Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

A cellular automaton method to simulate the microstructure and evolution of low-enriched uranium (LEU) U-Mo/Al dispersion type fuel plates

NASA Astrophysics Data System (ADS)

Drera, Saleem S.; Hofman, Gerard L.; Kee, Robert J.; King, Jeffrey C.

2014-10-01

Low-enriched uranium (LEU) fuel plates for high power materials test reactors (MTR) are composed of nominally spherical uranium-molybdenum (U-Mo) particles within an aluminum matrix. Fresh U-Mo particles typically range between 10 and 100 μm in diameter, with particle volume fractions up to 50%. As the fuel ages, reaction-diffusion processes cause the formation and growth of interaction layers that surround the fuel particles. The growth rate depends upon the temperature and radiation environment. The cellular automaton algorithm described in this paper can synthesize realistic random fuel-particle structures and simulate the growth of the intermetallic interaction layers. Examples in the present paper pack approximately 1000 particles into three-dimensional rectangular fuel structures that are approximately 1 mm on each side. The computational approach is designed to yield synthetic microstructures consistent with images from actual fuel plates and is validated by comparison with empirical data on actual fuel plates.

Cellular automaton for migration in ecosystem: Application of traffic model to a predator-prey system

NASA Astrophysics Data System (ADS)

Nagatani, Takashi; Tainaka, Kei-ichi

2018-01-01

In most cases, physicists have studied the migration of biospecies by the use of random walk. In the present article, we apply cellular automaton of traffic model. For simplicity, we deal with an ecosystem contains a prey and predator, and use one-dimensional lattice with two layers. Preys stay on the first layer, but predators uni-directionally move on the second layer. The spatial and temporal evolution is numerically explored. It is shown that the migration has the important effect on populations of both prey and predator. Without migration, the phase transition between a prey-phase and coexisting-phase occurs. In contrast, the phase transition disappears by migration. This is because predator can survive due to migration. We find another phase transition for spatial distribution: in one phase, prey and predator form a stripe pattern of condensation and rarefaction, while in the other phase, they uniformly distribute. The self-organized stripe may be similar to the migration patterns in real ecosystems.

Evolution of Cellular Automata toward a LIFE-Like Rule Guided by 1/ƒ Noise

NASA Astrophysics Data System (ADS)

Ninagawa, Shigeru

There is evidence in favor of a relationship between the presence of 1/ƒ noise and computational universality in cellular automata. To confirm the relationship, we search for two-dimensional cellular automata with a 1/ƒ power spectrum by means of genetic algorithms. The power spectrum is calculated from the evolution of the state of the cell, starting from a random initial configuration. The fitness is estimated by the power spectrum with consideration of the spectral similarity to the 1/ƒ spectrum. The result shows that the rule with the highest fitness over the most runs exhibits a 1/ƒ type spectrum and its transition function and behavior are quite similar to those of the Game of Life, which is known to be a computationally universal cellular automaton. These results support the relationship between the presence of 1/ƒ noise and computational universality.

Probabilistic Cellular Automata

PubMed Central

Agapie, Alexandru; Giuclea, Marius

2014-01-01

Abstract Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case—connecting the probability of a configuration in the stationary distribution to its number of zero-one borders—the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557

Probabilistic cellular automata.

PubMed

Agapie, Alexandru; Andreica, Anca; Giuclea, Marius

2014-09-01

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

An outline of cellular automaton universe via cosmological KdV equation

NASA Astrophysics Data System (ADS)

Christianto, V.; Smarandache, F.; Umniyati, Y.

2018-03-01

It has been known for long time that the cosmic sound wave was there since the early epoch of the Universe. Signatures of its existence are abound. However, such a sound wave model of cosmology is rarely developed fully into a complete framework. This paper can be considered as our second attempt towards such a complete description of the Universe based on soliton wave solution of cosmological KdV equation. Then we advance further this KdV equation by virtue of Cellular Automaton method to solve the PDEs. We submit wholeheartedly Robert Kuruczs hypothesis that Big Bang should be replaced with a finite cellular automaton universe with no expansion [4][5]. Nonetheless, we are fully aware that our model is far from being complete, but it appears the proposed cellular automaton model of the Universe is very close in spirit to what Konrad Zuse envisaged long time ago. It is our hope that the new proposed method can be verified with observation data. But we admit that our model is still in its infancy, more researches are needed to fill all the missing details.

Self-organized criticality in a two-dimensional cellular automaton model of a magnetic flux tube with background flow

NASA Astrophysics Data System (ADS)

Dănilă, B.; Harko, T.; Mocanu, G.

2015-11-01

We investigate the transition to self-organized criticality in a two-dimensional model of a flux tube with a background flow. The magnetic induction equation, represented by a partial differential equation with a stochastic source term, is discretized and implemented on a two-dimensional cellular automaton. The energy released by the automaton during one relaxation event is the magnetic energy. As a result of the simulations, we obtain the time evolution of the energy release, of the system control parameter, of the event lifetime distribution and of the event size distribution, respectively, and we establish that a self-organized critical state is indeed reached by the system. Moreover, energetic initial impulses in the magnetohydrodynamic flow can lead to one-dimensional signatures in the magnetic two-dimensional system, once the self-organized critical regime is established. The applications of the model for the study of gamma-ray bursts (GRBs) is briefly considered, and it is shown that some astrophysical parameters of the bursts, like the light curves, the maximum released energy and the number of peaks in the light curve can be reproduced and explained, at least on a qualitative level, by working in a framework in which the systems settles in a self-organized critical state via magnetic reconnection processes in the magnetized GRB fireball.

A cellular automaton model of wildfire propagation and extinction

Treesearch

Keith C. Clarke; James A. Brass; Phillip J. Riggan

1994-01-01

We propose a new model to predict the spatial and temporal behavior of wildfires. Fire spread and intensity were simulated using a cellular automaton model. Monte Carlo techniques were used to provide fire risk probabilities for areas where fuel loadings and topography are known. The model assumes predetermined or measurable environmental variables such as wind...

A Hybrid Cellular Automaton Model of Clonal Evolution in Cancer: The Emergence of the Glycolytic Phenotype

PubMed Central

Gerlee, P.; Anderson, A.R.A.

2009-01-01

We present a cellular automaton model of clonal evolution in cancer aimed at investigating the emergence of the glycolytic phenotype. In the model each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells divide. This implies that cells might react differently to the environment and when space and nutrients are limited only the fittest cells will survive. With this model we have investigated the impact of the environment on the growth dynamics of the tumour. In particular we have analysed the influence of the tissue oxygen concentration and extra-cellular matrix density on the dynamics of the model. We found that the environment influences both the growth and evolutionary dynamics of the tumour. For low oxygen concentration we observe tumours with a fingered morphology, while increasing the matrix density gives rise to more compact tumours with wider fingers. The distribution of phenotypes in the tumour is also affected, and we observe that the glycolytic phenotype is most likely to emerge in a poorly oxygenated tissue with a high matrix density. Our results suggest that it is the combined effect of the oxygen concentration and matrix density that creates an environment where the glycolytic phenotype has a growth advantage and consequently is most likely to appear. PMID:18068192

Application of cellular automatons and ant algorithms in avionics

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Selvesiuk, N. I.; Platoshin, G. A.; Semenova, E. V.

2018-03-01

The paper considers two algorithms for searching quasi-optimal solutions of discrete optimization problems with regard to the tasks of avionics placing. The first one solves the problem of optimal placement of devices by installation locations, the second one is for the problem of finding the shortest route between devices. Solutions are constructed using a cellular automaton and the ant colony algorithm.

A cellular automaton method to simulate the microstructure and evolution of low-enriched uranium (LEU) U–Mo/Al dispersion type fuel plates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drera, Saleem S.; Hofman, Gerard L.; Kee, Robert J.

Low-enriched uranium (LEU) fuel plates for high power materials test reactors (MTR) are composed of nominally spherical uranium-molybdenum (U-Mo) particles within an aluminum matrix. Fresh U-Mo particles typically range between 10 and 100 mu m in diameter, with particle volume fractions up to 50%. As the fuel ages, reaction-diffusion processes cause the formation and growth of interaction layers that surround the fuel particles. The growth rate depends upon the temperature and radiation environment. The cellular automaton algorithm described in this paper can synthesize realistic random fuel-particle structures and simulate the growth of the intermetallic interaction layers. Examples in the presentmore » paper pack approximately 1000 particles into three-dimensional rectangular fuel structures that are approximately 1 mm on each side. The computational approach is designed to yield synthetic microstructures consistent with images from actual fuel plates and is validated by comparison with empirical data on actual fuel plates. (C) 2014 Elsevier B.V. All rights reserved.« less

A cellular automaton for the signed particle formulation of quantum mechanics

NASA Astrophysics Data System (ADS)

Sellier, J. M.; Kapanova, K. G.; Dimov, I.

2017-02-01

Recently, a new formulation of quantum mechanics, based on the concept of signed particles, has been suggested. In this paper, we introduce a cellular automaton which mimics the dynamics of quantum objects in the phase-space in a time-dependent fashion. This is twofold: it provides a simplified and accessible language to non-physicists who wants to simulate quantum mechanical systems, at the same time it enables a different way to explore the laws of Physics. Moreover, it opens the way towards hybrid simulations of quantum systems by combining full quantum models with cellular automata when the former fail. In order to show the validity of the suggested cellular automaton and its combination with the signed particle formalism, several numerical experiments are performed, showing very promising results. Being this article a preliminary study on quantum simulations in phase-space by means of cellular automata, some conclusions are drawn about the encouraging results obtained so far and the possible future developments.

Modeling of Microstructure Evolution During Alloy Solidification

NASA Astrophysics Data System (ADS)

Zhu, Mingfang; Pan, Shiyan; Sun, Dongke

In recent years, considerable advances have been achieved in the numerical modeling of microstructure evolution during solidification. This paper presents the models based on the cellular automaton (CA) technique and lattice Boltzmann method (LBM), which can reproduce a wide variety of solidification microstructure features observed experimentally with an acceptable computational efficiency. The capabilities of the models are addressed by presenting representative examples encompassing a broad variety of issues, such as the evolution of dendritic structure and microsegregation in two and three dimensions, dendritic growth in the presence of convection, divorced eutectic solidification of spheroidal graphite irons, and gas porosity formation. The simulations offer insights into the underlying physics of microstructure formation during alloy solidification.

Wavefront cellular learning automata.

PubMed

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Wavefront cellular learning automata

NASA Astrophysics Data System (ADS)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

2D photonic crystal complete band gap search using a cyclic cellular automaton refination

NASA Astrophysics Data System (ADS)

González-García, R.; Castañón, G.; Hernández-Figueroa, H. E.

2014-11-01

We present a refination method based on a cyclic cellular automaton (CCA) that simulates a crystallization-like process, aided with a heuristic evolutionary method called differential evolution (DE) used to perform an ordered search of full photonic band gaps (FPBGs) in a 2D photonic crystal (PC). The solution is proposed as a combinatorial optimization of the elements in a binary array. These elements represent the existence or absence of a dielectric material surrounded by air, thus representing a general geometry whose search space is defined by the number of elements in such array. A block-iterative frequency-domain method was used to compute the FPBGs on a PC, when present. DE has proved to be useful in combinatorial problems and we also present an implementation feature that takes advantage of the periodic nature of PCs to enhance the convergence of this algorithm. Finally, we used this methodology to find a PC structure with a 19% bandgap-to-midgap ratio without requiring previous information of suboptimal configurations and we made a statistical study of how it is affected by disorder in the borders of the structure compared with a previous work that uses a genetic algorithm.

Life's Still Lifes

NASA Astrophysics Data System (ADS)

McIntosh, Harold V.

The de Bruijn diagram describing those decompositions of the neighborhoods of a one dimensional cellular automaton which conform to predetermined requirements of periodicity and translational symmetry shows how to construct extended configurations satisfying the same requirements. Similar diagrams, formed by stages, describe higher dimensional automata, although they become more laborious to compute with increasing neighborhood size. The procedure is illustrated by computing some still lifes for Conway's game of Life, a widely known two dimensional cellular automaton. This paper is written in September 10, 1988.

Three-dimensional microstructure simulation of Ni-based superalloy investment castings

NASA Astrophysics Data System (ADS)

Pan, Dong; Xu, Qingyan; Liu, Baicheng

2011-05-01

An integrated macro and micro multi-scale model for the three-dimensional microstructure simulation of Ni-based superalloy investment castings was developed, and applied to industrial castings to investigate grain evolution during solidification. A ray tracing method was used to deal with the complex heat radiation transfer. The microstructure evolution was simulated based on the Modified Cellular Automaton method, which was coupled with three-dimensional nested macro and micro grids. Experiments for Ni-based superalloy turbine wheel investment casting were carried out, which showed a good correspondence with the simulated results. It is indicated that the proposed model is able to predict the microstructure of the casting precisely, which provides a tool for the optimizing process.

Ordering phase transition in the one-dimensional Axelrod model

NASA Astrophysics Data System (ADS)

Vilone, D.; Vespignani, A.; Castellano, C.

2002-12-01

We study the one-dimensional behavior of a cellular automaton aimed at the description of the formation and evolution of cultural domains. The model exhibits a non-equilibrium transition between a phase with all the system sharing the same culture and a disordered phase of coexisting regions with different cultural features. Depending on the initial distribution of the disorder the transition occurs at different values of the model parameters. This phenomenology is qualitatively captured by a mean-field approach, which maps the dynamics into a multi-species reaction-diffusion problem.

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

USGS Publications Warehouse

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

Evolution of cellular automata with memory: The Density Classification Task.

PubMed

Stone, Christopher; Bull, Larry

2009-08-01

The Density Classification Task is a well known test problem for two-state discrete dynamical systems. For many years researchers have used a variety of evolutionary computation approaches to evolve solutions to this problem. In this paper, we investigate the evolvability of solutions when the underlying Cellular Automaton is augmented with a type of memory based on the Least Mean Square algorithm. To obtain high performance solutions using a simple non-hybrid genetic algorithm, we design a novel representation based on the ternary representation used for Learning Classifier Systems. The new representation is found able to produce superior performance to the bit string traditionally used for representing Cellular automata. Moreover, memory is shown to improve evolvability of solutions and appropriate memory settings are able to be evolved as a component part of these solutions.

Computational study on cortical spreading depression based on a generalized cellular automaton model

NASA Astrophysics Data System (ADS)

Chen, Shangbin; Hu, Lele; Li, Bing; Xu, Changcheng; Liu, Qian

2009-02-01

Cortical spreading depression (CSD) is an important neurophysiological phenomenon correlating with some neural disorders, such as migraine, cerebral ischemia and epilepsy. By now, we are still not clear about the mechanisms of CSD's initiation and propagation, also the relevance between CSD and those neural diseases. Nevertheless, characterization of CSD, especially the spatiotemporal evolution, will promote the understanding of the CSD's nature and mechanisms. Besides the previous experimental work on charactering the spatiotemporal evolution of CSD in rats by optical intrinsic signal imaging, a computational study based on a generalized cellular automaton (CA) model was proposed here. In the model, we exploited a generalized neighborhood connection rule: a central CA cell is related with a group of surrounding CA cells with different weight coefficients. By selecting special parameters, the generalized CA model could be transformed to the traditional CA models with von Neumann, Moore and hexagon neighborhood connection means. Hence, the new model covered several properties of CSD simulated in traditional CA models: 1) expanding from the origin site like a circular wave; 2) annihilation of two waves traveling in opposite directions after colliding; 3) wavefront of CSD breaking and recovering when and after encountering an obstacle. By setting different refractory period in the different CA lattice field, different connection coefficient in different direction within the defined neighborhood, inhomogeneous propagation of CSD was simulated with high fidelity. The computational results were analogous to the reported time-varying CSD waves by optical imaging. So, the generalized CA model would be useful to study CSD because of its intuitive appeal and computational efficiency.

Modeling of the static recrystallization for 7055 aluminum alloy by cellular automaton

NASA Astrophysics Data System (ADS)

Zhang, Tao; Lu, Shi-hong; Zhang, Jia-bin; Li, Zheng-fang; Chen, Peng; Gong, Hai; Wu, Yun-xin

2017-09-01

In order to simulate the flow behavior and microstructure evolution during the pass interval period of the multi-pass deformation process, models of static recovery (SR) and static recrystallization (SRX) by the cellular automaton (CA) method for the 7055 aluminum alloy were established. Double-pass hot compression tests were conducted to acquire flow stress and microstructure variation during the pass interval period. With the basis of the material constants obtained from the compression tests, models of the SR, incubation period, nucleation rate and grain growth were fitted by least square method. A model of the grain topology and a statistical computation of the CA results were also introduced. The effects of the pass interval time, temperature, strain, strain rate and initial grain size on the microstructure variation for the SRX of the 7055 aluminum alloy were studied. The results show that a long pass interval time, large strain, high temperature and large strain rate are beneficial for finer grains during the pass interval period. The stable size of the static recrystallized grain is not concerned with the initial grain size, but mainly depends on the strain rate and temperature. The SRX plays a vital role in grain refinement, while the SR has no effect on the variation of microstructure morphology. Using flow stress and microstructure comparisons of the simulated and experimental CA results, the established CA models can accurately predict the flow stress and microstructure evolution during the pass interval period, and provide guidance for the selection of optimized parameters for the multi-pass deformation process.

New cellular automaton designed to simulate geometration in gel electrophoresis

NASA Astrophysics Data System (ADS)

Krawczyk, M. J.; Kułakowski, K.; Maksymowicz, A. Z.

2002-08-01

We propose a new kind of cellular automaton to simulate transportation of molecules of DNA through agarose gel. Two processes are taken into account: reptation at strong electric field E, described in the particle model, and geometration, i.e. subsequent hookings and releases of long molecules at and from gel fibres. The automaton rules are deterministic and they are designed to describe both processes within one unified approach. Thermal fluctuations are not taken into account. The number of simultaneous hookings is limited by the molecule length. The features of the automaton are: (i) the size of the cell neighbourhood for the automaton rule varies dynamically, from nearest neighbors to the entire molecule; (ii) the length of the time step is determined at each step according to dynamic rules. Calculations are made up to N=244 reptons in a molecule. Two subsequent stages of the motion are found. Firstly, an initial set of random configurations of molecules is transformed into a more ordered phase, where most molecules are elongated along the applied field direction. After some transient time, the mobility μ reaches a constant value. Then, it varies with N as 1/ N for long molecules. The band dispersion varies with time t approximately as Nt1/2. Our results indicate that the well-known plateau of the mobility μ vs. N does not hold at large electric fields.

An epidemiological modeling and data integration framework.

PubMed

Pfeifer, B; Wurz, M; Hanser, F; Seger, M; Netzer, M; Osl, M; Modre-Osprian, R; Schreier, G; Baumgartner, C

2010-01-01

In this work, a cellular automaton software package for simulating different infectious diseases, storing the simulation results in a data warehouse system and analyzing the obtained results to generate prediction models as well as contingency plans, is proposed. The Brisbane H3N2 flu virus, which has been spreading during the winter season 2009, was used for simulation in the federal state of Tyrol, Austria. The simulation-modeling framework consists of an underlying cellular automaton. The cellular automaton model is parameterized by known disease parameters and geographical as well as demographical conditions are included for simulating the spreading. The data generated by simulation are stored in the back room of the data warehouse using the Talend Open Studio software package, and subsequent statistical and data mining tasks are performed using the tool, termed Knowledge Discovery in Database Designer (KD3). The obtained simulation results were used for generating prediction models for all nine federal states of Austria. The proposed framework provides a powerful and easy to handle interface for parameterizing and simulating different infectious diseases in order to generate prediction models and improve contingency plans for future events.

Simulating pedestrian flow by an improved two-process cellular automaton model

NASA Astrophysics Data System (ADS)

Jin, Cheng-Jie; Wang, Wei; Jiang, Rui; Dong, Li-Yun

In this paper, we study the pedestrian flow with an Improved Two-Process (ITP) cellular automaton model, which is originally proposed by Blue and Adler. Simulations of pedestrian counterflow have been conducted, under both periodic and open boundary conditions. The lane formation phenomenon has been reproduced without using the place exchange rule. We also present and discuss the flow-density and velocity-density relationships of both uni-directional flow and counterflow. By the comparison with the Blue-Adler model, we find the ITP model has higher values of maximum flow, critical density and completely jammed density under different conditions.

Simulation and analysis of traffic flow based on cellular automaton

NASA Astrophysics Data System (ADS)

Ren, Xianping; Liu, Xia

2018-03-01

In this paper, single-lane and two-lane traffic model are established based on cellular automaton. Different values of vehicle arrival rate at the entrance and vehicle departure rate at the exit are set to analyze their effects on density, average speed and traffic flow. If the road exit is unblocked, vehicles can pass through the road smoothly despite of the arrival rate at the entrance. If vehicles enter into the road continuously, the traffic condition is varied with the departure rate at the exit. To avoid traffic jam, reasonable vehicle departure rate should be adopted.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: A Realistic Cellular Automaton Model for Synchronized Traffic Flow

NASA Astrophysics Data System (ADS)

Zhao, Bo-Han; Hu, Mao-Bin; Jiang, Rui; Wu, Qing-Song

2009-11-01

A cellular automaton model is proposed to consider the anticipation effect in drivers' behavior. It is shown that the anticipation effect can be one of the origins of synchronized traffic flow. With anticipation effect, the congested traffic flow simulated by the model exhibits the features of synchronized flow. The spatiotemporal patterns induced by an on-ramp are also consistent with the three-phase traffic theory. Since the origin of synchronized flow is still controversial, our work can shed some light on the mechanism of synchronized flow.

CAFE simulation of columnar-to-equiaxed transition in Al-7wt%Si alloys directionally solidified under microgravity

NASA Astrophysics Data System (ADS)

Liu, D. R.; Mangelinck-Noël, N.; Gandin, Ch-A.; Zimmermann, G.; Sturz, L.; Nguyen Thi, H.; Billia, B.

2016-03-01

A two-dimensional multi-scale cellular automaton - finite element (CAFE) model is used to simulate grain structure evolution and microsegregation formation during solidification of refined Al-7wt%Si alloys under microgravity. The CAFE simulations are first qualitatively compared with the benchmark experimental data under microgravity. Qualitative agreement is obtained for the position of columnar to equiaxed transition (CET) and the CET transition mode (sharp or progressive). Further comparisons of the distributions of grain elongation factor and equivalent diameter are conducted and reveal a fair quantitative agreement.

How synapses can enhance sensibility of a neural network

NASA Astrophysics Data System (ADS)

Protachevicz, P. R.; Borges, F. S.; Iarosz, K. C.; Caldas, I. L.; Baptista, M. S.; Viana, R. L.; Lameu, E. L.; Macau, E. E. N.; Batista, A. M.

2018-02-01

In this work, we study the dynamic range in a neural network modelled by cellular automaton. We consider deterministic and non-deterministic rules to simulate electrical and chemical synapses. Chemical synapses have an intrinsic time-delay and are susceptible to parameter variations guided by learning Hebbian rules of behaviour. The learning rules are related to neuroplasticity that describes change to the neural connections in the brain. Our results show that chemical synapses can abruptly enhance sensibility of the neural network, a manifestation that can become even more predominant if learning rules of evolution are applied to the chemical synapses.

CAM: A high-performance cellular-automaton machine

NASA Astrophysics Data System (ADS)

Toffoli, Tommaso

1984-01-01

CAM is a high-performance machine dedicated to the simulation of cellular automata and other distributed dynamical systems. Its speed is about one-thousand times greater than that of a general-purpose computer programmed to do the same task; in practical terms, this means that CAM can show the evolution of cellular automata on a color monitor with an update rate, dynamic range, and spatial resolution comparable to those of a Super-8 movie, thus permitting intensive interactive experimentation. Machines of this kind can open up novel fields of research, and in this context it is important that results be easy to obtain, reproduce, and transmit. For these reasons, in designing CAM it was important to achieve functional simplicity, high flexibility, and moderate production cost. We expect that many research groups will be able to own their own copy of the machine to do research with.

A Study of Chaos in Cellular Automata

NASA Astrophysics Data System (ADS)

Kamilya, Supreeti; Das, Sukanta

This paper presents a study of chaos in one-dimensional cellular automata (CAs). The communication of information from one part of the system to another has been taken into consideration in this study. This communication is formalized as a binary relation over the set of cells. It is shown that this relation is an equivalence relation and all the cells form a single equivalence class when the cellular automaton (CA) is chaotic. However, the communication between two cells is sometimes blocked in some CAs by a subconfiguration which appears in between the cells during evolution. This blocking of communication by a subconfiguration has been analyzed in this paper with the help of de Bruijn graph. We identify two types of blocking — full and partial. Finally a parameter has been developed for the CAs. We show that the proposed parameter performs better than the existing parameters.

Cellular automata and its applications in protein bioinformatics.

PubMed

Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen

2011-09-01

With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.

GENERAL: A modified weighted probabilistic cellular automaton traffic flow model

NASA Astrophysics Data System (ADS)

Zhuang, Qian; Jia, Bin; Li, Xin-Gang

2009-08-01

This paper modifies the weighted probabilistic cellular automaton model (Li X L, Kuang H, Song T, et al 2008 Chin. Phys. B 17 2366) which considered a diversity of traffic behaviors under real traffic situations induced by various driving characters and habits. In the new model, the effects of the velocity at the last time step and drivers' desire for acceleration are taken into account. The fundamental diagram, spatial-temporal diagram, and the time series of one-minute data are analyzed. The results show that this model reproduces synchronized flow. Finally, it simulates the on-ramp system with the proposed model. Some characteristics including the phase diagram are studied.

An implementation of cellular automaton model for single-line train working diagram

NASA Astrophysics Data System (ADS)

Hua, Wei; Liu, Jun

2006-04-01

According to the railway transportation system's characteristics, a new cellular automaton model for the single-line railway system is presented in this paper. Based on this model, several simulations were done to imitate the train operation under three working diagrams. From a different angle the results show how the organization of train operation impacts on the railway carrying capacity. By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest. Many slow-trains have to wait in-between neighbouring stations to let the fast-train(s) pass through first. So the slow-train will advance like a wave propagating from the departure station to the arrival station. This also resembles the situation of a highway jammed traffic flow. Furthermore, the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity. After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged, all three carrying capacities are improved greatly as shown by simulation. It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transportation system.

Numerical simulation of dendrite growth in nickel-based superalloy and validated by in-situ observation using high temperature confocal laser scanning microscopy

NASA Astrophysics Data System (ADS)

Yan, Xuewei; Xu, Qingyan; Liu, Baicheng

2017-12-01

Dendritic structures are the predominant microstructural constituents of nickel-based superalloys, an understanding of the dendrite growth is required in order to obtain the desirable microstructure and improve the performance of castings. For this reason, numerical simulation method and an in-situ observation technology by employing high temperature confocal laser scanning microscopy (HT-CLSM) were used to investigate dendrite growth during solidification process. A combined cellular automaton-finite difference (CA-FD) model allowing for the prediction of dendrite growth of binary alloys was developed. The algorithm of cells capture was modified, and a deterministic cellular automaton (DCA) model was proposed to describe neighborhood tracking. The dendrite and detail morphology, especially hundreds of dendrites distribution at a large scale and three-dimensional (3-D) polycrystalline growth, were successfully simulated based on this model. The dendritic morphologies of samples before and after HT-CLSM were both observed by optical microscope (OM) and scanning electron microscope (SEM). The experimental observations presented a reasonable agreement with the simulation results. It was also found that primary or secondary dendrite arm spacing, and segregation pattern were significantly influenced by dendrite growth. Furthermore, the directional solidification (DS) dendritic evolution behavior and detail morphology were also simulated based on the proposed model, and the simulation results also agree well with experimental results.

Simulating flaring events in complex active regions driven by observed magnetograms

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M. K.

2011-05-01

Context. We interpret solar flares as events originating in active regions that have reached the self organized critical state, by using a refined cellular automaton model with initial conditions derived from observations. Aims: We investigate whether the system, with its imposed physical elements, reaches a self organized critical state and whether well-known statistical properties of flares, such as scaling laws observed in the distribution functions of characteristic parameters, are reproduced after this state has been reached. Methods: To investigate whether the distribution functions of total energy, peak energy and event duration follow the expected scaling laws, we first applied a nonlinear force-free extrapolation that reconstructs the three-dimensional magnetic fields from two-dimensional vector magnetograms. We then locate magnetic discontinuities exceeding a threshold in the Laplacian of the magnetic field. These discontinuities are relaxed in local diffusion events, implemented in the form of cellular automaton evolution rules. Subsequent loading and relaxation steps lead the system to self organized criticality, after which the statistical properties of the simulated events are examined. Physical requirements, such as the divergence-free condition for the magnetic field vector, are approximately imposed on all elements of the model. Results: Our results show that self organized criticality is indeed reached when applying specific loading and relaxation rules. Power-law indices obtained from the distribution functions of the modeled flaring events are in good agreement with observations. Single power laws (peak and total flare energy) are obtained, as are power laws with exponential cutoff and double power laws (flare duration). The results are also compared with observational X-ray data from the GOES satellite for our active-region sample. Conclusions: We conclude that well-known statistical properties of flares are reproduced after the system has reached self organized criticality. A significant enhancement of our refined cellular automaton model is that it commences the simulation from observed vector magnetograms, thus facilitating energy calculation in physical units. The model described in this study remains consistent with fundamental physical requirements, and imposes physically meaningful driving and redistribution rules.

Predictability in cellular automata.

PubMed

Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius

2014-01-01

Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case.

Genetic Algorithms and Nucleation in VIH-AIDS transition.

NASA Astrophysics Data System (ADS)

Barranon, Armando

2003-03-01

VIH to AIDS transition has been modeled via a genetic algorithm that uses boom-boom principle and where population evolution is simulated with a cellular automaton based on SIR model. VIH to AIDS transition is signed by nucleation of infected cells and low probability of infection are obtained for different mutation rates in agreement with clinical results. A power law is obtained with a critical exponent close to the critical exponent of cubic, spherical percolation, colossal magnetic resonance, Ising Model and liquid-gas phase transition in heavy ion collisions. Computations were carried out at UAM-A Supercomputing Lab and author acknowledges financial support from Division of CBI at UAM-A.

A SIMPLE CELLULAR AUTOMATON MODEL FOR HIGH-LEVEL VEGETATION DYNAMICS

EPA Science Inventory

We have produced a simple two-dimensional (ground-plan) cellular automata model of vegetation dynamics specifically to investigate high-level community processes. The model is probabilistic, with individual plant behavior determined by physiologically-based rules derived from a w...

Toward an improvement over Kerner-Klenov-Wolf three-phase cellular automaton model.

PubMed

Jiang, Rui; Wu, Qing-Song

2005-12-01

The Kerner-Klenov-Wolf (KKW) three-phase cellular automaton model has a nonrealistic velocity of the upstream front in widening synchronized flow pattern which separates synchronized flow downstream and free flow upstream. This paper presents an improved model, which is a combination of the initial KKW model and a modified Nagel-Schreckenberg (MNS) model. In the improved KKW model, a parameter is introduced to determine the vehicle moves according to the MNS model or the initial KKW model. The improved KKW model can not only simulate the empirical observations as the initial KKW model, but also overcome the nonrealistic velocity problem. The mechanism of the improvement is discussed.

Time-spatial model on the dynamics of the proliferation of Aedes aegypti

NASA Astrophysics Data System (ADS)

Gouvêa, Maury Meirelles, Jr.

2017-03-01

Some complex physical systems, such as cellular regulation, ecosystems, and societies, can be represented by local interactions between agents. Then, complex behaviors may emerge. A cellular automaton is a discrete dynamic system with these features. Among the several complex systems, epidemic diseases are given special attention by researchers with respect to their dynamics. Understanding the behavior of an epidemic may well benefit a society. For instance, different proliferation scenarios may be produced and a prevention policy set. This paper presents a new simulation method of the time-spatial spread of the Dengue mosquito with a cellular automaton. Thus, it will be possible to create different dissemination scenarios and preventive policies for these in several regions. Simulations were performed with different initial conditions and parameters as a result of which the behavior of the proposed method was characterized.

An intrinsic poperty of memory of the Cellular automaton infrastructure of Nature leading to the organization of the physical world as an Internet o things; TOE = IOT

NASA Astrophysics Data System (ADS)

Berkovich, Simon

2015-04-01

The undamental advantage of a Cellular automaton construction foris that it can be viewed as an undetectable absolute frame o reference, in accordance with Lorentz-Poincare's interpretation.. The cellular automaton model for physical poblems comes upon two basic hurdles: (1) How to find the Elemental Rule that, and how to get non-locality from local transformations. Both problems are resolved considering the transfomation rule of mutual distributed synchronization Actually any information proessing device starts with a clocking system. and it turns out that ``All physical phenomena are different aspects of the high-level description of distributed mutual synchronization in a network of digital clocks''. Non-locality comes from two hugely different time-scales of signaling.. The universe is acombinines information and matter processes, These fast spreading diffusion wave solutions create the mechanism of the Holographic Universe. And thirdly Disengaged from synchronization, circular counters can perform memory functions by retaining phases of their oscillations, an idea of Von Neumann'. Thus, the suggested model generates the necessary constructs for the physical world as an Internet of Things. Life emerges due to the specifics of macromolecules that serve as communication means, with the holographic memory...

Simulation of emotional contagion using modified SIR model: A cellular automaton approach

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming

2014-07-01

Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.

Modeling the expected lifetime and evolution of a deme's principal genetic sequence.

NASA Astrophysics Data System (ADS)

Clark, Brian

2014-03-01

The principal genetic sequence (PGS) is the most common genetic sequence in a deme. The PGS changes over time because new genetic sequences are created by inversions, compete with the current PGS, and a small fraction become PGSs. A set of coupled difference equations provides a description of the evolution of the PGS distribution function in an ensemble of demes. Solving the set of equations produces the survival probability of a new genetic sequence and the expected lifetime of an existing PGS as a function of inversion size and rate, recombination rate, and deme size. Additionally, the PGS distribution function is used to explain the transition pathway from old to new PGSs. We compare these results to a cellular automaton based representation of a deme and the drosophila species, D. melanogaster and D. yakuba.

Predictability in Cellular Automata

PubMed Central

Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius

2014-01-01

Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case. PMID:25271778

Simulation of miniature endplate potentials in neuromuscular junctions by using a cellular automaton

NASA Astrophysics Data System (ADS)

Avella, Oscar Javier; Muñoz, José Daniel; Fayad, Ramón

2008-01-01

Miniature endplate potentials are recorded in the neuromuscular junction when the acetylcholine contents of one or a few synaptic vesicles are spontaneously released into the synaptic cleft. Since their discovery by Fatt and Katz in 1952, they have been among the paradigms in neuroscience. Those potentials are usually simulated by means of numerical approaches, such as Brownian dynamics, finite differences and finite element methods. Hereby we propose that diffusion cellular automata can be a useful alternative for investigating them. To illustrate this point, we simulate a miniature endplate potential by using experimental parameters. Our model reproduces the potential shape, amplitude and time course. Since our automaton is able to track the history and interactions of each single particle, it is very easy to introduce non-linear effects with little computational effort. This makes cellular automata excellent candidates for simulating biological reaction-diffusion processes, where no other external forces are involved.

