MONTE CARLO SIMULATION OF AGEING: BEYOND BIT-STRING MODELS

1996 ◽  
Vol 06 (06) ◽  
pp. 789-806 ◽  
Author(s):  
AMERICO T. BERNARDES ◽  
DIETRICH STAUFFER
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Population Size ◽  
String Model ◽  
Deleterious Mutations ◽  
Approach To Equilibrium ◽  
Biological Ageing ◽  
Penna Model ◽  
String Models ◽  
Mutational Meltdown

Penna's bit-string model of biological ageing due to the accumulation of deleterious mutations is generalized to allow for more than one disease per year. The results remain qualitatively unchanged except for a more complicated non-monotonic approach to equilibrium. We also look at "mutational meltdown", the extinction of the whole population if all mutations are deleterious and heritable, and why the Penna model can escape this extinction. No dependence on population size is found for mutational meltdown, with up to 108 individuals.

Why do Women Live Longer than Men? A Monte Carlo Simulation of Penna-type Models with X and Y Chromosomes

1998 ◽  
Vol 09 (05) ◽  
pp. 721-725 ◽  
Author(s):  
J. Schneider ◽  
S. Cebrat ◽  
D. Stauffer
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
String Model ◽  
Female Mortality ◽  
Male And Female ◽  
Biological Ageing ◽  
Y Chromosomes ◽  
Simple Simulation

This work presents a simple simulation of the differences in male and female mortality and ageing. The simulation is based on Penna's bit-string model of biological ageing.

Least Squares Regression Estimates of the Schaefer Production Model: Some Monte Carlo Simulation Results

1980 ◽  
Vol 37 (8) ◽  
pp. 1284-1294 ◽  
Author(s):  
Russell S. Uhler
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Least Squares ◽  
Population Size ◽  
Analytical Methods ◽  
Production Model ◽  
Parameter Estimates ◽  
Errors In Variables ◽  
Least Squares Regression ◽  
Harvest Rate

Both analytical methods and Monte Carlo experiments are used to determine the amount of bias in the regression estimates of the Schaefer model when it is estimated with catch and effort data. It is shown that the use of the catch–effort ratio and effort as regressors leads to the classical errors in variables problem which produces asymptotically biased parameter estimates. Since the seriousness of the bias, and even its direction in the case of certain formulations of the model, cannot be determined by analytical methods, Monte Carlo simulation experiments were used. Four variations of the Schaefer model were investigated; two of which come from a discrete formulation of the model and two of which come from a continuous formulation. The least squares regression estimates of all formulations result in substantial bias although one formulation is considerably better than the others.Bias in the optimal levels of the population size, the harvest rate, and fishing effort are also calculated. It is found that under likely conditions regarding the model equation errors that the optimal population size and harvest rate may be as much as 40–50% in error depending on the model used. In general, however, the bias in these quantities is much smaller than the bias in the parameter estimates themselves.Key words: Schaefer model, Monte Carlo, optimal fishery management, errors in variables, biased estimates

EXTINCTION OF SMALL POPULATIONS IN THE BIT-STRING MODEL OF BIOLOGICAL AGEING

1996 ◽  
Vol 07 (06) ◽  
pp. 899-908 ◽  
Author(s):  
KÁROLY F. PÁL
Keyword(s):  
Population Size ◽  
Carrying Capacity ◽  
String Model ◽  
Small Population ◽  
Small Populations ◽  
Genetic Condition ◽  
Gradual Decline ◽  
Biological Ageing ◽  
Survival Chance

In the framework of the bit-string model of biological ageing we show that the survival chance of a small population in an environment of limited carrying capacity grows exponentially with the size of the habitat. Extinction is usually preceded by a gradual decline of the genetic condition of the population. With death due to senescence coming earlier, the typical population size shrinks, and at some stage the population dies out due to the fluctuations.

scholarly journals EFFICIENT MONTE CARLO SIMULATION OF BIOLOGICAL AGING

1995 ◽  
Vol 06 (02) ◽  
pp. 233-239 ◽  
Author(s):  
T.J.P. PENNA ◽  
D. STAUFFER
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Life Histories ◽  
String Model ◽  
Biological Aging ◽  
Survival Probabilities

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.

Genetic Crossing vs Cloning by Computer Simulation

1997 ◽  
Vol 08 (03) ◽  
pp. 605-608 ◽  
Author(s):  
Subinay Dasgupta
Keyword(s):  
Computer Simulation ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Natural Disaster ◽  
Asexual Reproduction ◽  
String Model ◽  
Genetic Crossing

We perform Monte Carlo simulation using Penna's bit string model, and compare the process of asexual reproduction by cloning with that by genetic crossover. We find them to be comparable as regards survival of a species, and also if a natural disaster is simulated.

Why Sex? — Monte Carlo Simulations of Survival after Catastrophes

1998 ◽  
Vol 09 (03) ◽  
pp. 421-432 ◽  
Author(s):  
J. S. Sá Martins ◽  
S. Moss de Oliveira
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Sexual Reproduction ◽  
Natural Disaster ◽  
Asexual Reproduction ◽  
Survival Rates ◽  
String Model ◽  
Common Type ◽  
Population Diversity ◽  
Biological Ageing

Using the Penna bit-string model for biological ageing we compare two kinds of reproductive regimes: Sexual reproduction (SR) and meiotic parthenogenesis (MP). The last one is a common type of asexual reproduction with recombination, found in diploid organisms. We show that although both regimes present roughly the same survival rates, the diversity generated by SR is much larger, and can prevent the extinction of a population submitted to a natural disaster. The fixation of bad genes inside an MP population, after many generations, explains our results. We also study the consequences of cloning (simple copy) on population diversity.

scholarly journals PENNA BIT-STRING MODEL WITH CONSTANT POPULATION

2004 ◽  
Vol 15 (02) ◽  
pp. 301-305 ◽  
Author(s):  
P. M. C de OLIVEIRA ◽  
S. MOSS de OLIVEIRA ◽  
J. S. SÁ MARTINS
Keyword(s):  
Population Size ◽  
Genetic Diseases ◽  
String Model ◽  
Biological Aging ◽  
Exponential Increase ◽  
Penna Model

We removed from the Penna model for biological aging any random killing Verhulst factor. Deaths are due only to genetic diseases and the population size is fixed, instead of fluctuating around some constant value. We show that these modifications give qualitatively the same results obtained in an earlier paper, where the random killings (used to avoid an exponential increase of the population) were applied only to newborns.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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