A preocupação com o destino de produtos químicos e água, aplicados ao solo, tem motivado vários pesquisadores a desenvolverem e aplicarem modelos teóricos, objetivando descrever os processos físicos envolvidos no transporte desses produtos no perfil do solo. Nesse sentido, a presente pesquisa teve como objetivo a aplicação do modelo Hydrus-1D para simulação do movimento da água e dos íons nitrato e potássio, em condições de laboratório, utilizando-se para tal colunas segmentadas preenchidas com dois tipos de solo não-saturado (Latossolo Vermelho Amarelo e Nitossolo Vermelho), bem como avaliar o desempenho e sensibilidade do referido modelo. Para a obtenção dos parâmetros de transporte de cada soluto, foram elaboradas as curvas de distribuição de efluentes (Breakthrough Curves BTC). Os parâmetros de transporte obtidos e as condições de contorno de cada ensaio foram inseridos no modelo Hydrus- 1D para realização das simulações. O desempenho do modelo foi avaliado com base nos parâmetros estatísticos: erro máximo, erro absoluto médio, raiz quadrada do erro médio normalizado, coeficiente de massa residual, coeficiente de determinação, eficiência e índice de concordância de Willmott. A sensibilidade do modelo foi avaliada conforme o método proposto por McCuen e Snyder (1986) e a análise foi aplicada aos parâmetros: fluxo de entrada, condutividade hidráulica do solo saturado, teor de água na saturação, alfa e n (parâmetros de ajuste da curva de retenção), coeficiente de distribuição e dispersividade. Os resultados experimentais mostraram que o deslocamento do íon nitrato acompanhou a frente de molhamento e em relação ao potássio, observou-se uma maior retenção nas camadas superficiais da coluna de solo, para ambos os solos. Pôde-se concluir que o modelo Hydrus-1D foi eficiente para simulações de deslocamento de potássio e água para ambos os solos estudados e mediante a utilização do modelo de equilíbrio para o transporte de solutos no solo, o modelo Hydrus-1D não foi eficiente para simular o deslocamento de nitrato, para ambos os solos. Os procedimentos experimentais para estimativa de parâmetros de transporte, como as curvas de distribuição de efluentes, foram suficientes para descrever a movimentação de potássio no solo, gerando informações de entrada precisas para os modelos de simulação. Para a simulação do deslocamento do íon nitrato, concluiu-se que o modelo Hydrus-1D requer um processo experimental mais detalhado, sendo necessária a estimativa de um maior número de parâmetros de transporte. Em relação à análise de sensibilidade, ao simular os teores de potássio e água no solo, o modelo apresentou maior sensibilidade aos parâmetros teor de água na saturação e fluxo de entrada da solução. Tais parâmetros, portanto, precisam ser determinados com maior precisão. Houve baixa sensibilidade aos parâmetros condutividade hidráulica do solo saturado e dispersividade, para ambos os solos estudados. / The concern about the fate of chemical products and water, applied to the soil, has been motivating several researchers to develop and apply theoretical models, aiming to describe the physical processes involved in the transport of those products in soil profile. The present research had as objective the application of the model Hydrus- 1D for water and solute (nitrate and potassium) simulation profile, in laboratory conditions, using soil columns filled with two types of unsaturated soil (Oxisol (Haplustox) and Hapludox), as well to evaluate the acting and sensitivity of the model. The transport parameters were obtained for each solute by breakthrough curves (BTCs). The transport parameters obtained and the boundary conditions were inserted in the Hydrus-1D model to realize the simulations. The acting of the Hydrus-1D model was evaluated using the statistical indicators: maximum error, mean absolute error, normalized root mean-square error, coefficient of residual mass, determination coefficient, efficiency and Willmott concordance index. The model sensitivity was evaluated by the method proposed by McCuen and Snyder (1986) and applied to the parameters: input flow, soil saturated hydraulic conductivity, water content (saturation point), alpha and n (soil water retention curve parameters), distribution coefficient and dispersivity. The obtained results, experimentally, showed the nitrate displacement following the wetting front and, in relation to the potassium ion, a larger retention was observed at the superficial soil columns layers. Therefore, was possible