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

Classifying elementary cellular automata using compressibility, diversity and sensitivity measures

NASA Astrophysics Data System (ADS)

Ninagawa, Shigeru; Adamatzky, Andrew

2014-10-01

An elementary cellular automaton (ECA) is a one-dimensional, synchronous, binary automaton, where each cell update depends on its own state and states of its two closest neighbors. We attempt to uncover correlations between the following measures of ECA behavior: compressibility, sensitivity and diversity. The compressibility of ECA configurations is calculated using the Lempel-Ziv (LZ) compression algorithm LZ78. The sensitivity of ECA rules to initial conditions and perturbations is evaluated using Derrida coefficients. The generative morphological diversity shows how many different neighborhood states are produced from a single nonquiescent cell. We found no significant correlation between sensitivity and compressibility. There is a substantial correlation between generative diversity and compressibility. Using sensitivity, compressibility and diversity, we uncover and characterize novel groupings of rules.

A cellular automaton model for evacuation flow using game theory

NASA Astrophysics Data System (ADS)

Guan, Junbiao; Wang, Kaihua; Chen, Fangyue

2016-11-01

Game theory serves as a good tool to explore crowd dynamic conflicts during evacuation processes. The purpose of this study is to simulate the complicated interaction behavior among the conflicting pedestrians in an evacuation flow. Two types of pedestrians, namely, defectors and cooperators, are considered, and two important factors including fear index and cost coefficient are taken into account. By combining the snowdrift game theory with a cellular automaton (CA) model, it is shown that the increase of fear index and cost coefficient will lengthen the evacuation time, which is more apparent for large values of cost coefficient. Meanwhile, it is found that the defectors to cooperators ratio could always tend to consistent states despite different values of parameters, largely owing to self-organization effects.

Consistent evolution in a pedestrian flow

NASA Astrophysics Data System (ADS)

Guan, Junbiao; Wang, Kaihua

2016-03-01

In this paper, pedestrian evacuation considering different human behaviors is studied by using a cellular automaton (CA) model combined with the snowdrift game theory. The evacuees are divided into two types, i.e. cooperators and defectors, and two different human behaviors, herding behavior and independent behavior, are investigated. It is found from a large amount of numerical simulations that the ratios of the corresponding evacuee clusters are evolved to consistent states despite 11 typically different initial conditions, which may largely owe to self-organization effect. Moreover, an appropriate proportion of initial defectors who are of herding behavior, coupled with an appropriate proportion of initial defectors who are of rationally independent thinking, are two necessary factors for short evacuation time.

Coupled THM processes in EDZ of crystalline rocks using an elasto-plastic cellular automaton

NASA Astrophysics Data System (ADS)

Pan, Peng-Zhi; Feng, Xia-Ting; Huang, Xiao-Hua; Cui, Qiang; Zhou, Hui

2009-05-01

This paper aims at a numerical study of coupled thermal, hydrological and mechanical processes in the excavation disturbed zones (EDZ) around nuclear waste emplacement drifts in fractured crystalline rocks. The study was conducted for two model domains close to an emplacement tunnel; (1) a near-field domain and (2) a smaller wall-block domain. Goodman element and weak element were used to represent the fractures in the rock mass and the rock matrix was represented as elasto-visco-plastic material. Mohr-Coulomb criterion and a non-associated plastic flow rule were adopted to consider the viscoplastic deformation in the EDZ. A relation between volumetric strain and permeability was established. Using a self-developed EPCA2D code, the elastic, elasto-plastic and creep analyses to study the evolution of stress and deformations, as well as failure and permeability evolution in the EDZ were conducted. Results indicate a strong impact of fractures, plastic deformation and time effects on the behavior of EDZ especially the evolution of permeability around the drift.

Update schemes of multi-velocity floor field cellular automaton for pedestrian dynamics

NASA Astrophysics Data System (ADS)

Luo, Lin; Fu, Zhijian; Cheng, Han; Yang, Lizhong

2018-02-01

Modeling pedestrian movement is an interesting problem both in statistical physics and in computational physics. Update schemes of cellular automaton (CA) models for pedestrian dynamics govern the schedule of pedestrian movement. Usually, different update schemes make the models behave in different ways, which should be carefully recalibrated. Thus, in this paper, we investigated the influence of four different update schemes, namely parallel/synchronous scheme, random scheme, order-sequential scheme and shuffled scheme, on pedestrian dynamics. The multi-velocity floor field cellular automaton (FFCA) considering the changes of pedestrians' moving properties along walking paths and heterogeneity of pedestrians' walking abilities was used. As for parallel scheme only, the collisions detection and resolution should be considered, resulting in a great difference from any other update schemes. For pedestrian evacuation, the evacuation time is enlarged, and the difference in pedestrians' walking abilities is better reflected, under parallel scheme. In face of a bottleneck, for example a exit, using a parallel scheme leads to a longer congestion period and a more dispersive density distribution. The exit flow and the space-time distribution of density and velocity have significant discrepancies under four different update schemes when we simulate pedestrian flow with high desired velocity. Update schemes may have no influence on pedestrians in simulation to create tendency to follow others, but sequential and shuffled update scheme may enhance the effect of pedestrians' familiarity with environments.

A Cellular Automaton Framework for Infectious Disease Spread Simulation

PubMed Central

Pfeifer, Bernhard; Kugler, Karl; Tejada, Maria M; Baumgartner, Christian; Seger, Michael; Osl, Melanie; Netzer, Michael; Handler, Michael; Dander, Andreas; Wurz, Manfred; Graber, Armin; Tilg, Bernhard

2008-01-01

In this paper, a cellular automaton framework for processing the spatiotemporal spread of infectious diseases is presented. The developed environment simulates and visualizes how infectious diseases might spread, and hence provides a powerful instrument for health care organizations to generate disease prevention and contingency plans. In this study, the outbreak of an avian flu like virus was modeled in the state of Tyrol, and various scenarios such as quarantine, effect of different medications on viral spread and changes of social behavior were simulated. The proposed framework is implemented using the programming language Java. The set up of the simulation environment requires specification of the disease parameters and the geographical information using a population density colored map, enriched with demographic data. The results of the numerical simulations and the analysis of the computed parameters will be used to get a deeper understanding of how the disease spreading mechanisms work, and how to protect the population from contracting the disease. Strategies for optimization of medical treatment and vaccination regimens will also be investigated using our cellular automaton framework. In this study, six different scenarios were simulated. It showed that geographical barriers may help to slow down the spread of an infectious disease, however, when an aggressive and deadly communicable disease spreads, only quarantine and controlled medical treatment are able to stop the outbreak, if at all. PMID:19415136

Simulation of the Burridge-Knopoff model of earthquakes with variable range stress transfer.

PubMed

Xia, Junchao; Gould, Harvey; Klein, W; Rundle, J B

2005-12-09

Simple models of earthquake faults are important for understanding the mechanisms for their observed behavior, such as Gutenberg-Richter scaling and the relation between large and small events, which is the basis for various forecasting methods. Although cellular automaton models have been studied extensively in the long-range stress transfer limit, this limit has not been studied for the Burridge-Knopoff model, which includes more realistic friction forces and inertia. We find that the latter model with long-range stress transfer exhibits qualitatively different behavior than both the long-range cellular automaton models and the usual Burridge-Knopoff model with nearest-neighbor springs, depending on the nature of the velocity-weakening friction force. These results have important implications for our understanding of earthquakes and other driven dissipative systems.

An improved Burgers cellular automaton model for bicycle flow

NASA Astrophysics Data System (ADS)

Xue, Shuqi; Jia, Bin; Jiang, Rui; Li, Xingang; Shan, Jingjing

2017-12-01

As an energy-efficient and healthy transport mode, bicycling has recently attracted the attention of governments, transport planners, and researchers. The dynamic characteristics of the bicycle flow must be investigated to improve the facility design and traffic operation of bicycling. We model the bicycle flow by using an improved Burgers cellular automaton model. Through a following move mechanism, the modified model enables bicycles to move smoothly and increase the critical density to a more rational level than the original model. The model is calibrated and validated by using experimental data and field data. The results show that the improved model can effectively simulate the bicycle flow. The performance of the model under different parameters is investigated and discussed. Strengths and limitations of the improved model are suggested for future work.

Modeling transport across the running-sandpile cellular automaton by means of fractional transport equations

NASA Astrophysics Data System (ADS)

Sánchez, R.; Newman, D. E.; Mier, J. A.

2018-05-01

Fractional transport equations are used to build an effective model for transport across the running sandpile cellular automaton [Hwa et al., Phys. Rev. A 45, 7002 (1992), 10.1103/PhysRevA.45.7002]. It is shown that both temporal and spatial fractional derivatives must be considered to properly reproduce the sandpile transport features, which are governed by self-organized criticality, at least over sufficiently long or large scales. In contrast to previous applications of fractional transport equations to other systems, the specifics of sand motion require in this case that the spatial fractional derivatives used for the running sandpile must be of the completely asymmetrical Riesz-Feller type. Appropriate values for the fractional exponents that define these derivatives in the case of the running sandpile are obtained numerically.

Reversible elementary cellular automaton with rule number 150 and periodic boundary conditions over 𝔽p

NASA Astrophysics Data System (ADS)

Martín Del Rey, A.; Rodríguez Sánchez, G.

2015-03-01

The study of the reversibility of elementary cellular automata with rule number 150 over the finite state set 𝔽p and endowed with periodic boundary conditions is done. The dynamic of such discrete dynamical systems is characterized by means of characteristic circulant matrices, and their analysis allows us to state that the reversibility depends on the number of cells of the cellular space and to explicitly compute the corresponding inverse cellular automata.

Resonance, criticality, and emergence in city traffic investigated in cellular automaton models.

PubMed

Varas, A; Cornejo, M D; Toledo, B A; Muñoz, V; Rogan, J; Zarama, R; Valdivia, J A

2009-11-01

The complex behavior that occurs when traffic lights are synchronized is studied for a row of interacting cars. The system is modeled through a cellular automaton. Two strategies are considered: all lights in phase and a "green wave" with a propagating green signal. It is found that the mean velocity near the resonant condition follows a critical scaling law. For the green wave, it is shown that the mean velocity scaling law holds even for random separation between traffic lights and is not dependent on the density. This independence on car density is broken when random perturbations are considered in the car velocity. Random velocity perturbations also have the effect of leading the system to an emergent state, where cars move in clusters, but with an average velocity which is independent of traffic light switching for large injection rates.

A Cellular Automaton model for pedestrian counterflow with swapping

NASA Astrophysics Data System (ADS)

Tao, Y. Z.; Dong, L. Y.

2017-06-01

In this paper, we propose a new floor field Cellular Automaton (CA) model with considering the swapping behaviors of pedestrians. The neighboring pedestrians in opposite directions take swapping in a probability decided by the linear density of pedestrian flow. The swapping which happens simultaneously with the normal movement is introduced to eliminate the gridlock in low density region. Numerical results show that the fundamental diagram is in good agreement with the measured data. Then the model is applied to investigate the counterflow and four typical states such as free flow, lane, intermediate and congestion states are found. More attention is paid on the intermediate state which lane-formation and local congestions switch in an irregular manner. The swapping plays a vital role in reducing the gridlock. Furthermore, the influence of the corridor size and individual's eyesight on counterflow are discussed in detail.

Cellular automaton simulation examining progenitor hierarchy structure effects on mammary ductal carcinoma in situ.

PubMed

Bankhead, Armand; Magnuson, Nancy S; Heckendorn, Robert B

2007-06-07

A computer simulation is used to model ductal carcinoma in situ, a form of non-invasive breast cancer. The simulation uses known histological morphology, cell types, and stochastic cell proliferation to evolve tumorous growth within a duct. The ductal simulation is based on a hybrid cellular automaton design using genetic rules to determine each cell's behavior. The genetic rules are a mutable abstraction that demonstrate genetic heterogeneity in a population. Our goal was to examine the role (if any) that recently discovered mammary stem cell hierarchies play in genetic heterogeneity, DCIS initiation and aggressiveness. Results show that simpler progenitor hierarchies result in greater genetic heterogeneity and evolve DCIS significantly faster. However, the more complex progenitor hierarchy structure was able to sustain the rapid reproduction of a cancer cell population for longer periods of time.

A quantum Samaritan’s dilemma cellular automaton

PubMed Central

Situ, Haozhen

2017-01-01

The dynamics of a spatial quantum formulation of the iterated Samaritan’s dilemma game with variable entangling is studied in this work. The game is played in the cellular automata manner, i.e. with local and synchronous interaction. The game is assessed in fair and unfair contests, in noiseless scenarios and with disrupting quantum noise. PMID:28680654

Modelling the time behaviour of a self-organized seismic region: a cellular automaton with memory

NASA Astrophysics Data System (ADS)

Cisternas, A.; Rivera, L.; Munoz, D.

2003-04-01

The range of a cumulative sequence of earthquake moments in a seismic region varies according to Hurst's law, namely a power law in the length of the time window. The range allows for an estimation of Mmax in a seismic zone. In the case of an independent process, the Hurst exponent H is 0.5. Memory implies 0.5

A Simple Model for the Evolution of Multi-Stranded Coronal Loops

NASA Technical Reports Server (NTRS)

Fuentes, M. C. Lopez; Klimchuk, J. A.

2010-01-01

We develop and analyze a simple cellular automaton (CA) model that reproduces the main properties of the evolution of soft X-ray coronal loops. We are motivated by the observation that these loops evolve in three distinguishable phases that suggest the development, maintainance, and decay of a self-organized system. The model is based on the idea that loops are made of elemental strands that are heated by the relaxation of magnetic stress in the form of nanoflares. In this vision, usually called "the Parker conjecture" (Parker 1988), the origin of stress is the displacement of the strand footpoints due to photospheric convective motions. Modeling the response and evolution of the plasma we obtain synthetic light curves that have the same characteristic properties (intensity, fluctuations, and timescales) as the observed cases. We study the dependence of these properties on the model parameters and find scaling laws that can be used as observational predictions of the model. We discuss the implications of our results for the interpretation of recent loop observations in different wavelengths. Subject headings: Sun: corona - Sun: flares - Sun: magnetic topology - Sun: X-rays, gamma rays

A cellular automaton implementation of a quantum battle of the sexes game with imperfect information

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón

2015-10-01

The dynamics of a spatial quantum formulation of the iterated battle of the sexes game with imperfect information is studied in this work. The game is played with variable entangling in a cellular automata manner, i.e. with local and synchronous interaction. The effect of spatial structure is assessed in fair and unfair scenarios.

High Severity Wildfire Effect On Rainfall Infiltration And Runoff: A Cellular Automata Based Simulation

NASA Astrophysics Data System (ADS)

Vergara-Blanco, J. E.; Leboeuf-Pasquier, J.; Benavides-Solorio, J. D. D.

2017-12-01

A simulation software that reproduces rainfall infiltration and runoff for a storm event in a particular forest area is presented. A cellular automaton is utilized to represent space and time. On the time scale, the simulation is composed by a sequence of discrete time steps. On the space scale, the simulation is composed of forest surface cells. The software takes into consideration rain intensity and length, individual forest cell soil absorption capacity evolution, and surface angle of inclination. The software is developed with the C++ programming language. The simulation is executed on a 100 ha area within La Primavera Forest in Jalisco, Mexico. Real soil texture for unburned terrain and high severity wildfire affected terrain is employed to recreate the specific infiltration profile. Historical rainfall data of a 92 minute event is used. The Horton infiltration equation is utilized for infiltration capacity calculation. A Digital Elevation Model (DEM) is employed to reproduce the surface topography. The DEM is displayed with a 3D mesh graph where individual surface cells can be observed. The plot colouring renders water content development at the cell level throughout the storm event. The simulation shows that the cumulative infiltration and runoff which take place at the surface cell level depend on the specific storm intensity, fluctuation and length, overall terrain topography, cell slope, and soil texture. Rainfall cumulative infiltration for unburned and high severity wildfire terrain are compared: unburned terrain exhibits a significantly higher amount of rainfall infiltration.It is concluded that a cellular automaton can be utilized with a C++ program to reproduce rainfall infiltration and runoff under diverse soil texture, topographic and rainfall conditions in a forest setting. This simulation is geared for an optimization program to pinpoint the locations of a series of forest land remediation efforts to support reforestation or to minimize runoff.

A Moore's cellular automaton model to get probabilistic seismic hazard maps for different magnitude releases: A case study for Greece

NASA Astrophysics Data System (ADS)

Jiménez, A.; Posadas, A. M.

2006-09-01

Cellular automata are simple mathematical idealizations of natural systems and they supply useful models for many investigations in natural science. Examples include sandpile models, forest fire models, and slider block models used in seismology. In the present paper, they have been used for establishing temporal relations between the energy releases of the seismic events that occurred in neighboring parts of the crust. The catalogue is divided into time intervals, and the region is divided into cells which are declared active or inactive by means of a threshold energy release criterion. Thus, a pattern of active and inactive cells which evolves over time is determined. A stochastic cellular automaton is constructed starting with these patterns, in order to simulate their spatio-temporal evolution, by supposing a Moore's neighborhood interaction between the cells. The best model is chosen by maximizing the mutual information between the past and the future states. Finally, a Probabilistic Seismic Hazard Map is given for the different energy releases considered. The method has been applied to the Greece catalogue from 1900 to 1999. The Probabilistic Seismic Hazard Maps for energies corresponding to m = 4 and m = 5 are close to the real seismicity after the data in that area, and they correspond to a background seismicity in the whole area. This background seismicity seems to cover the whole area in periods of around 25-50 years. The optimum cell size is in agreement with other studies; for m > 6 the optimum area increases according to the threshold of clear spatial resolution, and the active cells are not so clustered. The results are coherent with other hazard studies in the zone and with the seismicity recorded after the data set, as well as provide an interaction model which points out the large scale nature of the earthquake occurrence.

Simulation of glioblastoma multiforme (GBM) tumor cells using ising model on the Creutz Cellular Automaton

NASA Astrophysics Data System (ADS)

Züleyha, Artuç; Ziya, Merdan; Selçuk, Yeşiltaş; Kemal, Öztürk M.; Mesut, Tez

2017-11-01

Computational models for tumors have difficulties due to complexity of tumor nature and capacities of computational tools, however, these models provide visions to understand interactions between tumor and its micro environment. Moreover computational models have potential to develop strategies for individualized treatments for cancer. To observe a solid brain tumor, glioblastoma multiforme (GBM), we present a two dimensional Ising Model applied on Creutz cellular automaton (CCA). The aim of this study is to analyze avascular spherical solid tumor growth, considering transitions between non tumor cells and cancer cells are like phase transitions in physical system. Ising model on CCA algorithm provides a deterministic approach with discrete time steps and local interactions in position space to view tumor growth as a function of time. Our simulation results are given for fixed tumor radius and they are compatible with theoretical and clinic data.

A cellular automaton model for neurogenesis in Drosophila

NASA Astrophysics Data System (ADS)

Luthi, Pascal O.; Chopard, Bastien; Preiss, Anette; Ramsden, Jeremy J.

1998-07-01

A cellular automaton (CA) is constructed for the formation of the central nervous system of the Drosophila embryo. This is an experimentally well-studied system in which complex interactions between neighbouring cells appear to drive their differentiation into different types. It appears that all the cells initially have the potential to become neuroblasts, and all strive to this end, but those which differentiate first block their as yet undifferentiated neighbours from doing so. The CA makes use of observational evidence for a lateral inhibition mechanism involving signalling products S of the ‘proneural’ or neuralizing genes. The key concept of the model is that cells are continuously producing S, but the production rate is lowered by inhibitory signals received from neighbouring cells which have advanced further along the developmental pathway. Comparison with experimental data shows that it well accounts for the observed proportion of neuroectodermal cells delaminating as neuroblasts.

A Cellular Automata-based Model for Simulating Restitution Property in a Single Heart Cell.

PubMed

Sabzpoushan, Seyed Hojjat; Pourhasanzade, Fateme

2011-01-01

Ventricular fibrillation is the cause of the most sudden mortalities. Restitution is one of the specific properties of ventricular cell. The recent findings have clearly proved the correlation between the slope of restitution curve with ventricular fibrillation. This; therefore, mandates the modeling of cellular restitution to gain high importance. A cellular automaton is a powerful tool for simulating complex phenomena in a simple language. A cellular automaton is a lattice of cells where the behavior of each cell is determined by the behavior of its neighboring cells as well as the automata rule. In this paper, a simple model is depicted for the simulation of the property of restitution in a single cardiac cell using cellular automata. At first, two state variables; action potential and recovery are introduced in the automata model. In second, automata rule is determined and then recovery variable is defined in such a way so that the restitution is developed. In order to evaluate the proposed model, the generated restitution curve in our study is compared with the restitution curves from the experimental findings of valid sources. Our findings indicate that the presented model is not only capable of simulating restitution in cardiac cell, but also possesses the capability of regulating the restitution curve.

Dynamic data-driven integrated flare model based on self-organized criticality

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M. K.

2013-05-01

Context. We interpret solar flares as events originating in active regions that have reached the self-organized critical state. We describe them with a dynamic integrated flare model whose initial conditions and driving mechanism are derived from observations. Aims: We investigate whether well-known scaling laws observed in the distribution functions of characteristic flare parameters are reproduced after the self-organized critical state has been reached. Methods: To investigate whether the distribution functions of total energy, peak energy, and event duration follow the expected scaling laws, we first applied the previously reported static cellular automaton model to a time series of seven solar vector magnetograms of the NOAA active region 8210 recorded by the Imaging Vector Magnetograph on May 1 1998 between 18:59 UT and 23:16 UT until the self-organized critical state was reached. We then evolved the magnetic field between these processed snapshots through spline interpolation, mimicking a natural driver in our dynamic model. We identified magnetic discontinuities that exceeded a threshold in the Laplacian of the magnetic field after each interpolation step. These discontinuities were relaxed in local diffusion events, implemented in the form of cellular automaton evolution rules. Subsequent interpolation and relaxation steps covered all transitions until the end of the processed magnetograms' sequence. We additionally advanced each magnetic configuration that has reached the self-organized critical state (SOC configuration) by the static model until 50 more flares were triggered, applied the dynamic model again to the new sequence, and repeated the same process sufficiently often to generate adequate statistics. Physical requirements, such as the divergence-free condition for the magnetic field, were approximately imposed. Results: We obtain robust power laws in the distribution functions of the modeled flaring events with scaling indices that agree well with observations. Peak and total flare energy obey single power laws with indices -1.65 ± 0.11 and -1.47 ± 0.13, while the flare duration is best fitted with a double power law (-2.15 ± 0.15 and -3.60 ± 0.09 for the flatter and steeper parts, respectively). Conclusions: We conclude that well-known statistical properties of flares are reproduced after active regions reach the state of self-organized criticality. A significant enhancement of our refined cellular automaton model is that it initiates and further drives the simulation from observed evolving vector magnetograms, thus facilitating energy calculation in physical units, while a separation between MHD and kinetic timescales is possible by assigning distinct MHD timestamps to each interpolation step.

Particle Models with Self Sustained Current

NASA Astrophysics Data System (ADS)

Colangeli, M.; De Masi, A.; Presutti, E.

2017-06-01

We present some computer simulations run on a stochastic cellular automaton (CA). The CA simulates a gas of particles which are in a channel,the interval [1, L] in Z, but also in "reservoirs" R_1 and R_2. The evolution in the channel simulates a lattice gas with Kawasaki dynamics with attractive Kac interactions; the temperature is chosen smaller than the mean field critical one. There are also exchanges of particles between the channel and the reservoirs and among reservoirs. When the rate of exchanges among reservoirs is in a suitable interval the CA reaches an apparently stationary state with a non zero current; for different choices of the initial condition the current changes sign. We have a quite satisfactory theory of the phenomenon but we miss a full mathematical proof.

An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

PubMed

Matsubara, Takashi; Torikai, Hiroyuki

2016-04-01

Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources.

Modeling Emergent Macrophyte Distributions: Including Sub-dominant Species

EPA Science Inventory

Mixed stands of emergent vegetation are often present following drawdowns but models of wetland plant distributions fail to include subdominant species when predicting distributions. Three variations of a spatial plant distribution cellular automaton model were developed to explo...

Reconstruction of DNA sequences using genetic algorithms and cellular automata: towards mutation prediction?

PubMed

Mizas, Ch; Sirakoulis, G Ch; Mardiris, V; Karafyllidis, I; Glykos, N; Sandaltzopoulos, R

2008-04-01

Change of DNA sequence that fuels evolution is, to a certain extent, a deterministic process because mutagenesis does not occur in an absolutely random manner. So far, it has not been possible to decipher the rules that govern DNA sequence evolution due to the extreme complexity of the entire process. In our attempt to approach this issue we focus solely on the mechanisms of mutagenesis and deliberately disregard the role of natural selection. Hence, in this analysis, evolution refers to the accumulation of genetic alterations that originate from mutations and are transmitted through generations without being subjected to natural selection. We have developed a software tool that allows modelling of a DNA sequence as a one-dimensional cellular automaton (CA) with four states per cell which correspond to the four DNA bases, i.e. A, C, T and G. The four states are represented by numbers of the quaternary number system. Moreover, we have developed genetic algorithms (GAs) in order to determine the rules of CA evolution that simulate the DNA evolution process. Linear evolution rules were considered and square matrices were used to represent them. If DNA sequences of different evolution steps are available, our approach allows the determination of the underlying evolution rule(s). Conversely, once the evolution rules are deciphered, our tool may reconstruct the DNA sequence in any previous evolution step for which the exact sequence information was unknown. The developed tool may be used to test various parameters that could influence evolution. We describe a paradigm relying on the assumption that mutagenesis is governed by a near-neighbour-dependent mechanism. Based on the satisfactory performance of our system in the deliberately simplified example, we propose that our approach could offer a starting point for future attempts to understand the mechanisms that govern evolution. The developed software is open-source and has a user-friendly graphical input interface.

Self-organisation in Cellular Automata with Coalescent Particles: Qualitative and Quantitative Approaches

NASA Astrophysics Data System (ADS)

Hellouin de Menibus, Benjamin; Sablik, Mathieu

2017-06-01

This article introduces new tools to study self-organisation in a family of simple cellular automata which contain some particle-like objects with good collision properties (coalescence) in their time evolution. We draw an initial configuration at random according to some initial shift-ergodic measure, and use the limit measure to describe the asymptotic behaviour of the automata. We first take a qualitative approach, i.e. we obtain information on the limit measure(s). We prove that only particles moving in one particular direction can persist asymptotically. This provides some previously unknown information on the limit measures of various deterministic and probabilistic cellular automata: 3 and 4-cyclic cellular automata [introduced by Fisch (J Theor Probab 3(2):311-338, 1990; Phys D 45(1-3):19-25, 1990)], one-sided captive cellular automata [introduced by Theyssier (Captive Cellular Automata, 2004)], the majority-traffic cellular automaton, a self stabilisation process towards a discrete line [introduced by Regnault and Rémila (in: Mathematical Foundations of Computer Science 2015—40th International Symposium, MFCS 2015, Milan, Italy, Proceedings, Part I, 2015)]. In a second time we restrict our study to a subclass, the gliders cellular automata. For this class we show quantitative results, consisting in the asymptotic law of some parameters: the entry times [generalising K ůrka et al. (in: Proceedings of AUTOMATA, 2011)], the density of particles and the rate of convergence to the limit measure.

On the effect of memory in a quantum prisoner's dilemma cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Revuelta, Fabio

2018-03-01

The disrupting effect of quantum memory on the dynamics of a spatial quantum formulation of the iterated prisoner's dilemma game with variable entangling is studied. The game is played within a cellular automata framework, i.e., with local and synchronous interactions. The main findings of this work refer to the shrinking effect of memory on the disruption induced by noise.

Wolfram's class IV automata and a good life

NASA Astrophysics Data System (ADS)

McIntosh, Harold V.

1990-09-01

A comprehensive discussion of Wolfram's four classes of cellular automata is given, with the intention of relating them to Conway's criteria for a good game of Life. Although it is known that such classifications cannot be entirely rigorous, much information about the behavior of an automaton can be gleaned from the statistical properties of its transition table. Still more information can be deduced from the mean field approximation to its state densities, in particular, from the distribution of horizontal and diagonal tangents of the latter. In turn these characteristics can be related to the presence or absence of certain loops in the de Bruijn diagram of the automaton.

Dirac Cellular Automaton from Split-step Quantum Walk

PubMed Central

Mallick, Arindam; Chandrashekar, C. M.

2016-01-01

Simulations of one quantum system by an other has an implication in realization of quantum machine that can imitate any quantum system and solve problems that are not accessible to classical computers. One of the approach to engineer quantum simulations is to discretize the space-time degree of freedom in quantum dynamics and define the quantum cellular automata (QCA), a local unitary update rule on a lattice. Different models of QCA are constructed using set of conditions which are not unique and are not always in implementable configuration on any other system. Dirac Cellular Automata (DCA) is one such model constructed for Dirac Hamiltonian (DH) in free quantum field theory. Here, starting from a split-step discrete-time quantum walk (QW) which is uniquely defined for experimental implementation, we recover the DCA along with all the fine oscillations in position space and bridge the missing connection between DH-DCA-QW. We will present the contribution of the parameters resulting in the fine oscillations on the Zitterbewegung frequency and entanglement. The tuneability of the evolution parameters demonstrated in experimental implementation of QW will establish it as an efficient tool to design quantum simulator and approach quantum field theory from principles of quantum information theory. PMID:27184159

Modeling of Dendritic Evolution of Continuously Cast Steel Billet with Cellular Automaton

NASA Astrophysics Data System (ADS)

Wang, Weiling; Ji, Cheng; Luo, Sen; Zhu, Miaoyong

2018-02-01

In order to predict the dendritic evolution during the continuous steel casting process, a simple mechanism to connect the heat transfer at the macroscopic scale and the dendritic growth at the microscopic scale was proposed in the present work. As the core of the across-scale simulation, a two-dimensional cell automaton (CA) model with a decentered square algorithm was developed and parallelized. Apart from nucleation undercooling and probability, a temperature gradient was introduced to deal with the columnar-to-equiaxed transition (CET) by considering its variation during continuous casting. Based on the thermal history, the dendritic evolution in a 4 mm × 40 mm region near the centerline of a SWRH82B steel billet was predicted. The influences of the secondary cooling intensity, superheat, and casting speed on the dendritic structure of the billet were investigated in detail. The results show that the predicted equiaxed dendritic solidification of Fe-5.3Si alloy and columnar dendritic solidification of Fe-0.45C alloy are consistent with in situ experimental results [Yasuda et al. Int J Cast Metals Res 22:15-21 (2009); Yasuda et al. ISIJ Int 51:402-408 (2011)]. Moreover, the predicted dendritic arm spacing and CET location agree well with the actual results in the billet. The primary dendrite arm spacing of columnar dendrites decreases with increasing secondary cooling intensity, or decreasing superheat and casting speed. Meanwhile, the CET is promoted as the secondary cooling intensity and superheat decrease. However, the CET is not influenced by the casting speed, owing to the adjusting of the flow rate of secondary spray water. Compared with the superheat and casting speed, the secondary cooling intensity can influence the cooling rate and temperature gradient in deeper locations, and accordingly exerts a more significant influence on the equiaxed dendritic structure.

Universal microfluidic automaton for autonomous sample processing: application to the Mars Organic Analyzer.

PubMed

Kim, Jungkyu; Jensen, Erik C; Stockton, Amanda M; Mathies, Richard A

2013-08-20

A fully integrated multilayer microfluidic chemical analyzer for automated sample processing and labeling, as well as analysis using capillary zone electrophoresis is developed and characterized. Using lifting gate microfluidic control valve technology, a microfluidic automaton consisting of a two-dimensional microvalve cellular array is fabricated with soft lithography in a format that enables facile integration with a microfluidic capillary electrophoresis device. The programmable sample processor performs precise mixing, metering, and routing operations that can be combined to achieve automation of complex and diverse assay protocols. Sample labeling protocols for amino acid, aldehyde/ketone and carboxylic acid analysis are performed automatically followed by automated transfer and analysis by the integrated microfluidic capillary electrophoresis chip. Equivalent performance to off-chip sample processing is demonstrated for each compound class; the automated analysis resulted in a limit of detection of ~16 nM for amino acids. Our microfluidic automaton provides a fully automated, portable microfluidic analysis system capable of autonomous analysis of diverse compound classes in challenging environments.

Cellular automata in photonic cavity arrays.

PubMed

Li, Jing; Liew, T C H

2016-10-31

We propose theoretically a photonic Turing machine based on cellular automata in arrays of nonlinear cavities coupled with artificial gauge fields. The state of the system is recorded making use of the bistability of driven cavities, in which losses are fully compensated by an external continuous drive. The sequential update of the automaton layers is achieved automatically, by the local switching of bistable states, without requiring any additional synchronization or temporal control.

A coarse-grained Monte Carlo approach to diffusion processes in metallic nanoparticles

NASA Astrophysics Data System (ADS)

Hauser, Andreas W.; Schnedlitz, Martin; Ernst, Wolfgang E.

2017-06-01

A kinetic Monte Carlo approach on a coarse-grained lattice is developed for the simulation of surface diffusion processes of Ni, Pd and Au structures with diameters in the range of a few nanometers. Intensity information obtained via standard two-dimensional transmission electron microscopy imaging techniques is used to create three-dimensional structure models as input for a cellular automaton. A series of update rules based on reaction kinetics is defined to allow for a stepwise evolution in time with the aim to simulate surface diffusion phenomena such as Rayleigh breakup and surface wetting. The material flow, in our case represented by the hopping of discrete portions of metal on a given grid, is driven by the attempt to minimize the surface energy, which can be achieved by maximizing the number of filled neighbor cells.

Intelligent traffic signals : extending the range of self-organization in the BML model.

DOT National Transportation Integrated Search

2013-04-01

The two-dimensional traffic model of Biham, Middleton and Levine (Phys. Rev. A, 1992) is : a simple cellular automaton that exhibits a wide range of complex behavior. It consists of both : northbound and eastbound cars traveling on a rectangular arra...

1/f Noise in the ``Game of Life''

NASA Astrophysics Data System (ADS)

Andrecut, Mircea

Conway's celebrated ``game of life'' cellular automaton possesses computational universality. The Fourier analysis reported here shows that the power spectra of the ``game of life'' exhibit 1/f noise. The obtained result suggests a connection between 1/f noise and computational universality.

A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing

NASA Astrophysics Data System (ADS)

Lian, Yanping; Lin, Stephen; Yan, Wentao; Liu, Wing Kam; Wagner, Gregory J.

2018-05-01

In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.

A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing

NASA Astrophysics Data System (ADS)

Lian, Yanping; Lin, Stephen; Yan, Wentao; Liu, Wing Kam; Wagner, Gregory J.

2018-01-01

In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.

Macroscopic Spatial Complexity of the Game of Life Cellular Automaton: A Simple Data Analysis

NASA Astrophysics Data System (ADS)

Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Rodríguez-Achach, M. E.

In this chapter we present a simple data analysis of an ensemble of 20 time series, generated by averaging the spatial positions of the living cells for each state of the Game of Life Cellular Automaton (GoL). We show that at the macroscopic level described by these time series, complexity properties of GoL are also presented and the following emergent properties, typical of data extracted complex systems such as financial or economical come out: variations of the generated time series following an asymptotic power law distribution, large fluctuations tending to be followed by large fluctuations, and small fluctuations tending to be followed by small ones, and fast decay of linear correlations, however, the correlations associated to their absolute variations exhibit a long range memory. Finally, a Detrended Fluctuation Analysis (DFA) of the generated time series, indicates that the GoL spatial macro states described by the time series are not either completely ordered or random, in a measurable and very interesting way.

