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Over the past years, several studies have raised concerns about the possible interactions between methane hydrate decomposition and external change. To carry out such an investigation, it is essential to characterize the baseline dynamics of gas hydrate systems related to natural geological and sedimentary processes. This is usually treated through the analysis of sulfate-reduction coupled to anaerobic oxidation of methane (AOM). Here, we model sulfate reduction coupled with AOM as a two-dimensional (2D) problem including, advective and diffusive transport. This is applied to a case study from a deep-water site off Nigeria’s coast where lateral methane advection through turbidite layers was suspected. We show by analyzing the acquired data in combination with computational modeling that a two-dimensional approach is able to accurately describe the recent past dynamics of such a complex natural system. Our results show that the sulfate-methane-transition-zone (SMTZ) is not a vertical barrier for dissolved sulfate and methane. We also show that such a modeling is able to assess short timescale variations in the order of decades to centuries.
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Nitric Oxide (NO) has been known for long to regulate vessel tone. However, the close proximity of the site of NO production to “sinks” of NO such as hemoglobin (Hb) in blood suggest that blood will scavenge most of the NO produced. Therefore, it is unclear how NO is able to play its physiological roles. The current study deals with means by which this could be understood. Towards studying the role of nitrosothiols and nitrite in preserving NO availability, a study of the kinetics of glutathione (GSH) nitrosation by NO donors in aerated buffered solutions was undertaken first. Results suggest an increase in the rate of the corresponding nitrosothiol (GSNO) formation with an increase in GSH with a half-maximum constant EC50 that depends on NO concentration, thus indicating a significant contribution of ∙NO2 mediated nitrosation in the production of GSNO. Next, the ability of nitrite to be reduced to NO in the smooth muscle cells was evaluated. The NO formed was inhibited by sGC inhibitors and accelerated by activators and was independent of O2 concentration. Nitrite transport mechanisms and effects of exogenous nitrate on transport and reduction of nitrite were examined. The results showed that sGC can mediate nitrite reduction to NO and nitrite is transported across the smooth muscle cell membrane via anion channels, both of which can be attenuated by nitrate. Finally, a 2 – D axisymmetric diffusion model was constructed to test the accumulation of NO in the smooth muscle layer from reduction of nitrite. It was observed that at the end of the simulation period with physiological concentrations of nitrite in the smooth muscle cells (SMC), a low sustained NO generated from nitrite reduction could maintain significant sGC activity and might affect vessel tone. The major nitrosating mechanism in the circulation at reduced O2 levels was found to be anaerobic and a Cu+ dependent GSNO reduction activity was found to deliver minor amounts of NO from physiological GSNO levels in the tissue.
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Recreational abuse of the drugs cocaine, methamphetamine, and morphine continues to be prevalent in the United States of America and around the world. While numerous methods of detection exist for each drug, they are generally limited by the lifetime of the parent drug and its metabolites in the body. However, the covalent modification of endogenous proteins by these drugs of abuse may act as biomarkers of exposure and allow for extension of detection windows for these drugs beyond the lifetime of parent molecules or metabolites in the free fraction. Additionally, existence of covalently bound molecules arising from drug ingestion can offer insight into downstream toxicities associated with each of these drugs. This research investigated the metabolism of cocaine, methamphetamine, and morphine in common in vitro assay systems, specifically focusing on the generation of reactive intermediates and metabolites that have the potential to form covalent protein adducts. Results demonstrated the formation of covalent adduction products between biological cysteine thiols and reactive moieties on cocaine and morphine metabolites. Rigorous mass spectrometric analysis in conjunction with in vitro metabolic activation, pharmacogenetic reaction phenotyping, and computational modeling were utilized to characterize structures and mechanisms of formation for each resultant thiol adduction product. For cocaine, data collected demonstrated the formation of adduction products from a reactive arene epoxide intermediate, designating a novel metabolic pathway for cocaine. In the case of morphine, data expanded on known adduct-forming pathways using sensitive and selective analysis techniques, following the known reactive metabolite, morphinone, and a proposed novel metabolite, morphine quinone methide. Data collected in this study describe novel metabolic events for multiple important drugs of abuse, culminating in detection methods and mechanistic descriptors useful to both medical and forensic investigators when examining the toxicology associated with cocaine, methamphetamine, and morphine.