to conclude that Hydrus-1D model was efficient for both water and potassium displacement simulations, for both studied soils and by the balance model for solute transport in soil, the Hydrus- 1D model was not efficient to simulate the nitrate displacement in both soils. The experimental procedures to estimate transport parameters, by the BTCs, were enough to describe the potassium movement in soil, generating input information necessary to the model simulation. To the simulation of the nitrate displacement, was possible to conclude that the model Hydrus-1D requests a more detailed experimental process, being necessary the estimate of a larger number of transport parameters. In relation to the sensitivity analysis of the Hydrus-1D model, when simulated the content of potassium and water at the soil columns, was observed that the model shows more sensitivity about to the parameters: water content (saturation point) and input flow. This parameters need to be estimated with more precision. There was a low sensitivity to the parameters soil saturated hydraulic conductivity and dispersivity for both studied soils.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-03-06T17:46:11Z No. of bitstreams: 1 carlarezendebarbosabonin.pdf: 3328861 bytes, checksum: 72bd85d272ff7cf9ee9d0cfb275e0d7e (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-03-06T20:26:25Z (GMT) No. of bitstreams: 1 carlarezendebarbosabonin.pdf: 3328861 bytes, checksum: 72bd85d272ff7cf9ee9d0cfb275e0d7e (MD5) / Made available in DSpace on 2017-03-06T20:26:25Z (GMT). No. of bitstreams: 1 carlarezendebarbosabonin.pdf: 3328861 bytes, checksum: 72bd85d272ff7cf9ee9d0cfb275e0d7e (MD5) Previous issue date: 2015-02-26 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Desde 1937 está disponível uma vacina eficaz contra febre amarela. Ainda assim, questões relativas a seu uso permanecem pouco entendidas, como, por exemplo, a necessidade da dose reforço a cada dez anos. O objetivo deste trabalho é demonstrar que ferramentas matemático-computacionais podem ser utilizadas para simular diferentes cenários referentes à vacinação e aos indivíduos a fim de auxiliar a busca pelas respostas de algumas destas questões em aberto. Neste contexto, este trabalho apresenta um modelo matemático-computacional da resposta imune humana à vacinação contra febre amarela. O modelo leva em conta importantes células dos sistemas inato e adaptativo, como células apresentadoras de antígeno, anticorpos, células B e células T (CD4+ e CD8+). Também são consideradas populações de células de memória, importantes na aquisição da imunidade conferida pela vacina. O modelo foi capaz de gerar curvas de anticorpos que estão de acordo com dados experimentais, além de representar o comportamento de diversas populações importantes do sistema imune de acordo com o que é esperado pela literatura. Este é o início de um caminho que, em um cenário ideal, permitirá simular diferentes situações relacionadas ao emprego da vacina contra febre amarela, como sua aplicação em indivíduos com imunodeficiências, diferentes estratégias de vacinação, duração da imunidade e necessidade de dose reforço. / An effective vaccine against yellow fever is available since 1937, but some issues regarding its use remain poorly understood, for example, the need for a booster dose every ten years. The objective of this study is to demonstrate that mathematical-computational tools can be used to simulate distinct scenarios related both to vaccination and individuals in order to assist the search for the answers to some of these open issues. In this context, this study presents a mathematical-computational model of the human immune response to vaccination against yellow fever. The model takes into account important cells of the innate and adaptive systems, such as antigen presenting cells, antibodies, B cells and T cells (CD4 + and CD8 +). Memory cell populations, important on the immunity induced by a vaccine, were also considered in the model. The model was able to generate antibodies curves which are in accordance with experimental data as well as to represent the behavior of several important populations of the immune system according to the results of the literature surveyed. This is the first step towards an ideal scenario where it will be possible to simulate distinct situations related to the use of yellow fever vaccine, as its application in immunodeficient individuals, different vaccination strategies, duration of immunity and the need for a booster dose.

