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Resumenes 102 trees are contagious if one of them is sick, which can be determined by the existing distance between the branches of the trees. A connected couple are two immediate trees which mutual contagion is inevitable. 3) A function exists x(a) that defines the probability of which two immediate trees chosen at random form a connected couple. This one depends basically on the distance, which implies that on having diminished a, the probability of contagion increases. In the language of the clusters, this can be seen this way: if two trees form a connected couple, a wire will represent a union among them, but if being immediate they do not form connected couple, a cutting wire will show among them. A model of the evolution pre-biological is proposed that explains the evolutionary processes in the alive beings, and, while greater is the number of critical states or of changes of phase states of a biological process, better will be the prediction that can be done using the percolation theory, which can be used for to optimize states futures of the alive being, and this has wide applications in bio-technology. To simulate these situations, two experiments were realized: In the first one, there is used a grid that has two electrodes welded to your sides. This assembly is connected to an electrical circuit. One starts blocking every node cutting the four wires that connect it, there is done a study of the electrical resistance in conformity with the quantity of blocked nodes. The node that it must be submitted to blockade is chosen in random form. For it there are used random numbers obtained with the Montecarlo Method for to determine the coordinates of all the nodes and then by means of a selection there is chosen the node that must be blocked. Also a computational program of simulation has been implemented using LabView. In the second experiment, there was realized an montage that consists of a group of thousand conductive spheres and thousand dielectrics spheres, and the spheres were located in a container in a random form and when they were deposited the percolation threshold is measuring, that is to say, the minimal point where it is possible to establish a way of conduction in a random form. The percolation threshold is equal to the number of conductive spheres divided among the total number of spheres. When a greater number of spheres were taken, the percolation threshold obtained was more near of the theoretical value. According to the model of auto organization of the macromolecules, this one is possible if the molecular system a-biogenic possesses metabolism, auto-reproduction and mutability. The metabolism means that the system is opened and that in it the polymerization and decomposition of the polymers occurs. Since the system is far from the equilibrium, these two processes are not tied by the condition of the microscopic reversibility. For the maintenance of the metabolism is necessary the abundance of substances, which possesses an excess of free energy. The auto-reproduction (copies matricial of the polymer) is an autocatalytic process, which the auto-organization assures. The mutagenesis is necessary for the creation of the new information. In this experiment, there was taken in account that the principal difference between a biological process and an inert process is the level of fluctuations or instabilities, due to the fact that on having increased the concentration of these there is modified the future behavior of the alive being (evolution).
Resumenes 103 Referencias • Stauffer, D..(1979). Scaling Theory of Percolation Cluster, Phys. Reports, Vol. 54, p.1. • Stauffer, D.(1985). Introduction to the Percolation Theory, Taylor and Francis. • Castellani, C.(1982). Disordered Systems and Localization, Lecture Notes in Physics, Vol.149, Springer-Verlag. • Deutscher, G. (1983).Percolation Structures and Processes, Adam Hilger. • Shklovski, B. y Efros, A. L. (1984). Electronics Properties of Doped Semiconductor, Cap. 5, Springer-Verlag • Efros, A. (1987). Física y Geometría del Desorden.Mir, Moscú. • Deutscher G. Zallen, R.(1989).Percolation Structures and Processes, Annals of the Israel Physical Society, Vol 5. • Liggett, T.M.(1985).Interacting Particle Systems, Springer Verlag. • Nahmias, J. y Tephany H. (1989). Rev. Phys, Appl., 24, 773. • Ziff, R.M., y Gulari E. (1986).Phys. Rev. Lett., 56, 2553. • Eiswirth, R.M.y Krischer K..(1990). Appl. Phys., A 51, 79. • Stauffer, D.y Coniglio A.(1982). Adv. Polymer. Sci., 44, 103. • Grassberger, P.(1991). La Percolación o la Geometría del Contagio, Mundo Científico, Nº 115, p.764-770. • Bak, P., Tang C. y Wienselfeld K.(1988).Phys. Rev., A 38, 364. • Bak, P. y Chen K. (1989). Physica, D38, 5. • Jaramillo, S.A., López L.F. y Villa J.M. (2003). Aplicación de la Teoría de la Percolación en las Predicciones Cualitativas de los Procesos Aleatorios, Memorias del VI Simposio Brasileiro de Automação Inteligente, SBAI 2003, Baurú, São Paulo, Brasil. • Jaramillo, S.A., (2004). Aplicación de la Teoría de la Percolación en las Predicciones Cualitativas de los Procesos Biológicos, Memorias del Congresso Brasileiro de Automática CBA2004, Gramado, RGS, Brasil. • Grassberger, P.(1991). La Percolación o la Geometría del Contagio, Mundo Científico, Nº 115, p.764-770. • Volkenstein, M.V. (1985). Biofísica, Mir, Moscú. • Jaramillo, S.A., (2005). Aplicación de la Teoría de la Percolación a la Inteligencia Artificial, Memorias del Congreso Internacional de Inteligencia Computacional CIIC 2005, Montería, Colombia.
