Entendimento de processos que levem ao surgimento de opiniões extremas é valioso na prevenção de atos de violência. Os modelos são ferramentas úteis para identificar possíveis padrões relacionados a estes processos. No entanto, modelos discretos ou contínuos com confiança limitada não se mostram adequados para estudar dinâmicas caracterizadas pela divergência de opiniões. É proposta uma extensão cultural do modelo de Opiniões Contínuas e Ações Discretas (CODA) com múltiplos assuntos alternados por um mecanismo de ligação preferencial. Os agentes são influenciados não só em suas opiniões, mas também nas importâncias que atribuem aos diferentes assuntos. As principais características do modelo são o surgimento de preferências e consensos locais, aos quais estão associadas as opiniões mais extremas. Há, em contrapartida, persistência de opiniões brandas nos temas menos preferidos. O estudo do espaço paramétrico do modelo revelou que modificações diminuindo a localidade das interações aumentam maiorias e amenizam opiniões. Duas estratégias distintas de debate foram testadas. Zelotes têm poder de conversão aumentado quando dispersos. Evitadores minimizam o número de interações indesejável se agrupados. Foram esboçadas abordagens para inserção de efeitos da mídia na dinâmica / Understanding processes leading to extremism is invaluable to prevent violence outbursts. Models are useful tools that allow for identifying patterns related to those processes. Nevertheless, discrete models and bounded-confidence continuous models are unfit for studying diversion-based dynamics. We present a cultural extension of CODA model, with multiple subjects selected through a preferential attachment rule. Agents are influenced in their opinions and relevance attributed to different subjects. The most notable results of the dynamics are the establishment of local subject preferences and consensus, associated with more extreme opinions. On the other hand, there is persistence of immature undeveloped opinion in the locally less regarded subjects. The study of parametric space has shown that settings reducing the locality of interactions both increase the majority size and make opinions less extreme. Two distinct debate strategies were simulated. Zealots increase conversions when spread throughout the network. In contrast, subject avoiders decrease the number of unwanted interactions by grouping together. Some ideas for introducing media influence to the model were outlined

O presente trabalho tem como objetivo analisar a dinâmica da transmissão da política monetária através dos canais de crédito (Canal de Empréstimo Bancário e Canal dos Balanços Patrimoniais), utilizando conceitos e ferramentas da área de Sistemas Complexos para simular uma economia representada por diferentes setores em que os agentes estão interconectados através de relacionamentos de crédito. O presente modelo baseia-se no trabalho de Gatti et al. (2009). A novidade foi introduzir um mecanismo de transmissão da política monetária através de um mercado interbancário e de uma taxa básica de juros permitindo analisar os impactos na economia através dos canais de crédito. O resultado da simulação mostra que o impacto das políticas monetárias no âmbito microeconômico podem se desenvolver como resultado da interação complexa desses agentes heterogêneos através de relacionamentos de crédito ao longo do tempo, e as variáveis no âmbito macroeconômico, como a taxa básica de juros, afetam o próprio sistema através de um processo de retroalimentação ou feedback. / This study aims to analyze the dynamics of the monetary policy transmission through the credit channels (Bank Lending Channel and Balance Sheets Channel), using concepts and tools from the Complex Systems field to simulate an economy represented by different sectors in which agents are interconnected via credit relationships. This model is based on the work of Gatti et al. (2009) that used agent-based modeling. The novelty was to introduce a transmission mechanism of monetary policy through an interbank market and a primary interest rate, allowing the analysis of the impacts on the economy through the credit channels. The simulation results show that the impact of monetary policy on microeconomic level can be developed as a result of the complex interaction of these heterogeneous agents via credit relationships over time, and the variables in the macroeconomic context, such as the primary interest rate, affect the system through a feedback process.

[pt] Correntes de turbidez são correntes gravitacionais turbulentas transportando grãos em alta velocidade e formando uma solução de água e sedimentos esparramados, sendo responsáveis pela formação de um tipo de reservatório petrolífero. O lobo turbidítico é um importante elemento arquitetural nos reservatórios turbidíticos e neste trabalho propomos uma modelagem assistida deste objeto, a partir de dados de pressão medidos durante um teste de formação. Para isto, foi desenvolvido um método de estimar as permeabilidades e parâmetros geométricos dos lobos com auxílio do simulador IMEX da CMG e da interpretação assistida do teste de formação simulado, utilizando como base os dados de pressão extraídos de testes de formação de referência. Na modelagem do lobo turbidítico incluímos a alocação de uma superfície de base. / [en] Turbidite currents are turbulent gravitational currents transporting grains in high speed creating a solution of water and dispersed sedments, being responsable for the formation of an oil reservoir. The turbidite lobe is an important architectural element for the turbidite reservoirs. In this work we propose an assisted modeling of this object based on measured well testing pressures. A method was developed to estimate permeabities and geometric parameters for this lobes using the IMEX fluid flow simulator and an assisted interpretation of the simulated well test comparing simulated pressures to those measured in a reference well test. In the modeling of the turbidite lobe, we allocate a base surface.