A New Cellular Automaton Method Coupled with a Rate-dependent (CARD) Model for Predicting Dynamic Recrystallization Behavior

NASA Astrophysics Data System (ADS)

Azarbarmas, M.; Aghaie-Khafri, M.

2018-03-01

A comprehensive cellular automaton (CA) model should be coupled with a rate-dependent (RD) model for analyzing the RD deformation of alloys at high temperatures. In the present study, a new CA technique coupled with an RD model—namely, CARD—was developed. The proposed CARD model was used to simulate the dynamic recrystallization phenomenon during the hot deformation of the Inconel 718 superalloy. This model is capable of calculating the mean grain size and volume fraction of dynamic recrystallized grains, and estimating the phenomenological flow behavior of the material. In the presented model, an actual orientation definition comprising three Euler angles was used by implementing the electron backscatter diffraction data. For calculating the lattice rotation of grains, it was assumed that all slip systems of grains are active during the high-temperature deformation because of the intrinsic rate dependency of the procedure. Moreover, the morphological changes in grains were obtained using a topological module.

3D simulation of friction stir welding based on movable cellular automaton method

NASA Astrophysics Data System (ADS)

Eremina, Galina M.

2017-12-01

The paper is devoted to a 3D computer simulation of the peculiarities of material flow taking place in friction stir welding (FSW). The simulation was performed by the movable cellular automaton (MCA) method, which is a representative of particle methods in mechanics. Commonly, the flow of material in FSW is simulated based on computational fluid mechanics, assuming the material as continuum and ignoring its structure. The MCA method considers a material as an ensemble of bonded particles. The rupture of interparticle bonds and the formation of new bonds enable simulations of crack nucleation and healing as well as mas mixing and microwelding. The simulation results showed that using pins of simple shape (cylinder, cone, and pyramid) without a shoulder results in small displacements of plasticized material in workpiece thickness directions. Nevertheless, the optimal ratio of longitudinal velocity to rotational speed makes it possible to transport the welded material around the pin several times and to produce a joint of good quality.

The transition between immune and disease states in a cellular automaton model of clonal immune response

NASA Astrophysics Data System (ADS)

Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.

1997-02-01

In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infections virus and killer T cells (cellular response). The model represents molecules and cells with bitstrings. The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connected to spatial extension is lost, as is the oscillating feature. Thus the mean field approximation introduced with coupled maps destroys oscillations.

New cellular automaton model for magnetohydrodynamics

NASA Technical Reports Server (NTRS)

Chen, Hudong; Matthaeus, William H.

1987-01-01

A new type of two-dimensional cellular automation method is introduced for computation of magnetohydrodynamic fluid systems. Particle population is described by a 36-component tensor referred to a hexagonal lattice. By appropriate choice of the coefficients that control the modified streaming algorithm and the definition of the macroscopic fields, it is possible to compute both Lorentz-force and magnetic-induction effects. The method is local in the microscopic space and therefore suited to massively parallel computations.

Cellular automaton formulation of passive scalar dynamics

NASA Technical Reports Server (NTRS)

Chen, Hudong; Matthaeus, William H.

1987-01-01

Cellular automata modeling of the advection of a passive scalar in a two-dimensional flow is examined in the context of discrete lattice kinetic theory. It is shown that if the passive scalar is represented by tagging or 'coloring' automation particles a passive advection-diffusion equation emerges without use of perturbation expansions. For the specific case of the hydrodynamic lattice gas model of Frisch et al. (1986), the diffusion coefficient is calculated by perturbation.

Cellular Automata for Spatiotemporal Pattern Formation from Reaction-Diffusion Partial Differential Equations

NASA Astrophysics Data System (ADS)

Ohmori, Shousuke; Yamazaki, Yoshihiro

2016-01-01

Ultradiscrete equations are derived from a set of reaction-diffusion partial differential equations, and cellular automaton rules are obtained on the basis of the ultradiscrete equations. Some rules reproduce the dynamical properties of the original reaction-diffusion equations, namely, bistability and pulse annihilation. Furthermore, other rules bring about soliton-like preservation and periodic pulse generation with a pacemaker, which are not obtained from the original reaction-diffusion equations.

Understanding the complex dynamics of stock markets through cellular automata

NASA Astrophysics Data System (ADS)

Qiu, G.; Kandhai, D.; Sloot, P. M. A.

2007-04-01

We present a cellular automaton (CA) model for simulating the complex dynamics of stock markets. Within this model, a stock market is represented by a two-dimensional lattice, of which each vertex stands for a trader. According to typical trading behavior in real stock markets, agents of only two types are adopted: fundamentalists and imitators. Our CA model is based on local interactions, adopting simple rules for representing the behavior of traders and a simple rule for price updating. This model can reproduce, in a simple and robust manner, the main characteristics observed in empirical financial time series. Heavy-tailed return distributions due to large price variations can be generated through the imitating behavior of agents. In contrast to other microscopic simulation (MS) models, our results suggest that it is not necessary to assume a certain network topology in which agents group together, e.g., a random graph or a percolation network. That is, long-range interactions can emerge from local interactions. Volatility clustering, which also leads to heavy tails, seems to be related to the combined effect of a fast and a slow process: the evolution of the influence of news and the evolution of agents’ activity, respectively. In a general sense, these causes of heavy tails and volatility clustering appear to be common among some notable MS models that can confirm the main characteristics of financial markets.

Numerical Simulation and Experimental Casting of Nickel-Based Single-Crystal Superalloys by HRS and LMC Directional Solidification Processes

NASA Astrophysics Data System (ADS)

Yan, Xuewei; Wang, Run'nan; Xu, Qingyan; Liu, Baicheng

2017-04-01

Mathematical models for dynamic heat radiation and convection boundary in directional solidification processes are established to simulate the temperature fields. Cellular automaton (CA) method and Kurz-Giovanola-Trivedi (KGT) growth model are used to describe nucleation and growth. Primary dendritic arm spacing (PDAS) and secondary dendritic arm spacing (SDAS) are calculated by the Ma-Sham (MS) and Furer-Wunderlin (FW) models respectively. The mushy zone shape is investigated based on the temperature fields, for both high-rate solidification (HRS) and liquid metal cooling (LMC) processes. The evolution of the microstructure and crystallographic orientation are analyzed by simulation and electron back-scattered diffraction (EBSD) technique, respectively. Comparison of the simulation results from PDAS and SDAS with experimental results reveals a good agreement with each other. The results show that LMC process can provide both dendritic refinement and superior performance for castings due to the increased cooling rate and thermal gradient.

Influence of Secondary Cooling Mode on Solidification Structure and Macro-segregation Behavior for High-carbon Continuous Casting Bloom

NASA Astrophysics Data System (ADS)

Dou, Kun; Yang, Zhenguo; Liu, Qing; Huang, Yunhua; Dong, Hongbiao

2017-07-01

A cellular automaton-finite element coupling model for high-carbon continuously cast bloom of GCr15 steel is established to simulate the solidification structure and to investigate the influence of different secondary cooling modes on characteristic parameters such as equiaxed crystal ratio, grain size and secondary dendrite arm spacing, in which the effect of phase transformation and electromagnetic stirring is taken into consideration. On this basis, evolution of carbon macro-segregation for GCr15 steel bloom is researched correspondingly via industrial tests. Based on above analysis, the relationship among secondary cooling modes, characteristic parameters for solidification structure as well as carbon macro-segregation is illustrated to obtain optimum secondary cooling strategy and alleviate carbon macro-segregation degree for GCr15 steel bloom in continuous casting process. The evaluating method for element macro-segregation is applicable in various steel types.

Special relativity in a discrete quantum universe

NASA Astrophysics Data System (ADS)

Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo

2016-10-01

The hypothesis of a discrete fabric of the universe, the "Planck scale," is always on stage since it solves mathematical and conceptual problems in the infinitely small. However, it clashes with special relativity, which is designed for the continuum. Here, we show how the clash can be overcome within a discrete quantum theory where the evolution of fields is described by a quantum cellular automaton. The reconciliation is achieved by defining the change of observer as a change of representation of the dynamics, without any reference to space-time. We use the relativity principle, i.e., the invariance of dynamics under change of inertial observer, to identify a change of inertial frame with a symmetry of the dynamics. We consider the full group of such symmetries, and recover the usual Lorentz group in the relativistic regime of low energies, while at the Planck scale the covariance is nonlinearly distorted.

Growth and Decay in Life-Like Cellular Automata

NASA Astrophysics Data System (ADS)

Eppstein, David

Since the study of life began, many have asked: is it unique in the universe, or are there other interesting forms of life elsewhere? Before we can answer that question, we should ask others: What makes life special? If we happen across another system with life-like behavior, how would we be able to recognize it? We are speaking, of course, of the mathematical systems of cellular automata, of the fascinating patterns that have been discovered and engineered in Conway's Game of Life, and of the possible existence of other cellular automaton rules with equally complex behavior to that of Life.

A Cellular Automaton / Finite Element model for predicting grain texture development in galvanized coatings

NASA Astrophysics Data System (ADS)

Guillemot, G.; Avettand-Fènoël, M.-N.; Iosta, A.; Foct, J.

2011-01-01

Hot-dipping galvanizing process is a widely used and efficient way to protect steel from corrosion. We propose to master the microstructure of zinc grains by investigating the relevant process parameters. In order to improve the texture of this coating, we model grain nucleation and growth processes and simulate the zinc solid phase development. A coupling scheme model has been applied with this aim. This model improves a previous two-dimensional model of the solidification process. It couples a cellular automaton (CA) approach and a finite element (FE) method. CA grid and FE mesh are superimposed on the same domain. The grain development is simulated at the micro-scale based on the CA grid. A nucleation law is defined using a Gaussian probability and a random set of nucleating cells. A crystallographic orientation is defined for each one with a choice of Euler's angle (Ψ,θ,φ). A small growing shape is then associated to each cell in the mushy domain and a dendrite tip kinetics is defined using the model of Kurz [2]. The six directions of basal plane and the two perpendicular directions develop in each mushy cell. During each time step, cell temperature and solid fraction are then determined at micro-scale using the enthalpy conservation relation and variations are reassigned at macro-scale. This coupling scheme model enables to simulate the three-dimensional growing kinetics of the zinc grain in a two-dimensional approach. Grain structure evolutions for various cooling times have been simulated. Final grain structure has been compared to EBSD measurements. We show that the preferentially growth of dendrite arms in the basal plane of zinc grains is correctly predicted. The described coupling scheme model could be applied for simulated other product or manufacturing processes. It constitutes an approach gathering both micro and macro scale models.

Spatiotemporal modelling of viral infection dynamics

NASA Astrophysics Data System (ADS)

Beauchemin, Catherine

Viral kinetics have been studied extensively in the past through the use of ordinary differential equations describing the time evolution of the diseased state in a spatially well-mixed medium. However, emerging spatial structures such as localized populations of dead cells might affect the spread of infection, similar to the manner in which a counter-fire can stop a forest fire from spreading. In the first phase of the project, a simple two-dimensional cellular automaton model of viral infections was developed. It was validated against clinical immunological data for uncomplicated influenza A infections and shown to be accurate enough to adequately model them. In the second phase of the project, the simple two-dimensional cellular automaton model was used to investigate the effects of relaxing the well-mixed assumption on viral infection dynamics. It was shown that grouping the initially infected cells into patches rather than distributing them uniformly on the grid reduced the infection rate as only cells on the perimeter of the patch have healthy neighbours to infect. Use of a local epithelial cell regeneration rule where dead cells are replaced by healthy cells when an immediate neighbour divides was found to result in more extensive damage of the epithelium and yielded a better fit to experimental influenza A infection data than a global regeneration rule based on division rate of healthy cell. Finally, the addition of immune cell at the site of infection was found to be a better strategy at low infection levels, while addition at random locations on the grid was the better strategy at high infection level. In the last project, the movement of T cells within lymph nodes in the absence of antigen, was investigated. Based on individual T cell track data captured by two-photon microscopy experiments in vivo, a simple model was proposed for the motion of T cells. This is the first step towards the implementation of a more realistic spatiotemporal model of HIV than those proposed thus far.

A cellular automata model of Ebola virus dynamics

NASA Astrophysics Data System (ADS)

Burkhead, Emily; Hawkins, Jane

2015-11-01

We construct a stochastic cellular automaton (SCA) model for the spread of the Ebola virus (EBOV). We make substantial modifications to an existing SCA model used for HIV, introduced by others and studied by the authors. We give a rigorous analysis of the similarities between models due to the spread of virus and the typical immune response to it, and the differences which reflect the drastically different timing of the course of EBOV. We demonstrate output from the model and compare it with clinical data.

Microcanonical model for interface formation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rucklidge, A.; Zaleski, S.

1988-04-01

We describe a new cellular automaton model which allows us to simulate separation of phases. The model is an extension of existing cellular automata for the Ising model, such as Q2R. It conserves particle number and presents the qualitative features of spinodal decomposition. The dynamics is deterministic and does not require random number generators. The spins exchange energy with small local reservoirs or demons. The rate of relaxation to equilibrium is investigated, and the results are compared to the Lifshitz-Slyozov theory.

A quantum relativistic battle of the sexes cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Situ, Haozhen

2017-02-01

The effect of variable entangling on the dynamics of a spatial quantum relativistic formulation of the iterated battle of the sexes game is studied in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. The game is assessed in fair and unfair contests. Despite the full range of quantum parameters initially accessible, they promptly converge into fairly stable configurations, that often show rich spatial structures in simulations with no negligible entanglement.

Mapping Thermal Habitat of Ectotherms Based on Behavioral Thermoregulation in a Controlled Thermal Environment

NASA Astrophysics Data System (ADS)

Fei, T.; Skidmore, A.; Liu, Y.

2012-07-01

Thermal environment is especially important to ectotherm because a lot of physiological functions rely on the body temperature such as thermoregulation. The so-called behavioural thermoregulation function made use of the heterogeneity of the thermal properties within an individual's habitat to sustain the animal's physiological processes. This function links the spatial utilization and distribution of individual ectotherm with the thermal properties of habitat (thermal habitat). In this study we modelled the relationship between the two by a spatial explicit model that simulates the movements of a lizard in a controlled environment. The model incorporates a lizard's transient body temperatures with a cellular automaton algorithm as a way to link the physiology knowledge of the animal with the spatial utilization of its microhabitat. On a larger spatial scale, 'thermal roughness' of the habitat was defined and used to predict the habitat occupancy of the target species. The results showed the habitat occupancy can be modelled by the cellular automaton based algorithm at a smaller scale, and can be modelled by the thermal roughness index at a larger scale.

Simulation study of overtaking in pedestrian flow using floor field cellular automaton model

NASA Astrophysics Data System (ADS)

Fu, Zhijian; Xia, Liang; Yang, Hongtai; Liu, Xiaobo; Ma, Jian; Luo, Lin; Yang, Lizhong; Chen, Junmin

Properties of pedestrian may change along the moving path, for example, as a result of fatigue or injury, which has never been properly investigated in the past research. The paper attempts to study tactical overtaking in pedestrian flow. That is difficult to be modeled using a microscopic discrete model because of the complexity of the detailed overtaking behavior, and crossing/overlaps of pedestrian routes. Thus, a multi-velocity floor field cellular automaton model explaining the detailed psychical process of overtaking decision was proposed. Pedestrian can be either in normal state or in tactical overtaking state. Without tactical decision, pedestrians in normal state are driven by the floor field. Pedestrians make their tactical overtaking decisions by evaluating the walking environment around the overtaking route (the average velocity and density around the route, visual field of pedestrian) and obstructing conditions (the distance and velocity difference between the overtaking pedestrian and the obstructing pedestrian). The effects of tactical overtaking ratio, free velocity dispersion, and visual range on fundamental diagram, conflict density, and successful overtaking ratio were explored. Besides, the sensitivity analysis of the route factor relative intensity was performed.

A Data-Driven, Integrated Flare Model Based on Self-Organized Criticality

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M.

2013-09-01

We interpret solar flares as events originating in solar active regions having reached the self-organized critical state, by alternatively using two versions of an "integrated flare model" - one static and one dynamic. In both versions the initial conditions are derived from observations aiming to investigate whether well-known scaling laws observed in the distribution functions of characteristic flare parameters are reproduced after the self-organized critical state has been reached. In the static model, we first apply a nonlinear force-free extrapolation that reconstructs the three-dimensional magnetic fields from two-dimensional vector magnetograms. We then locate magnetic discontinuities exceeding a threshold in the Laplacian of the magnetic field. These discontinuities are relaxed in local diffusion events, implemented in the form of cellular-automaton evolution rules. Subsequent loading and relaxation steps lead the system to self-organized criticality, after which the statistical properties of the simulated events are examined. In the dynamic version we deploy an enhanced driving mechanism, which utilizes the observed evolution of active regions, making use of sequential vector magnetograms. We first apply the static cellular automaton model to consecutive solar vector magnetograms until the self-organized critical state is reached. We then evolve the magnetic field inbetween these processed snapshots through spline interpolation, acting as a natural driver in the dynamic model. The identification of magnetically unstable sites as well as their relaxation follow the same rules as in the static model after each interpolation step. Subsequent interpolation/driving and relaxation steps cover all transitions until the end of the sequence. Physical requirements, such as the divergence-free condition for the magnetic field vector, are approximately satisfied in both versions of the model. We obtain robust power laws in the distribution functions of the modelled flaring events with scaling indices in good agreement with observations. We therefore conclude that well-known statistical properties of flares are reproduced after active regions reach self-organized criticality. The significant enhancement in both the static and the dynamic integrated flare models is that they initiate the simulation from observations, thus facilitating energy calculation in physical units. Especially in the dynamic version of the model, the driving of the system is based on observed, evolving vector magnetograms, allowing for the separation between MHD and kinetic timescales through the assignment of distinct MHD timestamps to each interpolation step.

Towards self-correcting quantum memories

NASA Astrophysics Data System (ADS)

Michnicki, Kamil

This thesis presents a model of self-correcting quantum memories where quantum states are encoded using topological stabilizer codes and error correction is done using local measurements and local dynamics. Quantum noise poses a practical barrier to developing quantum memories. This thesis explores two types of models for suppressing noise. One model suppresses thermalizing noise energetically by engineering a Hamiltonian with a high energy barrier between code states. Thermalizing dynamics are modeled phenomenologically as a Markovian quantum master equation with only local generators. The second model suppresses stochastic noise with a cellular automaton that performs error correction using syndrome measurements and a local update rule. Several ways of visualizing and thinking about stabilizer codes are presented in order to design ones that have a high energy barrier: the non-local Ising model, the quasi-particle graph and the theory of welded stabilizer codes. I develop the theory of welded stabilizer codes and use it to construct a code with the highest known energy barrier in 3-d for spin Hamiltonians: the welded solid code. Although the welded solid code is not fully self correcting, it has some self correcting properties. It has an increased memory lifetime for an increased system size up to a temperature dependent maximum. One strategy for increasing the energy barrier is by mediating an interaction with an external system. I prove a no-go theorem for a class of Hamiltonians where the interaction terms are local, of bounded strength and commute with the stabilizer group. Under these conditions the energy barrier can only be increased by a multiplicative constant. I develop cellular automaton to do error correction on a state encoded using the toric code. The numerical evidence indicates that while there is no threshold, the model can extend the memory lifetime significantly. While of less theoretical importance, this could be practical for real implementations of quantum memories. Numerical evidence also suggests that the cellular automaton could function as a decoder with a soft threshold.

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

PubMed Central

Zhu, Hao; Sun, Yan; Rajagopal, Gunaretnam; Mondry, Adrian; Dhar, Pawan

2004-01-01

Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described. PMID:15339335

On the combined gradient-stochastic plasticity model: Application to Mo-micropillar compression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konstantinidis, A. A., E-mail: akonsta@civil.auth.gr; Zhang, X., E-mail: zhangxu26@126.com; Aifantis, E. C., E-mail: mom@mom.gen.auth.gr

2015-02-17

A formulation for addressing heterogeneous material deformation is proposed. It is based on the use of a stochasticity-enhanced gradient plasticity model implemented through a cellular automaton. The specific application is on Mo-micropillar compression, for which the irregularities of the strain bursts observed have been experimentally measured and theoretically interpreted through Tsallis' q-statistics.

Computing aggregate properties of preimages for 2D cellular automata.

PubMed

Beer, Randall D

2017-11-01

Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm-incremental aggregation-that can compute aggregate properties of the set of precursors exponentially faster than naïve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach.

Computing aggregate properties of preimages for 2D cellular automata

NASA Astrophysics Data System (ADS)

Beer, Randall D.

2017-11-01

Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm—incremental aggregation—that can compute aggregate properties of the set of precursors exponentially faster than naïve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach.

Octree-based, GPU implementation of a continuous cellular automaton for the simulation of complex, evolving surfaces

NASA Astrophysics Data System (ADS)

Ferrando, N.; Gosálvez, M. A.; Cerdá, J.; Gadea, R.; Sato, K.

2011-03-01

Presently, dynamic surface-based models are required to contain increasingly larger numbers of points and to propagate them over longer time periods. For large numbers of surface points, the octree data structure can be used as a balance between low memory occupation and relatively rapid access to the stored data. For evolution rules that depend on neighborhood states, extended simulation periods can be obtained by using simplified atomistic propagation models, such as the Cellular Automata (CA). This method, however, has an intrinsic parallel updating nature and the corresponding simulations are highly inefficient when performed on classical Central Processing Units (CPUs), which are designed for the sequential execution of tasks. In this paper, a series of guidelines is presented for the efficient adaptation of octree-based, CA simulations of complex, evolving surfaces into massively parallel computing hardware. A Graphics Processing Unit (GPU) is used as a cost-efficient example of the parallel architectures. For the actual simulations, we consider the surface propagation during anisotropic wet chemical etching of silicon as a computationally challenging process with a wide-spread use in microengineering applications. A continuous CA model that is intrinsically parallel in nature is used for the time evolution. Our study strongly indicates that parallel computations of dynamically evolving surfaces simulated using CA methods are significantly benefited by the incorporation of octrees as support data structures, substantially decreasing the overall computational time and memory usage.

An improved cellular automata model for train operation simulation with dynamic acceleration

NASA Astrophysics Data System (ADS)

Li, Wen-Jun; Nie, Lei

2018-03-01

Urban rail transit plays an important role in the urban public traffic because of its advantages of fast speed, large transport capacity, high safety, reliability and low pollution. This study proposes an improved cellular automaton (CA) model by considering the dynamic characteristic of the train acceleration to analyze the energy consumption and train running time. Constructing an effective model for calculating energy consumption to aid train operation improvement is the basis for studying and analyzing energy-saving measures for urban rail transit system operation.

Random Evolution of Idiotypic Networks: Dynamics and Architecture

NASA Astrophysics Data System (ADS)

Brede, Markus; Behn, Ulrich

The paper deals with modelling a subsystem of the immune system, the so-called idiotypic network (INW). INWs, conceived by N.K. Jerne in 1974, are functional networks of interacting antibodies and B cells. In principle, Jernes' framework provides solutions to many issues in immunology, such as immunological memory, mechanisms for antigen recognition and self/non-self discrimination. Explaining the interconnection between the elementary components, local dynamics, network formation and architecture, and possible modes of global system function appears to be an ideal playground of statistical mechanics. We present a simple cellular automaton model, based on a graph representation of the system. From a simplified description of idiotypic interactions, rules for the random evolution of networks of occupied and empty sites on these graphs are derived. In certain biologically relevant parameter ranges the resultant dynamics leads to stationary states. A stationary state is found to correspond to a specific pattern of network organization. It turns out that even these very simple rules give rise to a multitude of different kinds of patterns. We characterize these networks by classifying `static' and `dynamic' network-patterns. A type of `dynamic' network is found to display many features of real INWs.

Modeling of microstructure evolution of magnesium alloy during the high pressure die casting process

NASA Astrophysics Data System (ADS)

Wu, Mengwu; Xiong, Shoumei

2012-07-01

Two important microstructure characteristics of high pressure die cast magnesium alloy are the externally solidified crystals (ESCs) and the fully divorced eutectic which form at the filling stage of the shot sleeve and at the last stage of solidification in the die cavity, respectively. Both of them have a significant influence on the mechanical properties and performance of magnesium alloy die castings. In the present paper, a numerical model based on the cellular automaton (CA) method was developed to simulate the microstructure evolution of magnesium alloy during cold-chamber high pressure die casting (HPDC) process. Modeling of dendritic growth of magnesium alloy with six-fold symmetry was achieved by defining a special neighbourhood configuration and calculating of the growth kinetics from complete solution of the transport equations. Special attention was paid to establish a nucleation model considering both of the nucleation of externally solidified crystals in the shot sleeve and the massive nucleation in the die cavity. Meanwhile, simulation of the formation of fully divorced eutectic was also taken into account in the present CA model. Validation was performed and the capability of the present model was addressed by comparing the simulated results with those obtained by experiments.

Modeling the effect of microscopic driving behaviors on Kerner's time-delayed traffic breakdown at traffic signal using cellular automata

NASA Astrophysics Data System (ADS)

Wang, Yang; Chen, Yan-Yan

2016-12-01

The signalized traffic is considerably complex due to the fact that various driving behaviors have emerged to respond to traffic signals. However, the existing cellular automaton models take the signal-vehicle interactions into account inadequately, resulting in a potential risk that vehicular traffic flow dynamics may not be completely explored. To remedy this defect, this paper proposes a more realistic cellular automaton model by incorporating a number of the driving behaviors typically observed when the vehicles are approaching a traffic light. In particular, the anticipatory behavior proposed in this paper is realized with a perception factor designed by considering the vehicle speed implicitly and the gap to its preceding vehicle explicitly. Numerical simulations have been performed based on a signal controlled road which is partitioned into three sections according to the different reactions of drivers. The effects of microscopic driving behaviors on Kerner's time-delayed traffic breakdown at signal (Kerner 2011, 2013) have been investigated with the assistance of spatiotemporal pattern and trajectory analysis. Furthermore, the contributions of the driving behaviors on the traffic breakdown have been statistically examined. Finally, with the activation of the anticipatory behavior, the influences of the other driving behaviors on the formation of platoon have been investigated in terms of the number of platoons, the averaged platoon size, and the averaged flow rate.

Phase transitions in coupled map lattices and in associated probabilistic cellular automata.

PubMed

Just, Wolfram

2006-10-01

Analytical tools are applied to investigate piecewise linear coupled map lattices in terms of probabilistic cellular automata. The so-called disorder condition of probabilistic cellular automata is closely related with attracting sets in coupled map lattices. The importance of this condition for the suppression of phase transitions is illustrated by spatially one-dimensional systems. Invariant densities and temporal correlations are calculated explicitly. Ising type phase transitions are found for one-dimensional coupled map lattices acting on repelling sets and for a spatially two-dimensional Miller-Huse-like system with stable long time dynamics. Critical exponents are calculated within a finite size scaling approach. The relevance of detailed balance of the resulting probabilistic cellular automaton for the critical behavior is pointed out.

FAST TRACK COMMUNICATION Solving the ultradiscrete KdV equation

NASA Astrophysics Data System (ADS)

Willox, Ralph; Nakata, Yoichi; Satsuma, Junkichi; Ramani, Alfred; Grammaticos, Basile

2010-12-01

We show that a generalized cellular automaton, exhibiting solitonic interactions, can be explicitly solved by means of techniques first introduced in the context of the scattering problem for the KdV equation. We apply this method to calculate the phase-shifts caused by interactions between the solitonic and non-solitonic parts into which arbitrary initial states separate in time.

The Game of Life Rules on Penrose Tilings: Still Life and Oscillators

NASA Astrophysics Data System (ADS)

Owens, Nick; Stepney, Susan

John Horton Conway's Game of Life is a simple two-dimensional, two state cellular automaton (CA), remarkable for its complex behaviour. That behaviour is known to be very sensitive to a change in the CA rules. Here we continue our investigations into its sensitivity to changes in the lattice, by the use of an aperiodic Penrose tiling lattice.

Complex traffic flow that allows as well as hampers lane-changing intrinsically contains social-dilemma structures

NASA Astrophysics Data System (ADS)

Iwamura, Yoshiro; Tanimoto, Jun

2018-02-01

To investigate an interesting question as to whether or not social dilemma structures can be found in a realistic traffic flow reproduced by a model, we built a new microscopic model in which an intentional driver may try lane-changing to go in front of other vehicles and may hamper others’ lane-changes. Our model consists of twofold parts; cellular automaton emulating a real traffic flow and evolutionary game theory to implement a driver’s decision making-process. Numerical results reveal that a social dilemma like the multi-player chicken game or prisoner’s dilemma game emerges depending on the traffic phase. This finding implies that a social dilemma, which has been investigated by applied mathematics so far, hides behind a traffic flow, which has been explored by fluid dynamics. Highlight - Complex system of traffic flow with consideration of driver’s decision making process is concerned. - A new model dovetailing cellular automaton with game theory is established. - Statistical result from numerical simulations reveals a social dilemma structure underlying traffic flow. - The social dilemma is triggered by a driver’s egocentric actions of lane-changing and hampering other’s lane-change.

Four-phase or two-phase signal plan? A study on four-leg intersection by cellular automaton simulations

NASA Astrophysics Data System (ADS)

Jin, Cheng-Jie; Wang, Wei; Jiang, Rui

2016-08-01

The proper setting of traffic signals at signalized intersections is one of the most important tasks in traffic control and management. This paper has evaluated the four-phase traffic signal plans at a four-leg intersection via cellular automaton simulations. Each leg consists of three lanes, an exclusive left-turn lane, a through lane, and a through/right-turn lane. For a comparison, we also evaluate the two-phase signal plan. The diagram of the intersection states in the space of inflow rate versus turning ratio has been presented, which exhibits four regions: In region I/II/III, congestion will propagate upstream and laterally and result in queue spillover with both signal plans/two-phase signal plan/four-phase signal plan, respectively. Therefore, neither signal plan works in region I, and only the four-phase signal plan/two-phase signal plan works in region II/III. In region IV, both signal plans work, but two-phase signal plan performs better in terms of average delays of vehicles. Finally, we study the diagram of the intersection states and average delays in the asymmetrical configurations.

A cellular automaton - finite volume method for the simulation of dendritic and eutectic growth in binary alloys using an adaptive mesh refinement

NASA Astrophysics Data System (ADS)

Dobravec, Tadej; Mavrič, Boštjan; Šarler, Božidar

2017-11-01

A two-dimensional model to simulate the dendritic and eutectic growth in binary alloys is developed. A cellular automaton method is adopted to track the movement of the solid-liquid interface. The diffusion equation is solved in the solid and liquid phases by using an explicit finite volume method. The computational domain is divided into square cells that can be hierarchically refined or coarsened using an adaptive mesh based on the quadtree algorithm. Such a mesh refines the regions of the domain near the solid-liquid interface, where the highest concentration gradients are observed. In the regions where the lowest concentration gradients are observed the cells are coarsened. The originality of the work is in the novel, adaptive approach to the efficient and accurate solution of the posed multiscale problem. The model is verified and assessed by comparison with the analytical results of the Lipton-Glicksman-Kurz model for the steady growth of a dendrite tip and the Jackson-Hunt model for regular eutectic growth. Several examples of typical microstructures are simulated and the features of the method as well as further developments are discussed.

Multiscale modeling of porous ceramics using movable cellular automaton method

NASA Astrophysics Data System (ADS)

Smolin, Alexey Yu.; Smolin, Igor Yu.; Smolina, Irina Yu.

2017-10-01

The paper presents a multiscale model for porous ceramics based on movable cellular automaton method, which is a particle method in novel computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the unique position in space. As a result, we get the average values of Young's modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behavior at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via effective properties determined earliar. If the pore size distribution function of the material has N maxima we need to perform computations for N-1 levels in order to get the properties step by step from the lowest scale up to the macroscale. The proposed approach was applied to modeling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behavior of the model sample at the macroscale.

Numerical simulation of biofilm growth in flow channels using a cellular automaton approach coupled with a macro flow computation.

PubMed

Yamamoto, Takehiro; Ueda, Shuya

2013-01-01

Biofilm is a slime-like complex aggregate of microorganisms and their products, extracellular polymer substances, that grows on a solid surface. The growth phenomenon of biofilm is relevant to the corrosion and clogging of water pipes, the chemical processes in a bioreactor, and bioremediation. In these phenomena, the behavior of the biofilm under flow has an important role. Therefore, controlling the biofilm behavior in each process is important. To provide a computational tool for analyzing biofilm growth, the present study proposes a computational model for the simulation of biofilm growth in flows. This model accounts for the growth, decay, detachment and adhesion of biofilms. The proposed model couples the computation of the surrounding fluid flow, using the finite volume method, with the simulation of biofilm growth, using the cellular automaton approach, a relatively low-computational-cost method. Furthermore, a stochastic approach for considering the adhesion process is proposed. Numerical simulations for the biofilm growth on a planar wall and that in an L-shaped rectangular channel were carried out. A variety of biofilm structures were observed depending on the strength of the flow. Moreover, the importance of the detachment and adhesion processes was confirmed.

A new cellular automaton for signal controlled traffic flow based on driving behaviors

NASA Astrophysics Data System (ADS)

Wang, Yang; Chen, Yan-Yan

2015-03-01

The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined. Project supported by the National Basic Research Program of China (Grand No. 2012CB723303) and the Beijing Committee of Science and Technology, China (Grand No. Z1211000003120100).

Microstructure simulation of rapidly solidified ASP30 high-speed steel particles by gas atomization

NASA Astrophysics Data System (ADS)

Ma, Jie; Wang, Bo; Yang, Zhi-liang; Wu, Guang-xin; Zhang, Jie-yu; Zhao, Shun-li

2016-03-01

In this study, the microstructure evolution of rapidly solidified ASP30 high-speed steel particles was predicted using a simulation method based on the cellular automaton-finite element (CAFE) model. The dendritic growth kinetics, in view of the characteristics of ASP30 steel, were calculated and combined with macro heat transfer calculations by user-defined functions (UDFs) to simulate the microstructure of gas-atomized particles. The relationship among particle diameter, undercooling, and the convection heat transfer coefficient was also investigated to provide cooling conditions for simulations. The simulated results indicated that a columnar grain microstructure was observed in small particles, whereas an equiaxed microstructure was observed in large particles. In addition, the morphologies and microstructures of gas-atomized ASP30 steel particles were also investigated experimentally using scanning electron microscopy (SEM). The experimental results showed that four major types of microstructures were formed: dendritic, equiaxed, mixed, and multi-droplet microstructures. The simulated results and the available experimental data are in good agreement.

Conway's "Game of Life" and the Epigenetic Principle.

PubMed

Caballero, Lorena; Hodge, Bob; Hernandez, Sergio

2016-01-01

Cellular automatons and computer simulation games are widely used as heuristic devices in biology, to explore implications and consequences of specific theories. Conway's Game of Life has been widely used for this purpose. This game was designed to explore the evolution of ecological communities. We apply it to other biological processes, including symbiopoiesis. We show that Conway's organization of rules reflects the epigenetic principle, that genetic action and developmental processes are inseparable dimensions of a single biological system, analogous to the integration processes in symbiopoiesis. We look for similarities and differences between two epigenetic models, by Turing and Edelman, as they are realized in Game of Life objects. We show the value of computer simulations to experiment with and propose generalizations of broader scope with novel testable predictions. We use the game to explore issues in symbiopoiesis and evo-devo, where we explore a fractal hypothesis: that self-similarity exists at different levels (cells, organisms, ecological communities) as a result of homologous interactions of two as processes modeled in the Game of Life.

