En préservation-transplantation rénale, l’ischémie-reperfusion (IR) induit inflammation, fibrose, dysfonction et perte du greffon. Les événements d’IR sont de mieux en mieux identifiés, mais leurs complexité limite prédiction et thérapeutique. A partir d’une analyse bibliographique détaillée, nous proposons un modèle par agents de la réponse rénale aux lésions d’IR au niveau cellulaire/tissulaire, réalisé avec l'outil de modélisation NetLogo.Dans un premier temps, nous développons un modèle dynamique de l’oxygénation du cortex rénal, avec apport et diffusion de l’oxygène (O2), et consommation dépendant de la filtration. Nous adaptons ce modèle à l’état stationnaire pour l’O2, puis nous couplons les niveaux de PO2 à l'état énergétique (ATP) des cellules épithéliales et endothéliales (avec voies aérobie et anaérobie). Le statut de viabilité cellulaire est lié au niveau d'ATP, aboutissant à une représentation semi-phénoménologique de la réparation/survie vs apoptose/nécrose. Enfin, nous explorons le destin cellulaire et tissulaire lors d’IR simulées, avec l’ajout progressif d’éléments clefs de l’inflammation (invasion tissulaire par leucocytes, signaux lésionnels, phagocytose) et de la fibrose (fibroblastes, collagène). L’évolution du modèle vers la résolution de l’inflammation/régénération du tissu ou vers la fibrose tissulaire est observée selon les conditions imposées (durée/intensité, ischémie vs hypoxémie).Cette construction constitue le premier modèle des effets de l’oxygénation sur la dynamique cellulaire-tissulaire de l’inflammation-fibrose rénale en réponse à l’IR. A terme, elle permettra d'aborder clinique et thérapeutique de la conservation-transplantation rénale. / In renal preservation-transplantation, ischemia-reperfusion (IR) causes graft inflammation and fibrosis, dysfunction and loss. Events involved in IR injury grow identified, but their intricacy hampers prediction and therapeutics. Based on a detailed bibliographical analysis, we propose an Agent-Based Model of renal response to IR injury at cell and tissue levels, created with the modeling tool NetLogo.First, we develop and validate a dynamic model of the oxygenation of the renal cortex, featuring blood perfusion, oxygen diffusion, and oxygen consumption (driven by sodium filtered load and transport). We then adapt this model to oxygen steady-state, and PO2 level is coupled to energetic status (ATP) in epithelial and endothelial cells (aerobic and anaerobic pathways). Cell viability is coupled to ATP level, leading to a semi-phenomenological representation of repair/survival versus apoptosis/necrosis. Finally, we explore (and verify) cell and tissue fate during simulated IR sequences, with the gradual addition of key elements of inflammation (leukocytes infiltration, injury signals, phagocytosis) and fibrosis (fibroblasts, collagen). Model evolution toward the resolution of inflammation/tissue regeneration or toward tissue fibrosis is observed along imposed conditions (duration/intensity, ischemia vs hypoxemia). Results are compared to experiments from our laboratory.This construction is the first model of the effects of oxygenation on cell-tissue dynamics during renal inflammation-fibrosis response to IR. Ultimately, it will allow to address clinical and therapeutic aspects of renal transplantation and conservation.

