Narrow Results

In this paper the Penna bit-string model of biological aging with different lengths of bit-strings genome is considered. We show from computer simulation that changes in genome length may be crucial for determining population characterization and seem to be irreversible by scaling the other model control parameters.

We derive catastrophic senescence of the Pacific salmon from an aging model which was recently proposed by Stauffer. The model is based on the postulates of a minimum reproduction age and a maximal genetic lifespan. It allows for self-organization of a typical age of first reproduction and a typical age of death. Our Monte Carlo simulations of the population dynamics show that the model leads to catastrophic senescence for semelparous reproduction as it occurs in the case of salmon, to a more gradually increase of senescence for iteroparous reproduction.

It is shown that if the computer model of biological aging proposed by Stauffer is modified such that the late reproduction is privileged, then the Gompertz law of exponential increase of mortality can be retrieved.

We use a simple model for biological aging to study the mortality of the population, obtaining a good agreement with the Gompertz law. We also simulate the same model on a square lattice, considering different strategies of parental care. The results are in agreement with those obtained earlier with the more complicated Penna model for biological aging. Finally, we present the sexual version of this simple model.

To analyze aging processes, a concept based on these hypotheses was utilized: maturation and aging are affected by external influences and are related to the system's ability to learn, to adapt to sudden environmental changes rapidly and survive. To simulate the maturation and aging processes of systems, individuals and populations, a perceptron to classify two notably different classification tasks was trained. After lengthy training to learn the first task, the magnitudes of the perceptron's weights increase. The presence of nonlinearity in the output of the perceptron causes a saturation of the cost function. Saturation reduces the capability to learn a new task rapidly. The aging curves obtained show a rise and fall character. Factors that can be utilized to control re-training curves were considered. A new model allows us to analyze the aging process as a natural phenomenon that helps populations to survive in everlastingly changing environments was also introduced.

We introduce into the Penna Model of biological aging a mechanism to maximize the ability of a sperm to compete with those of other males. Such a selfish mechanism increases the rate of success of male reproduction, but may decrease the survival probability of the female population, depending on its mode of action. We also find a dynamic phase transition induced by the existence of an absorbing state, where no selfish males survive.

In this work we study, by means of numerical simulations, the out-of-equilibrium dynamics of the one-dimensional Edwards–Anderson model with long-range interactions of the form ± Jr^-α. In the limit α → 0 we recover the well known Sherrington–Kirkpatrick mean-field version of the model, which presents a very complex dynamical behavior. At the other extreme, for α → ∞ the model converges to the nearest-neighbor one-dimensional system. We focus our study on the dependence of the dynamics on the history of the sample (aging phenomena) for different values of α. The model is known to have mean-field exponents already for values of α = 2/3. Our results indicate that the crossover to the dynamic mean-field occurs at a value of α < 2/3.

Using a lattice model based on Monte Carlo simulations, we study the role of the reproduction pattern on the fate of an evolving population. Each individual is under the selection pressure from the environment and random mutations. The habitat ("climate") is changing periodically. Evolutions of populations following two reproduction patterns are compared, asexual and sexual. We show, via Monte Carlo simulations, that sexual reproduction by keeping more diversified populations gives them better chances to adapt themselves to the changing environment. However, in order to obtain a greater chance to mate, the birth rate should be high. In the case of low birth rate and high mutation probability there is a preference for the asexual reproduction.

In the Sznajd consensus model on the square lattice, two people who agree in their opinions convince their neighbors of this opinion. We generalize it to many layers representing many age levels, and check if a consensus among all layers is possible. Advertising sometimes, but not always, produces a consensus on the advertised opinion.

We model the evolution of a population on a 2D cellular automata (CA) lattice. Every individual holds a binary "genetic code". The code length and the number of "1"s in the chain correspond to the maximal and actual life-time of individual, respectively. The "genetic code" code is divided onto three life-episodes: "youth", "maturity" and "old age". Only "mature" individuals can procreate. We investigate the duration of the life-episodes and their role in protecting the population from extinction in hostile environments. We observe that in the stable environment, which does not influence the life-time of individuals, the "youth" and the "maturity" periods extend extremely long during evolution, while the "old age" remains short. The situation is different for hostile plaque-like conditions. Under these circumstances, the "youth" period vanishes, while the longer "old age" period stabilizes the population growth, increases its average age and thereby increases its chance of survival. We can conclude that the idle life-episodes set up the control mechanisms, which allow for self-adaptation of the population to varying environmental conditions.

Recently, individual-based models originally used for biological purposes revealed interesting insights into processes of the competition of languages. Within this new field of population dynamics a model considering sexual populations with aging is presented. The agents are situated on a lattice and each one speaks one of two languages or both. The stability and quantitative structure of an interface between two regions, initially speaking different languages, is studied. We find that individuals speaking both languages do not prefer any of these regions and have a different age structure than individuals speaking only one language.