On Patterns in Affective Media

NASA Astrophysics Data System (ADS)

ADAMATZKY, ANDREW

In computational experiments with cellular automaton models of affective solutions, where chemical species represent happiness, anger, fear, confusion and sadness, we study phenomena of space time dynamic of emotions. We demonstrate feasibility of the affective solution paradigm in example of emotional abuse therapy. Results outlined in the present paper offer unconventional but promising technique to design, analyze and interpret spatio-temporal dynamic of mass moods in crowds.

Theory of multicolor lattice gas - A cellular automaton Poisson solver

NASA Technical Reports Server (NTRS)

Chen, H.; Matthaeus, W. H.; Klein, L. W.

1990-01-01

The present class of models for cellular automata involving a quiescent hydrodynamic lattice gas with multiple-valued passive labels termed 'colors', the lattice collisions change individual particle colors while preserving net color. The rigorous proofs of the multicolor lattice gases' essential features are rendered more tractable by an equivalent subparticle representation in which the color is represented by underlying two-state 'spins'. Schemes for the introduction of Dirichlet and Neumann boundary conditions are described, and two illustrative numerical test cases are used to verify the theory. The lattice gas model is equivalent to a Poisson equation solution.

Game of Life on the Equal Degree Random Lattice

NASA Astrophysics Data System (ADS)

Shao, Zhi-Gang; Chen, Tao

2010-12-01

An effective matrix method is performed to build the equal degree random (EDR) lattice, and then a cellular automaton game of life on the EDR lattice is studied by Monte Carlo (MC) simulation. The standard mean field approximation (MFA) is applied, and then the density of live cells is given ρ=0.37017 by MFA, which is consistent with the result ρ=0.37±0.003 by MC simulation.

Multiscale Simulation of Porous Ceramics Based on Movable Cellular Automaton Method

NASA Astrophysics Data System (ADS)

Smolin, A.; Smolin, I.; Eremina, G.; Smolina, I.

2017-10-01

The paper presents a model for simulating mechanical behaviour of multiscale porous ceramics based on movable cellular automaton method, which is a novel particle method in computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the random unique position in space. As a result, we get the average values of Young’s modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behaviour at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via the effective properties determined at the previous scale level. If the pore size distribution function of the material has N maxima we need to perform computations for N - 1 levels in order to get the properties from the lowest scale up to the macroscale step by step. The proposed approach was applied to modelling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behaviour of the model sample at the macroscale.

Simple cellular automaton model for traffic breakdown, highway capacity, and synchronized flow.

PubMed

Kerner, Boris S; Klenov, Sergey L; Schreckenberg, Michael

2011-10-01

We present a simple cellular automaton (CA) model for two-lane roads explaining the physics of traffic breakdown, highway capacity, and synchronized flow. The model consists of the rules "acceleration," "deceleration," "randomization," and "motion" of the Nagel-Schreckenberg CA model as well as "overacceleration through lane changing to the faster lane," "comparison of vehicle gap with the synchronization gap," and "speed adaptation within the synchronization gap" of Kerner's three-phase traffic theory. We show that these few rules of the CA model can appropriately simulate fundamental empirical features of traffic breakdown and highway capacity found in traffic data measured over years in different countries, like characteristics of synchronized flow, the existence of the spontaneous and induced breakdowns at the same bottleneck, and associated probabilistic features of traffic breakdown and highway capacity. Single-vehicle data derived in model simulations show that synchronized flow first occurs and then self-maintains due to a spatiotemporal competition between speed adaptation to a slower speed of the preceding vehicle and passing of this slower vehicle. We find that the application of simple dependences of randomization probability and synchronization gap on driving situation allows us to explain the physics of moving synchronized flow patterns and the pinch effect in synchronized flow as observed in real traffic data.

Effect of psychological tension on pedestrian counter flow via an extended cost potential field cellular automaton model

NASA Astrophysics Data System (ADS)

Li, Xingli; Guo, Fang; Kuang, Hua; Zhou, Huaguo

2017-12-01

Psychology tells us that the different level of tension may lead to different behavior variation for individuals. In this paper, an extended cost potential field cellular automaton is proposed to simulate pedestrian counter flow under an emergency by considering behavior variation of pedestrian induced by psychological tension. A quantitative formula is introduced to describe behavioral changes caused by psychological tension, which also leads to the increasing cost of discomfort. The numerical simulations are performed under the periodic boundary condition and show that the presented model can capture some essential features of pedestrian counter flow, such as lane formation and segregation phenomenon for normal condition. Furthermore, an interesting feature is found that when pedestrians are in an extremely nervous state, a stable lane formation will be broken by a disordered mixture flow. The psychological nervousness under an emergency is not always negative to moving efficiency and a moderate level of tension will delay the occurrence of jamming phase. In addition, a larger asymmetrical ratio of left walkers to right walkers will improve the critical density related to the jamming phase and retard the occurrence of completely jammed phase. These findings will be helpful in pedestrian control and management under an emergency.

On the effect of quantum noise in a quantum prisoner's dilemma cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón

2017-06-01

The disrupting effect of quantum noise on the dynamics of a spatial quantum formulation of the iterated prisoner's dilemma game with variable entangling is studied in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. It is concluded in this article that quantum noise induces in fair games the need for higher entanglement in order to make possible the emergence of the strategy pair ( Q, Q), which produces the same payoff of mutual cooperation. In unfair quantum versus classic player games, quantum noise delays the prevalence of the quantum player.

Uniform and Multi-Grid Modeling of Acoustic Wave Propagation With Cellular Automaton Techniques

DTIC Science & Technology

2013-03-01

39 Figure 26. CurrvedHillIndices fuction used to created a curved hill in the bottom...to safe passage of a submarine. Driving factors influencing SONAR improvements have alluded to the fact that primary naval missions have shifted from...CurvedHillIndices function after reaching line 12 42 Figure 26. CurrvedHillIndices fuction used to created a curved hill in the bottom of any 2D or

Computational complexity of symbolic dynamics at the onset of chaos

NASA Astrophysics Data System (ADS)

Lakdawala, Porus

1996-05-01

In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behavior of cellular automata, that the computational basis for modeling this region is the universal Turing machine. In this paper, following a suggestion of Crutchfield, we try to show that the Turing machine model may often be too powerful as a computational model to describe the boundary of order and chaos. In particular we study the region of the first accumulation of period doubling in unimodal and bimodal maps of the interval, from the point of view of language theory. We show that in relation to the ``extended'' Chomsky hierarchy, the relevant computational model in the unimodal case is the nested stack automaton or the related indexed languages, while the bimodal case is modeled by the linear bounded automaton or the related context-sensitive languages.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM.

PubMed

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2015-07-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM

PubMed Central

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2016-01-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location. PMID:27789918

Potential field cellular automata model for pedestrian flow

NASA Astrophysics Data System (ADS)

Zhang, Peng; Jian, Xiao-Xia; Wong, S. C.; Choi, Keechoo

2012-02-01

This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.

Quantum Locality, Rings a Bell?: Bell's Inequality Meets Local Reality and True Determinism

NASA Astrophysics Data System (ADS)

Sánchez-Kuntz, Natalia; Nahmad-Achar, Eduardo

2018-01-01

By assuming a deterministic evolution of quantum systems and taking realism into account, we carefully build a hidden variable theory for Quantum Mechanics (QM) based on the notion of ontological states proposed by 't Hooft (The cellular automaton interpretation of quantum mechanics, arXiv:1405.1548v3, 2015; Springer Open 185, https://doi.org/10.1007/978-3-319-41285-6, 2016). We view these ontological states as the ones embedded with realism and compare them to the (usual) quantum states that represent superpositions, viewing the latter as mere information of the system they describe. Such a deterministic model puts forward conditions for the applicability of Bell's inequality: the usual inequality cannot be applied to the usual experiments. We build a Bell-like inequality that can be applied to the EPR scenario and show that this inequality is always satisfied by QM. In this way we show that QM can indeed have a local interpretation, and thus meet with the causal structure imposed by the Theory of Special Relativity in a satisfying way.

Material Implementation of Hyperincursive Field on Slime Mold Computer

NASA Astrophysics Data System (ADS)

Aono, Masashi; Gunji, Yukio-Pegio

2004-08-01

"Elementary Conflictable Cellular Automaton (ECCA)" was introduced by Aono and Gunji as a problematic computational syntax embracing the non-deterministic/non-algorithmic property due to its hyperincursivity and nonlocality. Although ECCA's hyperincursive evolution equation indicates the occurrence of the deadlock/infinite-loop, we do not consider that this problem declares the fundamental impossibility of implementing ECCA materially. Dubois proposed to call a computing system where uncertainty/contradiction occurs "the hyperincursive field". In this paper we introduce a material implementation of the hyperincursive field by using plasmodia of the true slime mold Physarum polycephalum. The amoeboid organism is adopted as a computing media of ECCA slime mold computer (ECCA-SMC) mainly because; it is a parallel non-distributed system whose locally branched tips (components) can act in parallel with asynchronism and nonlocal correlation. A notable characteristic of ECCA-SMC is that a cell representing a spatio-temporal segment of computation is occupied (overlapped) redundantly by multiple spatially adjacent computing operations and by temporally successive computing events. The overlapped time representation may contribute to the progression of discussions on unconventional notions of the time.

Conway's “Game of Life” and the Epigenetic Principle

PubMed Central

Caballero, Lorena; Hodge, Bob; Hernandez, Sergio

2016-01-01

Cellular automatons and computer simulation games are widely used as heuristic devices in biology, to explore implications and consequences of specific theories. Conway's Game of Life has been widely used for this purpose. This game was designed to explore the evolution of ecological communities. We apply it to other biological processes, including symbiopoiesis. We show that Conway's organization of rules reflects the epigenetic principle, that genetic action and developmental processes are inseparable dimensions of a single biological system, analogous to the integration processes in symbiopoiesis. We look for similarities and differences between two epigenetic models, by Turing and Edelman, as they are realized in Game of Life objects. We show the value of computer simulations to experiment with and propose generalizations of broader scope with novel testable predictions. We use the game to explore issues in symbiopoiesis and evo-devo, where we explore a fractal hypothesis: that self-similarity exists at different levels (cells, organisms, ecological communities) as a result of homologous interactions of two as processes modeled in the Game of Life PMID:27379213

Pitting corrosion as a mixed system: coupled deterministic-probabilistic simulation of pit growth

NASA Astrophysics Data System (ADS)

Ibrahim, Israr B. M.; Fonna, S.; Pidaparti, R.

2018-05-01

Stochastic behavior of pitting corrosion poses a unique challenge in its computational analysis. However, it also stems from electrochemical activity causing general corrosion. In this paper, a framework for corrosion pit growth simulation based on the coupling of the Cellular Automaton (CA) and Boundary Element Methods (BEM) is presented. The framework assumes that pitting corrosion is controlled by electrochemical activity inside the pit cavity. The BEM provides the prediction of electrochemical activity given the geometrical data and polarization curves, while the CA is used to simulate the evolution of pit shapes based on electrochemical activity provided by BEM. To demonstrate the methodology, a sample case of local corrosion cells formed in pitting corrosion with varied dimensions and polarization functions is considered. Results show certain shapes tend to grow in certain types of environments. Some pit shapes appear to pose a higher risk by being potentially significant stress raisers or potentially increasing the rate of corrosion under the surface. Furthermore, these pits are comparable to commonly observed pit shapes in general corrosion environments.

Dynamics of traffic flow with real-time traffic information

NASA Astrophysics Data System (ADS)

Yokoya, Yasushi

2004-01-01

We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.

Lattice Boltzmann model for simulation of magnetohydrodynamics

NASA Technical Reports Server (NTRS)

Chen, Shiyi; Chen, Hudong; Martinez, Daniel; Matthaeus, William

1991-01-01

A numerical method, based on a discrete Boltzmann equation, is presented for solving the equations of magnetohydrodynamics (MHD). The algorithm provides advantages similar to the cellular automaton method in that it is local and easily adapted to parallel computing environments. Because of much lower noise levels and less stringent requirements on lattice size, the method appears to be more competitive with traditional solution methods. Examples show that the model accurately reproduces both linear and nonlinear MHD phenomena.

Using economy of means to evolve transition rules within 2D cellular automata.

PubMed

Ripps, David L

2010-01-01

Running a cellular automaton (CA) on a rectangular lattice is a time-honored method for studying artificial life on a digital computer. Commonly, the researcher wishes to investigate some specific or general mode of behavior, say, the ability of a coherent pattern of points to glide within the lattice, or to generate copies of itself. This technique has a problem: how to design the transitions table-the set of distinct rules that specify the next content of a cell from its current content and that of its near neighbors. Often the table is painstakingly designed manually, rule by rule. The problem is exacerbated by the potentially vast number of individual rules that need be specified to cover all combinations of center and neighbors when there are several symbols in the alphabet of the CA. In this article a method is presented to have the set of rules evolve automatically while running the CA. The transition table is initially empty, with rules being added as the need arises. A novel principle drives the evolution: maximum economy of means-maximizing the reuse of rules introduced on previous cycles. This method may not be a panacea applicable to all CA studies. Nevertheless, it is sufficiently potent to evolve sets of rules and associated patterns of points that glide (periodically regenerate themselves at another location) and to generate gliding "children" that then "mate" by collision.

Marine traffic model based on cellular automaton: Considering the change of the ship's velocity under the influence of the weather and sea

NASA Astrophysics Data System (ADS)

Qi, Le; Zheng, Zhongyi; Gang, Longhui

2017-10-01

It was found that the ships' velocity change, which is impacted by the weather and sea, e.g., wind, sea wave, sea current, tide, etc., is significant and must be considered in the marine traffic model. Therefore, a new marine traffic model based on cellular automaton (CA) was proposed in this paper. The characteristics of the ship's velocity change are taken into account in the model. First, the acceleration of a ship was divided into two components: regular component and random component. Second, the mathematical functions and statistical distribution parameters of the two components were confirmed by spectral analysis, curve fitting and auto-correlation analysis methods. Third, by combining the two components, the acceleration was regenerated in the update rules for ships' movement. To test the performance of the model, the ship traffic flows in the Dover Strait, the Changshan Channel and the Qiongzhou Strait were studied and simulated. The results show that the characteristics of ships' velocities in the simulations are consistent with the measured data by Automatic Identification System (AIS). Although the characteristics of the traffic flow in different areas are different, the velocities of ships can be simulated correctly. It proves that the velocities of ships under the influence of weather and sea can be simulated successfully using the proposed model.

Investigation of primary static recrystallization in a NiTiFe shape memory alloy subjected to cold canning compression using the coupling crystal plasticity finite element method with cellular automaton

NASA Astrophysics Data System (ADS)

Zhang, Yanqiu; Jiang, Shuyong; Hu, Li; Zhao, Yanan; Sun, Dong

2017-10-01

The behavior of primary static recrystallization (SRX) in a NiTiFe shape memory alloy (SMA) subjected to cold canning compression was investigated using the coupling crystal plasticity finite element method (CPFEM) with the cellular automaton (CA) method, where the distribution of the dislocation density and the deformed grain topology quantified by CPFEM were used as the input for the subsequent SRX simulation performed using the CA method. The simulation results were confirmed by the experimental ones in terms of microstructures, average grain size and recrystallization fraction, which indicates that the proposed coupling method is well able to describe the SRX behavior of the NiTiFe SMA. The results show that the dislocation density exhibits an inhomogeneous distribution in the deformed sample and the recrystallization nuclei mainly concentrate on zones where the dislocation density is relatively higher. An increase in the compressive deformation degree leads to an increase in nucleation rate and a decrease in grain boundary spaces in the compression direction, which reduces the growth spaces for the SRX nuclei and impedes their further growth. In addition, both the mechanisms of local grain refinement in the incomplete SRX and the influence of compressive deformation degree on the grain size of SRX were vividly illustrated by the corresponding physical models.

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

PubMed

Feng, Yongjiu; Tong, Xiaohua

2017-09-22

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.

Simple cellular automaton model for traffic breakdown, highway capacity, and synchronized flow

NASA Astrophysics Data System (ADS)

Kerner, Boris S.; Klenov, Sergey L.; Schreckenberg, Michael

2011-10-01

We present a simple cellular automaton (CA) model for two-lane roads explaining the physics of traffic breakdown, highway capacity, and synchronized flow. The model consists of the rules “acceleration,” “deceleration,” “randomization,” and “motion” of the Nagel-Schreckenberg CA model as well as “overacceleration through lane changing to the faster lane,” “comparison of vehicle gap with the synchronization gap,” and “speed adaptation within the synchronization gap” of Kerner's three-phase traffic theory. We show that these few rules of the CA model can appropriately simulate fundamental empirical features of traffic breakdown and highway capacity found in traffic data measured over years in different countries, like characteristics of synchronized flow, the existence of the spontaneous and induced breakdowns at the same bottleneck, and associated probabilistic features of traffic breakdown and highway capacity. Single-vehicle data derived in model simulations show that synchronized flow first occurs and then self-maintains due to a spatiotemporal competition between speed adaptation to a slower speed of the preceding vehicle and passing of this slower vehicle. We find that the application of simple dependences of randomization probability and synchronization gap on driving situation allows us to explain the physics of moving synchronized flow patterns and the pinch effect in synchronized flow as observed in real traffic data.

A refined and dynamic cellular automaton model for pedestrian-vehicle mixed traffic flow

NASA Astrophysics Data System (ADS)

Liu, Mianfang; Xiong, Shengwu

2016-12-01

Mixed traffic flow sharing the “same lane” and having no discipline on road is a common phenomenon in the developing countries. For example, motorized vehicles (m-vehicles) and nonmotorized vehicles (nm-vehicles) may share the m-vehicle lane or nm-vehicle lane and pedestrians may share the nm-vehicle lane. Simulating pedestrian-vehicle mixed traffic flow consisting of three kinds of traffic objects: m-vehicles, nm-vehicles and pedestrians, can be a challenge because there are some erratic drivers or pedestrians who fail to follow the lane disciplines. In the paper, we investigate various moving and interactive behavior associated with mixed traffic flow, such as lateral drift including illegal lane-changing and transverse crossing different lanes, overtaking and forward movement, and propose some new moving and interactive rules for pedestrian-vehicle mixed traffic flow based on a refined and dynamic cellular automaton (CA) model. Simulation results indicate that the proposed model can be used to investigate the traffic flow characteristic in a mixed traffic flow system and corresponding complicated traffic problems, such as, the moving characteristics of different traffic objects, interaction phenomenon between different traffic objects, traffic jam, traffic conflict, etc., which are consistent with the actual mixed traffic system. Therefore, the proposed model provides a solid foundation for the management, planning and evacuation of the mixed traffic flow.

Collective dynamics in heterogeneous networks of neuronal cellular automata

NASA Astrophysics Data System (ADS)

Manchanda, Kaustubh; Bose, Amitabha; Ramaswamy, Ramakrishna

2017-12-01

We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r - b - 1 refractory states, and can show 'spiking' or 'bursting' behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs-Rényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent.

A 3D Cellular Automaton for Cell Differentiation in a Solid Tumor with Plasticity

NASA Astrophysics Data System (ADS)

Margarit, David H.; Romanelli, Lilia; Fendrik, Alejandro J.

A model with spherical symmetry is proposed. We analyze the appropriate parameters of cell differentiation for different kinds of cells (Cancer Stem Cells (CSC) and Differentiated Cells (DC)). The plasticity (capacity to return from a DC to its previous state of CSC) is taken into account. Following this hypothesis, the dissemination of CSCs to another organ is analyzed. The location of the cells in the tumor and the plasticity range for possible metastasis is discussed.

Larger than Life's Extremes: Rigorous Results for Simplified Rules and Speculation on the Phase Boundaries

NASA Astrophysics Data System (ADS)

Evans, Kellie Michele

Larger than Life (LtL), is a four-parameter family of two-dimensional cellular automata that generalizes John Conway's Game of Life (Life) to large neighborhoods and general birth and survival thresholds. LtL was proposed by David Griffeath in the early 1990s to explore whether Life might be a clue to a critical phase point in the threshold-range scaling limit. The LtL family of rules includes Life as well as a rich set of two-dimensional rules, some of which exhibit dynamics vastly different from Life. In this chapter we present rigorous results and conjectures about the ergodic classifications of several sets of "simplified" LtL rules, each of which has a property that makes the rule easier to analyze. For example, these include symmetric rules such as the threshold voter automaton and the anti-voter automaton, monotone rules such as the threshold growth models, and others. We also provide qualitative results and speculation about LtL rules on various phase boundaries and summarize results and open questions about our favorite "Life-like" LtL rules.

A novel method of multi-scale simulation of macro-scale deformation and microstructure evolution on metal forming

NASA Astrophysics Data System (ADS)

Huang, Shiquan; Yi, Youping; Li, Pengchuan

2011-05-01

In recent years, multi-scale simulation technique of metal forming is gaining significant attention for prediction of the whole deformation process and microstructure evolution of product. The advances of numerical simulation at macro-scale level on metal forming are remarkable and the commercial FEM software, such as Deform2D/3D, has found a wide application in the fields of metal forming. However, the simulation method of multi-scale has little application due to the non-linearity of microstructure evolution during forming and the difficulty of modeling at the micro-scale level. This work deals with the modeling of microstructure evolution and a new method of multi-scale simulation in forging process. The aviation material 7050 aluminum alloy has been used as example for modeling of microstructure evolution. The corresponding thermal simulated experiment has been performed on Gleeble 1500 machine. The tested specimens have been analyzed for modeling of dislocation density, nucleation and growth of recrystallization(DRX). The source program using cellular automaton (CA) method has been developed to simulate the grain nucleation and growth, in which the change of grain topology structure caused by the metal deformation was considered. The physical fields at macro-scale level such as temperature field, stress and strain fields, which can be obtained by commercial software Deform 3D, are coupled with the deformed storage energy at micro-scale level by dislocation model to realize the multi-scale simulation. This method was explained by forging process simulation of the aircraft wheel hub forging. Coupled the results of Deform 3D with CA results, the forging deformation progress and the microstructure evolution at any point of forging could be simulated. For verifying the efficiency of simulation, experiments of aircraft wheel hub forging have been done in the laboratory and the comparison of simulation and experiment result has been discussed in details.

A self-organized criticality model for ion temperature gradient mode driven turbulence in confined plasma

NASA Astrophysics Data System (ADS)

Isliker, H.; Pisokas, Th.; Strintzi, D.; Vlahos, L.

2010-08-01

A new self-organized criticality (SOC) model is introduced in the form of a cellular automaton (CA) for ion temperature gradient (ITG) mode driven turbulence in fusion plasmas. Main characteristics of the model are that it is constructed in terms of the actual physical variable, the ion temperature, and that the temporal evolution of the CA, which necessarily is in the form of rules, mimics actual physical processes as they are considered to be active in the system, i.e., a heating process and a local diffusive process that sets on if a threshold in the normalized ITG R /LT is exceeded. The model reaches the SOC state and yields ion temperature profiles of exponential shape, which exhibit very high stiffness, in that they basically are independent of the loading pattern applied. This implies that there is anomalous heat transport present in the system, despite the fact that diffusion at the local level is imposed to be of a normal kind. The distributions of the heat fluxes in the system and of the heat out-fluxes are of power-law shape. The basic properties of the model are in good qualitative agreement with experimental results.

Application of a simple power law for transport ratio with bimodal distributions of spherical grains under oscillatory forcing

NASA Astrophysics Data System (ADS)

Holway, Kevin; Thaxton, Christopher S.; Calantoni, Joseph

2012-11-01

Morphodynamic models of coastal evolution require relatively simple parameterizations of sediment transport for application over larger scales. Calantoni and Thaxton (2008) [6] presented a transport parameterization for bimodal distributions of coarse quartz grains derived from detailed boundary layer simulations for sheet flow and near sheet flow conditions. The simulation results, valid over a range of wave forcing conditions and large- to small-grain diameter ratios, were successfully parameterized with a simple power law that allows for the prediction of the transport rates of each size fraction. Here, we have applied the simple power law to a two-dimensional cellular automaton to simulate sheet flow transport. Model results are validated with experiments performed in the small oscillating flow tunnel (S-OFT) at the Naval Research Laboratory at Stennis Space Center, MS, in which sheet flow transport was generated with a bed composed of a bimodal distribution of non-cohesive grains. The work presented suggests that, under the conditions specified, algorithms that incorporate the power law may correctly reproduce laboratory bed surface measurements of bimodal sheet flow transport while inherently incorporating vertical mixing by size.

Gaussian Mean Field Lattice Gas

NASA Astrophysics Data System (ADS)

Scoppola, Benedetto; Troiani, Alessio

2018-03-01

We study rigorously a lattice gas version of the Sherrington-Kirckpatrick spin glass model. In discrete optimization literature this problem is known as unconstrained binary quadratic programming and it belongs to the class NP-hard. We prove that the fluctuations of the ground state energy tend to vanish in the thermodynamic limit, and we give a lower bound of such ground state energy. Then we present a heuristic algorithm, based on a probabilistic cellular automaton, which seems to be able to find configurations with energy very close to the minimum, even for quite large instances.

The Finite-Size Scaling Relation for the Order-Parameter Probability Distribution of the Six-Dimensional Ising Model

NASA Astrophysics Data System (ADS)

Merdan, Ziya; Karakuş, Özlem

2016-11-01

The six dimensional Ising model with nearest-neighbor pair interactions has been simulated and verified numerically on the Creutz Cellular Automaton by using five bit demons near the infinite-lattice critical temperature with the linear dimensions L=4,6,8,10. The order parameter probability distribution for six dimensional Ising model has been calculated at the critical temperature. The constants of the analytical function have been estimated by fitting to probability function obtained numerically at the finite size critical point.

Evidence of Nanoflare Heating in Coronal Loops Observed with Hinolde-XRT and SDO-AIA

NASA Technical Reports Server (NTRS)

Lopez-Fuentes, M. C.; Klimchuk, James

2013-01-01

We study a series of coronal loop lightcurves from X-ray and EUV observations. In search for signatures of nanoflare heating, we analyze the statistical properties of the observed lightcurves and compare them with synthetic cases obtained with a 2D cellular-automaton model based on nanoflare heating driven by photospheric motions. Our analysis shows that the observed and the model lightcurves have similar statistical properties. The asymmetries observed in the distribution of the intensity fluctuations indicate the possible presence of widespread cooling processes in sub-resolution magnetic strands.

Computer-aided study of key factors determining high mechanical properties of nanostructured surface layers in metal-ceramic composites

NASA Astrophysics Data System (ADS)

Konovalenko, Igor S.; Shilko, Evgeny V.; Ovcharenko, Vladimir E.; Psakhie, Sergey G.

2017-12-01

The paper presents the movable cellular automaton method. It is based on numerical models of surface layers of the metal-ceramic composite NiCr-TiC modified under electron beam irradiation in inert gas plasmas. The models take into account different geometric, concentration and mechanical parameters of ceramic and metallic components. The authors study the contributions of key structural factors in mechanical properties of surface layers and determine the ranges of their variations by providing the optimum balance of strength, strain hardening and fracture toughness.

The discrete Toda equation revisited: dual β-Grothendieck polynomials, ultradiscretization, and static solitons

NASA Astrophysics Data System (ADS)

Iwao, Shinsuke; Nagai, Hidetomo

2018-04-01

This paper presents a study of the discrete Toda equation that was introduced in 1977. In this paper, it is proved that the determinantal solution of the discrete Toda equation, obtained via the Lax formalism, is naturally related to the dual Grothendieck polynomials, a K-theoretic generalization of the Schur polynomials. A tropical permanent solution to the ultradiscrete Toda equation is also derived. The proposed method gives a tropical algebraic representation of the static solitons. Lastly, a new cellular automaton realization of the ultradiscrete Toda equation is proposed.

The MATCHIT Automaton: Exploiting Compartmentalization for the Synthesis of Branched Polymers

PubMed Central

Weyland, Mathias S.; Fellermann, Harold; Hadorn, Maik; Sorek, Daniel; Lancet, Doron; Rasmussen, Steen; Füchslin, Rudolf M.

2013-01-01

We propose an automaton, a theoretical framework that demonstrates how to improve the yield of the synthesis of branched chemical polymer reactions. This is achieved by separating substeps of the path of synthesis into compartments. We use chemical containers (chemtainers) to carry the substances through a sequence of fixed successive compartments. We describe the automaton in mathematical terms and show how it can be configured automatically in order to synthesize a given branched polymer target. The algorithm we present finds an optimal path of synthesis in linear time. We discuss how the automaton models compartmentalized structures found in cells, such as the endoplasmic reticulum and the Golgi apparatus, and we show how this compartmentalization can be exploited for the synthesis of branched polymers such as oligosaccharides. Lastly, we show examples of artificial branched polymers and discuss how the automaton can be configured to synthesize them with maximal yield. PMID:24489601

Ocean acidification affects competition for space: projections of community structure using cellular automata.

PubMed

McCoy, Sophie J; Allesina, Stefano; Pfister, Catherine A

2016-03-16

Historical ecological datasets from a coastal marine community of crustose coralline algae (CCA) enabled the documentation of ecological changes in this community over 30 years in the Northeast Pacific. Data on competitive interactions obtained from field surveys showed concordance between the 1980s and 2013, yet also revealed a reduction in how strongly species interact. Here, we extend these empirical findings with a cellular automaton model to forecast ecological dynamics. Our model suggests the emergence of a new dominant competitor in a global change scenario, with a reduced role of herbivory pressure, or trophic control, in regulating competition among CCA. Ocean acidification, due to its energetic demands, may now instead play this role in mediating competitive interactions and thereby promote species diversity within this guild. © 2016 The Author(s).

THE SPATIO-TEMPORAL EVOLUTION OF SOLAR FLARES OBSERVED WITH AIA/SDO: FRACTAL DIFFUSION, SUB-DIFFUSION, OR LOGISTIC GROWTH?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aschwanden, Markus J., E-mail: aschwanden@lmsal.com

2012-09-20

We explore the spatio-temporal evolution of solar flares by fitting a radial expansion model r(t) that consists of an exponentially growing acceleration phase, followed by a deceleration phase that is parameterized by the generalized diffusion function r(t){proportional_to}{kappa}(t - t{sub 1}){sup {beta}/2}, which includes the logistic growth limit ({beta} = 0), sub-diffusion ({beta} = 0-1), classical diffusion ({beta} = 1), super-diffusion ({beta} = 1-2), and the linear expansion limit ({beta} = 2). We analyze all M- and X-class flares observed with Geostationary Operational Environmental Satellite and Atmospheric Imaging Assembly/Solar Dynamics Observatory (SDO) during the first two years of the SDO mission,more » amounting to 155 events. We find that most flares operate in the sub-diffusive regime ({beta} = 0.53 {+-} 0.27), which we interpret in terms of anisotropic chain reactions of intermittent magnetic reconnection episodes in a low plasma-{beta} corona. We find a mean propagation speed of v = 15 {+-} 12 km s{sup -1}, with maximum speeds of v{sub max} = 80 {+-} 85 km s{sup -1} per flare, which is substantially slower than the sonic speeds expected for thermal diffusion of flare plasmas. The diffusive characteristics established here (for the first time for solar flares) is consistent with the fractal-diffusive self-organized criticality model, which predicted diffusive transport merely based on cellular automaton simulations.« less

A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area

USGS Publications Warehouse

Clarke, K.C.; Hoppen, S.; Gaydos, L.

1997-01-01

In this paper we describe a cellular automaton (CA) simulation model developed to predict urban growth as part of a project for estimating the regional and broader impact of urbanization on the San Francisco Bay area's climate. The rules of the model are more complex than those of a typical CA and involve the use of multiple data sources, including topography, road networks, and existing settlement distributions, and their modification over time. In addition, the control parameters of the model are allowed to self-modify: that is, the CA adapts itself to the circumstances it generates, in particular, during periods of rapid growth or stagnation. In addition, the model was written to allow the accumulation of probabilistic estimates based on Monte Carlo methods. Calibration of the model has been accomplished by the use of historical maps to compare model predictions of urbanization, based solely upon the distribution in year 1900, with observed data for years 1940, 1954, 1962, 1974, and 1990. The complexity of this model has made calibration a particularly demanding step. Lessons learned about the methods, measures, and strategies developed to calibrate the model may be of use in other environmental modeling contexts. With the calibration complete, the model is being used to generate a set of future scenarios for the San Francisco Bay area along with their probabilities based on the Monte Carlo version of the model. Animated dynamic mapping of the simulations will be used to allow visualization of the impact of future urban growth.

Emergent Behaviors from a Cellular Automaton Model for Invasive Tumor Growth in Heterogeneous Microenvironments

PubMed Central

Jiao, Yang; Torquato, Salvatore

2011-01-01

Understanding tumor invasion and metastasis is of crucial importance for both fundamental cancer research and clinical practice. In vitro experiments have established that the invasive growth of malignant tumors is characterized by the dendritic invasive branches composed of chains of tumor cells emanating from the primary tumor mass. The preponderance of previous tumor simulations focused on non-invasive (or proliferative) growth. The formation of the invasive cell chains and their interactions with the primary tumor mass and host microenvironment are not well understood. Here, we present a novel cellular automaton (CA) model that enables one to efficiently simulate invasive tumor growth in a heterogeneous host microenvironment. By taking into account a variety of microscopic-scale tumor-host interactions, including the short-range mechanical interactions between tumor cells and tumor stroma, degradation of the extracellular matrix by the invasive cells and oxygen/nutrient gradient driven cell motions, our CA model predicts a rich spectrum of growth dynamics and emergent behaviors of invasive tumors. Besides robustly reproducing the salient features of dendritic invasive growth, such as least-resistance paths of cells and intrabranch homotype attraction, we also predict nontrivial coupling between the growth dynamics of the primary tumor mass and the invasive cells. In addition, we show that the properties of the host microenvironment can significantly affect tumor morphology and growth dynamics, emphasizing the importance of understanding the tumor-host interaction. The capability of our CA model suggests that sophisticated in silico tools could eventually be utilized in clinical situations to predict neoplastic progression and propose individualized optimal treatment strategies. PMID:22215996

Symbolic Dynamics and Grammatical Complexity

NASA Astrophysics Data System (ADS)

Hao, Bai-Lin; Zheng, Wei-Mou

The following sections are included: * Formal Languages and Their Complexity * Formal Language * Chomsky Hierarchy of Grammatical Complexity * The L-System * Regular Language and Finite Automaton * Finite Automaton * Regular Language * Stefan Matrix as Transfer Function for Automaton * Beyond Regular Languages * Feigenbaum and Generalized Feigenbaum Limiting Sets * Even and Odd Fibonacci Sequences * Odd Maximal Primitive Prefixes and Kneading Map * Even Maximal Primitive Prefixes and Distinct Excluded Blocks * Summary of Results

Cellular automata models for diffusion of information and highway traffic flow

NASA Astrophysics Data System (ADS)

Fuks, Henryk

In the first part of this work we study a family of deterministic models for highway traffic flow which generalize cellular automaton rule 184. This family is parameterized by the speed limit m and another parameter k that represents degree of 'anticipatory driving'. We compare two driving strategies with identical maximum throughput: 'conservative' driving with high speed limit and 'anticipatory' driving with low speed limit. Those two strategies are evaluated in terms of accident probability. We also discuss fundamental diagrams of generalized traffic rules and examine limitations of maximum achievable throughput. Possible modifications of the model are considered. For rule 184, we present exact calculations of the order parameter in a transition from the moving phase to the jammed phase using the method of preimage counting, and use this result to construct a solution to the density classification problem. In the second part we propose a probabilistic cellular automaton model for the spread of innovations, rumors, news, etc., in a social system. We start from simple deterministic models, for which exact expressions for the density of adopters are derived. For a more realistic model, based on probabilistic cellular automata, we study the influence of a range of interaction R on the shape of the adoption curve. When the probability of adoption is proportional to the local density of adopters, and individuals can drop the innovation with some probability p, the system exhibits a second order phase transition. Critical line separating regions of parameter space in which asymptotic density of adopters is positive from the region where it is equal to zero converges toward the mean-field line when the range of the interaction increases. In a region between R=1 critical line and the mean-field line asymptotic density of adopters depends on R, becoming zero if R is too small (smaller than some critical value). This result demonstrates the importance of connectivity in diffusion of information. We also define a new class of automata networks which incorporates non-local interactions, and discuss its applicability in modeling of diffusion of innovations.