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In this book are published results of high-tech application of computational modeling and simulation the dynamics of different flows, heat and mass transfer in different fields of science and engineering.
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This work presents an analysis of the wavelet-Galerkin method for one-dimensional elastoplastic-damage problems. Time-stepping algorithm for non-linear dynamics is presented. Numerical treatment of the constitutive models is developed by the use of return-mapping algorithm. For spacial discretization we can use wavelet-Galerkin method instead of standard finite element method. This approach allows to locate singularities. The discrete formulation developed can be applied to the simulation of one-dimensional problems for elastic-plastic-damage models. (C) 2007 Elsevier Inc. All rights reserved.
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La présente thèse s'intitule "Développent et Application des Méthodologies Computationnelles pour la Modélisation Qualitative". Elle comprend tous les différents projets que j'ai entrepris en tant que doctorante. Plutôt qu'une mise en oeuvre systématique d'un cadre défini a priori, cette thèse devrait être considérée comme une exploration des méthodes qui peuvent nous aider à déduire le plan de processus regulatoires et de signalisation. Cette exploration a été mue par des questions biologiques concrètes, plutôt que par des investigations théoriques. Bien que tous les projets aient inclus des systèmes divergents (réseaux régulateurs de gènes du cycle cellulaire, réseaux de signalisation de cellules pulmonaires) ainsi que des organismes (levure à fission, levure bourgeonnante, rat, humain), nos objectifs étaient complémentaires et cohérents. Le projet principal de la thèse est la modélisation du réseau de l'initiation de septation (SIN) du S.pombe. La cytokinèse dans la levure à fission est contrôlée par le SIN, un réseau signalant de protéines kinases qui utilise le corps à pôle-fuseau comme échafaudage. Afin de décrire le comportement qualitatif du système et prédire des comportements mutants inconnus, nous avons décidé d'adopter l'approche de la modélisation booléenne. Dans cette thèse, nous présentons la construction d'un modèle booléen étendu du SIN, comprenant la plupart des composantes et des régulateurs du SIN en tant que noeuds individuels et testable expérimentalement. Ce modèle utilise des niveaux d'activité du CDK comme noeuds de contrôle pour la simulation d'évènements du SIN à différents stades du cycle cellulaire. Ce modèle a été optimisé en utilisant des expériences d'un seul "knock-out" avec des effets phénotypiques connus comme set d'entraînement. Il a permis de prédire correctement un set d'évaluation de "knock-out" doubles. De plus, le modèle a fait des prédictions in silico qui ont été validées in vivo, permettant d'obtenir de nouvelles idées de la régulation et l'organisation hiérarchique du SIN. Un autre projet concernant le cycle cellulaire qui fait partie de cette thèse a été la construction d'un modèle qualitatif et minimal de la réciprocité des cyclines dans la S.cerevisiae. Les protéines Clb dans la levure bourgeonnante présentent une activation et une dégradation caractéristique et séquentielle durant le cycle cellulaire, qu'on appelle communément les vagues des Clbs. Cet évènement est coordonné avec la courbe d'activation inverse du Sic1, qui a un rôle inhibitoire dans le système. Pour l'identification des modèles qualitatifs minimaux qui peuvent expliquer ce phénomène, nous avons sélectionné des expériences bien définies et construit tous les modèles minimaux possibles qui, une fois simulés, reproduisent les résultats attendus. Les modèles ont été filtrés en utilisant des simulations ODE qualitatives et standardisées; seules celles qui reproduisaient le phénotype des vagues ont été gardées. L'ensemble des modèles minimaux peut être utilisé pour suggérer des relations regulatoires entre les molécules participant qui peuvent ensuite être testées expérimentalement. Enfin, durant mon doctorat, j'ai participé au SBV Improver Challenge. Le but était de déduire des réseaux spécifiques à des espèces (humain et rat) en utilisant des données de phosphoprotéines, d'expressions des gènes et des cytokines, ainsi qu'un réseau de référence, qui était mis à disposition comme donnée préalable. Notre solution pour ce concours a pris la troisième place. L'approche utilisée est expliquée en détail dans le dernier chapitre de la thèse. -- The present dissertation is entitled "Development and Application of Computational Methodologies in Qualitative Modeling". It encompasses the diverse projects that were undertaken during my time as a PhD student. Instead