Optimized Gillespie algorithms for the simulation of Markovian epidemic processes on large and heterogeneous networks

Numerical simulation of continuous-time Markovian processes is an essential and widely applied tool in the investigation of epidemic spreading on complex networks. Due to the high heterogeneity of the connectivity structure through which epidemics is transmitted, efficient and accurate implementations of generic epidemic processes are not trivial and deviations from statistically exact prescriptions can lead to uncontrolled biases. Based on the Gillespie algorithm (GA), in which only steps that change the state are considered, we develop numerical recipes and describe their computer implementations for statistically exact and computationally efficient simulations of generic Markovian epidemic processes aiming at highly heterogeneous and large networks. The central point of the recipes investigated here is to include phantom processes, that do not change the states but do count for time increments. We compare the efficiencies for the susceptible-infected-susceptible, contact process and susceptible-infected-recovered models, that are particular cases of a generic model considered here. We numerically confirm that the simulation outcomes of the optimized algorithms are statistically indistinguishable from the original GA and can be several orders of magnitude more efficient.Comment: 12 pages, 9 figure

Griffiths effects of the susceptible-infected-susceptible epidemic model on random power-law networks

We provide numerical evidence for slow dynamics of the susceptible-infected-susceptible model evolving on finite-size random networks with power-law degree distributions. Extensive simulations were done by averaging the activity density over many realizations of networks. We investigated the effects of outliers in both highly fluctuating (natural cutoff) and non-fluctuating (hard cutoff) most connected vertices. Logarithmic and power-law decays in time were found for natural and hard cutoffs, respectively. This happens in extended regions of the control parameter space $\lambda_1<\lambda<\lambda_2$, suggesting Griffiths effects, induced by the topological inhomogeneities. Optimal fluctuation theory considering sample-to-sample fluctuations of the pseudo thresholds is presented to explain the observed slow dynamics. A quasistationary analysis shows that response functions remain bounded at $\lambda_2$. We argue these to be signals of a smeared transition. However, in the thermodynamic limit the Griffiths effects loose their relevancy and have a conventional critical point at $\lambda_c=0$. Since many real networks are composed by heterogeneous and weakly connected modules, the slow dynamics found in our analysis of independent and finite networks can play an important role for the deeper understanding of such systems.Comment: 10 pages, 8 figure

Griffiths phases in infinite-dimensional, non-hierarchical modular networks

Griffiths phases (GPs), generated by the heterogeneities on modular networks, have recently been suggested to provide a mechanism, rid of fine parameter tuning, to explain the critical behavior of complex systems. One conjectured requirement for systems with modular structures was that the network of modules must be hierarchically organized and possess finite dimension. We investigate the dynamical behavior of an activity spreading model, evolving on heterogeneous random networks with highly modular structure and organized non-hierarchically. We observe that loosely coupled modules act as effective rare-regions, slowing down the extinction of activation. As a consequence, we find extended control parameter regions with continuously changing dynamical exponents for single network realizations, preserved after finite size analyses, as in a real GP. The avalanche size distributions of spreading events exhibit robust power-law tails. Our findings relax the requirement of hierarchical organization of the modular structure, which can help to rationalize the criticality of modular systems in the framework of GPs.Comment: 14 pages, 8 figure

Quantifying echo chamber effects in information spreading over political communication networks

Echo chambers in online social networks, in which users prefer to interact only with ideologically-aligned peers, are believed to facilitate misinformation spreading and contribute to radicalize political discourse. In this paper, we gauge the effects of echo chambers in information spreading phenomena over political communication networks. Mining 12 million Twitter messages, we reconstruct a network in which users interchange opinions related to the impeachment of the former Brazilian President Dilma Rousseff. We define a continuous {political position} parameter, independent of the network's structure, that allows to quantify the presence of echo chambers in the strongly connected component of the network, reflected in two well-separated communities of similar sizes with opposite views of the impeachment process. By means of simple spreading models, we show that the capability of users in propagating the content they produce, measured by the associated spreadability, strongly depends on their attitude. Users expressing pro-impeachment sentiments are capable to transmit information, on average, to a larger audience than users expressing anti-impeachment sentiments. Furthermore, the users' spreadability is correlated to the diversity, in terms of political position, of the audience reached. Our method can be exploited to identify the presence of echo chambers and their effects across different contexts and shed light upon the mechanisms allowing to break echo chambers.Comment: 9 pages, 4 figures. Supplementary Information available as ancillary fil