Emerging properties of financial time series in the ``Game of Life''

NASA Astrophysics Data System (ADS)

Hernández-Montoya, A. R.; Coronel-Brizio, H. F.; Stevens-Ramírez, G. A.; Rodríguez-Achach, M.; Politi, M.; Scalas, E.

2011-12-01

We explore the spatial complexity of Conway’s “Game of Life,” a prototypical cellular automaton by means of a geometrical procedure generating a two-dimensional random walk from a bidimensional lattice with periodical boundaries. The one-dimensional projection of this process is analyzed and it turns out that some of its statistical properties resemble the so-called stylized facts observed in financial time series. The scope and meaning of this result are discussed from the viewpoint of complex systems. In particular, we stress how the supposed peculiarities of financial time series are, often, overrated in their importance.

Cellular automaton supercomputing

NASA Technical Reports Server (NTRS)

Wolfram, Stephen

1987-01-01

Many of the models now used in science and engineering are over a century old. And most of them can be implemented on modern digital computers only with considerable difficulty. Some new basic models are discussed which are much more directly suitable for digital computer simulation. The fundamental principle is that the models considered herein are as suitable as possible for implementation on digital computers. It is then a matter of scientific analysis to determine whether such models can reproduce the behavior seen in physical and other systems. Such analysis was carried out in several cases, and the results are very encouraging.

Multi-layer composite mechanical modeling for the inhomogeneous biofilm mechanical behavior.

PubMed

Wang, Xiaoling; Han, Jingshi; Li, Kui; Wang, Guoqing; Hao, Mudong

2016-08-01

Experiments showed that bacterial biofilms are heterogeneous, for example, the density, the diffusion coefficient, and mechanical properties of the biofilm are different along the biofilm thickness. In this paper, we establish a multi-layer composite model to describe the biofilm mechanical inhomogeneity based on unified multiple-component cellular automaton (UMCCA) model. By using our model, we develop finite element simulation procedure for biofilm tension experiment. The failure limit and biofilm extension displacement obtained from our model agree well with experimental measurements. This method provides an alternative theory to study the mechanical inhomogeneity in biological materials.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Information Feedback Strategies in a Signal Controlled Network with Overlapped Routes

NASA Astrophysics Data System (ADS)

Tian, Li-Jun; Huang, Hai-Jun; Liu, Tian-Liang

2009-07-01

We investigate the effects of four different information feedback strategies on the dynamics of traffic, travelers' route choice and the resultant system performance in a signal controlled network with overlapped routes. Simulation results given by the cellular automaton model show that the system purpose-based mean velocity feedback strategy and the congestion coefficient feedback strategy have more advantages in improving network utilization efficiency and reducing travelers' travel times. The travel time feedback strategy and the individual purposed-based mean velocity feedback strategy behave slightly better to ensure user equity.

Emerging properties of financial time series in the "Game of Life".

PubMed

Hernández-Montoya, A R; Coronel-Brizio, H F; Stevens-Ramírez, G A; Rodríguez-Achach, M; Politi, M; Scalas, E

2011-12-01

We explore the spatial complexity of Conway's "Game of Life," a prototypical cellular automaton by means of a geometrical procedure generating a two-dimensional random walk from a bidimensional lattice with periodical boundaries. The one-dimensional projection of this process is analyzed and it turns out that some of its statistical properties resemble the so-called stylized facts observed in financial time series. The scope and meaning of this result are discussed from the viewpoint of complex systems. In particular, we stress how the supposed peculiarities of financial time series are, often, overrated in their importance.

Large-scale parallel lattice Boltzmann-cellular automaton model of two-dimensional dendritic growth

NASA Astrophysics Data System (ADS)

Jelinek, Bohumir; Eshraghi, Mohsen; Felicelli, Sergio; Peters, John F.

2014-03-01

An extremely scalable lattice Boltzmann (LB)-cellular automaton (CA) model for simulations of two-dimensional (2D) dendritic solidification under forced convection is presented. The model incorporates effects of phase change, solute diffusion, melt convection, and heat transport. The LB model represents the diffusion, convection, and heat transfer phenomena. The dendrite growth is driven by a difference between actual and equilibrium liquid composition at the solid-liquid interface. The CA technique is deployed to track the new interface cells. The computer program was parallelized using the Message Passing Interface (MPI) technique. Parallel scaling of the algorithm was studied and major scalability bottlenecks were identified. Efficiency loss attributable to the high memory bandwidth requirement of the algorithm was observed when using multiple cores per processor. Parallel writing of the output variables of interest was implemented in the binary Hierarchical Data Format 5 (HDF5) to improve the output performance, and to simplify visualization. Calculations were carried out in single precision arithmetic without significant loss in accuracy, resulting in 50% reduction of memory and computational time requirements. The presented solidification model shows a very good scalability up to centimeter size domains, including more than ten million of dendrites. Catalogue identifier: AEQZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEQZ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, UK Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 29,767 No. of bytes in distributed program, including test data, etc.: 3131,367 Distribution format: tar.gz Programming language: Fortran 90. Computer: Linux PC and clusters. Operating system: Linux. Has the code been vectorized or parallelized?: Yes. Program is parallelized using MPI. Number of processors used: 1-50,000 RAM: Memory requirements depend on the grid size Classification: 6.5, 7.7. External routines: MPI (http://www.mcs.anl.gov/research/projects/mpi/), HDF5 (http://www.hdfgroup.org/HDF5/) Nature of problem: Dendritic growth in undercooled Al-3 wt% Cu alloy melt under forced convection. Solution method: The lattice Boltzmann model solves the diffusion, convection, and heat transfer phenomena. The cellular automaton technique is deployed to track the solid/liquid interface. Restrictions: Heat transfer is calculated uncoupled from the fluid flow. Thermal diffusivity is constant. Unusual features: Novel technique, utilizing periodic duplication of a pre-grown “incubation” domain, is applied for the scaleup test. Running time: Running time varies from minutes to days depending on the domain size and number of computational cores.

A cellular automation model accounting for bicycle's group behavior

NASA Astrophysics Data System (ADS)

Tang, Tie-Qiao; Rui, Ying-Xu; Zhang, Jian; Shang, Hua-Yan

2018-02-01

Recently, bicycle has become an important traffic tool in China, again. Due to the merits of bicycle, the group behavior widely exists in urban traffic system. However, little effort has been made to explore the impacts of the group behavior on bicycle flow. In this paper, we propose a CA (cellular automaton) model with group behavior to explore the complex traffic phenomena caused by shoulder group behavior and following group behavior on an open road. The numerical results illustrate that the proposed model can qualitatively describe the impacts of the two kinds of group behaviors on bicycle flow and that the effects are related to the mode and size of group behaviors. The results can help us to better understand the impacts of the bicycle's group behaviors on urban traffic system and effectively control the bicycle's group behavior.

Disordered cellular automaton traffic flow model: phase separated state, density waves and self organized criticality

NASA Astrophysics Data System (ADS)

Fourrate, K.; Loulidi, M.

2006-01-01

We suggest a disordered traffic flow model that captures many features of traffic flow. It is an extension of the Nagel-Schreckenberg (NaSch) stochastic cellular automata for single line vehicular traffic model. It incorporates random acceleration and deceleration terms that may be greater than one unit. Our model leads under its intrinsic dynamics, for high values of braking probability pr, to a constant flow at intermediate densities without introducing any spatial inhomogeneities. For a system of fast drivers pr→0, the model exhibits a density wave behavior that was observed in car following models with optimal velocity. The gap of the disordered model we present exhibits, for high values of pr and random deceleration, at a critical density, a power law distribution which is a hall mark of a self organized criticality phenomena.

Simple stochastic cellular automaton model for starved beds and implications about formation of sand topographic features in terms of sand flux

NASA Astrophysics Data System (ADS)

Endo, Noritaka

2016-12-01

A simple stochastic cellular automaton model is proposed for simulating bedload transport, especially for cases with a low transport rate and where available sediments are very sparse on substrates in a subaqueous system. Numerical simulations show that the bed type changes from sheet flow through sand patches to ripples as the amount of sand increases; this is consistent with observations in flume experiments and in the field. Without changes in external conditions, the sand flux calculated for a given amount of sand decreases over time as bedforms develop from a flat bed. This appears to be inconsistent with the general understanding that sand flux remains unchanged under the constant-fluid condition, but it is consistent with the previous experimental data. For areas of low sand abundance, the sand flux versus sand amount (flux-density relation) in the simulation shows a single peak with an abrupt decrease, followed by a long tail; this is very similar to the flux-density relation seen in automobile traffic flow. This pattern (the relation between segments of the curve and the corresponding bed states) suggests that sand sheets, sand patches, and sand ripples correspond respectively to the free-flow phase, congested phase, and jam phase of traffic flows. This implies that sand topographic features on starved beds are determined by the degree of interference between sand particles. Although the present study deals with simple cases only, this can provide a simplified but effective modeling of the more complicated sediment transport processes controlled by interference due to contact between grains, such as the pulsatory migration of grain-size bimodal mixtures with repetition of clustering and scattering.

A hybrid finite-element and cellular-automaton framework for modeling 3D microstructure of Ti–6Al–4V alloy during solid–solid phase transformation in additive manufacturing

NASA Astrophysics Data System (ADS)

Chen, Shaohua; Xu, Yaopengxiao; Jiao, Yang

2018-06-01

Additive manufacturing such as selective laser sintering and electron beam melting has become a popular technique which enables one to build near-net-shape product from packed powders. The performance and properties of the manufactured product strongly depends on its material microstructure, which is in turn determined by the processing conditions including beam power density, spot size, scanning speed and path etc. In this paper, we develop a computational framework that integrates the finite element method (FEM) and cellular automaton (CA) simulation to model the 3D microstructure of additively manufactured Ti–6Al–4V alloy, focusing on the β → α + β transition pathway in a consolidated alloy region as the power source moves away from this region. Specifically, the transient temperature field resulted from a scanning laser/electron beam following a zig-zag path is first obtained by solving nonlinear heat transfer equations using the FEM. Next, a CA model for the β → α + β phase transformation in the consolidated alloy is developed which explicitly takes into account the temperature dependent heterogeneous nucleation and anisotropic growth of α grains from the parent β phase field. We verify our model by reproducing the overall transition kinetics predicted by the Johnson–Mehl–Avrami–Kolmogorov theory under a typical processing condition and by quantitatively comparing our simulation results with available experimental data. The utility of the model is further demonstrated by generating large-field realistic 3D alloy microstructures for subsequent structure-sensitive micro-mechanical analysis. In addition, we employ our model to generate a wide spectrum of alloy microstructures corresponding to different processing conditions for establishing quantitative process-structure relations for the system.

Modeling the Potential Spread of the Recently Identified Non-Native Panther Grouper (Chromileptes altivelis) in the Atlantic Using a Cellular Automaton Approach

PubMed Central

Johnston, Matthew W.; Purkis, Sam J.

2013-01-01

The Indo-pacific panther grouper (Chromileptes altiveli) is a predatory fish species and popular imported aquarium fish in the United States which has been recently documented residing in western Atlantic waters. To date, the most successful marine invasive species in the Atlantic is the lionfish (Pterois volitans/miles), which, as for the panther grouper, is assumed to have been introduced to the wild through aquarium releases. However, unlike lionfish, the panther grouper is not yet thought to have an established breeding population in the Atlantic. Using a proven modeling technique developed to track the lionfish invasion, presented is the first known estimation of the potential spread of panther grouper in the Atlantic. The employed cellular automaton-based computer model examines the life history of the subject species including fecundity, mortality, and reproductive potential and combines this with habitat preferences and physical oceanic parameters to forecast the distribution and periodicity of spread of this potential new invasive species. Simulations were examined for origination points within one degree of capture locations of panther grouper from the United States Geological Survey Nonindigenous Aquatic Species Database to eliminate introduction location bias, and two detailed case studies were scrutinized. The model indicates three primary locations where settlement is likely given the inputs and limits of the model; Jupiter Florida/Vero Beach, the Cape Hatteras Tropical Limit/Myrtle Beach South Carolina, and Florida Keys/Ten Thousand Islands locations. Of these locations, Jupiter Florida/Vero Beach has the highest settlement rate in the model and is indicated as the area in which the panther grouper is most likely to become established. This insight is valuable if attempts are to be made to halt this potential marine invasive species. PMID:24009726

Modeling the potential spread of the recently identified non-native panther grouper (Chromileptes altivelis) in the Atlantic using a cellular automaton approach.

PubMed

Johnston, Matthew W; Purkis, Sam J

2013-01-01

The Indo-pacific panther grouper (Chromileptes altiveli) is a predatory fish species and popular imported aquarium fish in the United States which has been recently documented residing in western Atlantic waters. To date, the most successful marine invasive species in the Atlantic is the lionfish (Pterois volitans/miles), which, as for the panther grouper, is assumed to have been introduced to the wild through aquarium releases. However, unlike lionfish, the panther grouper is not yet thought to have an established breeding population in the Atlantic. Using a proven modeling technique developed to track the lionfish invasion, presented is the first known estimation of the potential spread of panther grouper in the Atlantic. The employed cellular automaton-based computer model examines the life history of the subject species including fecundity, mortality, and reproductive potential and combines this with habitat preferences and physical oceanic parameters to forecast the distribution and periodicity of spread of this potential new invasive species. Simulations were examined for origination points within one degree of capture locations of panther grouper from the United States Geological Survey Nonindigenous Aquatic Species Database to eliminate introduction location bias, and two detailed case studies were scrutinized. The model indicates three primary locations where settlement is likely given the inputs and limits of the model; Jupiter Florida/Vero Beach, the Cape Hatteras Tropical Limit/Myrtle Beach South Carolina, and Florida Keys/Ten Thousand Islands locations. Of these locations, Jupiter Florida/Vero Beach has the highest settlement rate in the model and is indicated as the area in which the panther grouper is most likely to become established. This insight is valuable if attempts are to be made to halt this potential marine invasive species.

Equiaxed and columnar dendrite growth simulation in Al-7Si- Mg ternary alloys using cellular automaton method

NASA Astrophysics Data System (ADS)

Chen, Rui; Xu, Qingyan; Liu, Baicheng

2015-06-01

In this paper, a modified cellular automaton (MCA) model allowing for the prediction of dendrite growth of Al-Si-Mg ternary alloys in two and three dimensions is presented. The growth kinetic of S/L interface is calculated based on the solute equilibrium approach. In order to describe the dendrite growth with arbitrarily crystallographic orientations, this model introduces a modified decentered octahedron algorithm for neighborhood tracking to eliminate the effect of mesh dependency on dendrite growth. The thermody namic and kinetic data needed for dendrite growth is obtained through coupling with Pandat software package in combination with thermodynamic/kinetic/equilibrium phase diagram calculation databases. The effect of interactions between various alloying elements on solute diffusion coefficient is considered in the model. This model has first been used to simulate Al-7Si (weight percent) binary dendrite growth followed by a validation using theoretical predictions. For ternary alloy, Al-7Si-0.5Mg dendrite simulation has been carried out and the effects of solute interactions on diffusion matrix as well as the differences of Si and Mg in solute distribution have been analyzed. For actual application, this model has been applied to simulate the equiaxed dendrite growth with various crystallographic orientations of Al-7Si-0.36Mg ternary alloy, and the predicted secondary dendrite arm spacing (SDAS) shows a reasonable agreement with the experimental ones. Furthermore, the columnar dendrite growth in directional solidification has also been simulated and the predicted primary dendrite arm spacing (PDAS) is in good agreement with experiments. The simulated results effectively demonstrate the abilities of the model in prediction of dendritic microstructure of Al-Si-Mg ternary alloy.

Effect of Temperature and Fluid Flow on Dendrite Growth During Solidification of Al-3 Wt Pct Cu Alloy by the Two-Dimensional Cellular Automaton Method

NASA Astrophysics Data System (ADS)

Gu, Cheng; Wei, Yanhong; Liu, Renpei; Yu, Fengyi

2017-12-01

A two-dimensional cellular automaton-finite volume model was developed to simulate dendrite growth of Al-3 wt pct Cu alloy during solidification to investigate the effect of temperature and fluid flow on dendrite morphology, solute concentration distribution, and dendrite growth velocity. Different calculation conditions that may influence the results of the simulation, including temperature and flow, were considered. The model was also employed to study the effect of different undercoolings, applied temperature fields, and forced flow velocities on solute segregation and dendrite growth. The initial temperature and fluid flow have a significant impact on the dendrite morphologies and solute profiles during solidification. The release of energy is operated with solidification and results in the increase of temperature. A larger undercooling leads to larger solute concentration near the solid/liquid interface and solute concentration gradient at the same time-step. Solute concentration in the solid region tends to increase with the increase of undercooling. Four vortexes appear under the condition when natural flow exists: the two on the right of the dendrite rotate clockwise, and those on the left of the dendrite rotate counterclockwise. With the increase of forced flow velocity, the rejected solute in the upstream region becomes easier to be washed away and enriched in the downstream region, resulting in acceleration of the growth of the dendrite in the upstream and inhibiting the downstream dendrite growth. The dendrite perpendicular to fluid flow shows a coarser morphology in the upstream region than that of the downstream. Almost no secondary dendrite appears during the calculation process.

Exponential growth for self-reproduction in a catalytic reaction network: relevance of a minority molecular species and crowdedness

NASA Astrophysics Data System (ADS)

Kamimura, Atsushi; Kaneko, Kunihiko

2018-03-01

Explanation of exponential growth in self-reproduction is an important step toward elucidation of the origins of life because optimization of the growth potential across rounds of selection is necessary for Darwinian evolution. To produce another copy with approximately the same composition, the exponential growth rates for all components have to be equal. How such balanced growth is achieved, however, is not a trivial question, because this kind of growth requires orchestrated replication of the components in stochastic and nonlinear catalytic reactions. By considering a mutually catalyzing reaction in two- and three-dimensional lattices, as represented by a cellular automaton model, we show that self-reproduction with exponential growth is possible only when the replication and degradation of one molecular species is much slower than those of the others, i.e., when there is a minority molecule. Here, the synergetic effect of molecular discreteness and crowding is necessary to produce the exponential growth. Otherwise, the growth curves show superexponential growth because of nonlinearity of the catalytic reactions or subexponential growth due to replication inhibition by overcrowding of molecules. Our study emphasizes that the minority molecular species in a catalytic reaction network is necessary for exponential growth at the primitive stage of life.

A coupled vegetation/sediment transport model for dryland environments

NASA Astrophysics Data System (ADS)

Mayaud, Jerome R.; Bailey, Richard M.; Wiggs, Giles F. S.

2017-04-01

Dryland regions are characterized by patchy vegetation, erodible surfaces, and erosive aeolian processes. Understanding how these constituent factors interact and shape landscape evolution is critical for managing potential environmental and anthropogenic impacts in drylands. However, modeling wind erosion on partially vegetated surfaces is a complex problem that has remained challenging for researchers. We present the new, coupled cellular automaton Vegetation and Sediment TrAnsport (ViSTA) model, which is designed to address fundamental questions about the development of arid and semiarid landscapes in a spatially explicit way. The technical aspects of the ViSTA model are described, including a new method for directly imposing oblique wind and transport directions onto a cell-based domain. Verification tests for the model are reported, including stable state solutions, the impact of drought and fire stress, wake flow dynamics, temporal scaling issues, and the impact of feedbacks between sediment movement and vegetation growth on landscape morphology. The model is then used to simulate an equilibrium nebkha dune field, and the resultant bed forms are shown to have very similar size and spacing characteristics to nebkhas observed in the Skeleton Coast, Namibia. The ViSTA model is a versatile geomorphological tool that could be used to predict threshold-related transitions in a range of dryland ecogeomorphic systems.

Transcriptional bursting is intrinsically caused by interplay between RNA polymerases on DNA

NASA Astrophysics Data System (ADS)

Fujita, Keisuke; Iwaki, Mitsuhiro; Yanagida, Toshio

2016-12-01

Cell-to-cell variability plays a critical role in cellular responses and decision-making in a population, and transcriptional bursting has been broadly studied by experimental and theoretical approaches as the potential source of cell-to-cell variability. Although molecular mechanisms of transcriptional bursting have been proposed, there is little consensus. An unsolved key question is whether transcriptional bursting is intertwined with many transcriptional regulatory factors or is an intrinsic characteristic of RNA polymerase on DNA. Here we design an in vitro single-molecule measurement system to analyse the kinetics of transcriptional bursting. The results indicate that transcriptional bursting is caused by interplay between RNA polymerases on DNA. The kinetics of in vitro transcriptional bursting is quantitatively consistent with the gene-nonspecific kinetics previously observed in noisy gene expression in vivo. Our kinetic analysis based on a cellular automaton model confirms that arrest and rescue by trailing RNA polymerase intrinsically causes transcriptional bursting.

Two-material optimization of plate armour for blast mitigation using hybrid cellular automata

NASA Astrophysics Data System (ADS)

Goetz, J.; Tan, H.; Renaud, J.; Tovar, A.

2012-08-01

With the increased use of improvised explosive devices in regions at war, the threat to military and civilian life has risen. Cabin penetration and gross acceleration are the primary threats in an explosive event. Cabin penetration crushes occupants, damaging the lower body. Acceleration causes death at high magnitudes. This investigation develops a process of designing armour that simultaneously mitigates cabin penetration and acceleration. The hybrid cellular automaton (HCA) method of topology optimization has proven efficient and robust in problems involving large, plastic deformations such as crash impact. Here HCA is extended to the design of armour under blast loading. The ability to distribute two metallic phases, as opposed to one material and void, is also added. The blast wave energy transforms on impact into internal energy (IE) inside the solid medium. Maximum attenuation occurs with maximized IE. The resulting structures show HCA's potential for designing blast mitigating armour structures.

Fast encryption of RGB color digital images using a tweakable cellular automaton based schema

NASA Astrophysics Data System (ADS)

Faraoun, Kamel Mohamed

2014-12-01

We propose a new tweakable construction of block-enciphers using second-order reversible cellular automata, and we apply it to encipher RGB-colored images. The proposed construction permits a parallel encryption of the image content by extending the standard definition of a block cipher to take into account a supplementary parameter used as a tweak (nonce) to control the behavior of the cipher from one region of the image to the other, and hence avoid the necessity to use slow sequential encryption's operating modes. The proposed construction defines a flexible pseudorandom permutation that can be used with efficacy to solve the electronic code book problem without the need to a specific sequential mode. Obtained results from various experiments show that the proposed schema achieves high security and execution performances, and enables an interesting mode of selective area decryption due to the parallel character of the approach.

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

PubMed

Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

2003-05-01

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

Role of sublayers in mechanical response of pulsed electron beam irradiated surface layers to contact load

NASA Astrophysics Data System (ADS)

Konovalenko, Igor S.

2017-12-01

Here we develop the movable cellular automaton method based a numerical model of surface layers in a NiCr-TiC metal ceramic composite modified by pulsed electron beam irradiation in inert gas plasmas. The model explicitly takes into account the presence of several sublayers differing in structure and mechanical properties. The contribution of each sublayer to the mechanical response of the modified surface to contact loading is studied. It is shown that the maximum strength and fracture toughness are achieved in surface layers containing thin and stiff external sublayers and a more ductile thick internal sublayer.

A New Interpretation of Effects of the Probabilistic Delayed Start on the One-Dimensional Traffic Flow

NASA Astrophysics Data System (ADS)

Ishibashi, Yoshihiro; Fukui, Minoru

2018-03-01

The effect of the probabilistic delayed start on the one-dimensional traffic flow is investigated on the basis of several models. Analogy with the degeneracy of the states and its resolution, as well as that with the mathematical procedures adopted for them, is utilized. The perturbation is assumed to be proportional to the probability of the delayed start, and the perturbation function is determined so that imposed conditions are fulfilled. The obtained formulas coincide with those previously derived on the basis of the mean-field analyses of the Nagel-Schreckenberg and Fukui-Ishibashi models, and reproduce the cellular automaton simulation results.

Toward micro-scale spatial modeling of gentrification

NASA Astrophysics Data System (ADS)

O'Sullivan, David

A simple preliminary model of gentrification is presented. The model is based on an irregular cellular automaton architecture drawing on the concept of proximal space, which is well suited to the spatial externalities present in housing markets at the local scale. The rent gap hypothesis on which the model's cell transition rules are based is discussed. The model's transition rules are described in detail. Practical difficulties in configuring and initializing the model are described and its typical behavior reported. Prospects for further development of the model are discussed. The current model structure, while inadequate, is well suited to further elaboration and the incorporation of other interesting and relevant effects.

Nonlinear dynamics of the cellular-automaton ``game of Life''

NASA Astrophysics Data System (ADS)

Garcia, J. B. C.; Gomes, M. A. F.; Jyh, T. I.; Ren, T. I.; Sales, T. R. M.

1993-11-01

A statistical analysis of the ``game of Life'' due to Conway [Berlekamp, Conway, and Guy, Winning Ways for Your Mathematical Plays (Academic, New York, 1982), Vol. 2] is reported. The results are based on extensive computer simulations starting with uncorrelated distributions of live sites at t=0. The number n(s,t) of clusters of s live sites at time t, the mean cluster size s¯(t), and the diversity of sizes among other statistical functions are obtained. The dependence of the statistical functions with the initial density of live sites is examined. Several scaling relations as well as static and dynamic critical exponents are found.

Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues

PubMed Central

Bloomfield, J. M.; Sherratt, J. A.; Painter, K. J.; Landini, G.

2010-01-01

Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios. PMID:20375040

Conway's Game of Life is a near-critical metastable state in the multiverse of cellular automata.

PubMed

Reia, Sandro M; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ = 0) and an active phase density, with ρ = 0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ(2D) ≈ 0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

Conway's game of life is a near-critical metastable state in the multiverse of cellular automata

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ =0) and an active phase density, with ρ =0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ2D≈0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

Cellular Automata

NASA Astrophysics Data System (ADS)

Gutowitz, Howard

1991-08-01

Cellular automata, dynamic systems in which space and time are discrete, are yielding interesting applications in both the physical and natural sciences. The thirty four contributions in this book cover many aspects of contemporary studies on cellular automata and include reviews, research reports, and guides to recent literature and available software. Chapters cover mathematical analysis, the structure of the space of cellular automata, learning rules with specified properties: cellular automata in biology, physics, chemistry, and computation theory; and generalizations of cellular automata in neural nets, Boolean nets, and coupled map lattices. Current work on cellular automata may be viewed as revolving around two central and closely related problems: the forward problem and the inverse problem. The forward problem concerns the description of properties of given cellular automata. Properties considered include reversibility, invariants, criticality, fractal dimension, and computational power. The role of cellular automata in computation theory is seen as a particularly exciting venue for exploring parallel computers as theoretical and practical tools in mathematical physics. The inverse problem, an area of study gaining prominence particularly in the natural sciences, involves designing rules that possess specified properties or perform specified task. A long-term goal is to develop a set of techniques that can find a rule or set of rules that can reproduce quantitative observations of a physical system. Studies of the inverse problem take up the organization and structure of the set of automata, in particular the parameterization of the space of cellular automata. Optimization and learning techniques, like the genetic algorithm and adaptive stochastic cellular automata are applied to find cellular automaton rules that model such physical phenomena as crystal growth or perform such adaptive-learning tasks as balancing an inverted pole. Howard Gutowitz is Collaborateur in the Service de Physique du Solide et Résonance Magnetique, Commissariat a I'Energie Atomique, Saclay, France.

An immersed boundary-lattice Boltzmann model for biofilm growth and its impact on the NAPL dissolution in porous media

NASA Astrophysics Data System (ADS)

Benioug, M.; Yang, X.

2017-12-01

The evolution of microbial phase within porous medium is a complex process that involves growth, mortality, and detachment of the biofilm or attachment of moving cells. A better understanding of the interactions among biofilm growth, flow and solute transport and a rigorous modeling of such processes are essential for a more accurate prediction of the fate of pollutants (e.g. NAPLs) in soils. However, very few works are focused on the study of such processes in multiphase conditions (oil/water/biofilm systems). Our proposed numerical model takes into account the mechanisms that control bacterial growth and its impact on the dissolution of NAPL. An Immersed Boundary - Lattice Boltzmann Model (IB-LBM) is developed for flow simulations along with non-boundary conforming finite volume methods (volume of fluid and reconstruction methods) used for reactive solute transport. A sophisticated cellular automaton model is also developed to describe the spatial distribution of bacteria. A series of numerical simulations have been performed on complex porous media. A quantitative diagram representing the transitions between the different biofilm growth patterns is proposed. The bioenhanced dissolution of NAPL in the presence of biofilms is simulated at the pore scale. A uniform dissolution approach has been adopted to describe the temporal evolution of trapped blobs. Our simulations focus on the dissolution of NAPL in abiotic and biotic conditions. In abiotic conditions, we analyze the effect of the spatial distribution of NAPL blobs on the dissolution rate under different assumptions (blobs size, Péclet number). In biotic conditions, different conditions are also considered (spatial distribution, reaction kinetics, toxicity) and analyzed. The simulated results are consistent with those obtained from the literature.

Finite driving rate and anisotropy effects in landslide modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piegari, E.; Cataudella, V.; Di Maio, R.

2006-02-15

In order to characterize landslide frequency-size distributions and individuate hazard scenarios and their possible precursors, we investigate a cellular automaton where the effects of a finite driving rate and the anisotropy are taken into account. The model is able to reproduce observed features of landslide events, such as power-law distributions, as experimentally reported. We analyze the key role of the driving rate and show that, as it is increased, a crossover from power-law to non-power-law behaviors occurs. Finally, a systematic investigation of the model on varying its anisotropy factors is performed and the full diagram of its dynamical behaviors ismore » presented.« less

Modelling the morphology of migrating bacterial colonies

NASA Astrophysics Data System (ADS)

Nishiyama, A.; Tokihiro, T.; Badoual, M.; Grammaticos, B.

2010-08-01

We present a model which aims at describing the morphology of colonies of Proteus mirabilis and Bacillus subtilis. Our model is based on a cellular automaton which is obtained by the adequate discretisation of a diffusion-like equation, describing the migration of the bacteria, to which we have added rules simulating the consolidation process. Our basic assumption, following the findings of the group of Chuo University, is that the migration and consolidation processes are controlled by the local density of the bacteria. We show that it is possible within our model to reproduce the morphological diagrams of both bacteria species. Moreover, we model some detailed experiments done by the Chuo University group, obtaining a fine agreement.

Towards the simplest hydrodynamic lattice-gas model.

PubMed

Boghosian, Bruce M; Love, Peter J; Meyer, David A

2002-03-15

It has been known since 1986 that it is possible to construct simple lattice-gas cellular automata whose hydrodynamics are governed by the Navier-Stokes equations in two dimensions. The simplest such model heretofore known has six bits of state per site on a triangular lattice. In this work, we demonstrate that it is possible to construct a model with only five bits of state per site on a Kagome lattice. Moreover, the model has a simple, deterministic set of collision rules and is easily implemented on a computer. In this work, we derive the equilibrium distribution function for this lattice-gas automaton and carry out the Chapman-Enskog analysis to determine the form of the Navier-Stokes equations.

Self-Organized Criticality and Scaling in Lifetime of Traffic Jams

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

1995-01-01

The deterministic cellular automaton 184 (the one-dimensional asymmetric simple-exclusion model with parallel dynamics) is extended to take into account injection or extraction of particles. The model presents the traffic flow on a highway with inflow or outflow of cars.Introducing injection or extraction of particles into the asymmetric simple-exclusion model drives the system asymptotically into a steady state exhibiting a self-organized criticality. The typical lifetime of traffic jams scales as \\cong Lν with ν=0.65±0.04. It is shown that the cumulative distribution Nm (L) of lifetimes satisfies the finite-size scaling form Nm (L) \\cong L-1 f(m/Lν).

Two-dimensional DFA scaling analysis applied to encrypted images

NASA Astrophysics Data System (ADS)

Vargas-Olmos, C.; Murguía, J. S.; Ramírez-Torres, M. T.; Mejía Carlos, M.; Rosu, H. C.; González-Aguilar, H.

2015-01-01

The technique of detrended fluctuation analysis (DFA) has been widely used to unveil scaling properties of many different signals. In this paper, we determine scaling properties in the encrypted images by means of a two-dimensional DFA approach. To carry out the image encryption, we use an enhanced cryptosystem based on a rule-90 cellular automaton and we compare the results obtained with its unmodified version and the encryption system AES. The numerical results show that the encrypted images present a persistent behavior which is close to that of the 1/f-noise. These results point to the possibility that the DFA scaling exponent can be used to measure the quality of the encrypted image content.

Characterizing autopoiesis in the game of life.

PubMed

Beer, Randall D

2015-01-01

Maturana and Varela's concept of autopoiesis defines the essential organization of living systems and serves as a foundation for their biology of cognition and the enactive approach to cognitive science. As an initial step toward a more formal analysis of autopoiesis, this article investigates its application to the compact, recurrent spatiotemporal patterns that arise in Conway's Game-of-Life cellular automaton. In particular, we demonstrate how such entities can be formulated as self-constructing networks of interdependent processes that maintain their own boundaries. We then characterize the specific organizations of several such entities, suggest a way to simplify the descriptions of these organizations, and briefly consider the transformation of such organizations over time.

Signal Waveform Detection with Statistical Automaton for Internet and Web Service Streaming

PubMed Central

Liu, Yiming; Huang, Nai-Lun; Zeng, Fufu; Lin, Fang-Ying

2014-01-01

In recent years, many approaches have been suggested for Internet and web streaming detection. In this paper, we propose an approach to signal waveform detection for Internet and web streaming, with novel statistical automatons. The system records network connections over a period of time to form a signal waveform and compute suspicious characteristics of the waveform. Network streaming according to these selected waveform features by our newly designed Aho-Corasick (AC) automatons can be classified. We developed two versions, that is, basic AC and advanced AC-histogram waveform automata, and conducted comprehensive experimentation. The results confirm that our approach is feasible and suitable for deployment. PMID:25032231

An Automaton Rover for Extreme Environments: Rethinking an Approach to Surface Mobility

NASA Astrophysics Data System (ADS)

Sauder, J.; Hilgemman, E.; Stack, K.; Kawata, J.; Parness, A.; Johnson, M.

2017-11-01

An Automaton Rover for Extreme Environments (AREE) enables long duration in-situ mobility on the surface of Venus through a simplified design and robust mechanisms. The goal is to design a rover capable of operating for months on the surface of Venus.