We present some simulations results of population growth and evolution, using the standard asexual Penna model, with individuals characterized by a string of bits representing a genome containing some possible mutations. After about 20 000 simulation steps, when only a few genetic families are still present from among rich variety of families at the beginning of the simulation game, strong peaks in mutation distribution functions are observed. This known effect is due to evolution rules with hereditary mechanism. The birth and death balance in the simulation game also leads to elimination of families specified by different genomes. The number of families G(t) versus time t follow the power law, G∝tⁿ. Our results show the power coefficient exponent n is changing with time. Starting from about -1, smoothly achieves about -2 after hundreds of steps, and finally has semi-smooth transition to 0, when only one family exists in the environment. This is in contrast with constant n about -1 as found, for example, in Ref. 1. We suspect that this discrepancy may be due to two different time scales in simulations — initial stages follow the n ≈ -1 law, yet for large number of simulation steps we get n ≈ -2, provided the random initial population was sufficiently big to allow for still reliable statistical analysis. The n ≈ -1 evolution stage seems to be associated with the Verhulst mechanism of population elimination due to the limited environmental capacity — when the standard evolution rules were modified, we observed a plateau (n =0) in the power law in short time scale, again followed by n ≈ -2 law for longer times. The modified model uses birth rate controlled by the current population instead of the standard Verhulst death factor.

The understanding of language competition helps us to predict extinction and survival of languages spoken by minorities. A simple agent-based model of a sexual population, based on the Penna model, is built in order to find out under which circumstances one language dominates other ones. This model considers that only young people learn foreign languages. The simulations show a first order phase transition of the ratio between the number of speakers of different languages with the mutation rate as control parameter.

The collaboration network is an example of a social network which has both non-trivial temporal and spatial dependence. Based on the observations of collaborations in Physical Review Letters, a model of collaboration network is proposed which correctly reproduces the time evolution of the link length distributions, clustering coefficients, degree distributions, and assortative property of real data to a large extent.

We simulate the response of an age-structured population face to an abrupt increasing of fertility. Contrary to the exponential decay of original model, as reported by Coe and Mao, we have found that the relaxation to the equilibrium can be algebraic under certain conditions. We show results from computer simulation for a large range of parameters, although the fertility itself seems to be the most relevant factor.

A bit-string model of biological life-histories is parallelized, with hundreds of millions of individuals. It gives the desired drastic decay of survival probabilities with increasing age for 32 age intervals.

Age-specific predators are introduced into the Penna model of biological aging. It is shown that populations with a variable minimum reproduction age find a stable state with an earlier onset of reproduction, if older ages are eaten by the predators. This behavior agrees with the demographic data of the Virgina opossum.

Using Monte Carlo simulations, we have studied aging phenomena in three-dimensional Gaussian Ising spin-glass model focusing on quasi-equilibrium behavior of the spin auto-correlation functions. Weak violation of the time translational invariance in the quasi-equilibrium regime is analyzed in terms of effective stiffness for droplet excitations in the presence of domain walls. The simulation results not only in isothermal aging but also in T-shift aging process. T-shift aging processes exhibit the expected scaling behavior with respect to the characteristic length scales associated with droplet excitations and domain walls in spite of the fact that the growth law for these length scales still shows a pre-asymptotic behavior compared with the asymptotic form proposed by the droplet theory. Implications of our simulational results are also discussed in relation to experimental observations.

It is known that aging affects neuroplasticity. On the other hand, neuroplasticity can be studied by analyzing the electroencephalogram (EEG) signal. An important challenge in brain research is to study the variations of neuroplasticity during aging for patients suffering from epilepsy. This study investigates the variations of the complexity of EEG signal during aging for patients with epilepsy. For this purpose, we employed fractal dimension as an indicator of process complexity. We classified the subjects in different age groups and computed the fractal dimension of their EEG signals. Our investigations showed that as patients get older, their EEG signal will be more complex. The method of investigation that has been used in this study can be further employed to study the variations of EEG signal in case of other brain disorders during aging.

It is known that heart activity changes during aging. In this paper, we evaluated alterations of heart activity from the complexity point of view. We analyzed the variations of heart rate of patients with congestive heart failure that are categorized into four different age groups, namely 30–39, 50–59, 60–69, and 70–79 years old. For this purpose, we employed three complexity measures that include fractal dimension, sample entropy, and approximate entropy. The results showed that the trend of increment of subjects’ age is reflected in the trend of increment of the complexity of heart rate variability (HRV) since the values of fractal dimension, approximate entropy, and sample entropy increase as subjects get older. The analysis of the complexity of other physiological signals can be further considered to investigate the variations of activity of other organs due to aging.