No contexto dos sistemas complexos, o presente trabalho investiga 3 estratégias de precificação:(1)desnatação,(2) penetração e (3)aprendizado, na difusão de carros elétricos em diferentes contextos.Por meio da modelagem baseada em agentes com 100.000 entidades autônomas, o primeiro modelo testa três situações relacionados à demanda energética:(1)desabastecimento,(2)estabilidade e (3)crescimento moderado da demanda.A forte escassez de energia estimulou a rápida migração dos agentes aos carros elétricos. As três estratégias de precificação exibiram resultados similares em termos de faturamento e % na participação do mercado, no entanto a estratégia de penetração foi capaz de capturar uma parcela maior do mercado em menor tempo.No segundo modelo,3 diferentes comportamentos sociais são aplicadas aos agentes: (1)conservador,(2)racional e (3) social,em diferentes proporções afim de avaliar a influência da composição social na dinâmica difusora.No que concerne ao faturamento e % na participação do mercado, o segundo modelo detectou diferenças estatisticamente significativas para cada estratégia de precificação.Em sociedades proeminentemente conservadoras, as três estratégias não apresentaram indícios de diferença significativa no tocante relação ao faturamento,% na participação final do mercado e taxa de adoção média.Sociedades compostas majoritariamente por agentes racionais, apresentaram a mais rápida convergência aos carros elétricos,sendo este, o veículo mais caro.Isto se deve à percepção positiva do custo/benefício ao longo prazo.O maior faturamento é proveniente das sociedades compostas preponderantemente por agentes com atitudes sociais dado à compra e troca mais recorrente entre diferentes veículos no decorrer das interações.A estratégia de desnatação demonstrou maior versatilidade ao exibir performance superior com maior regularidade no que tange em faturamento em todas as composições sociais testadas.A estratégia de penetração exibiu índices maiores em taxa de adoção e faturamento em redes compostas integralmente por agentes com comportamentos sociais iguais,mas não foi possível detectar este padrão em redes parciais. Por fim, a estratégia de aprendizado apresentou o menor faturamento em todos os cenários, no entanto, sua taxa de adoção similar à estratégia de penetração, pode ser a estratégia de precificação mais crível e eficiente para empresas iniciantes / In the context of complex systems,the following research investigated 3 pricing strategies:(1)skimming,(2)penetration and (3)learning, at electric car diffusion in several different scenarios. Through the agent-based modelling with 100.000 autonomous entities, the first model tested 3 situations related to energy demand:(1)severe shortage,(2)stability and (3)moderate growing of demand. The strong shortage of energy forced an fast-paced migration of agents towards the electric cars. The 3 strategies showed up similar results in terms revenues and market share, however the penetration strategy was able to capture a large part of the market faster than others. At the second model, 3 different social behaviors were implemented in each agent:(1)conservative,(2)rational and (3)social,in different proportions in order to assess social composition and its influence in the innovation diffusion process. Revenue and market share as concerned,the second model detected significant statistic difference for each pricing strategy. For societies predominantly conservative, all strategies did not show significant differences evidences regarding to revenue,market share and average adoption rate. Societies comprised mostly of rational agents presented the quickest convergence to electric cars, which it is the most expensive car. This is because a positive perception of benefits over cost in the long term.The largest revenue were derived from societies primarily composed of agents with social behaviors due to recurrent purchase and exchange between different vehicles over the interactions. Skimming strategy demonstrated greater versatility by displaying superior performance more regularly in terms of revenue in every social composition simulated. Penetration strategy exhibited highest rates of adoption and revenue in social networks composed entirely of agents with same social behavior, but it was not possible to detect such pattern at partial social networks. Finally, the learning strategy reported the lowest revenues at every scenario, none the less, its rate of adoption was equivalent to penetrations strategy rates, this strategy could be the most feasible and efficient to startups and small companies

In public policies, agents are part of an emergent and complex context, reason for which their actions should not be examined in isolation. The state of an agent is influenced by the state of others, in an environment where feedback is continuous and full of interactions. These characteristics result in a system where the total is more unpredictable and dazzling than the mere sum of its parts. As a result, there are a growing number of studies that use typical methods of complex systems to analyze public policies in various areas, such as healthcare, education, crime prevention, energy resources and others. Moreover, such distinct approach allows for more accessible investigations of public policy models, including policies that were not evaluated ex ante from the traditional lenses. This research had two main objectives: to verify how complex systems apply to the context of public policies theoretically and to present a practical application of a model, which was built based upon a case study. Since there is not a clear comprehension on how complex systems could benefit policy makers, this study presents, in its first part, a systematic literature review including some existing applications and the benefits of complexity