Submitted by isabela.moljf@hotmail.com (isabela.moljf@hotmail.com) on 2017-05-25T13:52:08Z No. of bitstreams: 1 danielaschimitzdecarvalho.pdf: 5044623 bytes, checksum: 7bd83afb9efa8bcad933dd398237160a (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-05-25T14:47:16Z (GMT) No. of bitstreams: 1 danielaschimitzdecarvalho.pdf: 5044623 bytes, checksum: 7bd83afb9efa8bcad933dd398237160a (MD5) / Made available in DSpace on 2017-05-25T14:47:16Z (GMT). No. of bitstreams: 1 danielaschimitzdecarvalho.pdf: 5044623 bytes, checksum: 7bd83afb9efa8bcad933dd398237160a (MD5) Previous issue date: 2016-03-29 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O câncer mamário acomete milhões de mulheres no mundo a cada ano, sendo considerado um problema de saúde pública mundial. Esta doença apresenta uma alta mortalidade e uma elevada incidência entre os tipos de câncer na população feminina. No Brasil, esta patologia também se estaca como a primeira nas taxas de incidência e mortalidade entre os cânceres no sexo feminino. O comportamento evolutivo do câncer em um indivíduo, sua origem, sua composição e expansão são características ainda não bem elucidadas. A eficiência dos diferentes tratamentos está relacionada com vários fatores referentes ao comportamento tumoral, e principalmente com o estadiamento clínico. Neste trabalho, descrevem-se as principais características biológicas e clínicas do câncer mamário e investigam-se alguns modelos matem áticos disponíveis na literatura que representam o seu crescimento. Particularmente, são abordados modelos empíricos clássicos que consideram a popula ção tumoral com constituição celular homogênea; e modelos mais recentes mecanicistas que incluem características da heterogeneidade celular e a hipótese das células tronco cancerígenas. Além disso, foram propostas e implementadas computacionalmente duas alternativas para a consideração da atuação de fármacos no crescimento tumoral. Simulações numéricas foram realizadas empregando estes modelos e os resultados obtidos discutidos. Através destas simulações foi possível entender as limitações dos modelos frente a complexidade do crescimento tumoral. / Breast cancer a ects millions of women worldwide each year and is considered a problem of world public health. The disease presents a high mortality and incidence rates among cancer types in the female population. In Brazil, this patology is also associated with the highest incidence and mortality rates among cancers in women. The evolutionary behavior of cancer cells are not well elucidated, such as their origin, composition and expansion characteristics. The e ciency of the distinct treatments is related to several factors involving the tumor behavior, and especially with the clinical staging. In this work, the biological and clinical characteristics of breast cancer were described and relevant mathematical models of tumor growth were investigated. Particularly, the empirical models that consider the tumor population with the homogeneous cells; and the latest mechanistic models including cellular heterogeneity characteristics and the hypothesis of cancer stem cells. Furthermore, two alternatives were proposed and computationally implemented in order to simulate the e ects of the drug in the tumor growth. Numerical simulations were achieved using these models and the results discussed. From these simulations, it was possible to understand the limitations of these models compared with the complexity of the tumor growth.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-07-04T17:30:00Z No. of bitstreams: 1 raphaelpereiracordeiro.pdf: 17027543 bytes, checksum: 91ef68c2021ff4c93dc8b4fe66217cf2 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-08-08T13:42:41Z (GMT) No. of bitstreams: 1 raphaelpereiracordeiro.pdf: 17027543 bytes, checksum: 91ef68c2021ff4c93dc8b4fe66217cf2 (MD5) / Made available in DSpace on 2017-08-08T13:42:41Z (GMT). No. of bitstreams: 1 raphaelpereiracordeiro.pdf: 17027543 bytes, checksum: 91ef68c2021ff4c93dc8b4fe66217cf2 (MD5) Previous issue date: 2017-03-10 / A modelagem computacional é uma ferramenta útil no estudo de diversos fenômenos complexos, como o comportamento eletro-mecânico do coração em condições normais e patológicas, sendo importante para o desenvolvimento de novos medicamentos e métodos de combate às doenças cardíacas. A alta complexidade de processos biofísicos se traduz em complexos modelos matemáticos e computacionais, o que faz com que simulações cardíacas necessitem de um grande poder computacional para serem executadas. Logo, o estado da arte em simuladores cardíacos é implementado para ser executado em arquiteturas paralelas. Este trabalho apresenta a implementação e avaliação de um método com dados e kernel agregados, método este utilizado para reduzir o tempo de computação de códigos que executam em