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

Effects of physical parameters on the cell-to-dendrite transition in directional solidification

NASA Astrophysics Data System (ADS)

Wei, Lei; Lin, Xin; Wang, Meng; Huang, Wei-Dong

2015-07-01

A quantitative cellular automaton model is used to study the cell-to-dendrite transition (CDT) in directional solidification. We give a detailed description of the CDT by carefully examining the influence of the physical parameters, including: the Gibbs-Thomson coefficient Γ, the solute diffusivity Dl, the solute partition coefficient k0, and the liquidus slope ml. It is found that most of the parameters agree with the Kurz and Fisher (KF) criterion, except for k0. The intrinsic relations among the critical velocity Vcd, the cellular primary spacing λc,max, and the critical spacing λcd are investigated. Project supported by the National Natural Science Foundation of China (Grant Nos. 51271213 and 51323008), the National Basic Research Program of China (Grant No. 2011CB610402), the National High Technology Research and Development Program of China (Grant No. 2013AA031103), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20116102110016), and the China Postdoctoral Science Foundation (Grant No. 2013M540771).

A fuzzy-theory-based behavioral model for studying pedestrian evacuation from a single-exit room

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lo, Siuming

2016-08-01

Many mass events in recent years have highlighted the importance of research on pedestrian evacuation dynamics. A number of models have been developed to analyze crowd behavior under evacuation situations. However, few focus on pedestrians' decision-making with respect to uncertainty, vagueness and imprecision. In this paper, a discrete evacuation model defined on the cellular space is proposed according to the fuzzy theory which is able to describe imprecise and subjective information. Pedestrians' percept information and various characteristics are regarded as fuzzy input. Then fuzzy inference systems with rule bases, which resemble human reasoning, are established to obtain fuzzy output that decides pedestrians' movement direction. This model is tested in two scenarios, namely in a single-exit room with and without obstacles. Simulation results reproduce some classic dynamics phenomena discovered in real building evacuation situations, and are consistent with those in other models and experiments. It is hoped that this study will enrich movement rules and approaches in traditional cellular automaton models for evacuation dynamics.

Accelerating a three-dimensional eco-hydrological cellular automaton on GPGPU with OpenCL

NASA Astrophysics Data System (ADS)

Senatore, Alfonso; D'Ambrosio, Donato; De Rango, Alessio; Rongo, Rocco; Spataro, William; Straface, Salvatore; Mendicino, Giuseppe

2016-10-01

This work presents an effective implementation of a numerical model for complete eco-hydrological Cellular Automata modeling on Graphical Processing Units (GPU) with OpenCL (Open Computing Language) for heterogeneous computation (i.e., on CPUs and/or GPUs). Different types of parallel implementations were carried out (e.g., use of fast local memory, loop unrolling, etc), showing increasing performance improvements in terms of speedup, adopting also some original optimizations strategies. Moreover, numerical analysis of results (i.e., comparison of CPU and GPU outcomes in terms of rounding errors) have proven to be satisfactory. Experiments were carried out on a workstation with two CPUs (Intel Xeon E5440 at 2.83GHz), one GPU AMD R9 280X and one GPU nVIDIA Tesla K20c. Results have been extremely positive, but further testing should be performed to assess the functionality of the adopted strategies on other complete models and their ability to fruitfully exploit parallel systems resources.

Calibrating cellular automaton models for pedestrians walking through corners

NASA Astrophysics Data System (ADS)

Dias, Charitha; Lovreglio, Ruggiero

2018-05-01

Cellular Automata (CA) based pedestrian simulation models have gained remarkable popularity as they are simpler and easier to implement compared to other microscopic modeling approaches. However, incorporating traditional floor field representations in CA models to simulate pedestrian corner navigation behavior could result in unrealistic behaviors. Even though several previous studies have attempted to enhance CA models to realistically simulate pedestrian maneuvers around bends, such modifications have not been calibrated or validated against empirical data. In this study, two static floor field (SFF) representations, namely 'discrete representation' and 'continuous representation', are calibrated for CA-models to represent pedestrians' walking behavior around 90° bends. Trajectory data collected through a controlled experiment are used to calibrate these model representations. Calibration results indicate that although both floor field representations can represent pedestrians' corner navigation behavior, the 'continuous' representation fits the data better. Output of this study could be beneficial for enhancing the reliability of existing CA-based models by representing pedestrians' corner navigation behaviors more realistically.

Bin packing problem solution through a deterministic weighted finite automaton

NASA Astrophysics Data System (ADS)

Zavala-Díaz, J. C.; Pérez-Ortega, J.; Martínez-Rebollar, A.; Almanza-Ortega, N. N.; Hidalgo-Reyes, M.

2016-06-01

In this article the solution of Bin Packing problem of one dimension through a weighted finite automaton is presented. Construction of the automaton and its application to solve three different instances, one synthetic data and two benchmarks are presented: N1C1W1_A.BPP belonging to data set Set_1; and BPP13.BPP belonging to hard28. The optimal solution of synthetic data is obtained. In the first benchmark the solution obtained is one more container than the ideal number of containers and in the second benchmark the solution is two more containers than the ideal solution (approximately 2.5%). The runtime in all three cases was less than one second.

On Matrices, Automata, and Double Counting

NASA Astrophysics Data System (ADS)

Beldiceanu, Nicolas; Carlsson, Mats; Flener, Pierre; Pearson, Justin

Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variables M, with the same constraint defined by a finite-state automaton A on each row of M and a global cardinality constraint gcc on each column of M. We give two methods for deriving, by double counting, necessary conditions on the cardinality variables of the gcc constraints from the automaton A. The first method yields linear necessary conditions and simple arithmetic constraints. The second method introduces the cardinality automaton, which abstracts the overall behaviour of all the row automata and can be encoded by a set of linear constraints. We evaluate the impact of our methods on a large set of nurse rostering problem instances.

Folding Automaton for Trees

NASA Astrophysics Data System (ADS)

Subashini, N.; Thiagarajan, K.

2018-04-01

In this paper we observed the definition of folding technique in graph theory and we derived the corresponding automaton for trees. Also derived some propositions on symmetrical structure tree, non-symmetrical structure tree, point symmetrical structure tree, edge symmetrical structure tree along with finite number of points. This approach provides to derive one edge after n’ number of foldings.

Algorithm for repairing the damaged images of grain structures obtained from the cellular automata and measurement of grain size

NASA Astrophysics Data System (ADS)

Ramírez-López, A.; Romero-Romo, M. A.; Muñoz-Negron, D.; López-Ramírez, S.; Escarela-Pérez, R.; Duran-Valencia, C.

2012-10-01

Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical inconsistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidification, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed algorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.

Cellular modelling of secondary radial growth in conifer trees: application to Pinus radiata (D. Don).

PubMed

Forest, Loïc; Demongeot, Jacques; Demongeota, Jacques

2006-05-01

The radial growth of conifer trees proceeds from the dynamics of a merismatic tissue called vascular cambium or cambium. Cambium is a thin layer of active proliferating cells. The purpose of this paper was to model the main characteristics of cambial activity and its consecutive radial growth. Cell growth is under the control of the auxin hormone indole-3-acetic. The model is composed of a discrete part, which accounts for cellular proliferation, and a continuous part involving the transport of auxin. Cambium is modeled in a two-dimensional cross-section by a cellular automaton that describes the set of all its constitutive cells. Proliferation is defined as growth and division of cambial cells under neighbouring constraints, which can eliminate some cells from the cambium. The cell-growth rate is determined from auxin concentration, calculated with the continuous model. We studied the integration of each elementary cambial cell activity into the global coherent movement of macroscopic morphogenesis. Cases of normal and abnormal growth of Pinus radiata (D. Don) are modelled. Abnormal growth includes deformed trees where gravity influences auxin transport, producing heterogeneous radial growth. Cross-sectional microscopic views are also provided to validate the model's hypothesis and results.

Survival of mutations arising during invasions.

PubMed

Miller, Judith R

2010-03-01

When a neutral mutation arises in an invading population, it quickly either dies out or 'surfs', i.e. it comes to occupy almost all the habitat available at its time of origin. Beneficial mutations can also surf, as can deleterious mutations over finite time spans. We develop descriptive statistical models that quantify the relationship between the probability that a mutation will surf and demographic parameters for a cellular automaton model of surfing. We also provide a simple analytic model that performs well at predicting the probability of surfing for neutral and beneficial mutations in one dimension. The results suggest that factors - possibly including even abiotic factors - that promote invasion success may also increase the probability of surfing and associated adaptive genetic change, conditioned on such success.

Multicomponent lattice Boltzmann model from continuum kinetic theory.

PubMed

Shan, Xiaowen

2010-04-01

We derive from the continuum kinetic theory a multicomponent lattice Boltzmann model with intermolecular interaction. The resulting model is found to be consistent with the model previously derived from a lattice-gas cellular automaton [X. Shan and H. Chen, Phys. Rev. E 47, 1815 (1993)] but applies in a much broader domain. A number of important insights are gained from the kinetic theory perspective. First, it is shown that even in the isothermal case, the energy equipartition principle dictates the form of the equilibrium distribution function. Second, thermal diffusion is shown to exist and the corresponding diffusivities are given in terms of macroscopic parameters. Third, the ordinary diffusion is shown to satisfy the Maxwell-Stefan equation at the ideal-gas limit.

Urban Flood Prevention and Early Warning System in Jinan City

NASA Astrophysics Data System (ADS)

Feng, Shiyuan; Li, Qingguo

2018-06-01

The system construction of urban flood control and disaster reduction in China is facing pressure and challenge from new urban water disaster. Under the circumstances that it is difficult to build high standards of flood protection engineering measures in urban areas, it is particularly important to carry out urban flood early warning. In Jinan City, a representative inland area, based on the index system of early warning of flood in Jinan urban area, the method of fuzzy comprehensive evaluation was adopted to evaluate the level of early warning. Based on the cumulative rainfall of 3 hours, the CAflood simulation results based on cellular automaton model of urban flooding were used as evaluation indexes to realize the accuracy and integration of urban flood control early warning.

Universal Computation and Construction in GoL Cellular Automata

NASA Astrophysics Data System (ADS)

Goucher, Adam P.

This chapter is concerned with the developments of universal computation and construction within Conway's Game of Life (GoL). I will begin by describing the history of the concepts and mechanisms for universal computation and construction in GoL, before explaining how a Universal Computer-Constructor (UCC) would operate in this automaton. Moreover, I shall present the design of a working UCC in the rule. It is both capable of computing any calculation (i.e. it is Turing-complete) and constructing most, if not all, of the constructible configurations within the rule. It cannot construct patterns which have no predecessor; neither can any machine in the rule (for obvious reasons). As such, it is more accurately a general constructor, rather than a universal constructor.

Exploring the concept of interaction computing through the discrete algebraic analysis of the Belousov-Zhabotinsky reaction.

PubMed

Dini, Paolo; Nehaniv, Chrystopher L; Egri-Nagy, Attila; Schilstra, Maria J

2013-05-01

Interaction computing (IC) aims to map the properties of integrable low-dimensional non-linear dynamical systems to the discrete domain of finite-state automata in an attempt to reproduce in software the self-organizing and dynamically stable properties of sub-cellular biochemical systems. As the work reported in this paper is still at the early stages of theory development it focuses on the analysis of a particularly simple chemical oscillator, the Belousov-Zhabotinsky (BZ) reaction. After retracing the rationale for IC developed over the past several years from the physical, biological, mathematical, and computer science points of view, the paper presents an elementary discussion of the Krohn-Rhodes decomposition of finite-state automata, including the holonomy decomposition of a simple automaton, and of its interpretation as an abstract positional number system. The method is then applied to the analysis of the algebraic properties of discrete finite-state automata derived from a simplified Petri net model of the BZ reaction. In the simplest possible and symmetrical case the corresponding automaton is, not surprisingly, found to contain exclusively cyclic groups. In a second, asymmetrical case, the decomposition is much more complex and includes five different simple non-abelian groups whose potential relevance arises from their ability to encode functionally complete algebras. The possible computational relevance of these findings is discussed and possible conclusions are drawn. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

The nature of turbulence in a triangular lattice gas automaton

NASA Astrophysics Data System (ADS)

Duong-Van, Minh; Feit, M. D.; Keller, P.; Pound, M.

1986-12-01

Power spectra calculated from the coarse-graining of a simple lattice gas automaton, and those of time averaging other stochastic times series that we have investigated, have exponents in the range -1.6 to -2, consistent with observation of fully developed turbulence. This power spectrum is a natural consequence of coarse-graining; the exponent -2 represents the continuum limit.

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

PubMed

Monteagudo, Ángel; Santos, José

2015-01-01

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

Solidification Microstructure, Segregation, and Shrinkage of Fe-Mn-C Twinning-Induced Plasticity Steel by Simulation and Experiment

NASA Astrophysics Data System (ADS)

Lan, Peng; Tang, Haiyan; Zhang, Jiaquan

2016-06-01

A 3D cellular automaton finite element model with full coupling of heat, flow, and solute transfer incorporating solidification grain nucleation and growth was developed for a multicomponent system. The predicted solidification process, shrinkage porosity, macrosegregation, grain orientation, and microstructure evolution of Fe-22Mn-0.7C twinning-induced plasticity (TWIP) steel match well with the experimental observation and measurement. Based on a new solute microsegregation model using the finite difference method, the thermophysical parameters including solid fraction, thermal conductivity, density, and enthalpy were predicted and compared with the results from thermodynamics and experiment. The effects of flow and solute transfer in the liquid phase on the solidification microstructure of Fe-22Mn-0.7C TWIP steel were compared numerically. Thermal convection decreases the temperature gradient in the liquid steel, leading to the enlargement of the equiaxed zone. Solute enrichment in front of the solid/liquid interface weakens the thermal convection, resulting in a little postponement of columnar-to-equiaxed transition (CET). The CET behavior of Fe-Mn-C TWIP steel during solidification was fully described and mathematically quantized by grain morphology statistics for the first time. A new methodology to figure out the CET location by linear regression of grain mean size with least-squares arithmetic was established, by which a composition design strategy for Fe-Mn-C TWIP steel according to solidification microstructure, matrix compactness, and homogeneity was developed.

Evolution and morphology of microenvironment-enhanced malignancy of three-dimensional invasive solid tumors

NASA Astrophysics Data System (ADS)

Jiao, Yang; Torquato, Salvatore

2013-05-01

The emergence of invasive and metastatic behavior in malignant tumors can often lead to fatal outcomes for patients. The collective malignant tumor behavior resulting from the complex tumor-host interactions and the interactions between the tumor cells is currently poorly understood. In this paper, we employ a cellular automaton (CA) model to investigate microenvironment-enhanced malignant behaviors and morphologies of in vitro avascular invasive solid tumors in three dimensions. Our CA model incorporates a variety of microscopic-scale tumor-host interactions, including the degradation of the extracellular matrix by the malignant cells, nutrient-driven cell migration, pressure buildup due to the deformation of the microenvironment by the growing tumor, and its effect on the local tumor-host interface stability. Moreover, the effects of cell-cell adhesion on tumor growth are explicitly taken into account. Specifically, we find that while strong cell-cell adhesion can suppress the invasive behavior of the tumors growing in soft microenvironments, cancer malignancy can be significantly enhanced by harsh microenvironmental conditions, such as exposure to high pressure levels. We infer from the simulation results a qualitative phase diagram that characterizes the expected malignant behavior of invasive solid tumors in terms of two competing malignancy effects: the rigidity of the microenvironment and cell-cell adhesion. This diagram exhibits phase transitions between noninvasive and invasive behaviors. We also discuss the implications of our results for the diagnosis, prognosis, and treatment of malignant tumors.

Path-preference cellular-automaton model for traffic flow through transit points and its application to the transcription process in human cells.

PubMed

Ohta, Yoshihiro; Nishiyama, Akinobu; Wada, Yoichiro; Ruan, Yijun; Kodama, Tatsuhiko; Tsuboi, Takashi; Tokihiro, Tetsuji; Ihara, Sigeo

2012-08-01

We all use path routing everyday as we take shortcuts to avoid traffic jams, or by using faster traffic means. Previous models of traffic flow of RNA polymerase II (RNAPII) during transcription, however, were restricted to one dimension along the DNA template. Here we report the modeling and application of traffic flow in transcription that allows preferential paths of different dimensions only restricted to visit some transit points, as previously introduced between the 5' and 3' end of the gene. According to its position, an RNAPII protein molecule prefers paths obeying two types of time-evolution rules. One is an asymmetric simple exclusion process (ASEP) along DNA, and the other is a three-dimensional jump between transit points in DNA where RNAPIIs are staying. Simulations based on our model, and comparison experimental results, reveal how RNAPII molecules are distributed at the DNA-loop-formation-related protein binding sites as well as CTCF insulator proteins (or exons). As time passes after the stimulation, the RNAPII density at these sites becomes higher. Apparent far-distance jumps in one dimension are realized by short-range three-dimensional jumps between DNA loops. We confirm the above conjecture by applying our model calculation to the SAMD4A gene by comparing the experimental results. Our probabilistic model provides possible scenarios for assembling RNAPII molecules into transcription factories, where RNAPII and related proteins cooperatively transcribe DNA.

An Automaton Analysis of the Learning of a Miniature System of Japanese. Psychology Series.

ERIC Educational Resources Information Center

Wexler, Kenneth Norman

The purpose of the study reported here was to do an automata-theoretical and experimental investigation of the learning of the syntax and semantics of a second natural language. The main thrust of the work was to ask what kind of automaton a person can become. Various kinds of automata were considered, predictions were made from them, and these…

Rough Finite State Automata and Rough Languages

NASA Astrophysics Data System (ADS)

Arulprakasam, R.; Perumal, R.; Radhakrishnan, M.; Dare, V. R.

2018-04-01

Sumita Basu [1, 2] recently introduced the concept of a rough finite state (semi)automaton, rough grammar and rough languages. Motivated by the work of [1, 2], in this paper, we investigate some closure properties of rough regular languages and establish the equivalence between the classes of rough languages generated by rough grammar and the classes of rough regular languages accepted by rough finite automaton.

Efficient coarse simulation of a growing avascular tumor

PubMed Central

Kavousanakis, Michail E.; Liu, Ping; Boudouvis, Andreas G.; Lowengrub, John; Kevrekidis, Ioannis G.

2013-01-01

The subject of this work is the development and implementation of algorithms which accelerate the simulation of early stage tumor growth models. Among the different computational approaches used for the simulation of tumor progression, discrete stochastic models (e.g., cellular automata) have been widely used to describe processes occurring at the cell and subcell scales (e.g., cell-cell interactions and signaling processes). To describe macroscopic characteristics (e.g., morphology) of growing tumors, large numbers of interacting cells must be simulated. However, the high computational demands of stochastic models make the simulation of large-scale systems impractical. Alternatively, continuum models, which can describe behavior at the tumor scale, often rely on phenomenological assumptions in place of rigorous upscaling of microscopic models. This limits their predictive power. In this work, we circumvent the derivation of closed macroscopic equations for the growing cancer cell populations; instead, we construct, based on the so-called “equation-free” framework, a computational superstructure, which wraps around the individual-based cell-level simulator and accelerates the computations required for the study of the long-time behavior of systems involving many interacting cells. The microscopic model, e.g., a cellular automaton, which simulates the evolution of cancer cell populations, is executed for relatively short time intervals, at the end of which coarse-scale information is obtained. These coarse variables evolve on slower time scales than each individual cell in the population, enabling the application of forward projection schemes, which extrapolate their values at later times. This technique is referred to as coarse projective integration. Increasing the ratio of projection times to microscopic simulator execution times enhances the computational savings. Crucial accuracy issues arising for growing tumors with radial symmetry are addressed by applying the coarse projective integration scheme in a cotraveling (cogrowing) frame. As a proof of principle, we demonstrate that the application of this scheme yields highly accurate solutions, while preserving the computational savings of coarse projective integration. PMID:22587128

Cellular automaton model of crowd evacuation inspired by slime mould

NASA Astrophysics Data System (ADS)

Kalogeiton, V. S.; Papadopoulos, D. P.; Georgilas, I. P.; Sirakoulis, G. Ch.; Adamatzky, A. I.

2015-04-01

In all the living organisms, the self-preservation behaviour is almost universal. Even the most simple of living organisms, like slime mould, is typically under intense selective pressure to evolve a response to ensure their evolution and safety in the best possible way. On the other hand, evacuation of a place can be easily characterized as one of the most stressful situations for the individuals taking part on it. Taking inspiration from the slime mould behaviour, we are introducing a computational bio-inspired model crowd evacuation model. Cellular Automata (CA) were selected as a fully parallel advanced computation tool able to mimic the Physarum's behaviour. In particular, the proposed CA model takes into account while mimicking the Physarum foraging process, the food diffusion, the organism's growth, the creation of tubes for each organism, the selection of optimum tube for each human in correspondence to the crowd evacuation under study and finally, the movement of all humans at each time step towards near exit. To test the model's efficiency and robustness, several simulation scenarios were proposed both in virtual and real-life indoor environments (namely, the first floor of office building B of the Department of Electrical and Computer Engineering of Democritus University of Thrace). The proposed model is further evaluated in a purely quantitative way by comparing the simulation results with the corresponding ones from the bibliography taken by real data. The examined fundamental diagrams of velocity-density and flow-density are found in full agreement with many of the already published corresponding results proving the adequacy, the fitness and the resulting dynamics of the model. Finally, several real Physarum experiments were conducted in an archetype of the aforementioned real-life environment proving at last that the proposed model succeeded in reproducing sufficiently the Physarum's recorded behaviour derived from observation of the aforementioned biological laboratory experiments.

Modeling dynamics of HIV infected cells using stochastic cellular automaton

NASA Astrophysics Data System (ADS)

Precharattana, Monamorn; Triampo, Wannapong

2014-08-01

Ever since HIV was first diagnosed in human, a great number of scientific works have been undertaken to explore the biological mechanisms involved in the infection and progression of the disease. Several cellular automata (CA) models have been introduced to gain insights into the dynamics of the disease progression but none of them has taken into account effects of certain immune cells such as the dendritic cells (DCs) and the CD8+ T lymphocytes (CD8+ T cells). In this work, we present a CA model, which incorporates effects of the HIV specific immune response focusing on the cell-mediated immunities, and investigate the interaction between the host immune response and the HIV infected cells in the lymph nodes. The aim of our work is to propose a model more realistic than the one in Precharattana et al. (2010) [10], by incorporating roles of the DCs, the CD4+ T cells, and the CD8+ T cells into the model so that it would reproduce the HIV infection dynamics during the primary phase of HIV infection.

Spatial patterns and scale freedom in Prisoner's Dilemma cellular automata with Pavlovian strategies

NASA Astrophysics Data System (ADS)

Fort, H.; Viola, S.

2005-01-01

A cellular automaton in which cells represent agents playing the Prisoner's Dilemma (PD) game following the simple 'win—stay, lose—shift' strategy is studied. Individuals with binary behaviour, such that they can either cooperate (C) or defect (D), play repeatedly with their neighbours (Von Neumann's and Moore's neighbourhoods). Their utilities in each round of the game are given by a rescaled pay-off matrix described by a single parameter τ, which measures the ratio of temptation to defect to reward for cooperation. Depending on the region of the parameter space τ, the system self-organizes—after a transient—into dynamical equilibrium states characterized by different definite fractions of C agents \\bar {c}_\\infty (two states for the von Neumann neighbourhood and four for the Moore neighbourhood). For some ranges of τ the cluster size distributions, the power spectra P(f) and the perimeter-area curves follow power law scalings. Percolation below threshold is also found for D agent clusters. We also analyse the asynchronous dynamics version of this model and compare results.

Traffic dynamics around weaving section influenced by accident: Cellular automata approach

NASA Astrophysics Data System (ADS)

Kong, Lin-Peng; Li, Xin-Gang; Lam, William H. K.

2015-07-01

The weaving section, as a typical bottleneck, is one source of vehicle conflicts and an accident-prone area. Traffic accident will block lanes and the road capacity will be reduced. Several models have been established to study the dynamics around traffic bottlenecks. However, little attention has been paid to study the complex traffic dynamics influenced by the combined effects of bottleneck and accident. This paper presents a cellular automaton model to characterize accident-induced traffic behavior around the weaving section. Some effective control measures are proposed and verified for traffic management under accident condition. The total flux as a function of inflow rates, the phase diagrams, the spatial-temporal diagrams, and the density and velocity profiles are presented to analyze the impact of accident. It was shown that the proposed control measures for weaving traffic can improve the capacity of weaving section under both normal and accident conditions; the accidents occurring on median lane in the weaving section are more inclined to cause traffic jam and reduce road capacity; the capacity of weaving section will be greatly reduced when the accident happens downstream the weaving section.

Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation

NASA Astrophysics Data System (ADS)

Chen, Jingxu; Li, Zhibin; Jiang, Hang; Zhu, Senlai; Wang, Wei

2017-02-01

In recent years, many bicycle lanes on urban streets are replaced with vehicle parking places. Spaces for bicycle riding are reduced, resulting in changes in bicycle and vehicle operational features. The objective of this study is to estimate the impacts of on-street parking on heterogeneous traffic operation on urban streets. A cellular automaton (CA) model is developed and calibrated to simulate bicycle lane-changing on streets with on-street parking. Two types of street segments with different bicycle lane width are considered. From the simulation, two types of conflicts between bicycles and vehicles are identified which are frictional conflicts and blocking conflicts. Factors affecting the frequency of conflicts are also identified. Based on the results, vehicle delay is estimated for various traffic situations considering the range of occupancy levels for on-street parking. Later, a numerical network example is analyzed to estimate the network impact of on-street parking on traffic assignment and operation. Findings of the study are helpful to policies and design regarding on-street vehicle parking to improve the efficiency of traffic operations.

Towards implementation of cellular automata in Microbial Fuel Cells.

PubMed

Tsompanas, Michail-Antisthenis I; Adamatzky, Andrew; Sirakoulis, Georgios Ch; Greenman, John; Ieropoulos, Ioannis

2017-01-01

The Microbial Fuel Cell (MFC) is a bio-electrochemical transducer converting waste products into electricity using microbial communities. Cellular Automaton (CA) is a uniform array of finite-state machines that update their states in discrete time depending on states of their closest neighbors by the same rule. Arrays of MFCs could, in principle, act as massive-parallel computing devices with local connectivity between elementary processors. We provide a theoretical design of such a parallel processor by implementing CA in MFCs. We have chosen Conway's Game of Life as the 'benchmark' CA because this is the most popular CA which also exhibits an enormously rich spectrum of patterns. Each cell of the Game of Life CA is realized using two MFCs. The MFCs are linked electrically and hydraulically. The model is verified via simulation of an electrical circuit demonstrating equivalent behaviours. The design is a first step towards future implementations of fully autonomous biological computing devices with massive parallelism. The energy independence of such devices counteracts their somewhat slow transitions-compared to silicon circuitry-between the different states during computation.

Towards implementation of cellular automata in Microbial Fuel Cells

PubMed Central

Adamatzky, Andrew; Sirakoulis, Georgios Ch.; Greenman, John; Ieropoulos, Ioannis

2017-01-01

The Microbial Fuel Cell (MFC) is a bio-electrochemical transducer converting waste products into electricity using microbial communities. Cellular Automaton (CA) is a uniform array of finite-state machines that update their states in discrete time depending on states of their closest neighbors by the same rule. Arrays of MFCs could, in principle, act as massive-parallel computing devices with local connectivity between elementary processors. We provide a theoretical design of such a parallel processor by implementing CA in MFCs. We have chosen Conway’s Game of Life as the ‘benchmark’ CA because this is the most popular CA which also exhibits an enormously rich spectrum of patterns. Each cell of the Game of Life CA is realized using two MFCs. The MFCs are linked electrically and hydraulically. The model is verified via simulation of an electrical circuit demonstrating equivalent behaviours. The design is a first step towards future implementations of fully autonomous biological computing devices with massive parallelism. The energy independence of such devices counteracts their somewhat slow transitions—compared to silicon circuitry—between the different states during computation. PMID:28498871

Survival of mutations arising during invasions

PubMed Central

Miller, Judith R

2010-01-01

When a neutral mutation arises in an invading population, it quickly either dies out or ‘surfs’, i.e. it comes to occupy almost all the habitat available at its time of origin. Beneficial mutations can also surf, as can deleterious mutations over finite time spans. We develop descriptive statistical models that quantify the relationship between the probability that a mutation will surf and demographic parameters for a cellular automaton model of surfing. We also provide a simple analytic model that performs well at predicting the probability of surfing for neutral and beneficial mutations in one dimension. The results suggest that factors – possibly including even abiotic factors – that promote invasion success may also increase the probability of surfing and associated adaptive genetic change, conditioned on such success. PMID:25567912

Predicting spatio-temporal failure in large scale observational and micro scale experimental systems

NASA Astrophysics Data System (ADS)

de las Heras, Alejandro; Hu, Yong

2006-10-01

Forecasting has become an essential part of modern thought, but the practical limitations still are manifold. We addressed future rates of change by comparing models that take into account time, and models that focus more on space. Cox regression confirmed that linear change can be safely assumed in the short-term. Spatially explicit Poisson regression, provided a ceiling value for the number of deforestation spots. With several observed and estimated rates, it was decided to forecast using the more robust assumptions. A Markov-chain cellular automaton thus projected 5-year deforestation in the Amazonian Arc of Deforestation, showing that even a stable rate of change would largely deplete the forest area. More generally, resolution and implementation of the existing models could explain many of the modelling difficulties still affecting forecasting.

The Ring of Fire: The Effects of Slope upon Pattern Formation in Simulated Forest Fire Systems

NASA Astrophysics Data System (ADS)

Morillo, Robin; Manz, Niklas

We report about spreading fire fronts under sloped conditions using the general cellular automaton model and data from physical scaled-down experiments. Punckt et al. published experimental and computational results for planar systems and our preliminary results confirmed the expected speed-slope dependence of fire fronts propagating up or down the hill with a cut-off slope value above which no fire front can exist. Here we focus on two fascinating structures in reaction-diffusion systems: circular expanding target pattern and rotating spirals. We investigated the behaviors of both structures with varied values for the slope of the forest and the homogeneity of the trees. For both variables, a range of values was found for which target pattern or spiral formation was possible.

Velocity statistics of the Nagel-Schreckenberg model

NASA Astrophysics Data System (ADS)

Bain, Nicolas; Emig, Thorsten; Ulm, Franz-Josef; Schreckenberg, Michael

2016-02-01

The statistics of velocities in the cellular automaton model of Nagel and Schreckenberg for traffic are studied. From numerical simulations, we obtain the probability distribution function (PDF) for vehicle velocities and the velocity-velocity (vv) covariance function. We identify the probability to find a standing vehicle as a potential order parameter that signals nicely the transition between free congested flow for a sufficiently large number of velocity states. Our results for the vv covariance function resemble features of a second-order phase transition. We develop a 3-body approximation that allows us to relate the PDFs for velocities and headways. Using this relation, an approximation to the velocity PDF is obtained from the headway PDF observed in simulations. We find a remarkable agreement between this approximation and the velocity PDF obtained from simulations.

Velocity statistics of the Nagel-Schreckenberg model.

PubMed

Bain, Nicolas; Emig, Thorsten; Ulm, Franz-Josef; Schreckenberg, Michael

2016-02-01

The statistics of velocities in the cellular automaton model of Nagel and Schreckenberg for traffic are studied. From numerical simulations, we obtain the probability distribution function (PDF) for vehicle velocities and the velocity-velocity (vv) covariance function. We identify the probability to find a standing vehicle as a potential order parameter that signals nicely the transition between free congested flow for a sufficiently large number of velocity states. Our results for the vv covariance function resemble features of a second-order phase transition. We develop a 3-body approximation that allows us to relate the PDFs for velocities and headways. Using this relation, an approximation to the velocity PDF is obtained from the headway PDF observed in simulations. We find a remarkable agreement between this approximation and the velocity PDF obtained from simulations.

Detachment and diffusive-convective transport in an evolving heterogeneous two-dimensional biofilm hybrid model.

PubMed

Luna, E; Domínguez-Zacarias, G; Ferreira, C Pio; Velasco-Hernandez, J X

2004-12-01

Under the hypothesis of correlation between biofilm survival and nutrient availability, by considering fluid drag forces and mortality due to nutrient depletion, a biofilm detachment/breaking condition is derived. The mechanisms leading to biofilm detachment/breaking are discussed. We construct and describe a hybrid model for a heterogeneous biofilm attached to walls in a channel where liquid is flowing. The model is called hybrid because it couples conservation equations with a cellular automaton. The biofilm layer is viewed as a porous medium with variable porosity, tortuosity, and permeability. The model is solved using asymptotic and finite differences methods. Results for porosity, nutrient distribution, and average surface location are presented. The model is capable of reproducing biofilm heterogeneity as well as the typical surface fingering (mushroomlike structure).

Optimization of the Design of Pre-Signal System Using Improved Cellular Automaton

PubMed Central

Li, Yan; Li, Ke; Tao, Siran; Chen, Kuanmin

2014-01-01

The pre-signal system can improve the efficiency of intersection approach under rational design. One of the main obstacles in optimizing the design of pre-signal system is that driving behaviors in the sorting area cannot be well evaluated. The NaSch model was modified by considering slow probability, turning-deceleration rules, and lane changing rules. It was calibrated with field observed data to explore the interactions among design parameters. The simulation results of the proposed model indicate that the length of sorting area, traffic demand, signal timing, and lane allocation are the most important influence factors. The recommendations of these design parameters are demonstrated. The findings of this paper can be foundations for the design of pre-signal system and show promising improvement in traffic mobility. PMID:25435871

Origins of Life: Open Questions and Debates

NASA Astrophysics Data System (ADS)

Brack, André

2017-10-01

Stanley Miller demonstrated in 1953 that it was possible to form amino acids from methane, ammonia, and hydrogen in water, thus launching the ambitious hope that chemists would be able to shed light on the origins of life by recreating a simple life form in a test tube. However, it must be acknowledged that the dream has not yet been accomplished, despite the great volume of effort and innovation put forward by the scientific community. A minima, primitive life can be defined as an open chemical system, fed with matter and energy, capable of self-reproduction (i.e., making more of itself by itself), and also capable of evolving. The concept of evolution implies that chemical systems would transfer their information fairly faithfully but make some random errors. If we compared the components of primitive life to parts of a chemical automaton, we could conceive that, by chance, some parts self-assembled to generate an automaton capable of assembling other parts to produce a true copy. Sometimes, minor errors in the building generated a more efficient automaton, which then became the dominant species. Quite different scenarios and routes have been followed and tested in the laboratory to explain the origin of life. There are two schools of thought in proposing the prebiotic supply of organics. The proponents of a metabolism-first call for the spontaneous formation of simple molecules from carbon dioxide and water to rapidly generate life. In a second hypothesis, the primeval soup scenario, it is proposed that rather complex organic molecules accumulated in a warm little pond prior to the emergence of life. The proponents of the primeval soup or replication first approach are by far the more active. They succeeded in reconstructing small-scale versions of proteins, membranes, and RNA. Quite different scenarios have been proposed for the inception of life: the RNA world, an origin within droplets, self-organization counteracting entropy, or a stochastic approach merging chemistry and geology. Understanding the emergence of a critical feature of life, its one-handedness, is a shared preoccupation in all these approaches.