abstract: This thesis consists of three projects employing complexity economics methods to explore firm dynamics. The first is the Firm Ecosystem Model, which addresses the institutional conditions of capital access and entrenched competitive advantage. Larger firms will be more competitive than smaller firms due to efficiencies of scale, but the persistence of larger firms is also supported institutionally through mechanisms such as tax policy, capital access mechanisms and industry-favorable legislation. At the same time, evidence suggests that small firms innovate more than larger firms, and an aggressive firm-as-value perspective incentivizes early investment in new firms in an attempt to capture that value. The Ecological Firm Model explores the effects of the differences in innovation and investment patterns and persistence rates between large and small firms. The second project is the Structural Inertia Model, which is intended to build theory around why larger firms may be less successful in capturing new marketshare than smaller firms, as well as to advance fitness landscape methods. The model explores the possibility that firms with larger scopes may be less effective in mitigating the costs of cooperation because conditions may arise that cause intrafirm conflicts. The model is implemented on structured fitness landscapes derived using the maximal order of interaction (NM) formulation and described using local optima networks (LONs), thus integrating these novel techniques. Finally, firm dynamics can serve as a proxy for the ease at which people can voluntarily enter into the legal cooperative agreements that constitute firms. The third project, the Emergent Firm model, is an exploration of how this dynamic of voluntary association may be affected by differing capital institutions, and explores the macroeconomic implications of the economies that emerge out of the various resulting firm populations. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics for the Life and Social Sciences 2018

Patient-specific multi-physics simulations have the potential to improve the diagnosis, treatment, and scientific inquiry of heart valve dynamics. It has been shown that the flow characteristics within the left ventricle are important to correctly capture the aortic and mitral valve motion and corresponding fluid dynamics, motivating the use of patient-specific imaging to describe the aortic and mitral valve geometries as well as the motion of the left ventricle (LV). The LV position can be captured at several time points in the cardiac cycle, such that its motion can be prescribed a priori as a Dirichlet boundary condition during a simulation. Valve leaflet motion, however, should be computed from soft-tissue models and incorporated using fully-coupled Fluid Structure Interaction (FSI) algorithms. While FSI simulations have in part or wholly been achieved by multiple groups, to date, no high-throughput models have been developed, which are needed for use in a clinical environment. This project seeks to enable patient-derived moving LV boundary conditions, and has been developed for use with a previously developed immersed boundary, fixed Cartesian grid FSI framework. One challenge in specifying LV motion from medical images stems from the low temporal resolution available. Typical imaging modalities contain only tens of images during the cardiac cycle to describe the change in position of the left ventricle. This temporal resolution is significantly lower than the time resolution needed to capture fluid dynamics of a highly deforming heart valve, and thus an approach to describe intermediate positions of the LV is necessary. Here, we propose a primarily Eulerian means of representing LV displacement. This is a natural extension, since an Eulerian framework is employed in the CFD model to describe the large displacement of the heart valve leaflets. This approach to using Eulerian interface representation is accomplished by applying “morphing” techniques commonly used in the field of computer graphics. For the approach developed in the current work, morphing is adapted to the unique characteristics of a Cartesian grid flow solver which presents challenges of adaptive mesh refinement, narrow band approach, parallel domain decomposition, and the need to supply a local surface velocity to the flow solver that describes both normal and tangential motion. This is accomplished by first generating a skeleton from the Eulerian interface representation, and deforming the skeleton between image frames to determine bulk displacement. After supplying bulk displacement, local displacement is determined using the Eulerian fields. The skeletons are also utilized to automate the simulation setup to track the locations upstream and downstream where the system inflow/outflow boundary conditions are to be applied, which in the current approach, are not limited to Cartesian domain boundaries.

This study focuses on the interrelationships between risky sexual practices, substance use, and arrest history. The sample consists of 948 newly arrested juvenile offenders processed at a centralized intake facility in 2006. A series of confirmatory factor analysis and structural equation modeling techniques are used to 1) determine if risky sexual behavior, marijuana and cocaine use, and arrest history form a unidimensional latent factor, 2) examine the direct effect of age on the latent factor, and 3) compare the factor structure, as well as the effect of age on the latent factor, across four demographic subgroups based on race and gender. Results provide moderate support for all three research objectives. Important similarities, as well as differences, in the factor structure across the four groups were found. The prevention and intervention implications of the findings, limitations of the current study, and directions for future research are discussed.

