By Jose Faro, Jaime Combadao, Isabel Gordo (auth.), Hugues Bersini, Jorge Carneiro (eds.)
ICARIS 2006 is the ?fth example of a chain of meetings devoted to the comprehension and the exploitation of immunological rules via their translation into computational phrases. All scienti?c disciplines sporting a reputation that starts off with “arti?cial” (followed via “life,” “reality,” “intelligence” or “- munesystem”) aresimilarlysu?ering froma veryambiguousidentity.Their axis of study attempts to stabilize an on-going id someplace within the crossroad of engineering (building worthwhile artifacts), ordinary sciences (biologyor psychology— bettering the comprehension and prediction of average phenomena) and t- oretical laptop sciences (developing and learning the algorithmic world). consequently and counting on which of those views gets extra s- port, they try at attracting di?erent varieties of scientists and at stimul- ing di?erent types of scienti?c attitudes. for a few years and within the past ICARIS meetings, it was once in actual fact the “engineering” viewpoint that used to be the main represented and prevailed throughout the courses. certainly, because the o- gin of engineering and expertise, nature has o?ered a reserve of inexhaustible inspirations that have motivated the improvement of helpful artifacts for guy. Biology has ended in the improvement of latest laptop instruments, comparable to genetic - gorithms, Boolean and neural networks, robots studying through adventure, mobile machines and others that create a brand new imaginative and prescient of IT for the engineer: parallel, ?exible andautonomous.Inthis kind of informatics,complexproblemsareta- led through easy mechanisms, yet in?nitely iterated in time and space.
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Additional info for Artificial Immune Systems: 5th International Conference, ICARIS 2006, Oeiras, Portugal, September 4-6, 2006. Proceedings
The agent-based model’s four states for epithelial cells, (Healthy, Containing, Secreting, and Dead), and the parameters responsible for controlling the transitions between these states that a healthy cell will become infected (enter the containing stage). In other words, k × Vm,n gives the probability that the healthy cell located at site (m, n) will become infected over the course of an hour. In order to ﬁt experimental data, we set the rate of infection of cells per virions in our model to k = 8 per virion at that site per hour.
Here, we describe the model as it is currently implemented. We are modeling inﬂuenza dynamics on an epithelial cell monolayer in vitro. The monolayer is represented as a two-dimensional hexagonal lattice where each site represents one epithelial cell. The spread of the infection is modeled by including virions. Rather than treat each virion explicitly, the model instead considers the concentration of virions by associating a continuous real-valued variable with each lattice site, which stores the local concentration of virions at that site.
Nature 440(7083) (2006) 435–436 29. : H5N1 virus attachment to lower respiratory tract. Science 312(5772) (2006) 399 Originally published in Science Express on 23 March 2006. ¨ 30. : Transcode. org. (2001) 31. : MASyV: A Multi-Agent System Visualization package. net. (2003) 32. : Probing the eﬀects of the well-mixed assumption on viral infection dynamics. J. Theor. Biol. CB/0505043. Cellular Frustration: A New Conceptual Framework for Understanding Cell-Mediated Immune Responses F. M. R. M. Davis2 1 Depto.