A Pipelined Non-Deterministic Finite Automaton-Based String Matching Scheme Using Merged State Transitions in an FPGA

PubMed Central

Choi, Kang-Il

2016-01-01

This paper proposes a pipelined non-deterministic finite automaton (NFA)-based string matching scheme using field programmable gate array (FPGA) implementation. The characteristics of the NFA such as shared common prefixes and no failure transitions are considered in the proposed scheme. In the implementation of the automaton-based string matching using an FPGA, each state transition is implemented with a look-up table (LUT) for the combinational logic circuit between registers. In addition, multiple state transitions between stages can be performed in a pipelined fashion. In this paper, it is proposed that multiple one-to-one state transitions, called merged state transitions, can be performed with an LUT. By cutting down the number of used LUTs for implementing state transitions, the hardware overhead of combinational logic circuits is greatly reduced in the proposed pipelined NFA-based string matching scheme. PMID:27695114

A Pipelined Non-Deterministic Finite Automaton-Based String Matching Scheme Using Merged State Transitions in an FPGA.

PubMed

Kim, HyunJin; Choi, Kang-Il

2016-01-01

This paper proposes a pipelined non-deterministic finite automaton (NFA)-based string matching scheme using field programmable gate array (FPGA) implementation. The characteristics of the NFA such as shared common prefixes and no failure transitions are considered in the proposed scheme. In the implementation of the automaton-based string matching using an FPGA, each state transition is implemented with a look-up table (LUT) for the combinational logic circuit between registers. In addition, multiple state transitions between stages can be performed in a pipelined fashion. In this paper, it is proposed that multiple one-to-one state transitions, called merged state transitions, can be performed with an LUT. By cutting down the number of used LUTs for implementing state transitions, the hardware overhead of combinational logic circuits is greatly reduced in the proposed pipelined NFA-based string matching scheme.

Fuzzy automata and pattern matching

NASA Technical Reports Server (NTRS)

Setzer, C. B.; Warsi, N. A.

1986-01-01

A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.

Monitoring with Data Automata

NASA Technical Reports Server (NTRS)

Havelund, Klaus

2014-01-01

We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.

Recurrence time statistics of landslide events simulated by a cellular automaton model

NASA Astrophysics Data System (ADS)

Piegari, Ester; Di Maio, Rosa; Avella, Adolfo

2014-05-01

The recurrence time statistics of a cellular automaton modelling landslide events is analyzed by performing a numerical analysis in the parameter space and estimating Fano factor behaviors. The model is an extended version of the OFC model, which is a paradigm for SOC in non-conserved systems, but it works differently from the original OFC model as a finite value of the driving rate is applied. By driving the system to instability with different rates, the model exhibits a smooth transition from a correlated to an uncorrelated regime as the effect of a change in predominant mechanisms to propagate instability. If the rate at which instability is approached is small, chain processes dominate the landslide dynamics, and power laws govern probability distributions. However, the power-law regime typical of SOC-like systems is found in a range of return intervals that becomes shorter and shorter by increasing the values of the driving rates. Indeed, if the rates at which instability is approached are large, domino processes are no longer active in propagating instability, and large events simply occur because a large number of cells simultaneously reach instability. Such a gradual loss of the effectiveness of the chain propagation mechanism causes the system gradually enter to an uncorrelated regime where recurrence time distributions are characterized by Weibull behaviors. Simulation results are qualitatively compared with those from a recent analysis performed by Witt et al.(Earth Surf. Process. Landforms, 35, 1138, 2010) for the first complete databases of landslide occurrences over a period as large as fifty years. From the comparison with the extensive landslide data set, the numerical analysis suggests that statistics of such landslide data seem to be described by a crossover region between a correlated regime and an uncorrelated regime, where recurrence time distributions are characterized by power-law and Weibull behaviors for short and long return times, respectively. Finally, in such a region of the parameter space, clear indications of temporal correlations and clustering by the Fano factor behaviors support, at least in part, the analysis performed by Witt et al. (2010).

Multi Car Elevator Control by using Learning Automaton

NASA Astrophysics Data System (ADS)

Shiraishi, Kazuaki; Hamagami, Tomoki; Hirata, Hironori

We study an adaptive control technique for multi car elevators (MCEs) by adopting learning automatons (LAs.) The MCE is a high performance and a near-future elevator system with multi shafts and multi cars. A strong point of the system is that realizing a large carrying capacity in small shaft area. However, since the operation is too complicated, realizing an efficient MCE control is difficult for top-down approaches. For example, “bunching up together" is one of the typical phenomenon in a simple traffic environment like the MCE. Furthermore, an adapting to varying environment in configuration requirement is a serious issue in a real elevator service. In order to resolve these issues, having an autonomous behavior is required to the control system of each car in MCE system, so that the learning automaton, as the solutions for this requirement, is supposed to be appropriate for the simple traffic control. First, we assign a stochastic automaton (SA) to each car control system. Then, each SA varies its stochastic behavior distributions for adapting to environment in which its policy is evaluated with each passenger waiting times. That is LA which learns the environment autonomously. Using the LA based control technique, the MCE operation efficiency is evaluated through simulation experiments. Results show the technique enables reducing waiting times efficiently, and we confirm the system can adapt to the dynamic environment.

Effect of Solute Diffusion on Dendrite Growth in the Molten Pool of Al-Cu Alloy

NASA Astrophysics Data System (ADS)

Zhan, Xiaohong; Gu, Cheng; Liu, Yun; Wei, Yanhong

2017-10-01

A cellular automaton (CA)-finite difference model is developed to simulate dendrite growth and solute diffusion during solidification process in the molten pool of Al-Cu alloy. In order to explain the interaction between the dendritic growth and solute distribution, a series of CA simulations with different solute diffusion velocity coefficients are carried out. It is concluded that the solute concentration increases with dendrite growing and solute accumulation in the dendrite tip. Converged value of the dendrite tip growth velocity is about 480 μm/s if the mesh size is refined to 2 μm or less. Growth of the primary dendrite and the secondary dendrite is mainly influenced by solute diffusion at the dendrite tips. And growth of secondary and tertiary dendrites is mainly influenced by solute diffusion at interdendrite.

Extinction threshold for spatial forest dynamics with height structure.

PubMed

Garcia-Domingo, Josep L; Saldaña, Joan

2011-05-07

We present a pair-approximation model for spatial forest dynamics defined on a regular lattice. The model assumes three possible states for a lattice site: empty (gap site), occupied by an immature tree, and occupied by a mature tree, and considers three nonlinearities in the dynamics associated to the processes of light interference, gap expansion, and recruitment. We obtain an expression of the basic reproduction number R(0) which, in contrast to the one obtained under the mean-field approach, uses information about the spatial arrangement of individuals close to extinction. Moreover, we analyze the corresponding survival-extinction transition of the forest and the spatial correlations among gaps, immature and mature trees close to this critical point. Predictions of the pair-approximation model are compared with those of a cellular automaton. Copyright © 2011 Elsevier Ltd. All rights reserved.

Synchronization of DNA array replication kinetics

NASA Astrophysics Data System (ADS)

Manturov, Alexey O.; Grigoryev, Anton V.

2016-04-01

In the present work we discuss the features of the DNA replication kinetics at the case of multiplicity of simultaneously elongated DNA fragments. The interaction between replicated DNA fragments is carried out by free protons that appears at the every nucleotide attachment at the free end of elongated DNA fragment. So there is feedback between free protons concentration and DNA-polymerase activity that appears as elongation rate dependence. We develop the numerical model based on a cellular automaton, which can simulate the elongation stage (growth of DNA strands) for DNA elongation process with conditions pointed above and we study the possibility of the DNA polymerases movement synchronization. The results obtained numerically can be useful for DNA polymerase movement detection and visualization of the elongation process in the case of massive DNA replication, eg, under PCR condition or for DNA "sequencing by synthesis" sequencing devices evaluation.

Competitive intransitivity promotes species coexistence.

PubMed

Laird, Robert A; Schamp, Brandon S

2006-08-01

Using a spatially explicit cellular automaton model with local competition, we investigate the potential for varied levels of competitive intransitivity (i.e., nonhierarchical competition) to promote species coexistence. As predicted, on average, increased levels of intransitivity result in more sustained coexistence within simulated communities, although the outcome of competition also becomes increasingly unpredictable. Interestingly, even a moderate degree of intransitivity within a community can promote coexistence, in terms of both the length of time until the first competitive exclusion and the number of species remaining in the community after 500 simulated generations. These results suggest that modest levels of intransitivity in nature, such as those that are thought to be characteristic of plant communities, can contribute to coexistence and, therefore, community-scale biodiversity. We explore a potential connection between competitive intransitivity and neutral theory, whereby competitive intransitivity may represent an important mechanism for "ecological equivalence."

Power-law rheology controls aftershock triggering and decay

PubMed Central

Zhang, Xiaoming; Shcherbakov, Robert

2016-01-01

The occurrence of aftershocks is a signature of physical systems exhibiting relaxation phenomena. They are observed in various natural or experimental systems and usually obey several non-trivial empirical laws. Here we consider a cellular automaton realization of a nonlinear viscoelastic slider-block model in order to infer the physical mechanisms of triggering responsible for the occurrence of aftershocks. We show that nonlinear viscoelasticity plays a critical role in the occurrence of aftershocks. The model reproduces several empirical laws describing the statistics of aftershocks. In case of earthquakes, the proposed model suggests that the power-law rheology of the fault gauge, underlying lower crust, and upper mantle controls the decay rate of aftershocks. This is verified by analysing several prominent aftershock sequences for which the rheological properties of the underlying crust and upper mantle were established. PMID:27819355

Microstructural evolution during the homogenization heat treatment of 6XXX and 7XXX aluminum alloys

NASA Astrophysics Data System (ADS)

Priya, Pikee

Homogenization heat treatment of as-cast billets is an important step in the processing of aluminum extrusions. Microstructural evolution during homogenization involves elimination of the eutectic morphology by spheroidisation of the interdendritic phases, minimization of the microsegregation across the grains through diffusion, dissolution of the low-melting phases, which enhances the surface finish of the extrusions, and precipitation of nano-sized dispersoids (for Cr-, Zr-, Mn-, Sc-containing alloys), which inhibit grain boundary motion to prevent recrystallization. Post-homogenization cooling reprecipitates some of the phases, changing the flow stress required for subsequent extrusion. These precipitates, however, are deleterious for the mechanical properties of the alloy and also hamper the age-hardenability and are hence dissolved during solution heat treatment. Microstructural development during homogenization and subsequent cooling occurs both at the length scale of the Secondary Dendrite Arm Spacing (SDAS) in micrometers and dispersoids in nanometers. Numerical tools to simulate microstructural development at both the length scales have been developed and validated against experiments. These tools provide easy and convenient means to study the process. A Cellular Automaton-Finite Volume-based model for evolution of interdendritic phases is coupled with a Particle Size Distribution-based model for precipitation of dispersoids across the grain. This comprehensive model has been used to study the effect of temperature, composition, as-cast microstructure, and cooling rates during post-homogenization quenching on microstructural evolution. The numerical study has been complimented with experiments involving Scanning Electron Microscopy, Energy Dispersive Spectroscopy, X-Ray Diffraction and Differential Scanning Calorimetry and a good agreement has with numerical results has been found. The current work aims to study the microstructural evolution during homogenization heat treatment at both length scales which include the (i) dissolution and transformation of the as-cast secondary phases; (ii) precipitation of dispersoids; and (iii) reprecipitation of some of the secondary phases during post-homogenization cooling. The kinetics of the phase transformations are mostly diffusion controlled except for the eta to S phase transformation in 7XXX alloys which is interface reaction rate controlled which has been implemented using a novel approach. Recommendations for homogenization temperature, time, cooling rates and compositions are made for Al-Si-Mg-Fe-Mn and Al-Zn-Cu-Mg-Zr alloys. The numerical model developed has been applied for a through process solidification-homogenization modeling of a Direct-Chill cast AA7050 cylindrical billet to study the radial variation of microstructure after solidification, homogenization and post-homogenization cooling.

Simulating Flaring Events via an Intelligent Cellular Automata Mechanism

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Vlahos, L.; Isliker, H.; Georgoulis, M.

2010-07-01

We simulate flaring events through a Cellular Automaton (CA) model, in which, for the first time, we use observed vector magnetograms as initial conditions. After non-linear force free extrapolation of the magnetic field from the vector magnetograms, we identify magnetic discontinuities, using two alternative criteria: (1) the average magnetic field gradient, or (2) the normalized magnetic field curl (i.e. the current). Magnetic discontinuities are identified at the grid-sites where the magnetic field gradient or curl exceeds a specified threshold. We then relax the magnetic discontinuities according to the rules of Lu and Hamilton (1991) or Lu et al. (1993), i.e. we redistribute the magnetic field locally so that the discontinuities disappear. In order to simulate the flaring events, we consider several alternative scenarios with regard to: (1) The threshold above which magnetic discontinuities are identified (applying low, high, and height-dependent threshold values); (2) The driving process that occasionally causes new discontinuities (at randomly chosen grid sites, magnetic field increments are added that are perpendicular (or may-be also parallel) to the existing magnetic field). We address the question whether the coronal active region magnetic fields can indeed be considered to be in the state of self-organized criticality (SOC).

Faster and exact implementation of the continuous cellular automaton for anisotropic etching simulations

NASA Astrophysics Data System (ADS)

Ferrando, N.; Gosálvez, M. A.; Cerdá, J.; Gadea, R.; Sato, K.

2011-02-01

The current success of the continuous cellular automata for the simulation of anisotropic wet chemical etching of silicon in microengineering applications is based on a relatively fast, approximate, constant time stepping implementation (CTS), whose accuracy against the exact algorithm—a computationally slow, variable time stepping implementation (VTS)—has not been previously analyzed in detail. In this study we show that the CTS implementation can generate moderately wrong etch rates and overall etching fronts, thus justifying the presentation of a novel, exact reformulation of the VTS implementation based on a new state variable, referred to as the predicted removal time (PRT), and the use of a self-balanced binary search tree that enables storage and efficient access to the PRT values in each time step in order to quickly remove the corresponding surface atom/s. The proposed PRT method reduces the simulation cost of the exact implementation from {O}(N^{5/3}) to {O}(N^{3/2} log N) without introducing any model simplifications. This enables more precise simulations (only limited by numerical precision errors) with affordable computational times that are similar to the less precise CTS implementation and even faster for low reactivity systems.

Convergence Time and Phase Transition in a Non-monotonic Family of Probabilistic Cellular Automata

NASA Astrophysics Data System (ADS)

Ramos, A. D.; Leite, A.

2017-08-01

In dynamical systems, some of the most important questions are related to phase transitions and convergence time. We consider a one-dimensional probabilistic cellular automaton where their components assume two possible states, zero and one, and interact with their two nearest neighbors at each time step. Under the local interaction, if the component is in the same state as its two neighbors, it does not change its state. In the other cases, a component in state zero turns into a one with probability α , and a component in state one turns into a zero with probability 1-β . For certain values of α and β , we show that the process will always converge weakly to δ 0, the measure concentrated on the configuration where all the components are zeros. Moreover, the mean time of this convergence is finite, and we describe an upper bound in this case, which is a linear function of the initial distribution. We also demonstrate an application of our results to the percolation PCA. Finally, we use mean-field approximation and Monte Carlo simulations to show coexistence of three distinct behaviours for some values of parameters α and β.

A two-lane cellular automaton traffic flow model with the influence of driver, vehicle and road

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Nie, Cen; Li, Jing-Ru; Wei, Yu-Ao

2016-07-01

On the basis of one-lane comfortable driving model, this paper established a two-lane traffic cellular automata model, which improves the slow randomization effected by brake light. Considering the driver psychological characteristics and mixed traffic, we studied the lateral influence between vehicles on adjacent lanes. Through computer simulation, the space-time diagram and the fundamental figure under different conditions are obtained. The study found that aggressive driver makes a slight congestion in low-density traffic and improves the capacity of high-density traffic, when the density exceeds 20pcu/km the more aggressive drivers the greater the flow, when the density below 40pcu/km driver character makes an effect, the more cautious driver, the lower the flow. The ratio of big cars has the same effect as the ratio of aggressive drivers. Brake lights have the greatest impact on traffic flow and when the density exceeds 10pcu/km the traffic flow fluctuates. Under periodic boundary conditions, the disturbance of road length on traffic is minimal. The lateral influence only play a limited role in the medium-density conditions, and only affect the average speed of traffic at low density.

Noisy transcription factor NF-κB oscillations stabilize and sensitize cytokine signaling in space

NASA Astrophysics Data System (ADS)

Gangstad, Sirin W.; Feldager, Cilie W.; Juul, Jeppe; Trusina, Ala

2013-02-01

NF-κB is a major transcription factor mediating inflammatory response. In response to a pro-inflammatory stimulus, it exhibits a characteristic response—a pulse followed by noisy oscillations in concentrations of considerably smaller amplitude. NF-κB is an important mediator of cellular communication, as it is both activated by and upregulates production of cytokines, signals used by white blood cells to find the source of inflammation. While the oscillatory dynamics of NF-κB has been extensively investigated both experimentally and theoretically, the role of the noise and the lower secondary amplitude has not been addressed. We use a cellular automaton model to address these issues in the context of spatially distributed communicating cells. We find that noisy secondary oscillations stabilize concentric wave patterns, thus improving signal quality. Furthermore, both lower secondary amplitude as well as noise in the oscillation period might be working against chronic inflammation, the state of self-sustained and stimulus-independent excitations. Our findings suggest that the characteristic irregular secondary oscillations of lower amplitude are not accidental. On the contrary, they might have evolved to increase robustness of the inflammatory response and the system's ability to return to a pre-stimulated state.

On the Nature of Design

NASA Astrophysics Data System (ADS)

Valverde, Sergi; Solé, Ricard V.

At the attention of scientist, philosophers and layman alike. It was so extraordinary in fact that even today we are fascinated by it and by the no less uncommon people who got involved. The subject of this story was an amazing machine, more precisely an automaton. Known as the Turk, it was a mechanical chess player, made of wood and dressed in a Turkish-like costume (see Fig. 1). It played chess with Napoleon, inspired Charles Babbage and moved the great Edgar Allan Poe to write a critical essay about the nature of the automaton [1].

Evacuation simulation with consideration of obstacle removal and using game theory

NASA Astrophysics Data System (ADS)

Lin, Guan-Wen; Wong, Sai-Keung

2018-06-01

In this paper, we integrate a cellular automaton model with game theory to simulate crowd evacuation from a room with consideration of obstacle removal. The room has one or more exits, one of which is blocked by obstacles. The obstacles at the exit can be removed by volunteers. We investigate the cooperative and defective behaviors of pedestrians during evacuation. The yielder game and volunteer's dilemma game are employed to resolve interpedestrian conflict. An anticipation floor field is proposed to guide the pedestrians to avoid obstacles that are being removed. We conducted experiments to determine how a variety of conditions affect overall crowd evacuation and volunteer evacuation times. The conditions were the start time of obstacle removal, number of obstacles, placement of obstacles, time spent in obstacle removal, strength of the anticipation floor field, and obstacle visibility distance. We demonstrate how reciprocity can be achieved among pedestrians and increases the efficiency of the entire evacuation process.

Influence of the Investor's Behavior on the Complexity of the Stock Market

NASA Astrophysics Data System (ADS)

Atman, A. P. F.; Gonçalves, Bruna Amin

2012-04-01

One of the pillars of the finance theory is the efficient-market hypothesis, which is used to analyze the stock market. However, in recent years, this hypothesis has been questioned by a number of studies showing evidence of unusual behaviors in the returns of financial assets ("anomalies") caused by behavioral aspects of the economic agents. Therefore, it is time to initiate a debate about the efficient-market hypothesis and the "behavioral finances." We here introduce a cellular automaton model to study the stock market complexity, considering different behaviors of the economical agents. From the analysis of the stationary standard of investment observed in the simulations and the Hurst exponents obtained for the term series of stock index, we draw conclusions concerning the complexity of the model compared to real markets. We also investigate which conditions of the investors are able to influence the efficient market hypothesis statements.

Advances in multi-scale modeling of solidification and casting processes

NASA Astrophysics Data System (ADS)

Liu, Baicheng; Xu, Qingyan; Jing, Tao; Shen, Houfa; Han, Zhiqiang

2011-04-01

The development of the aviation, energy and automobile industries requires an advanced integrated product/process R&D systems which could optimize the product and the process design as well. Integrated computational materials engineering (ICME) is a promising approach to fulfill this requirement and make the product and process development efficient, economic, and environmentally friendly. Advances in multi-scale modeling of solidification and casting processes, including mathematical models as well as engineering applications are presented in the paper. Dendrite morphology of magnesium and aluminum alloy of solidification process by using phase field and cellular automaton methods, mathematical models of segregation of large steel ingot, and microstructure models of unidirectionally solidified turbine blade casting are studied and discussed. In addition, some engineering case studies, including microstructure simulation of aluminum casting for automobile industry, segregation of large steel ingot for energy industry, and microstructure simulation of unidirectionally solidified turbine blade castings for aviation industry are discussed.

Time-based Reconstruction of Free-streaming Data in CBM

NASA Astrophysics Data System (ADS)

Akishina, Valentina; Kisel, Ivan; Vassiliev, Iouri; Zyzak, Maksym

2018-02-01

Traditional latency-limited trigger architectures typical for conventional experiments are inapplicable for the CBM experiment. Instead, CBM will ship and collect time-stamped data into a readout buffer in a form of a time-slice of a certain length and deliver it to a large computer farm, where online event reconstruction and selection will be performed. Grouping measurements into physical collisions must be performed in software and requires reconstruction not only in space, but also in time, the so-called 4-dimensional track reconstruction and event building. The tracks, reconstructed with 4D Cellular Automaton track finder, are combined into event-corresponding clusters according to the estimated time in the target position and the errors, obtained with the Kalman Filter method. The reconstructed events are given as inputs to the KF Particle Finder package for short-lived particle reconstruction. The results of time-based reconstruction of simulated collisions in CBM are presented and discussed in details.

Collective Traffic-like Movement of Ants on a Trail: Dynamical Phases and Phase Transitions

NASA Astrophysics Data System (ADS)

Kunwar, Ambarish; John, Alexander; Nishinari, Katsuhiro; Schadschneider, Andreas; Chowdhury, Debashish

2004-11-01

The traffic-like collective movement of ants on a trail can be described by a stochastic cellular automaton model. We have earlier investigated its unusual flow-density relation by using various mean field approximations and computer simulations. In this paper, we study the model following an alternative approach based on the analogy with the zero range process, which is one of the few known exactly solvable stochastic dynamical models. We show that our theory can quantitatively account for the unusual non-monotonic dependence of the average speed of the ants on their density for finite lattices with periodic boundary conditions. Moreover, we argue that the model exhibits a continuous phase transition at the critial density only in a limiting case. Furthermore, we investigate the phase diagram of the model by replacing the periodic boundary conditions by open boundary conditions.

Social dilemma structure hidden behind traffic flow with route selection

NASA Astrophysics Data System (ADS)

Tanimoto, Jun; Nakamura, Kousuke

2016-10-01

Several traffic flows contain social dilemma structures. Herein, we explored a route-selection problem using a cellular automaton simulation dovetailed with evolutionary game theory. In our model, two classes of driver-agents coexist: D agents (defective strategy), which refer to traffic information for route selection to move fast, and C agents (cooperative strategy), which are insensitive to information and less inclined to move fast. Although no evidence suggests that the social dilemma structure in low density causes vehicles to move freely and that in high density causes traffic jams, we found a structure that corresponds to an n-person (multiplayer) Chicken (n-Chicken) game if the provided traffic information is inappropriate. If appropriate traffic information is given to the agents, the n-Chicken game can be solved. The information delivered to vehicles is crucial for easing the social dilemma due to urban traffic congestion when developing technologies to support the intelligent transportation system (ITS).

Research of Pedestrian Crossing Safety Facilities Based on the Video Detection

NASA Astrophysics Data System (ADS)

Li, Sheng-Zhen; Xie, Quan-Long; Zang, Xiao-Dong; Tang, Guo-Jun

Since that the pedestrian crossing facilities at present is not perfect, pedestrian crossing is in chaos and pedestrians from opposite direction conflict and congest with each other, which severely affects the pedestrian traffic efficiency, obstructs the vehicle and bringing about some potential security problems. To solve these problems, based on video identification, a pedestrian crossing guidance system was researched and designed. It uses the camera to monitor the pedestrians in real time and sums up the number of pedestrians through video detection program, and a group of pedestrian's induction lamp array is installed at the interval of crosswalk, which adjusts color display according to the proportion of pedestrians from both sides to guide pedestrians from both opposite directions processing separately. The emulation analysis result from cellular automaton shows that the system reduces the pedestrian crossing conflict, shortens the time of pedestrian crossing and improves the safety of pedestrians crossing.

Characteristics of traffic flow at nonsignalized T-shaped intersection with U-turn movements.

PubMed

Fan, Hong-Qiang; Jia, Bin; Li, Xin-Gang; Tian, Jun-Fang; Yan, Xue-Dong

2013-01-01

Most nonsignalized T-shaped intersections permit U-turn movements, which make the traffic conditions of intersection complex. In this paper, a new cellular automaton (CA) model is proposed to characterize the traffic flow at the intersection of this type. In present CA model, new rules are designed to avoid the conflicts among different directional vehicles and eliminate the gridlock. Two kinds of performance measures (i.e., flux and average control delay) for intersection are compared. The impacts of U-turn movements are analyzed under different initial conditions. Simulation results demonstrate that (i) the average control delay is more practical than flux in measuring the performance of intersection, (ii) U-turn movements increase the range and degree of high congestion, and (iii) U-turn movements on the different direction of main road have asymmetrical influences on the traffic conditions of intersection.

Two-lane traffic-flow model with an exact steady-state solution.

PubMed

Kanai, Masahiro

2010-12-01

We propose a stochastic cellular-automaton model for two-lane traffic flow based on the misanthrope process in one dimension. The misanthrope process is a stochastic process allowing for an exact steady-state solution; hence, we have an exact flow-density diagram for two-lane traffic. In addition, we introduce two parameters that indicate, respectively, driver's driving-lane preference and passing-lane priority. Due to the additional parameters, the model shows a deviation of the density ratio for driving-lane use and a biased lane efficiency in flow. Then, a mean-field approach explicitly describes the asymmetric flow by the hop rates, the driving-lane preference, and the passing-lane priority. Meanwhile, the simulation results are in good agreement with an observational data, and we thus estimate these parameters. We conclude that the proposed model successfully produces two-lane traffic flow particularly with the driving-lane preference and the passing-lane priority.

3D CAFE modeling of grain structures: application to primary dendritic and secondary eutectic solidification

NASA Astrophysics Data System (ADS)

Carozzani, T.; Digonnet, H.; Gandin, Ch-A.

2012-01-01

A three-dimensional model is presented for the prediction of grain structures formed in casting. It is based on direct tracking of grain boundaries using a cellular automaton (CA) method. The model is fully coupled with a solution of the heat flow computed with a finite element (FE) method. Several unique capabilities are implemented including (i) the possibility to track the development of several types of grain structures, e.g. dendritic and eutectic grains, (ii) a coupling scheme that permits iterations between the FE method and the CA method, and (iii) tabulated enthalpy curves for the solid and liquid phases that offer the possibility to work with multicomponent alloys. The present CAFE model is also fully parallelized and runs on a cluster of computers. Demonstration is provided by direct comparison between simulated and recorded cooling curves for a directionally solidified aluminum-7 wt% silicon alloy.

Microscopic Spin Model for the STOCK Market with Attractor Bubbling on Regular and Small-World Lattices

NASA Astrophysics Data System (ADS)

Krawiecki, A.

A multi-agent spin model for changes of prices in the stock market based on the Ising-like cellular automaton with interactions between traders randomly varying in time is investigated by means of Monte Carlo simulations. The structure of interactions has topology of a small-world network obtained from regular two-dimensional square lattices with various coordination numbers by randomly cutting and rewiring edges. Simulations of the model on regular lattices do not yield time series of logarithmic price returns with statistical properties comparable with the empirical ones. In contrast, in the case of networks with a certain degree of randomness for a wide range of parameters the time series of the logarithmic price returns exhibit intermittent bursting typical of volatility clustering. Also the tails of distributions of returns obey a power scaling law with exponents comparable to those obtained from the empirical data.

Initial value sensitivity of the Chinese stock market and its relationship with the investment psychology

NASA Astrophysics Data System (ADS)

Ying, Shangjun; Li, Xiaojun; Zhong, Xiuqin

2015-04-01

This paper discusses the initial value sensitivity (IVS) of Chinese stock market, including the single stock market and the Chinese A-share stock market, with respect to real markets and evolving models. The aim is to explore the relationship between IVS of the Chinese A-share stock market and the investment psychology based on the evolving model of genetic cellular automaton (GCA). We find: (1) The Chinese stock market is sensitively dependent on the initial conditions. (2) The GCA model provides a considerable reliability in complexity simulation (e.g. the IVS). (3) The IVS of stock market is positively correlated with the imitation probability when the intensity of the imitation psychology reaches a certain threshold. The paper suggests that the government should seek to keep the imitation psychology under a certain level, otherwise it may induce severe fluctuation to the market.

The cognitive domain of a glider in the game of life.

PubMed

Beer, Randall D

2014-01-01

This article examines in some technical detail the application of Maturana and Varela's biology of cognition to a simple concrete model: a glider in the game of Life cellular automaton. By adopting an autopoietic perspective on a glider, the set of possible perturbations to it can be divided into destructive and nondestructive subsets. From a glider's reaction to each nondestructive perturbation, its cognitive domain is then mapped. In addition, the structure of a glider's possible knowledge of its immediate environment, and the way in which that knowledge is grounded in its constitution, are fully described. The notion of structural coupling is then explored by characterizing the paths of mutual perturbation that a glider and its environment can undergo. Finally, a simple example of a communicative interaction between two gliders is given. The article concludes with a discussion of the potential implications of this analysis for the enactive approach to cognition.

Material modeling of biofilm mechanical properties.

PubMed

Laspidou, C S; Spyrou, L A; Aravas, N; Rittmann, B E

2014-05-01

A biofilm material model and a procedure for numerical integration are developed in this article. They enable calculation of a composite Young's modulus that varies in the biofilm and evolves with deformation. The biofilm-material model makes it possible to introduce a modeling example, produced by the Unified Multi-Component Cellular Automaton model, into the general-purpose finite-element code ABAQUS. Compressive, tensile, and shear loads are imposed, and the way the biofilm mechanical properties evolve is assessed. Results show that the local values of Young's modulus increase under compressive loading, since compression results in the voids "closing," thus making the material stiffer. For the opposite reason, biofilm stiffness decreases when tensile loads are imposed. Furthermore, the biofilm is more compliant in shear than in compression or tension due to the how the elastic shear modulus relates to Young's modulus. Copyright © 2014 Elsevier Inc. All rights reserved.

Analysis of the changes in the tarcrete layer on the desert surface of Kuwait using satellite imagery and cell-based modeling

NASA Astrophysics Data System (ADS)

Al-Doasari, Ahmad E.

The 1991 Gulf War caused massive environmental damage in Kuwait. Deposition of oil and soot droplets from hundreds of burning oil-wells created a layer of tarcrete on the desert surface covering over 900 km2. This research investigates the spatial change in the tarcrete extent from 1991 to 1998 using Landsat Thematic Mapper (TM) imagery and statistical modeling techniques. The pixel structure of TM data allows the spatial analysis of the change in tarcrete extent to be conducted at the pixel (cell) level within a geographical information system (GIS). There are two components to this research. The first is a comparison of three remote sensing classification techniques used to map the tarcrete layer. The second is a spatial-temporal analysis and simulation of tarcrete changes through time. The analysis focuses on an area of 389 km2 located south of the Al-Burgan oil field. Five TM images acquired in 1991, 1993, 1994, 1995, and 1998 were geometrically and atmospherically corrected. These images were classified into six classes: oil lakes; heavy, intermediate, light, and traces of tarcrete; and sand. The classification methods tested were unsupervised, supervised, and neural network supervised (fuzzy ARTMAP). Field data of tarcrete characteristics were collected to support the classification process and to evaluate the classification accuracies. Overall, the neural network method is more accurate (60 percent) than the other two methods; both the unsupervised and the supervised classification accuracy assessments resulted in 46 percent accuracy. The five classifications were used in a lagged autologistic model to analyze the spatial changes of the tarcrete through time. The autologistic model correctly identified overall tarcrete contraction between 1991--1993 and 1995--1998. However, tarcrete contraction between 1993--1994 and 1994--1995 was less well marked, in part because of classification errors in the maps from these time periods. Initial simulations of tarcrete contraction with a cellular automaton model were not very successful. However, more accurate classifications could improve the simulations. This study illustrates how an empirical investigation using satellite images, field data, GIS, and spatial statistics can simulate dynamic land-cover change through the use of a discrete statistical and cellular automaton model.

Periodical cicadas: A minimal automaton model

NASA Astrophysics Data System (ADS)

de O. Cardozo, Giovano; de A. M. M. Silvestre, Daniel; Colato, Alexandre

2007-08-01

The Magicicada spp. life cycles with its prime periods and highly synchronized emergence have defied reasonable scientific explanation since its discovery. During the last decade several models and explanations for this phenomenon appeared in the literature along with a great deal of discussion. Despite this considerable effort, there is no final conclusion about this long standing biological problem. Here, we construct a minimal automaton model without predation/parasitism which reproduces some of these aspects. Our results point towards competition between different strains with limited dispersal threshold as the main factor leading to the emergence of prime numbered life cycles.

Automation Rover for Extreme Environments

NASA Technical Reports Server (NTRS)

Sauder, Jonathan; Hilgemann, Evan; Johnson, Michael; Parness, Aaron; Hall, Jeffrey; Kawata, Jessie; Stack, Kathryn

2017-01-01

Almost 2,300 years ago the ancient Greeks built the Antikythera automaton. This purely mechanical computer accurately predicted past and future astronomical events long before electronics existed1. Automata have been credibly used for hundreds of years as computers, art pieces, and clocks. However, in the past several decades automata have become less popular as the capabilities of electronics increased, leaving them an unexplored solution for robotic spacecraft. The Automaton Rover for Extreme Environments (AREE) proposes an exciting paradigm shift from electronics to a fully mechanical system, enabling longitudinal exploration of the most extreme environments within the solar system.

Quantum cellular automata and free quantum field theory

NASA Astrophysics Data System (ADS)

D'Ariano, Giacomo Mauro; Perinotti, Paolo

2017-02-01

In a series of recent papers [1-4] it has been shown how free quantum field theory can be derived without using mechanical primitives (including space-time, special relativity, quantization rules, etc.), but only considering the easiest quantum algorithm encompassing a countable set of quantum systems whose network of interactions satisfies the simple principles of unitarity, homogeneity, locality, and isotropy. This has opened the route to extending the axiomatic information-theoretic derivation of the quantum theory of abstract systems [5, 6] to include quantum field theory. The inherent discrete nature of the informational axiomatization leads to an extension of quantum field theory to a quantum cellular automata theory, where the usual field theory is recovered in a regime where the discrete structure of the automata cannot be probed. A simple heuristic argument sets the scale of discreteness to the Planck scale, and the customary physical regime where discreteness is not visible is the relativistic one of small wavevectors. In this paper we provide a thorough derivation from principles that in the most general case the graph of the quantum cellular automaton is the Cayley graph of a finitely presented group, and showing how for the case corresponding to Euclidean emergent space (where the group resorts to an Abelian one) the automata leads to Weyl, Dirac and Maxwell field dynamics in the relativistic limit. We conclude with some perspectives towards the more general scenario of non-linear automata for interacting quantum field theory.

Predicting pedestrian flow: a methodology and a proof of concept based on real-life data.

