The Redner - Ben-Avraham - Kahng cluster system

We consider a coagulation model first introduced by Redner, Ben-Avraham and Krapivsky in [Redner, Ben-Avraham, Kahng: Kinetics of 'cluster eating', J. Phys. A: Math. Gen., 20 (1987), 1231-1238], the main feature of which is that the reaction between a j-cluster and a k-cluster results in the creation of a |j-k|-cluster, and not, as in Smoluchowski's model, of a (j+k)-cluster. In this paper we prove existence and uniqueness of solutions under reasonably general conditions on the coagulation coefficients, and we also establish differenciability properties and continuous dependence of solutions. Some interesting invariance properties are also proved. Finally, we study the long-time behaviour of solutions, and also present a preliminary analysis of their scaling behaviour.Comment: 24 pages. 2 figures. Dedicated to Carlos Rocha and Luis Magalhaes on the occasion of their sixtieth birthday

The Redner - Ben-Avraham - Kahng coagulation system with constant coefficients: the finite dimensional case

We study the behaviour as $t\to\infty$ of solutions $(c_j(t))$ to the Redner--Ben-Avraham--Kahng coagulation system with positive and compactly supported initial data, rigorously proving and slightly extending results originally established in [4] by means of formal arguments.Comment: 13 pages, 1 figur

A relevância da pesquisa de impactos sociais.

bitstream/CNPS-2010/14911/1/doc77-2005-impactosocial.pd

Aspectos teórico-metodológicos da abordagem participativa na agricultura familiar.

bitstream/item/24820/1/doc121-2010-agricultura-familiar.pd

Knowledge Acquisition by Networks of Interacting Agents in the Presence of Observation Errors

In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erd\H{o}s-Renyi or Barabasi-Albert type. First we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall behavior of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.Comment: 10 pages, 7 figures. A working manuscrip

What are the Best Hierarchical Descriptors for Complex Networks?

This work reviews several hierarchical measurements of the topology of complex networks and then applies feature selection concepts and methods in order to quantify the relative importance of each measurement with respect to the discrimination between four representative theoretical network models, namely Erd\"{o}s-R\'enyi, Barab\'asi-Albert, Watts-Strogatz as well as a geographical type of network. The obtained results confirmed that the four models can be well-separated by using a combination of measurements. In addition, the relative contribution of each considered feature for the overall discrimination of the models was quantified in terms of the respective weights in the canonical projection into two dimensions, with the traditional clustering coefficient, hierarchical clustering coefficient and neighborhood clustering coefficient resulting particularly effective. Interestingly, the average shortest path length and hierarchical node degrees contributed little for the separation of the four network models.Comment: 9 pages, 4 figure

Ganho genético monetário para resistência ao carrapato com diferentes acurácias.

SIEPE

Delineamento de esquemas de seleção genômica para resistência ao carrapato bovino.

CONGREGA

Avaliação da tecnologia zoneamento de risco climático da cultura do sorgo no Estado de Pernambuco.

O zoneamento da área de risco climático do sorgo no Estado de Pernambuco veio atender a uma demanda do setor avícola que estava crescendo mas seus custos eram altos pela dependência do milho para a produção da ração das aves. O milho é muito sensível à estiagem enquanto o sorgo é cultivado em áreas muito secas e/ou muito quentes próprias da região do Semi-árido e Sertão, onde a produtividade de outros cereais é antieconômica. Este trabalho fez uma avaliação dos impactos da tecnologia do zoneamento do risco climático da cultura do sorgo nas áreas do semi-árido de Pernambuco, sob os aspectos econômicos, sociais e ambientais. O estudo abrangeu um período de três anos, empregando a Metodologia de Referência da Embrapa. Sob o ponto de vista econômico, o resultado encontrado foi de um grande aumento da área plantada, da quantidade produzida de sorgo e da renda gerada. No aspecto social houve aumento de emprego. Quanto ao aspecto ambiental não houve preocupação na conservação e recuperação dos recursos naturais.bitstream/CNPS-2010/14746/1/bpd139-2009-avaliacao-zoneamento-sorgo.pd

Surviving opinions in Sznajd models on complex networks

The Sznajd model has been largely applied to simulate many sociophysical phenomena. In this paper we applied the Sznajd model with more than two opinions on three different network topologies and observed the evolution of surviving opinions after many interactions among the nodes. As result, we obtained a scaling law which depends of the network size and the number of possible opinions. We also observed that this scaling law is not the same for all network topologies, being quite similar between scale-free networks and Sznajd networks but different for random networks.Comment: 9 pages, 3 figure