O USO DA ARTE COMO INSTRUMENTO DE INTERVENÇÃO NAS MANIFESTAÇÕES COTIDIANAS DAS EXPRESSÕES DA QUESTÃO SOCIAL

O presente estudo é fruto da experiência oportunizada pelo projeto de extensão Serviço Social Sociojurídico: Núcleo de Atendimento às Demandas de Violência Doméstica e/ou Intrafamiliar. Objetiva discutir acerca das possibilidades de intervenção, para o assistente social, utilizando a arte. Fundamentando-se no potencial sensibilizador desta para que os sujeitos se reconheçam enquanto agentes que reproduzem e fortalecem os processos de violência, mas que também sofrem com a violência estrutural, elemento determinante das relações sociais na sociedade capitalista, manifestada através das expressões da questão social. Os atendimentos, eram realizados a partir de entrevistas dialético-reflexivas. Ao final desse processo identificou-se a necessidade do processo de conhecimento antes de se iniciar qualquer processo de intervenção, para que a partir disto, e com o uso da arte, os usuários possam compreender os processos particulares de uma forma mais ampla, desvendamento as relações de estranhamento entre si e as coisas, no intuito de instigar processos reflexivo

Griffiths phases in infinite-dimensional, non-hierarchical modular networks

Griffiths phases (GPs), generated by the heterogeneities on modular networks, have recently been suggested to provide a mechanism, rid of fine parameter tuning, to explain the critical behavior of complex systems. One conjectured requirement for systems with modular structures was that the network of modules must be hierarchically organized and possess finite dimension. We investigate the dynamical behavior of an activity spreading model, evolving on heterogeneous random networks with highly modular structure and organized non-hierarchically. We observe that loosely coupled modules act as effective rare-regions, slowing down the extinction of activation. As a consequence, we find extended control parameter regions with continuously changing dynamical exponents for single network realizations, preserved after finite size analyses, as in a real GP. The avalanche size distributions of spreading events exhibit robust power-law tails. Our findings relax the requirement of hierarchical organization of the modular structure, which can help to rationalize the criticality of modular systems in the framework of GPs

Robustness and fragility of the susceptible-infected-susceptible epidemic models on complex networks

We analyze two alterations of the standard susceptible-infected-susceptible (SIS) dynamics that preserve the central properties of spontaneous healing and infection capacity of a vertex increasing unlimitedly with its degree. All models have the same epidemic thresholds in mean-field theories but depending on the network properties, simulations yield a dual scenario, in which the epidemic thresholds of the modified SIS models can be either dramatically altered or remain unchanged in comparison with the standard dynamics. For uncorrelated synthetic networks having a power-law degree distribution with exponent $\gamma<5/2$, the SIS dynamics are robust exhibiting essentially the same outcomes for all investigated models. A threshold in better agreement with the heterogeneous rather than quenched mean-field theory is observed in the modified dynamics for exponent $\gamma>5/2$. Differences are more remarkable for $\gamma>3$ where a finite threshold is found in the modified models in contrast with the vanishing threshold of the original one. This duality is elucidated in terms of epidemic lifespan on star graphs. We verify that the activation of the modified SIS models is triggered in the innermost component of the network given by a $k$-core decomposition for $\gamma<3$ while it happens only for $\gamma3$, the activation in the modified dynamics is collective involving essentially the whole network while it is triggered by hubs in the standard SIS. The duality also appears in the finite-size scaling of the critical quantities where mean-field behaviors are observed for the modified, but not for the original dynamics. Our results feed the discussions about the most proper conceptions of epidemic models to describe real systems and the choices of the most suitable theoretical approaches to deal with these models.Comment: 13 pages, 8 figure

Relatório de atividades do estágio supervisionado obrigatório : clínica médica e cirúrgica de animais silvestres

Orientador : Anderson Luiz de CarvalhoMonografia (graduação) - Universidade Federal do Paraná, Setor de Palotina, Curso de Graduação em Medicina VeterináriaInclui referênciasResumo : O presente relatório de estágio obrigatório refere-se às atividades desenvolvidas nas áreas de Clínica Médica e Cirúrgica de Animais Silvestres (CMCAS) na Universidade Federal do Paraná- Setor Palotina (UFPR Setor Palotina), no período de 26 de Fevereiro à 11 de Maio de 2018 totalizando 440 horas, sob orientação do Prof. Me. Anderson Luiz de Carvalho e supervisão da Médica Veterinária Residente Stacy Wu. No presente relatório será feita a descrição do funcionamento do Hospital Veterinário da Universidade Federal do Paraná- Setor Palotina (HV UFPR- Setor Palotina) bem como a sua estrutura, a casuística acompanhada incluindo a rotina da clínica médica e cirúrgica de animais silvestres durante o período de vigência do estágio, as saídas a campo e o manejo realizado nos animais silvestres internados no Hospital Veterinário (HV) incluindo as técnicas ambulatoriais empregadas tais como exame físico, interpretação de resultados, discussão de possíveis diagnósticos, tratamentos e medicações, alimentação e higienização do ambiente de internamento

Modelagem e simulação do processo de extração seletiva de cobalto e niquel por solução organica atraves da aplicação de tecnicas de redes neurais