ambientes computacionais compostos de múltiplas unidades de processamento gráfico (Graphics Processing Unit ou simplesmente GPUs). Este método foi testado na computação de uma importante parte da simulação da eletrofisiologia do coração, a resolução das equações diferenciais ordinárias (EDOs), resultando em uma redução pela metade do tempo necessário para a sua resolução, quando comparado com o esquema onde este método não foi implementado. Com o uso da técnica proposta neste trabalho, o tempo total de execução das simulações cardíacas foi reduzido em até 25%. / Computational modeling is a useful tool to study many distinct and complex phenomena, such as to describe the electrical and mechanical behavior of the heart, under normal and pathological conditions. The high complexity of the associated biophysical processes translates into complex mathematical and computational models. This, in turn, translates to cardiac simulators that demand a lot of computational power to be executed. Therefore, most of the state-of-the-art cardiac simulators are implemented to run in parallel architectures. In this work a new coalesced data and kernel scheme is evaluated. Its objective is to reduce the execution costs of cardiac simulations that run on multi-GPU environments. The new scheme was tested for an important part of the simulator, the solution of the systems of Ordinary Differential Equations (ODEs). The results have shown that the proposed scheme is very effective. The execution time to solve the systems of ODEs on the multi-GPU environment was reduced by half, when compared to a scheme that does not implemented the proposed data and kernel coalescing. As a result, the total execution time of cardiac simulations was 25% faster.

Les systèmes bactériens sont complexes et adaptatifs. Soumis à des perturbations, telles qu’un traitement antibiotique, ils survivent, se régénèrent et évoluent. Ceci est d’autant plus vrai pour les biofilms, capables de surmonter des traitements létaux à des bactéries planctoniques. La capacité des systèmes à retrouver leur équilibre initial, certaines fonctions ou compositions après un choc est appelée résilience. La résilience est souvent considérée comme complémentaire à la résistance en écologie. Pourtant, la résilience aux antibiotiques reçoit peu de considération en comparaison de la résistance aux antibiotiques en bactériologie. L’une des raisons de ce désintérêt est que ce concept est souvent mal défini et ambigu. Dans cette thèse, nous proposons tout d’abord une base conceptuelle de la résilience aux antibiotiques. A partir de l’analyse de différentes définitions existantes de la résilience, nous fournissons une démarche pour formaliser le concept de résilience dans le contexte d’une population bactérienne soumise à des traitements antibiotiques. De cette première analyse, le mécanisme biologique de persistance bactérienne est ressorti comme important dans la résilience aux antibiotiques. Ce phénomène repose sur la formation de cellules tolérantes aux antibiotiques, les persisters, dont la formation est influencée par les conditions environnementales. Afin de relier la formation des persisters aux conditions environnementales, nous avons développé des modèles mathématiques de transition phénotypique entre cellules sensibles et persisters que nous avons calibrés et testés à l’aide de données expérimentales. Enfin, nous avons étudié l’effet de la persistance bactérienne sur la résilience aux antibiotiques des biofilms. Pour cela, nous avons développé un modèle individu-centré de biofilm intégrant des transitions entre cellules sensibles et persisters. Différentes stratégies de transition ont été reliées à la capacité des biofilms à croître, survivre et se régénérer après un choc antibiotique. La mise en place d’expériences capables de fournir des données à comparer aux simulations est proposée dans la discussion de cette thèse. Cette thèse contribue à la clarification du concept de résilience aux antibiotiques et à la compréhension du phénomène de persistance bactérienne dans les biofilms. Elle ouvre des perspectives sur l’utilisation du concept de résilience en bactériologie clinique et souligne l’importance de l’hétérogénéité des populations bactériennes dans leur capacité à confronter les perturbations et évoluer. / Bacterial systems are complex and adaptive. When faced with disturbances, such as antibiotic treatments, they survive, recover and evolve. This is particularly true for biofilms, which survive treatments that planktonic cells cannot overcome. The capacity of systems to recover their initial state, some of their functions or composition after a disturbance is called resilience. The resilience concept is often considered complementary to resistance in ecology. However, antibiotic resilience has received little attention compared