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ORGANIZADO POR LA SOCIEDAD LATINOAM
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(en orden alfabético) COMITÉ CIEN
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CURSILLOS Cursillo Nº1: Dinámica
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CONFERENCIAS INVITADAS
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Conferencias 10 Estabilidad y persi
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Conferencias 12 (K, the ‘carrying
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Conferencias 14 Víctimas Inmigrant
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Conferencias 16 Influencia de la di
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Resumenes 19 Bifurcaciones de Hopf
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Resumenes 21 where y = y(t) represe
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Resumenes 23 Dinámica del modelo d
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Resumenes 25 In this work, we propo
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Resumenes 27 Simulação computacio
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Resumenes 29 of the minisymposium:
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Resumenes 31 Honeybee, Apis mellife
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Resumenes 33 The minimum ratio is t
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Resumenes 35 [1] On the role of end
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Resumenes 37 Modelo matemático de
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Resumenes 39 Figure 1: Plano de fas
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Resumenes 41 Dinámica de poblacion
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Resumenes 43 El método de las solu
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Resumenes 45 Dinámica de un tumor
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Resumenes 47 Several cancer models
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Resumenes 49 process is physically
Page 53 and 54: Resumenes 51 For the analysis of fr
Page 55 and 56: Resumenes 53 Sustainability in floo
Page 57 and 58: Resumenes 55 Sincronismo em redes d
Page 59 and 60: Resumenes 57 Um modelo de autômato
Page 61 and 62: Resumenes 59 Um modelo matemático
Page 63 and 64: Resumenes 61 Redes de mapas acoplad
Page 65 and 66: Resumenes 63 Sobre la dinámica de
Page 67 and 68: Resumenes 65 Un modelo de depredaci
Page 69 and 70: Resumenes 67 There exists wide evid
Page 71 and 72: Resumenes 69 Modelado del control n
Page 73 and 74: Resumenes 71 Modelo de red neuronal
Page 75 and 76: Resumenes 73 Efectos de la radiaci
Page 77 and 78: Resumenes 75 Un modelo matemático
Page 79 and 80: Resumenes 77 Estudio comparativo de
Page 81 and 82: Resumenes 79 Introduction The proje
Page 83 and 84: Resumenes 81 formulation to obtain
Page 85 and 86: Resumenes 83 tiene un único punto
Page 87 and 88: Resumenes 85 [4] Courchamp, F., Clu
Page 89 and 90: Resumenes 87 An important part of a
Page 91 and 92: Resumenes 89 A(H3N2). Starting in V
Page 93 and 94: Resumenes 91 i) Panmixia, donde se
Page 95 and 96: Resumenes 93 punto de equilibrio y
Page 97 and 98: Resumenes 95 Un modelo epidemiológ
Page 99 and 100: Resumenes 97 Aproximación saddlepo
Page 101 and 102: Resumenes 99 [3] Daniels, H. E. 196
Page 103: Resumenes 101 bloqueados. El nudo q
Page 107 and 108: Resumenes 105 Un modelo dinámico d
Page 109 and 110: Resumenes 107 Un modelo en ecuacion
Page 111 and 112: Resumenes 109 The mite show a prefe
Page 113 and 114: Resumenes 111 Ondas viajantes en un
Page 115 and 116: Resumenes 113 [5] Pregnolatto S. de
Page 117 and 118: Resumenes 115 All this will enable
Page 119 and 120: Resumenes 117 Extensión de un mode
Page 121 and 122: Resumenes 119 ∂C ∂C C = 0. = 0.
Page 123 and 124: Resumenes 121 Comparación de Enfoq
Page 125 and 126: Resumenes 123 Refúgios Espaciais e
Page 127 and 128: Resumenes 125 La dinámica del sest
Page 129 and 130: Resumenes 127 Dinámica poblacional
Page 131 and 132: Resumenes 129 Aproximación y simul
Page 133 and 134: Resumenes 131 An age-structured fin
Page 135 and 136: Resumenes 133 Respuestas demográfi
Page 137 and 138: Resumenes 135 Modelando el efecto A
Page 139 and 140: Resumenes 137 the Allee effect are
Page 141 and 142: Resumenes 139 Tratamientos de endom
Page 143 and 144: Resumenes 141 Implicaciones del efe
Page 145 and 146: Resumenes 143 phenomenon has been e
Page 147 and 148: Resumenes 145 Dinámica individual
Page 149 and 150: Resumenes 147 • f mixing ⇔ f mi
Page 151 and 152: Resumenes 149 Introduction The inve
Page 153 and 154: Resumenes 151 DNA microarrays are t
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Resumenes 153 V. Cholerae: Primeros
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Resumenes 155 Análisis cuantitativ
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Resumenes 157 Dinámica de un model
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Resumenes 159 Obtención de paráme
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Resumenes 161 [4] Nagy K. A (1987)
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Resumenes 163 diferencial automáti
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Resumenes 165 The localized peaks S
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Resumenes 167 obteniéndose que sie
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Resumenes 169 [CLARK 90] Clark, C.
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Resumenes 171 Numerical algorithms
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Resumenes 173 The second method of
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Resumenes 175 los parámetros son t
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Resumenes 177 Bifurcación hacia at
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Resumenes 179 Malaria is the tropic
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