of a systematic implementation of a framework defined a priori, this thesis should be considered as an exploration of the methods that can help us infer the blueprint of regulatory and signaling processes. This exploration was driven by concrete biological questions, rather than theoretical investigation. Even though the projects involved divergent systems (gene regulatory networks of cell cycle, signaling networks in lung cells), as well as organisms (fission yeast, budding yeast, rat, human), our goals were complementary and coherent. The main project of the thesis is the modeling of the Septation Initiation Network (SIN) in S.pombe. Cytokinesis in fission yeast is controlled by the SIN, a protein kinase signaling network that uses the spindle pole body as scaffold. In order to describe the qualitative behavior of the system and predict unknown mutant behaviors we decided to adopt a Boolean modeling approach. In this thesis, we report the construction of an extended, Boolean model of the SIN, comprising most SIN components and regulators as individual, experimentally testable nodes. The model uses CDK activity levels as control nodes for the simulation of SIN related events in different stages of the cell cycle. The model was optimized using single knock-out experiments of known phenotypic effect as a training set, and was able to correctly predict a double knock-out test set. Moreover, the model has made in silico predictions that have been validated in vivo, providing new insights into the regulation and hierarchical organization of the SIN. Another cell cycle related project that is part of this thesis was to create a qualitative, minimal model of cyclin interplay in S.cerevisiae. CLB proteins in budding yeast present a characteristic, sequential activation and decay during the cell cycle, commonly referred to as Clb waves. This event is coordinated with the inverse activation curve of Sic1, which has an inhibitory role in the system. To generate minimal qualitative models that can explain this phenomenon, we selected well-defined experiments and constructed all possible minimal models that, when simulated, reproduce the expected results. The models were filtered using standardized qualitative ODE simulations; only the ones reproducing the wave-like phenotype were kept. The set of minimal models can be used to suggest regulatory relations among the participating molecules, which will subsequently be tested experimentally. Finally, during my PhD I participated in the SBV Improver Challenge. The goal was to infer species-specific (human and rat) networks, using phosphoprotein, gene expression and cytokine data and a reference network provided as prior knowledge. Our solution to the challenge was selected as in the final chapter of the thesis.
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The aim of this study was to simulate blood flow in thoracic human aorta and understand the role of flow dynamics in the initialization and localization of atherosclerotic plaque in human thoracic aorta. The blood flow dynamics in idealized and realistic models of human thoracic aorta were numerically simulated in three idealized and two realistic thoracic aorta models. The idealized models of thoracic aorta were reconstructed with measurements available from literature, and the realistic models of thoracic aorta were constructed by image processing Computed Tomographic (CT) images. The CT images were made available by South Karelia Central Hospital in Lappeenranta. The reconstruction of thoracic aorta consisted of operations, such as contrast adjustment, image segmentations, and 3D surface rendering. Additional design operations were performed to make the aorta model compatible for the numerical method based computer code. The image processing and design operations were performed with specialized medical image processing software. Pulsatile pressure and velocity boundary conditions were deployed as inlet boundary conditions. The blood flow was assumed homogeneous and incompressible. The blood was assumed to be a Newtonian fluid. The simulations with idealized models of thoracic aorta were carried out with Finite Element Method based computer code, while the simulations with realistic models of thoracic aorta were carried out with Finite Volume Method based computer code. Simulations were carried out for four cardiac cycles. The distribution of flow, pressure and Wall Shear Stress (WSS) observed during the fourth cardiac cycle were extensively analyzed. The aim of carrying out the simulations with idealized model was to get an estimate of flow dynamics in a realistic aorta model. The motive behind the choice of three aorta models with distinct features was to understand the dependence of flow dynamics on aorta