to antibiotic resistance. One reason of this lack of interest comes from the fact that the resilience concept is often poorly defined and ambiguous. In this thesis, we firstly developed a conceptual framework of antibiotic resilience and applied this framework to the case of a bacterial population faced with antibiotics. This analysis highlighted the importance of the biological mechanism of bacterial persistence. This phenomenon is based on the formation of sub-populations of antibiotic tolerant cells, the persisters, which is influenced by environmental conditions. To relate persister formation to environmental conditions, we developed mathematical models of phenotypic switches between susceptible and persister cells and calibrated and tested them with experimental data. Lastly, we studied the influence of bacterial persistence on biofilm antibiotic resilience. For this purpose, we developed an individual-based model of biofilm with phenotypic switches between susceptible and persister cells. Different strategies of phenotypic switches were related to the dynamics of growth, survival and recovery of bacterial biofilms faced with antibiotic shocks. The setting up of experimentations to obtain data to compare to simulations is presented in the discussion of this thesis. Globally, this thesis contributes to the clarification of the concept of antibiotic resilience and to the understanding of bacterial persistence in biofilms. It gives new perspectives on the use of the resilience concept in clinical bacteriology and emphasizes the importance of the heterogeneity of bacterial populations in their capacity to face disturbances and evolve.

Small disturbances occur continuously in electrical systems mainly due to load and generation variations. This ends up causing low frequency voltage fluctuations that are usually observed in systems whose lines have weak connections. In addition to damaging loads connected to the same bus, they can even damage equipment and incurring in costs to the energy distributors. Moreover, such oscillations can resonate with the system parameters and cause a general collapse in energy supplies. In the literature, there are methods for the development of stabilizers for power systems that are implemented to counteract these perturbations. In this dissertation, we compared some objective functions and identified points that can be optimized for parameterization of power system stabilizers IEEE models: PSS2B, PSS4B and conventional Delta w PSS, by computer simulations. The adjustment methodology used in this dissertation is based on the genetic algorithm (GA) held in Simulink® with the aid of the Matlab toolbox Gatool®. The effectiveness of the suggested technique and stabilizers are checked using simulation results, where it is noticeable that the PSSs managed to dampen oscillations in almost all cases. The only one who did not realize the optimization was the Delta W PSS with ITSE objective function in the hydraulic turbine, which failed to dampen oscillations even for the best results. Moreover, it was also possible to notice that the same Delta W PSS with ITAE objective function had the best results for the two types of turbine. / Pequenas perturbações ocorrem continuamente em sistemas elétricos principalmente devido às variações de cargas e da geração. Isto acaba acarretando oscilações de tensão de baixa frequência que são normalmente observadas em sistemas cujas linhas possuem conexões fracas. Além de prejudicar as cargas conectadas no mesmo barramento, elas podem até danificar aparelhos e incorrer em ônus para as distribuidoras de energia. Além do mais, tais oscilações podem entrar em ressonância com os parâmetros do sistema e causar um colapso geral no abastecimento de energia. Na literatura encontram-se metodologias para o desenvolvimento de Estabilizadores para Sistemas de Potência que são implantadas para se contrapor a estas perturbações. Nesta dissertação, foram comparadas algumas funções objetivo para a parametrização dos estabilizadores de sistemas de potência modelos IEEE: PSS2B, PSS4B e convencional Delta w PSS, a partir de simulações computacionais. A metodologia de ajuste utilizada nesta dissertação é baseada no algoritmo genético (AG) realizada em Simulink® com auxílio do toolbox Gatool® do Matlab®. A eficácia da técnica sugerida e dos estabilizadores é verificada com os resultados de simulação, em que é possível perceber que os PSSs conseguiram amortecer oscilações em quase todos os casos. O único que não realizou a otimização foi o Delta W PSS com a função objetivo ITSE na turbina hidráulica, o qual não conseguiu amortecer as oscilações com seu melhor resultado encontrado. Por outro lado, foi possível perceber também que o mesmo Delta W PSS com a função objetivo ITAE teve o melhor resultado para os dois tipos de turbina.