science in the policy arena. On the whole, it can be asserted that there is a strong consensus that complex systems can be highly beneficial for policy makers and, consequently, for the overall population. Researchers perceive different benefits, such as the opportunity of testing policies a priori, the possibility of comparing different policies for the same topic, and the contemplation of new ideas and insights for better policy formulation. Although there are several simulations and models proposed for public policies in several areas, it lacks an empirical demonstration that effectively proves the benefits of applying complex systems in public policies, i.e., apparently, there are obstacles that prevent such models from having effects in the real world. In this way, the second part of the research presents an agent-based model that can be applied empirically in a government agency: a regulatory body. Such model allows policy makers to compare different enforcement strategies and anticipate side effects that would be difficult to predict without the use of simulations. In this sense, the objective of the second part of this research was to build an agent-based model of a public policy and for which a practical implementation could be carried out. Therefore, a public policy from a professional regulatory board in the healthcare area was chosen, for which two different strategies were tested, with the objective of comparing their efficiency and effectiveness. Such strategies were modeled and simulated with the use of Netlogo software with different scenarios. Results indicate that agent based models can serve as predictive tools for comparing and improving inspection strategies, and also as source of insights for anticipating unintended consequences that would hardly be noticed ex ante without the use of simulation tools / Em políticas públicas, as ações dos agentes envolvidos não podem ser analisadas de forma isolada. O estado de um agente é influenciado pelo estado dos demais, num ambiente em que o feedback é contínuo e repleto de interações. Essas características resultam num sistema onde o total é mais imprevisível e deslumbrante do que a mera soma de suas partes. Com isso, há um crescente número de estudos que utilizam métodos típicos de sistemas complexos para analisar políticas públicas de diversas áreas, como saúde pública, educação, segurança, recursos energéticos e outros. Além disso, essa forma diferente de abordagem permite que alguns modelos de políticas públicas sejam investigados com mais facilidade, incluindo políticas que sequer eram analisadas pelo prisma tradicional. Esta pesquisa teve dois objetivos principais: verificar como os sistemas complexos se aplicam às políticas públicas no campo teórico e apresentar uma aplicação prática de modelagem dentro do contexto de um estudo de caso. Como ainda não há um entendimento sistematizado sobre como sistemas complexos podem ser úteis em políticas públicas, este estudo apresenta, em sua primeira parte, uma revisão sistemática de literatura para uma melhor compreensão de como essas aplicações ocorrem e de quais benefícios essa ciência, de fato, pode trazer. Em decorrência desse estudo, pode-se afirmar que há consenso, na literatura, de que a teoria da complexidade é benéfica para formuladores de políticas e, consequentemente, para a população em geral. Tais benefícios são vistos de diversas formas pelos pesquisadores, como, por exemplo, a possibilidade de se testar políticas a priori, a possibilidade de se comparar diversos tipos de políticas para um mesmo problema e a obtenção de novas perspectivas e ideias para formulação de políticas. Apesar de haver diversas simulações e modelos propostos para políticas públicas em diversas áreas, não foi constatada uma demonstração empírica que comprove efetivamente o benefício de se aplicar sistemas complexos em políticas públicas, ou seja, aparentemente há obstáculos que impedem esses modelos terem efeitos nas políticas de facto. Dessa maneira, o objetivo da segunda parte da pesquisa foi o de construir um modelo baseado em agentes relacionado a uma política pública e cuja implementação prática fosse factível. Assim, foi selecionada uma política relacionada a um órgão público de fiscalização do exercício profissional (conselho de classe), especificamente na área da saúde, para a qual foram traçadas duas estratégias diferentes, com o objetivo de compará-las em termos de eficácia e de efetividade. Essas estratégias foram modeladas e simuladas em software específico de modelos baseados em agentes para análise dos resultados considerando diversos cenários possíveis. Os resultados indicam que os modelos baseados em agentes podem auxiliar o formulador de políticas a comparar diferentes estratégias de fiscalização e antecipar efeitos colaterais que dificilmente seriam constatados ex ante sem a utilização de simulações

In ecology literature, there is much data which suggests that conspecific negative density dependence (CNDD) and abiotic disturbances increase biodiversity in forests. This thesis elucidates the notion that not only do these two forces increase diversity, but they may also interact with one another in order to achieve higher levels of biodiversity. Abiotic disturbances, like fires and hurricanes, can indirectly impact conspecific effects because when these forces remove individuals from the landscape, the role of the conspecific effects will change. The interaction of these two factors in biodiversity are explored in an agent based forest simulation through a resource surface. Several different types of abiotic disturbances are simulated with either weak or strong CNDD effects in order to establish that different disturbances and conspecific effects cause certain levels of diversity. The underlying causes for the change in impact is also examined.