Orientadores : Milton Mori, Reinaldo Krause Spitzner JuniorDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia QuimicaResumo: A indústria química sofreu e tem sofrido mudanças constantes durante os últimos anos, principalmente devido à progressiva transformação dos recursos tecnológicos, aumento do custo de energia, às restrições ambientais e à crescente competitividade mundial, tendo como causa principal a globalização do mercado. Em função deste panorama, vê-se a necessidade do contínuo desenvolvimento de competências essenciais, que irão sustentar esta competitividade para assim diferenciá-la estrategicamente, aumentando a necessidade de conhecimento detalhado dos processos e maior demanda de desenvolvimento tecnológico. A inteligência artificial vem ao encontro deste interesse por ser atrativa e importante na compreensão de vários processos principalmente químicos, sendo um conjunto de técnicas promissoras na modelagem e simulação de processos industriais que apresentam não linearidades, como por exemplo, as técnicas de Redes Neurais Artificiais (R.NA). Este trabalho apresenta a aplicação da metodologia de redes neurais na modelagem, simulação e aplicação de uma parte do processo industrial da VOTORANTIN - CNT (Companhia Níquel Tocantins) de obtenção de níquel e cobalto eletrolíticos. Esta parte do processo consiste na extração de níquel e cobalto de uma solução de sulfatos através de uma solução orgânica fosfinica, em que os parâmetros característicos ainda não são bem conhecidos por apresentarem complexa modelagem fenomenológica. Foram gerados dados através de experimentos (removendo erros grosseiros), variando os valores dos seguintes parâmetros: pH temperatura e volume de orgânico. O Planejamento experimental foi realizado após estudo do processo e verificação das possibilidades e necessidades industriais para simular a extração dos metais e podendo assim mapear uma solução (otimização) através de redes neurais. Os resultados da modelagem via R.NA foram muito satisfatórios quando comparados a muitos da literatura, pois mostra a necessidade da qualidade dos dados e seu tratamento antes da alimentação à rede e a possibilidade de encontrar redes simples para modelagens complexas. Desta forma, as R.NA são apresentadas como importante ferramenta na otimização e controle de processos não linearesAbstract: The chemical industry changed and has been changing constantly during the last years, mainly due to the progressive transformation of the technological resources, energy increasing price, environmental restrictions and world increasing competition, being the market globalization the main cause. Thus, there is a necessity of a continuous development of essential competences that will support this competition to make it strategically different, increasing the necessity of a detailed knowledge of the processes and a higher request of technological development. The neural networks techniques come together with this interest because they are attractive and important to the several processes comprehension, mainly chemicals, being a part of a set of promising techniques in modeling and simulation of industrial processes that are non linear. This task presents the application of neural networks methodology for modeling, simulation and application of a part of VOTORANTIM - CNT (Companhia Níquel Tocantins) industrial processes, obtaining nickel and cobalt from a sulphate mixture through a phosphinic organic mixture where the characteristic parameters are not well known yet because they present a phenomenological modeling compound. Data were available from the changing the values of the following parameters, pH, temperature and organic volume. The experimental planning was accomplished after a study of the process and examination of the possibilities and industrial necessities to simulate the metals extraction and in this manner, being able to map a mixture (optimization) from neural networks. The results of the modeling via ANN were very satisfactory when compared to those of the literature, because they show the necessity of data quality and its treatment before net supplying and the possibility of finding ordinary nets to complex modeling. In this way the ANN are presented as important tools for the optimization and control of non linear processesMestradoMestre em Engenharia Químic

Recuperação de área degradada em reserva legal: uma proposta de análise econômica à luz da teoria dos custos de oportunidade

Artigo apresentado à Fundação Universidade Federal de Rondônia – UNIR, Campus de Cacoal, como requisito parcial para obtenção do grau de Bacharel em Ciências Contábeis. Orientadora: Professora Ma. Suzenir da Silva Aguiar SatoEste trabalho teve como objetivo verificar qual alternativa é mais viável economicamente a luz da teoria econômica do custo de oportunidade, para um possível investimento do valor a ser empregado na recuperação da reserva legal na área localizada na Linha 108, Lado Sul, Km 28,8, Gleba 10, Setor Primavera, Lote 70, Projeto Fundiário Guajará Mirim, no município de São Miguel do Guaporé-RO. A metodologia utilizada para realização deste trabalho foi uma revisão bibliográfica, análise documental e um estudo de caso realizado através do projeto de recuperação de reserva legal. O método de avaliação econômica foi o Valor Presente Líquido. Os resultados encontrados permitiram concluir que implantar a cultura do café robusta é mais viável, pois apresentou um VPL de R$ 1.014,65 por hectare, sendo que para criação de gado foi obtido um VPL negativo, o que inviabiliza o investimento. Já para o investimento em CDB o valor resultante foi igual a zero, o que mostra que renderia somente a taxa de atratividade esperada