Les infections associées aux soins représentent un enjeu majeur de santé publique dans le monde. Les bactéries multirésistantes (BMR) sont responsables d’une grande partie de ces infections. Mieux comprendre leur dissémination dans les établissements de soins est indispensable pour élaborer des mesures de contrôle et de prévention.L’objectif de cette thèse est d’utiliser des données détaillées sur les réseaux de contacts interindividuels, couplées à des méthodes de modélisation mathématique, pour étudier la dissémination des BMR à l’hôpital afin d’améliorer leur contrôle. Pour répondre à cette problématique, les données de l’étude i-Bird ont été analysées. Cette étude prospective longitudinale a eu lieu dans l’hôpital maritime de Berck-sur-Mer durant 4 mois en 2009. Pendant cette période, les interactions de proximités entre tous les individus de l’hôpital ont été enregistrées chaque jour grâce à des capteurs RFID (Radio Frequency Identification Devices) et des prélèvements microbiologiques ont été récoltés chaque semaineDans un premier temps, la structure des contacts interindividuels au sein de et entre les différentes catégories d’individus (patient, aide-soignant, infirmier, …) a été analysée. Cette première étude a souligné l’importance des contacts patient-patient en établissement de longue durée. De plus, certaines catégories de personnel hospitalier ont été identifiées comme de potentiels super-propagateurs, tel que les brancardiers et les médecins.Dans un deuxième temps, le rôle du réseau de contacts dans la dissémination de deux espèces (E. coli et K. pneumoniae) d’entérobactéries résistantes aux béta-lactamines à spectre étendue (BLSE) a été étudié. Cette étude a montré que le réseau d’interactions de proximités était suffisant pour expliquer la propagation des KP-BLSE. En revanche, il n’était pas suffisant pour retracer la dissémination des EC-BLSE.La dernière partie de la thèse a été consacrée au développement d’un modèle individu-centré de transmission de BMR à l’hôpital modélisant explicitement les contacts interindividuels. Ce modèle permet d’évaluer l’effet de mesures de contrôle ciblant la structure du réseau de contacts. A titre d’application, les données de l’étude i-Bird ont été utilisées pour simuler la transmission de Staphylococcus aureus résistant à la méticilline (SARM) durant les 4 mois de l’étude. La simulation de procédures de cohorting du personnel dans l’hôpital de Berck-sur-Mer suggère que la mise en place de telles mesures permet de réduire l’acquisition de SARM chez les patients.Cette thèse combine analyse de réseaux, épidémiologie des maladies infectieuses et modélisation dynamique. Elle apporte une meilleure compréhension de la diffusion et du contrôle des BMR dans les hôpitaux de longue durée. De plus, elle apporte un outil innovant, visant à être développé, pour la compréhension et le contrôle de la dissémination des BMR à travers les contacts en milieu hospitalier. / Healthcare-associated infections represent a huge public health issue worldwide. Multidrug resistant bacteria (MDR) are a major cause of these infections. Hence, better understanding their transmission routes in hospital settings is crucial to design efficient control measures.The purpose of this thesis is to use detailed data on interindividual contact networks, associated with mathematical modelling methods, to study MDR spread in hospitals and improve their control. To this end, data collected during the i-Bird study was used. This longitudinal prospective study took place at the Berck-sur-Mer hospital during 4 months in 2009. Close proximity interactions were recorded by the use of RFID (Radio Frequency Identification Devices) sensors everyday. Meanwhile, microbiological swabs were collected weekly.In a first part, interindividual contact patterns within and between each individual categories (patients, nurses, hospital porters, etc.) were analyzed. This first study notably underlined the importance of patient-to-patient contacts in long-term care facilities (LTCF). Moreover, some hospital staff categories, such as hospital porters and physicians, were