Die Arbeit beschreibt ein Modell, dass den Materialfluss in Transport- und Puffersystemen mit Hilfe eines agenten-basierten Ansatzes realistisch abbildet. Auf der Basis von Produktionsprogrammen werden individuelle Güter in beliebigen Netzwerkstrukturen mit Hilfe direkter und indirekter Interaktionen behinderungsvermeidend gesteuert. / The thesis describes a model that realistically illustrates the material flow in transport and buffer systems by means of an agent-based approach. Individual goods are steered hindrance-avoiding in arbitrary network structures based on production programs by means of direct and indirect interactions.

Univ., Diss.--Kassel, 2007.

本研究是利用代理人基模型 (Agent-Based model) 結合遺傳規劃法(genetic programming) 在模組化經濟體系下價格動態對市占率之影響。現今企業多數以市占率作為公司在市場上表現的主要指標，如果擁有高市占率的廠商，可以確定在這產業中生存。以往的文獻顯示模組化經濟下高價格廠商在市場上的表現會優於低價格廠商，取決重要因素為品質，因為高價產品通常品質也較高，容易取得消費者喜愛。本研究想探討是否在這個體系下，消費者所考量的都是以品質高低來決定是否購買產品，是否會有過去以往的價格競爭情形，以及在價格動態體系，市場所呈現的風貌如何。本研究設計39組的加成率參數組，並依據兩間廠商的決策上製作成價格動態矩陣圖表。試圖以這些已知參數組與線性內插法所預測之市占率的參數組進行分析。此研究模擬中發現，在模組化經濟下，價格競爭並不一定會讓市占率趨向於某一點均衡，也可能會趨向於一條路徑上。而且不一定是高價位的廠商會有很大機會獲得市場，也沒有所謂的贏家擁有超高市占率的情況產生。 / This study is the use of agent-based model combined with genetic programming to explore the impact of the price dynamics for the market share in the modular economy. Nowadays, the majority of enterprises use market share as the key performance indicators in the market, if the enterprise has a high market share, it can be determined to survive in this industry. The previous literature shows that manufacturers of high prices on the market under the modular economy will be better than the low-price manufacturers, depending on the important factors for quality. Expensive products are usually higher quality, easily favorite by consumers. My study is to investigate whether consumers consider in this system are based on the level of quality to decide to buy the product or not, and whether there will be price competitive situation, as well as the outlook presented by the market price dynamics system. In this paper, we design 39 markup rate’s parameter set and making price dynamic matrix diagram in accordance with the decisions of two manufacturers. Trying to analyze these known parameter set and the parameter set of the market share predicted by the linear interpolation. The simulation of the study found that in the modular economy price competition does not necessarily make the market share tends to a equilibrium point, or it may also tend to be a equilibrium path. But not necessarily high-priced manufacturers get to the market, there is no so-called winners with higher market share.

Coral reefs are one of the most productive, diverse and complex ecosystems on Earth. They are very important ecologically, economically and socially, but are subject to increasing deleterious disturbances. To protect coral reefs and manage the sustainable use of their resources it is necessary to understand how coral communities respond to disturbances and to use this understanding to project the likely ecological trajectories of disturbed coral reefs in spatial and temporal contexts. Three powerful tools exist to address this issue: (1) in situ monitoring that describes ecological transitions of coral communities at very fine spatial scale; (2) time-series of maps derived from high spatial resolution remote sensing images that provide multi-temporal synoptic views of the reefs; and (3) spatially- and temporally-explicit models that are able to handle ecosystems complexity and represent their spatial dynamics. The combination of these three tools to map and monitor coral communities remained to be addressed. This dissertation developed an integrative approach to characterise, map and model coral communities’ responses to disturbances. This approach provides a basis for monitoring coral reefs at temporal and spatial scales matched to disturbance impacts and coral reefs patchiness. This was achieved by investigating the dynamics of three different Indo-Pacific reefs and by following four steps: - Developing and applying a method to characterise how detailed coral communities can be mapped before and after a major cyclone event from a short time-series of high spatial resolution images (IKONOS, Quickbird) on Aboré Reef (New-Caledonia); - Using the methods developed in the first step to assess whether decadal-scale coral dynamics can be retraced and monitored from time-series of aerial photographs and satellite images spanning at least 30 years on Saint-Leu (Réunion Island) and Heron (Australia) Reefs; - Developing a spatially- and temporally-explicit model of coral communities’ dynamics with cellular agent-based formalism on the western section of Heron reef flat; and - Assessing the relevance of the mapping, monitoring and modelling tools developed in this work, into an integrated approach for coral reef monitoring. For the first step, accurate monitoring requires that descriptions of the reef features are coherent with the