anatomy. Highly disturbed and nonuniform distribution of velocity and WSS was observed in aortic arch, near brachiocephalic, left common artery, and left subclavian artery. On the other hand, the WSS profiles at the roots of branches show significant differences with geometry variation of aorta and branches. The comparison of instantaneous WSS profiles revealed that the model with straight branching arteries had relatively lower WSS compared to that in the aorta model with curved branches. In addition to this, significant differences were observed in the spatial and temporal profiles of WSS, flow, and pressure. The study with idealized model was extended to study blood flow in thoracic aorta under the effects of hypertension and hypotension. One of the idealized aorta models was modified along with the boundary conditions to mimic the thoracic aorta under the effects of hypertension and hypotension. The results of simulations with realistic models extracted from CT scans demonstrated more realistic flow dynamics than that in the idealized models. During systole, the velocity in ascending aorta was skewed towards the outer wall of aortic arch. The flow develops secondary flow patterns as it moves downstream towards aortic arch. Unlike idealized models, the distribution of flow was nonplanar and heavily guided by the artery anatomy. Flow cavitation was observed in the aorta model which was imaged giving longer branches. This could not be properly observed in the model with imaging containing a shorter length for aortic branches. The flow circulation was also observed in the inner wall of the aortic arch. However, during the diastole, the flow profiles were almost flat and regular due the acceleration of flow at the inlet. The flow profiles were weakly turbulent during the flow reversal. The complex flow patterns caused a non-uniform distribution of WSS. High WSS was distributed at the junction of branches and aortic arch. Low WSS was distributed at the proximal part of the junction, while intermedium WSS was distributed in the distal part of the junction. The pulsatile nature of the inflow caused oscillating WSS at the branch entry region and inner curvature of aortic arch. Based on the WSS distribution in the realistic model, one of the aorta models was altered to induce artificial atherosclerotic plaque at the branch entry region and inner curvature of aortic arch. Atherosclerotic plaque causing 50% blockage of lumen was introduced in brachiocephalic artery, common carotid artery, left subclavian artery, and aortic arch. The aim of this part of the study was first to study the effect of stenosis on flow and WSS distribution, understand the effect of shape of atherosclerotic plaque on flow and WSS distribution, and finally to investigate the effect of lumen blockage severity on flow and WSS distributions. The results revealed that the distribution of WSS is significantly affected by plaque with mere 50% stenosis. The asymmetric shape of stenosis causes higher WSS in branching arteries than in the cases with symmetric plaque. The flow dynamics within thoracic aorta models has been extensively studied and reported here. The effects of pressure and arterial anatomy on the flow dynamic were investigated. The distribution of complex flow and WSS is correlated with the localization of atherosclerosis. With the available results we can conclude that the thoracic aorta, with complex anatomy is the most vulnerable artery for the localization and development of atherosclerosis. The flow dynamics and arterial anatomy play a role in the localization of atherosclerosis. The patient specific image based models can be used to diagnose the locations in the aorta vulnerable to the development of arterial diseases such as atherosclerosis.
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Experimental Extended X-ray Absorption Fine Structure (EXAFS) spectra carry information about the chemical structure of metal protein complexes. However, pre- dicting the structure of such complexes from EXAFS spectra is not a simple task. Currently methods such as Monte Carlo optimization or simulated annealing are used in structure refinement of EXAFS. These methods have proven somewhat successful in structure refinement but have not been successful in finding the global minima. Multiple population based algorithms, including a genetic algorithm, a restarting ge- netic algorithm, differential evolution, and particle swarm optimization, are studied for their effectiveness in structure refinement of EXAFS. The oxygen-evolving com- plex in S1 is used as a benchmark for comparing the algorithms. These algorithms were successful in finding new atomic structures that produced improved calculated EXAFS spectra over atomic structures previously found.