Understanding coral disease dynamics within the heterogeneous populations in which they act is critical for predicting how the structure of reefs may change as a result of enzootic or epizootic levels of these important sources of mortality. This work focused on combining field studies and the development and testing of a spatially-explicit, individual-based epizootiological computer model with the aim of gaining a greater understanding of the dynamics and impact of white plague, a significant source of mortality on reef-building corals in the Caribbean region. Field studies focused on the incidence and distribution of all sources of coral mortality, including suspect white plague in situ, at two locations; the Florida Keys (United States of America) and Little Cayman Island (Cayman Islands, British West Indies). Results indicated that in both regions disease was the most significant source of mortality during the monitoring time periods, and that suspect white plague type II in Cayman is likely contributing to major structural changes. In Florida, observations made during a mass bleaching event indicated that a significant relationship exists between bleaching severity and disease incidence, and that mortality during the event was largely the result of disease and not bleaching. The simulation model was developed using a long-term data set from Little Cayman, and results of calibration indicated that suspect white plague type II on these reefs is transmissible between colonies within a limited field and require a yearly input from an outside source, and that host susceptibility to infection is low and likely not variable among species. Parameters describing the distribution and composition of the coral population were varied, and results indicated a significant effect of colony density, aggregation, and mean size on the impact of disease. Scenario testing of various disease management strategies indicated that should local prevention measures be developed in the future, it is they, and not treatment, that will likely be the most effective in limiting the impact of disease.

Many animal groups benefit from making decisions collectively. For example, colonies of many ant species are able to select the best possible nest to move into without every ant needing to visit each available nest site. Similarly, honey bee colonies can focus their foraging resources on the best possible food sources in their environment by sharing information with each other. In the same way, groups of human individuals are often able to make better decisions together than each individual group member can on his or her own. This phenomenon is known as "collective intelligence", or "wisdom of crowds." What unites all these examples is the fact that there is no centralized organization dictating how animal groups make their decisions. Instead, these successful decisions emerge from interactions and information transfer between individual members of the group and between individuals and their environment. In this thesis, I apply mathematical modeling techniques in order to better understand how groups of social animals make important decisions in situations where no single individual has complete information. This thesis consists of five papers, in which I collaborate with biologists and sociologists to simulate the results of their experiments on group decision-making in animals. The goal of the modeling process is to better understand the underlying mechanisms of interaction that allow animal groups to make accurate decisions that are vital to their survival. Mathematical models also allow us to make predictions about collective decisions made by animal groups that have not yet been studied experimentally or that cannot be easily studied. The combination of mathematical modeling and experimentation gives us a better insight into the benefits and drawbacks of collective decision making, and into the variety of mechanisms that are responsible for collective intelligence in animals. The models that I use in the thesis include differential equation models, agent-based models, stochastic models, and spatially explicit models. The biological systems studied included foraging honey bee colonies, house-hunting ants, and humans answering trivia questions.

This dissertation describes the development of CAMBIUM, an agent-based forest sector model for large-scale strategic analysis. This model is designed as a decision support tool for assessing the effect that changes in forest product demand and resource inventories can have on the structure and economic viability of the forest sector. CAMBIUM complements existing forest sector models by modeling aggregate product supply as an emergent property of individual companies’ production decisions and stand-level ecological processes. Modeling the forest products sector as a group of interacting autonomous agents makes it possible to introduce production capacity dynamics and the potential for mill insolvencies as factors in modeling the effects of market and forest inventory based disturbances. This thesis contains four main manuscripts. In the first manuscript I develop and test a dispersal algorithm that projects aggregated forest inventory information onto a lattice grid. This method can be used to generate ecologically and statistically consistent datasets where high-quality spatial inventory data is otherwise unavailable. The second manuscript utilizes this dataset in developing a provincial-level resource dynamics model for assessing the timber supply effects of introducing weevil-resistant spruce. This model employs a stand-level approach to simulating weevil infestation and associated merchantable volume losses. Provincial-level impacts are determined by simulating harvest activities over a 350 year time horizon. In the third manuscript I shift the focus to interactions between forest companies. I analyze the effects of strategic decisions on sector structure by developing CAMBIUM as an agent-based model of competition and industry structure evolution. The forest sector is modeled as a group of autonomous, interacting agents that evolve and compete within the limitations posed by resource inventories and product demand. In the final manuscript I calibrate CAMBIUM to current conditions in the British Columbia forest sector. Industry agents compete for roundwood inputs, as well as for profits in finished product markets for pulp, panel products, and lumber. To test the relevance and utility of this model, CAMBIUM is used to quantify the cumulative impacts of a market downturn for forest products and mountain pine beetle induced timber supply fluctuations on the structure of the forest sector.

Early systems engineering and requirements definition requires quantitative information about potential solutions prior to having sufficient information or time to develop detailed models. This research develops and demonstrates a transparent and repeatable process for rapidly creating quantitative models that leverage existing expert knowledge. This process is built upon established modeling frameworks and current literature for low fidelity modeling and hierarchical expert-based methods. The process includes system definition using interactive morphological analysis and gathering information from subject-matter experts with computer-based interfaces in order to create a series of linear performance models. Available volunteers provided data for a relevant aerospace design to test the process as a whole and several hypotheses about specific methodological decisions made during the development. The collected data was analyzed for similarity among participants and for similarity to model parameters of an existing trusted truth model. The results of the analysis demonstrated the ability for expert-based models to accurately match the behavior of the truth models and of historical data.