local scale of disturbance impacts in space and time. While such a monitoring paradigm is applied in terrestrial environments, it is not the case for coral reefs. A before-after cyclone time-series of satellite images from Aboré Reef was used to test this paradigm on coral reefs. In situ data provided a new three-level hierarchical coral community typology (45 classes at the finest level). Photo-interpretation and hierarchical mapping methods were applied to an IKONOS image and a Quickbird image taken before and after cyclone Erica respectively. Application of this paradigm yielded a highly detailed multi-temporal maps of pre- and post-cyclone coral communities and recommendations to design reef-scale monitoring protocols. For the second step, the temporal scale of monitoring projects needs also to match the inherent reef dynamics. To assess the applicability of this temporal component of the paradigm at a decadal scale, the hierarchical mapping approaches developed for Aboré Reef were applied to a 33-year time-series of satellite images (two Quickbird images) and airborne photographs (five scanned images) of Saint-Leu Reef. The mapping approach overcame challenges due to different images qualities and to the lack of in situ observations in time and space before cyclone Firinga in 1989. This demonstrated the potential for further applications of the approach in reef monitoring protocols based on complementary in situ and remote sensing data to help understand the dynamics of reef-top coral reef communities and geomorphology over years to decades. In the next step, the modelling component of this work focused on a proof-of-concept for spatially-explicit modelling of coral growth by simulating maps of reef flat colonisation on a 16 686 m2 section of Heron Reef. To do this a 35-year time-series of two satellite Quickbird pan-sharpened images and five aerial photographs of Heron Reef was first used to hierarchically map and quantify the areal expansion of coral on the reef flat. The coral growth was driven by several artificially induced local sea-level rises associated with engineering works on the reef flat. Vertical and horizontal growth rates were quantified in terms of percentage of the total area colonised each year by corals. Coral community maps and coral growth rates estimated from the image time-series were used to constrain an accretive cellular growth model. Although only preliminary the model produced coral growth likelihood maps corresponding to observed fine-scale coral growth patterns. This suggested the tool had promise for further applications in reef management. This dissertation developed an integrative approach to characterise, map and model coral communities’ responses to disturbances, providing a basis for monitoring coral reefs at ecological, temporal, and spatial scales matching the patchiness of the communities’ distribution and disturbance impacts. The contributions of the work to the applied fields of coral reef mapping, modelling and monitoring were demonstrated through the results achieved and the development of protocols that do not require specialized image processing algorithms and methods. This opens perspectives for further development of the approach on other coral reefs around the world.

Millions of users world-wide are sharing content using Peer-to-Peer (P2P) networks, such as Skype and Bit Torrent. While such new innovations undoubtedly bring benefits, there are nevertheless some associated threats. One of the main hazards is that P2P worms can penetrate the network, even from a single node and then spread rapidly. Understanding the propagation process of such worms has always been a challenge for researchers. Different techniques, such as simulations and analytical models, have been adopted in the literature. While simulations provide results for specific input parameter values, analytical models are rather more general and potentially cover the whole spectrum of given parameter values. Many attempts have been made to model the worm propagation process in P2P networks. However, the reported analytical models to-date have failed to cover the whole spectrum of all relevant parameters and have therefore resulted in high false-positives. This consequently affects the immunization and mitigation strategies that are adopted to cope with an outbreak of worms. The first key contribution of this thesis is the development of a susceptible, exposed, infectious, and Recovered (SEIR) analytical model for the worm propagation process in a P2P network, taking into account different factors such as the configuration diversity of nodes, user behaviour and the infection time-lag. These factors have not been considered in an integrated form previously and have been either ignored or partially addressed in state-of-the-art analytical models. Our proposed SEIR analytical model holistically integrates, for the first time, these key factors in order to capture a more realistic