identified as potential superspreaders based on their contact patterns.In a second part, we investigated the impact of the contact network on the spread of two species of Extended-spectrum beta-lactamases (ESBL) Enterobacteriaceae (E. coli and K. pneumoniae). This work showed that the contact network was an important driver of ESBL-K. pneumoniae dynamics, but not of ESBL-E. coli dynamics over the i-Bird study.The last part of the thesis was dedicated to the development of an agent-based model of MDR spread in hospital settings that explicitly formalizes detailed interindividual contacts. This model allows to assess control measures focused on contact patterns. The model was applied to the i-Bird data; we simulated methicillin-resistant Staphylococcus aureus (MRSA) transmission during the 4-month study over the reported contact network. Using our simations, we evaluated measures associated with hospital staff cohorting and showed it can lead to reduce the MRSA acquisition=.This thesis combines network analysis, epidemiology of infectious diseases and dynamic modeling. It allows a better understanding of MDR spread and control in LTCF. Moreover, it brings an innovative tool, intended to be developed, to understand and control BMR spread through contact networks in hospital settings.

High entropy alloys (HEAs) are alloys with five or more principal elements. Due to these distinct concept of alloying, the HEA exhibits unique and superior properties. The outstanding properties of HEA includes higher strength/hardness, superior wear resistance, high temperature stability, higher fatigue life, good corrosion and oxidation resistance. Such characteristics of HEA has been significant interest leading to researches on these emerging field. Even though many works are done to understand the characteristic of these HEAs, very few works are made on how the HEAs can be applied for commercial uses. This work discusses the application of High entropy alloys in biomedical applications. The coronary heart disease, the leading cause of death in the United States kills more than 350,000 persons/year and it costs $108.9 billion for the nation each year in spite of significant advancements in medical care and public awareness. A cardiovascular disease affects heart or blood vessels (arteries, veins and capillaries) or both by blocking the blood flow. As a surgical interventions, stent implants are deployed to cure or ameliorate the disease. However, the high failure rate of stents has lead researchers to give special attention towards analyzing stent structure, materials and characteristics. Many works related to alternate material and/or design are carried out in recent time. This paper discusses the feasibility of CoCrFeNiMn and Al0.1CoCrFeNi HEAs in stent implant application. This work is based on the speculation that CoCrFeNiMn and Al0.1CoCrFeNi HEAs are biocompatible material. These HEAs are characterized to determine the microstructure and mechanical properties. Computational modeling and analysis were carried out on stent implant by applying CoCrFeNiMn and Al0.1CoCrFeNi HEAs as material to understand the structural behavior.

This master's thesis is focused on determination and analysis of stress and strain in femur with distraction intramedullary nail for treating leg length discrepancy with the method of distraction osteogenesis. Thesis is mainly focused on states after distraction when the callus consolidates. Problem of determining stress and strain is solved by computational modeling using FEM. Detailed description of modeling is included in this thesis, complicated 3D geometry of bone was acquired from segmentation of CT images. Computational model is solve with 4 different types of callus geometry and also material properties of callus are varied. The influence on stress and strain when the middle distal screw is not applied is also analyzed.

This Master’s thesis is focused on thermal analyses of servomotors per computational modeling with finite element method. The goal was to set the model for the analyses and verify it with experiment and evaluate achieved results.