representation of the whole worm propagation process. The second key contribution is the extension of the proposed SEIR model to the mobile M-SEIR model by investigating and incorporating the role of node mobility, the size of the worm and the bandwidth of wireless links in the worm propagation process in mobile P2P networks. The model was designed to be flexible and applicable to both wired and wireless nodes. The third contribution is the exploitation of a promising modelling paradigm, Agent-based Modelling (ABM), in the P2P worm modelling context. Specifically, to exploit the synergies between ABM and P2P, an integrated ABM-Based worm propagation model has been built and trialled in this research for the first time. The introduced model combines the implementation of common, complex P2P protocols, such as Gnutella and GIA, along with the aforementioned analytical models. Moreover, a comparative evaluation between ABM and conventional modelling tools has been carried out, to demonstrate the key benefits of ease of real-time analysis and visualisation. As a fourth contribution, the research was further extended by utilizing the proposed SEIR model to examine and evaluate a real-world data set on one of the most recent worms, namely, the Conficker worm. Verification of the model was achieved using ABM and conventional tools and by then comparing the results on the same data set with those derived from developed benchmark models. Finally, the research concludes that the worm propagation process is to a great extent affected by different factors such as configuration diversity, user-behaviour, the infection time lag and the mobility of nodes. It was found that the infection propagation values derived from state-of-the-art mathematical models are hypothetical and do not actually reflect real-world values. In summary, our comparative research study has shown that infection propagation can be reduced due to the natural immunity against worms that can be provided by a holistic exploitation of the range of factors proposed in this work.

Submitted by ERIKA REGINA DA SILVA GALLO null (erika.regina@hotmail.com) on 2016-09-15T19:21:48Z No. of bitstreams: 1 Versão Final.pdf: 1593845 bytes, checksum: e99e5b67cc74cf377bfd115091bec7e9 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-09-21T20:08:06Z (GMT) No. of bitstreams: 1 gallo_ers_me_arafcl.pdf: 1593845 bytes, checksum: e99e5b67cc74cf377bfd115091bec7e9 (MD5) / Made available in DSpace on 2016-09-21T20:08:06Z (GMT). No. of bitstreams: 1 gallo_ers_me_arafcl.pdf: 1593845 bytes, checksum: e99e5b67cc74cf377bfd115091bec7e9 (MD5) Previous issue date: 2016-09-09 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Neste trabalho temos a intenção de contribuir com o debate na área de economia e finanças comportamentais ao realizar um estudo sobre o comportamento do mercado acionário ao incluirmos o viés de comportamento aversão à perda aos agentes que ali operam. Para tanto, em um primeiro momento, fez-se uma concisa revisão da teoria da decisão na escola econômica e seus desdobramentos em finanças, no que tange à Hipótese dos Mercados Eficientes. Em um segundo momento, apresentamos um modelo de agente aplicado ao mercado acionário que foi programado em software livre NetLogo, cujo método é, em parte, baseado em modelos de agentes já programados para mercados financeiros artificiais e, ao mesmo tempo, parcialmente novo ao propor a realização de testes com parâmetros diferentes dos utilizados por outros autores – a saber: aversão à perda. Os resultados encontrados sugerem que a subjetividade humana presente na tomada de decisão, isto é, quando os agentes possuem aversão à perda, faz com que o movimento do mercado acionário artificial apresente alguns ruídos. Destarte, concluímos que os experimentos realizados nos oferecem indícios de que há certa fragilidade em alguns pressupostos da Hipótese dos Mercados Eficientes. / In this work, we intend to contribute to the debate in behavioral economics and finance to conduct a study on how Stock Markets behaves by including the loss averse agent's bias on this environment. At first, we built a concise review of the decision theory on economic school and its developments in finance, regarding to Efficient Market Hypothesis. Secondly, we presented an agent-based model applied to the stock market which has been programmed in the free software NetLogo, whose has, in part, agent-based models already programmed for artificial financial markets and at the same time, is partially new to propose conduction tests, which differ from other parameters used by several authors such as: loss aversion. The results suggest that human's subjectivity, inherently presented in decision-making, that is, when agents have loss aversion, it may cause the artificial stock market movement to present some noise. Thus, we conclude that the experiments give us evidence that there is some fragility on the Efficient Market Hypothesis. / CNPq: 130136/2015-8