PubMed

Davidich, Maria; Köster, Gerta

2013-01-01

Building a reliable predictive model of pedestrian motion is very challenging: Ideally, such models should be based on observations made in both controlled experiments and in real-world environments. De facto, models are rarely based on real-world observations due to the lack of available data; instead, they are largely based on intuition and, at best, literature values and laboratory experiments. Such an approach is insufficient for reliable simulations of complex real-life scenarios: For instance, our analysis of pedestrian motion under natural conditions at a major German railway station reveals that the values for free-flow velocities and the flow-density relationship differ significantly from widely used literature values. It is thus necessary to calibrate and validate the model against relevant real-life data to make it capable of reproducing and predicting real-life scenarios. In this work we aim at constructing such realistic pedestrian stream simulation. Based on the analysis of real-life data, we present a methodology that identifies key parameters and interdependencies that enable us to properly calibrate the model. The success of the approach is demonstrated for a benchmark model, a cellular automaton. We show that the proposed approach significantly improves the reliability of the simulation and hence the potential prediction accuracy. The simulation is validated by comparing the local density evolution of the measured data to that of the simulated data. We find that for our model the most sensitive parameters are: the source-target distribution of the pedestrian trajectories, the schedule of pedestrian appearances in the scenario and the mean free-flow velocity. Our results emphasize the need for real-life data extraction and analysis to enable predictive simulations.

Synchronization, TIGoRS, and Information Flow in Complex Systems: Dispositional Cellular Automata.

PubMed

Sulis, William H

2016-04-01

Synchronization has a long history in physics where it refers to the phase matching of two identical oscillators. This notion has been extensively studied in physics as well as in biology, where it has been applied to such widely varying phenomena as the flashing of fireflies and firing of neurons in the brain. Human behavior, however, may be recurrent but it is not oscillatory even though many physiological systems do exhibit oscillatory tendencies. Moreover, much of human behaviour is collaborative and cooperative, where the individual behaviours may be distinct yet contemporaneous (if not simultaneous) and taken collectively express some functionality. In the context of behaviour, the important aspect is the repeated co-occurrence in time of behaviours that facilitate the propagation of information or of functionality, regardless of whether or not these behaviours are similar or identical. An example of this weaker notion of synchronization is transient induced global response synchronization (TIGoRS). Previous work has shown that TIGoRS is a ubiquitous phenomenon among complex systems, enabling them to stably parse environmental transients into salient units to which they stably respond. This leads to the notion of Sulis machines, which emergently generate a primitive linguistic structure through their dynamics. This article reviews the notion of TIGoRS and its expression in several complex systems models including tempered neural networks, driven cellular automata and cocktail party automata. The emergent linguistics of Sulis machines are discussed. A new class of complex systems model, the dispositional cellular automaton is introduced. A new metric for TIGoRS, the excess synchronization, is introduced and applied to the study of TIGoRS in dispositional cellular automata. It is shown that these automata exhibit a nonlinear synchronization response to certain perturbing transients.

A cellular automaton model for ship traffic flow in waterways

NASA Astrophysics Data System (ADS)

Qi, Le; Zheng, Zhongyi; Gang, Longhui

2017-04-01

With the development of marine traffic, waterways become congested and more complicated traffic phenomena in ship traffic flow are observed. It is important and necessary to build a ship traffic flow model based on cellular automata (CAs) to study the phenomena and improve marine transportation efficiency and safety. Spatial discretization rules for waterways and update rules for ship movement are two important issues that are very different from vehicle traffic. To solve these issues, a CA model for ship traffic flow, called a spatial-logical mapping (SLM) model, is presented. In this model, the spatial discretization rules are improved by adding a mapping rule. And the dynamic ship domain model is considered in the update rules to describe ships' interaction more exactly. Take the ship traffic flow in the Singapore Strait for example, some simulations were carried out and compared. The simulations show that the SLM model could avoid ship pseudo lane-change efficiently, which is caused by traditional spatial discretization rules. The ship velocity change in the SLM model is consistent with the measured data. At finally, from the fundamental diagram, the relationship between traffic ability and the lengths of ships is explored. The number of ships in the waterway declines when the proportion of large ships increases.

The influence of heavy vehicles on traffic dynamics around on-ramp system: Cellular automata approach

NASA Astrophysics Data System (ADS)

Kong, Dewen; Guo, Xiucheng; Wu, Dingxin

Although the on-ramp system has been widely studied, the influence of heavy vehicles is unknown because researchers only investigate the traffic dynamics around on-ramp system under homogeneous traffic conditions, which is different in real-world settings. This paper uses an improved cellular automaton model to study the heterogeneous traffic around on-ramp system. The forward motion rules are improved by considering the differences of driving behavior in different vehicle combinations. The lane change rules are improved by reflecting the aggressive behavior in mandatory lane changes. The phase diagram, traffic flow, capacity and spatial-temporal diagram are analyzed under the influences of heavy vehicles. The results show that by increasing the percentage of heavy vehicles, there will be more severe traffic congestion around on-ramp system, lower saturated flow and capacity. Also, the interactions between main road and on-ramp have been investigated. Increasing the percentage of heavy vehicles at the upstream of the conflict area on the main road or restricting heavy vehicles on the outside lane of the main road will deteriorate the performance of on-ramp. While the main road will have better performance as the percentage of heavy vehicles on the on-ramp increases when the on-ramp inflow rate is not low.

Water and Sediment Output Evaluation Using Cellular Automata on Alpine Catchment: Soana, Italy - Test Case

NASA Astrophysics Data System (ADS)

Pasculli, Antonio; Audisio, Chiara; Sciarra, Nicola

2017-12-01

In the alpine contest, the estimation of the rainfall (inflow) and the discharge (outflow) data are very important in order to, at least, analyse historical time series at catchment scale; determine the hydrological maximum and minimum estimate flood and drought frequency. Hydrological researches become a precious source of information for various human activities, in particular for land use management and planning. Many rainfall- runoff models have been proposed to reflect steady, gradually-varied flow condition inside a catchment. In these last years, the application of Reduced Complexity Models (RCM) has been representing an excellent alternative resource for evaluating the hydrological response of catchments, within a period of time up to decades. Hence, this paper is aimed at the discussion of the application of the research code CAESAR, based on cellular automaton (CA) approach, in order to evaluate the water and the sediment outputs from an alpine catchment (Soana, Italy), selected as test case. The comparison between the predicted numerical results, developed through parametric analysis, and the available measured data are discussed. Finally, the analysis of a numerical estimate of the sediment budget over ten years is presented. The necessity of a fast, but reliable numerical support when the measured data are not so easily accessible, as in Alpine catchments, is highlighted.

Modelling robot's behaviour using finite automata

NASA Astrophysics Data System (ADS)

Janošek, Michal; Žáček, Jaroslav

2017-07-01

This paper proposes a model of a robot's behaviour described by finite automata. We split robot's knowledge into several knowledge bases which are used by the inference mechanism of the robot's expert system to make a logic deduction. Each knowledgebase is dedicated to the particular behaviour domain and the finite automaton helps us switching among these knowledge bases with the respect of actual situation. Our goal is to simplify and reduce complexity of one big knowledgebase splitting it into several pieces. The advantage of this model is that we can easily add new behaviour by adding new knowledgebase and add this behaviour into the finite automaton and define necessary states and transitions.

Model Checking Temporal Logic Formulas Using Sticker Automata

PubMed Central

Feng, Changwei; Wu, Huanmei

2017-01-01

As an important complex problem, the temporal logic model checking problem is still far from being fully resolved under the circumstance of DNA computing, especially Computation Tree Logic (CTL), Interval Temporal Logic (ITL), and Projection Temporal Logic (PTL), because there is still a lack of approaches for DNA model checking. To address this challenge, a model checking method is proposed for checking the basic formulas in the above three temporal logic types with DNA molecules. First, one-type single-stranded DNA molecules are employed to encode the Finite State Automaton (FSA) model of the given basic formula so that a sticker automaton is obtained. On the other hand, other single-stranded DNA molecules are employed to encode the given system model so that the input strings of the sticker automaton are obtained. Next, a series of biochemical reactions are conducted between the above two types of single-stranded DNA molecules. It can then be decided whether the system satisfies the formula or not. As a result, we have developed a DNA-based approach for checking all the basic formulas of CTL, ITL, and PTL. The simulated results demonstrate the effectiveness of the new method. PMID:29119114

Reconfigurability of behavioural specifications for manufacturing systems

NASA Astrophysics Data System (ADS)

Schmidt, Klaus Werner

2017-12-01

Reconfigurable manufacturing systems (RMS) support flexibility in the product variety and the configuration of the manufacturing system itself in order to enable quick adjustments to new products and production requirements. As a consequence, an essential feature of RMS is their ability to rapidly modify the control strategy during run-time. In this paper, the particular problem of changing the specified operation of a RMS, whose logical behaviour is modelled as a finite state automaton, is addressed. The notion of reconfigurability of specifications (RoS) is introduced and it is shown that the stated reconfiguration problem can be formulated as a controlled language convergence problem. In addition, algorithms for the verification of RoS and the construction of a reconfiguration supervisor are proposed. The supervisor is realised in a modular way which facilitates the extension by new configurations. Finally, it is shown that a supremal nonblocking and controllable strict subautomaton of the plant automaton that fulfils RoS exists in case RoS is violated for the plant automaton itself and an algorithm for the computation of this strict subautomaton is presented. The developed concepts and results are illustrated by a manufacturing cell example.

Training a molecular automaton to play a game

NASA Astrophysics Data System (ADS)

Pei, Renjun; Matamoros, Elizabeth; Liu, Manhong; Stefanovic, Darko; Stojanovic, Milan N.

2010-11-01

Research at the interface between chemistry and cybernetics has led to reports of `programmable molecules', but what does it mean to say `we programmed a set of solution-phase molecules to do X'? A survey of recently implemented solution-phase circuitry indicates that this statement could be replaced with `we pre-mixed a set of molecules to do X and functional subsets of X'. These hard-wired mixtures are then exposed to a set of molecular inputs, which can be interpreted as being keyed to human moves in a game, or as assertions of logical propositions. In nucleic acids-based systems, stemming from DNA computation, these inputs can be seen as generic oligonucleotides. Here, we report using reconfigurable nucleic acid catalyst-based units to build a multipurpose reprogrammable molecular automaton that goes beyond single-purpose `hard-wired' molecular automata. The automaton covers all possible responses to two consecutive sets of four inputs (such as four first and four second moves for a generic set of trivial two-player two-move games). This is a model system for more general molecular field programmable gate array (FPGA)-like devices that can be programmed by example, which means that the operator need not have any knowledge of molecular computing methods.

Training a molecular automaton to play a game.

PubMed

Pei, Renjun; Matamoros, Elizabeth; Liu, Manhong; Stefanovic, Darko; Stojanovic, Milan N

2010-11-01

Research at the interface between chemistry and cybernetics has led to reports of 'programmable molecules', but what does it mean to say 'we programmed a set of solution-phase molecules to do X'? A survey of recently implemented solution-phase circuitry indicates that this statement could be replaced with 'we pre-mixed a set of molecules to do X and functional subsets of X'. These hard-wired mixtures are then exposed to a set of molecular inputs, which can be interpreted as being keyed to human moves in a game, or as assertions of logical propositions. In nucleic acids-based systems, stemming from DNA computation, these inputs can be seen as generic oligonucleotides. Here, we report using reconfigurable nucleic acid catalyst-based units to build a multipurpose reprogrammable molecular automaton that goes beyond single-purpose 'hard-wired' molecular automata. The automaton covers all possible responses to two consecutive sets of four inputs (such as four first and four second moves for a generic set of trivial two-player two-move games). This is a model system for more general molecular field programmable gate array (FPGA)-like devices that can be programmed by example, which means that the operator need not have any knowledge of molecular computing methods.

Implementation of a polling protocol for predicting celiac disease in videocapsule analysis.

PubMed

Ciaccio, Edward J; Tennyson, Christina A; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

2013-07-16

To investigate the presence of small intestinal villous atrophy in celiac disease patients from quantitative analysis of videocapsule image sequences. Nine celiac patient data with biopsy-proven villous atrophy and seven control patient data lacking villous atrophy were used for analysis. Celiacs had biopsy-proven disease with scores of Marsh II-IIIC except in the case of one hemophiliac patient. At four small intestinal levels (duodenal bulb, distal duodenum, jejunum, and ileum), video clips of length 200 frames (100 s) were analyzed. Twenty-four measurements were used for image characterization. These measurements were determined by quantitatively processing the videocapsule images via techniques for texture analysis, motility estimation, volumetric reconstruction using shape-from-shading principles, and image transformation. Each automated measurement method, or automaton, was polled as to whether or not villous atrophy was present in the small intestine, indicating celiac disease. Each automaton's vote was determined based upon an optimized parameter threshold level, with the threshold levels being determined from prior data. A prediction of villous atrophy was made if it received the majority of votes (≥ 13), while no prediction was made for tie votes (12-12). Thus each set of images was classified as being from either a celiac disease patient or from a control patient. Separated by intestinal level, the overall sensitivity of automata polling for predicting villous atrophy and hence celiac disease was 83.9%, while the specificity was 92.9%, and the overall accuracy of automata-based polling was 88.1%. The method of image transformation yielded the highest sensitivity at 93.8%, while the method of texture analysis using subbands had the highest specificity at 76.0%. Similar results of prediction were observed at all four small intestinal locations, but there were more tie votes at location 4 (ileum). Incorrect prediction which reduced sensitivity occurred for two celiac patients with Marsh type II pattern, which is characterized by crypt hyperplasia, but normal villous architecture. Pooled from all levels, there was a mean of 14.31 ± 3.28 automaton votes for celiac vs 9.67 ± 3.31 automaton votes for control when celiac patient data was analyzed (P < 0.001). Pooled from all levels, there was a mean of 9.71 ± 2.8128 automaton votes for celiac vs 14.32 ± 2.7931 automaton votes for control when control patient data was analyzed (P < 0.001). Automata-based polling may be useful to indicate presence of mucosal atrophy, indicative of celiac disease, across the entire small bowel, though this must be confirmed in a larger patient set. Since the method is quantitative and automated, it can potentially eliminate observer bias and enable the detection of subtle abnormality in patients lacking a clear diagnosis. Our paradigm was found to be more efficacious at proximal small intestinal locations, which may suggest a greater presence and severity of villous atrophy at proximal as compared with distal locations.

Potential Role of Lateral Gene Transfer in the Evolution of Biofilm Communities at the Lost City Hydrothermal Field and in the Earliest Stages of Cellular Evolution

NASA Astrophysics Data System (ADS)

Brazelton, W. J.; Mehta, M. P.; Baross, J. A.

2010-04-01

DNA sequencing and metabolic activity measurements show that lateral gene transfer promotes phenotypic diversity in single-species archaeal biofilms attached to hydrothermal chimneys. This system may be a useful model for early cellular evolution.

Evolution of the new vertebrate head by co-option of an ancient chordate skeletal tissue.

PubMed

Jandzik, David; Garnett, Aaron T; Square, Tyler A; Cattell, Maria V; Yu, Jr-Kai; Medeiros, Daniel M

2015-02-26

A defining feature of vertebrates (craniates) is a pronounced head that is supported and protected by a robust cellular endoskeleton. In the first vertebrates, this skeleton probably consisted of collagenous cellular cartilage, which forms the embryonic skeleton of all vertebrates and the adult skeleton of modern jawless and cartilaginous fish. In the head, most cellular cartilage is derived from a migratory cell population called the neural crest, which arises from the edges of the central nervous system. Because collagenous cellular cartilage and neural crest cells have not been described in invertebrates, the appearance of cellular cartilage derived from neural crest cells is considered a turning point in vertebrate evolution. Here we show that a tissue with many of the defining features of vertebrate cellular cartilage transiently forms in the larvae of the invertebrate chordate Branchiostoma floridae (Florida amphioxus). We also present evidence that during evolution, a key regulator of vertebrate cartilage development, SoxE, gained new cis-regulatory sequences that subsequently directed its novel expression in neural crest cells. Together, these results suggest that the origin of the vertebrate head skeleton did not depend on the evolution of a new skeletal tissue, as is commonly thought, but on the spread of this tissue throughout the head. We further propose that the evolution of cis-regulatory elements near an ancient regulator of cartilage differentiation was a major factor in the evolution of the vertebrate head skeleton.

On the Motion of Agents across Terrain with Obstacles

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.

2018-01-01

The paper is devoted to finding the time optimal route of an agent travelling across a region from a given source point to a given target point. At each point of this region, a maximum allowed speed is specified. This speed limit may vary in time. The continuous statement of this problem and the case when the agent travels on a grid with square cells are considered. In the latter case, the time is also discrete, and the number of admissible directions of motion at each point in time is eight. The existence of an optimal solution of this problem is proved, and estimates of the approximate solution obtained on the grid are obtained. It is found that decreasing the size of cells below a certain limit does not further improve the approximation. These results can be used to estimate the quasi-optimal trajectory of the agent motion across the rugged terrain produced by an algorithm based on a cellular automaton that was earlier developed by the author.

Temperature modeling of laser-irradiated azo-polymer thin films.

PubMed

Yager, Kevin G; Barrett, Christopher J

2004-01-08

Azobenzene polymer thin films exhibit reversible surface mass transport when irradiated with a light intensity and/or polarization gradient, although the exact mechanism remains unknown. In order to address the role of thermal effects in the surface relief grating formation process peculiar to azo polymers, a cellular automaton simulation was developed to model heat flow in thin films undergoing laser irradiation. Typical irradiation intensities of 50 mW/cm2 resulted in film temperature rises on the order of 5 K, confirmed experimentally. The temperature gradient between the light maxima and minima was found, however, to stabilize at only 10(-4) K within 2 micros. These results indicate that thermal effects play a negligible role during inscription, for films of any thickness. Experiments monitoring surface relief grating formation on substrates of different thermal conductivity confirm that inscription is insensitive to film temperature. Further simulations suggest that high-intensity pulsed irradiation leads to destructive temperatures and sample ablation, not to reversible optical mass transport. (c) 2004 American Institute of Physics

Modeling of Dendritic Structure and Microsegregation in Solidification of Al-Rich Quaternary Alloys

NASA Astrophysics Data System (ADS)

Dai, Ting; Zhu, Mingfang; Chen, Shuanglin; Cao, Weisheng

A two-dimensional cellular automaton (CA) model is coupled with a CALPHAD tool for the simulation of dendritic growth and microsegregation in solidification of quaternary alloys. The dynamics of dendritic growth is calculated according to the difference between the local equilibrium liquidus temperature and the actual temperature, incorporating with the Gibbs—Thomson effect and preferential dendritic growth orientations. Based on the local liquid compositions determined by solving the solutal transport equation in the domain, the local equilibrium liquidus temperature and the solid concentrations at the solid/liquid (SL) interface are calculated by the CALPHAD tool. The model was validated through the comparisons of the simulated results with the Scheil predictions for the solid composition profiles as a function of solid fraction in an Al-6wt%Cu-0.6wt%Mg-1wt%Si alloy. It is demonstrated that the model is capable of not only reproducing realistic dendrite morphologies, but also reasonably predicting microsegregation patterns in solidification of Al-rich quaternary alloys.

Scaling properties of a rice-pile model: inertia and friction effects.

PubMed

Khfifi, M; Loulidi, M

2008-11-01

We present a rice-pile cellular automaton model that includes inertial and friction effects. This model is studied in one dimension, where the updating of metastable sites is done according to a stochastic dynamics governed by a probabilistic toppling parameter p that depends on the accumulated energy of moving grains. We investigate the scaling properties of the model using finite-size scaling analysis. The avalanche size, the lifetime, and the residence time distributions exhibit a power-law behavior. Their corresponding critical exponents, respectively, tau, y, and yr, are not universal. They present continuous variation versus the parameters of the system. The maximal value of the critical exponent tau that our model gives is very close to the experimental one, tau=2.02 [Frette, Nature (London) 379, 49 (1996)], and the probability distribution of the residence time is in good agreement with the experimental results. We note that the critical behavior is observed only in a certain range of parameter values of the system which correspond to low inertia and high friction.

Discrete-continuum multiscale model for transport, biomass development and solid restructuring in porous media

NASA Astrophysics Data System (ADS)

Ray, Nadja; Rupp, Andreas; Prechtel, Alexander

2017-09-01

Upscaling transport in porous media including both biomass development and simultaneous structural changes in the solid matrix is extremely challenging. This is because both affect the medium's porosity as well as mass transport parameters and flow paths. We address this challenge by means of a multiscale model. At the pore scale, the local discontinuous Galerkin (LDG) method is used to solve differential equations describing particularly the bacteria's and the nutrient's development. Likewise, a sticky agent tightening together solid or bio cells is considered. This is combined with a cellular automaton method (CAM) capturing structural changes of the underlying computational domain stemming from biomass development and solid restructuring. Findings from standard homogenization theory are applied to determine the medium's characteristic time- and space-dependent properties. Investigating these results enhances our understanding of the strong interplay between a medium's functional properties and its geometric structure. Finally, integrating such properties as model parameters into models defined on a larger scale enables reflecting the impact of pore scale processes on the larger scale.

Characteristics of traffic flow at a non-signalized intersection in the framework of game theory

NASA Astrophysics Data System (ADS)

Fan, Hongqiang; Jia, Bin; Tian, Junfang; Yun, Lifen

2014-12-01

At a non-signalized intersection, some vehicles violate the traffic rules to pass the intersection as soon as possible. These behaviors may cause many traffic conflicts even traffic accidents. In this paper, a simulation model is proposed to research the effects of these behaviors at a non-signalized intersection. Vehicle’s movement is simulated by the cellular automaton (CA) model. The game theory is introduced for simulating the intersection dynamics. Two types of driver participate the game process: cooperator (C) and defector (D). The cooperator obey the traffic rules, but the defector does not. A transition process may occur when the cooperator is waiting before the intersection. The critical value of waiting time follows the Weibull distribution. One transition regime is found in the phase diagram. The simulation results illustrate the applicability of the proposed model and reveal a number of interesting insights into the intersection management, including that the existence of defectors is benefit for the capacity of intersection, but also reduce the safety of intersection.

Simulation of three lanes one-way freeway in low visibility weather by possible traffic accidents

NASA Astrophysics Data System (ADS)

Pang, Ming-bao; Zheng, Sha-sha; Cai, Zhang-hui

2015-09-01

The aim of this work is to investigate the traffic impact of low visibility weather on a freeway including the fraction of real vehicle rear-end accidents and road traffic capacity. Based on symmetric two-lane Nagel-Schreckenberg (STNS) model, a cellular automaton model of three-lane freeway mainline with the real occurrence of rear-end accidents in low visibility weather, which considers delayed reaction time and deceleration restriction, was established with access to real-time traffic information of intelligent transportation system (ITS). The characteristics of traffic flow in different visibility weather were discussed via the simulation experiments. The results indicate that incoming flow control (decreasing upstream traffic volume) and inputting variable speed limits (VSL) signal are effective in accident reducing and road actual traffic volume's enhancing. According to different visibility and traffic demand the appropriate control strategies should be adopted in order to not only decrease the probability of vehicle accidents but also avoid congestion.

Simulation of Channel Segregation During Directional Solidification of In—75 wt pct Ga. Qualitative Comparison with In Situ Observations

NASA Astrophysics Data System (ADS)

Saad, Ali; Gandin, Charles-André; Bellet, Michel; Shevchenko, Natalia; Eckert, Sven

2015-11-01

Freckles are common defects in industrial casting. They result from thermosolutal convection due to buoyancy forces generated from density variations in the liquid. The present paper proposes a numerical analysis for the formation of channel segregation using the three-dimensional (3D) cellular automaton (CA)—finite element (FE) model. The model integrates kinetics laws for the nucleation and growth of a microstructure with the solution of the conservation equations for the casting, while introducing an intermediate modeling scale for a direct representation of the envelope of the dendritic grains. Directional solidification of a cuboid cell is studied. Its geometry, the alloy chosen as well as the process parameters are inspired from experimental observations recently reported in the literature. Snapshots of the convective pattern, the solute distribution, and the morphology of the growth front are qualitatively compared. Similitudes are found when considering the coupled 3D CAFE simulations. Limitations of the model to reach direct simulation of the experiments are discussed.

Beyond input-output computings: error-driven emergence with parallel non-distributed slime mold computer.

PubMed

Aono, Masashi; Gunji, Yukio-Pegio

2003-10-01

The emergence derived from errors is the key importance for both novel computing and novel usage of the computer. In this paper, we propose an implementable experimental plan for the biological computing so as to elicit the emergent property of complex systems. An individual plasmodium of the true slime mold Physarum polycephalum acts in the slime mold computer. Modifying the Elementary Cellular Automaton as it entails the global synchronization problem upon the parallel computing provides the NP-complete problem solved by the slime mold computer. The possibility to solve the problem by giving neither all possible results nor explicit prescription of solution-seeking is discussed. In slime mold computing, the distributivity in the local computing logic can change dynamically, and its parallel non-distributed computing cannot be reduced into the spatial addition of multiple serial computings. The computing system based on exhaustive absence of the super-system may produce, something more than filling the vacancy.

Effects of the amount of feedback information on urban traffic with advanced traveler information system

NASA Astrophysics Data System (ADS)

Chen, Jie; Li, Ming; Jiang, Rui; Hu, Mao-Bin

2017-09-01

In a real traffic system, information feedback has already been proven to be a good way to alleviate traffic jams. However, due to the massive traffic information of real system, the procedure is often difficult in practice. In this paper, we study the effects of the amount of feedback information based on a cellular automaton model of urban traffic. What we found most interesting is that when providing the traffic information of a part of a road to travelers, the performance of the system will be better than that providing the road's full traffic information. From this basis, we can provide more effective routing strategy with less information. We demonstrate that only providing the traffic information of about first half road from upstream to downstream can maximize the traffic capacity of the system. We also give an explanation for these phenomena by studying the distribution pattern of vehicles and the detailed turning environment at the intersections. The effects of the traffic light period are also provided.

Inferring the Limit Behavior of Some Elementary Cellular Automata

NASA Astrophysics Data System (ADS)

Ruivo, Eurico L. P.; de Oliveira, Pedro P. B.

Cellular automata locally define dynamical systems, discrete in space, time and in the state variables, capable of displaying arbitrarily complex global emergent behavior. One core question in the study of cellular automata refers to their limit behavior, that is, to the global dynamical features in an infinite time evolution. Previous works have shown that for finite time evolutions, the dynamics of one-dimensional cellular automata can be described by regular languages and, therefore, by finite automata. Such studies have shown the existence of growth patterns in the evolution of such finite automata for some elementary cellular automata rules and also inferred the limit behavior of such rules based upon the growth patterns; however, the results on the limit behavior were obtained manually, by direct inspection of the structures that arise during the time evolution. Here we present the formalization of an automatic method to compute such structures. Based on this, the rules of the elementary cellular automata space were classified according to the existence of a growth pattern in their finite automata. Also, we present a method to infer the limit graph of some elementary cellular automata rules, derived from the analysis of the regular expressions that describe their behavior in finite time. Finally, we analyze some attractors of two rules for which we could not compute the whole limit set.

Digitally programmable microfluidic automaton for multiscale combinatorial mixing and sample processing†

PubMed Central

Jensen, Erik C.; Stockton, Amanda M.; Chiesl, Thomas N.; Kim, Jungkyu; Bera, Abhisek; Mathies, Richard A.

2013-01-01

A digitally programmable microfluidic Automaton consisting of a 2-dimensional array of pneumatically actuated microvalves is programmed to perform new multiscale mixing and sample processing operations. Large (µL-scale) volume processing operations are enabled by precise metering of multiple reagents within individual nL-scale valves followed by serial repetitive transfer to programmed locations in the array. A novel process exploiting new combining valve concepts is developed for continuous rapid and complete mixing of reagents in less than 800 ms. Mixing, transfer, storage, and rinsing operations are implemented combinatorially to achieve complex assay automation protocols. The practical utility of this technology is demonstrated by performing automated serial dilution for quantitative analysis as well as the first demonstration of on-chip fluorescent derivatization of biomarker targets (carboxylic acids) for microchip capillary electrophoresis on the Mars Organic Analyzer. A language is developed to describe how unit operations are combined to form a microfluidic program. Finally, this technology is used to develop a novel microfluidic 6-sample processor for combinatorial mixing of large sets (>26 unique combinations) of reagents. The digitally programmable microfluidic Automaton is a versatile programmable sample processor for a wide range of process volumes, for multiple samples, and for different types of analyses. PMID:23172232

[Evaluation of the analyzer of hematology Beckman Coulter® HmX™ in the university hospital of Oran].

PubMed

Zmouli, N; Moulasserdoun, K; Seghier, F

2013-11-01

The choice of an automaton of haematology is a determining stage, which has to take into account at the same time the quality of the results and the economic imperatives: workload, structure and organization of the laboratory. [corrected] It is in this spirit that we estimated during a period of 3 months the analyzer of haematology: the HmX™ Coulter with boatman of samples of the company Beckman. This automaton realizes the blood numeration, the formula leukocytic and the reticulocyte count. At first, we estimated the appropriate characteristics of device. Secondly, we estimated the relevance, the sensibility and the specificity of the alarms by comparing with the reference method, which is the optical microscopy. For that purpose, 125 blood smears resulting from service of haematology and from resuscitation were examined in optical microscopy. The technical tests were realized according to the recommendations of the International committee for evaluation of automatons of haematology. The analytical performances were satisfactory in particular the big interval of linearity and the absence of contamination. As regards the evaluation of the alarms system: rate of rejection is 63%, the sensibility 86%, the specificity 70%, the positive predictive value 80%, the negative predictive value 78% and the efficiency 80%. The alarms myelaemia and atypical lymphocytes were never sources of false negatives. The alarms erythroblasts and platelet aggregates did not engendered positive forgery. The blast cell alarm was responsible for a single case of false negative. The faithfulness of automaton is satisfactory: the absence of contamination, the big interval of linearity for the leukocytes, the red blood cells and the platelets as well as a good relevance of the alarms with regard to the anomalies found on the peripheral blood smear. From the user-friendliness and practicability point of view, the HmX™ Coulter was deeply appreciated. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Evolution paths for advanced automation

NASA Technical Reports Server (NTRS)

Healey, Kathleen J.

1990-01-01

As Space Station Freedom (SSF) evolves, increased automation and autonomy will be required to meet Space Station Freedom Program (SSFP) objectives. As a precursor to the use of advanced automation within the SSFP, especially if it is to be used on SSF (e.g., to automate the operation of the flight systems), the underlying technologies will need to be elevated to a high level of readiness to ensure safe and effective operations. Ground facilities supporting the development of these flight systems -- from research and development laboratories through formal hardware and software development environments -- will be responsible for achieving these levels of technology readiness. These facilities will need to evolve support the general evolution of the SSFP. This evolution will include support for increasing the use of advanced automation. The SSF Advanced Development Program has funded a study to define evolution paths for advanced automaton within the SSFP's ground-based facilities which will enable, promote, and accelerate the appropriate use of advanced automation on-board SSF. The current capability of the test beds and facilities, such as the Software Support Environment, with regard to advanced automation, has been assessed and their desired evolutionary capabilities have been defined. Plans and guidelines for achieving this necessary capability have been constructed. The approach taken has combined indepth interviews of test beds personnel at all SSF Work Package centers with awareness of relevant state-of-the-art technology and technology insertion methodologies. Key recommendations from the study include advocating a NASA-wide task force for advanced automation, and the creation of software prototype transition environments to facilitate the incorporation of advanced automation in the SSFP.

Cellular Particle Dynamics simulation of biomechanical relaxation processes of multi-cellular systems

NASA Astrophysics Data System (ADS)

McCune, Matthew; Kosztin, Ioan

2013-03-01

Cellular Particle Dynamics (CPD) is a theoretical-computational-experimental framework for describing and predicting the time evolution of biomechanical relaxation processes of multi-cellular systems, such as fusion, sorting and compression. In CPD, cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through numerical integration of their equations of motion. Here we present CPD simulation results for the fusion of both spherical and cylindrical multi-cellular aggregates. First, we calibrate the relevant CPD model parameters for a given cell type by comparing the CPD simulation results for the fusion of two spherical aggregates to the corresponding experimental results. Next, CPD simulations are used to predict the time evolution of the fusion of cylindrical aggregates. The latter is relevant for the formation of tubular multi-cellular structures (i.e., primitive blood vessels) created by the novel bioprinting technology. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

A DNA Logic Gate Automaton for Detection of Rabies and Other Lyssaviruses.

PubMed

Vijayakumar, Pavithra; Macdonald, Joanne

2017-07-05

Immediate activation of biosensors is not always desirable, particularly if activation is due to non-specific interactions. Here we demonstrate the use of deoxyribozyme-based logic gate networks arranged into visual displays to precisely control activation of biosensors, and demonstrate a prototype molecular automaton able to discriminate between seven different genotypes of Lyssaviruses, including Rabies virus. The device uses novel mixed-base logic gates to enable detection of the large diversity of Lyssavirus sequence populations, while an ANDNOT logic gate prevents non-specific activation across genotypes. The resultant device provides a user-friendly digital-like, but molecule-powered, dot-matrix text output for unequivocal results read-out that is highly relevant for point of care applications. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Implementation and evaluation of the Level Set method: Towards efficient and accurate simulation of wet etching for microengineering applications

NASA Astrophysics Data System (ADS)

Montoliu, C.; Ferrando, N.; Gosálvez, M. A.; Cerdá, J.; Colom, R. J.

2013-10-01

The use of atomistic methods, such as the Continuous Cellular Automaton (CCA), is currently regarded as a computationally efficient and experimentally accurate approach for the simulation of anisotropic etching of various substrates in the manufacture of Micro-electro-mechanical Systems (MEMS). However, when the features of the chemical process are modified, a time-consuming calibration process needs to be used to transform the new macroscopic etch rates into a corresponding set of atomistic rates. Furthermore, changing the substrate requires a labor-intensive effort to reclassify most atomistic neighborhoods. In this context, the Level Set (LS) method provides an alternative approach where the macroscopic forces affecting the front evolution are directly applied at the discrete level, thus avoiding the need for reclassification and/or calibration. Correspondingly, we present a fully-operational Sparse Field Method (SFM) implementation of the LS approach, discussing in detail the algorithm and providing a thorough characterization of the computational cost and simulation accuracy, including a comparison to the performance by the most recent CCA model. We conclude that the SFM implementation achieves similar accuracy as the CCA method with less fluctuations in the etch front and requiring roughly 4 times less memory. Although SFM can be up to 2 times slower than CCA for the simulation of anisotropic etchants, it can also be up to 10 times faster than CCA for isotropic etchants. In addition, we present a parallel, GPU-based implementation (gSFM) and compare it to an optimized, multicore CPU version (cSFM), demonstrating that the SFM algorithm can be successfully parallelized and the simulation times consequently reduced, while keeping the accuracy of the simulations. Although modern multicore CPUs provide an acceptable option, the massively parallel architecture of modern GPUs is more suitable, as reflected by computational times for gSFM up to 7.4 times faster than for cSFM.

Research on reconstructing spatial distribution of historical cropland over 300 years in traditional cultivated regions of China

NASA Astrophysics Data System (ADS)

Yang, Xuhong; Jin, Xiaobin; Guo, Beibei; Long, Ying; Zhou, Yinkang

2015-05-01

Constructing a spatially explicit time series of historical cultivated land is of upmost importance for climatic and ecological studies that make use of Land Use and Cover Change (LUCC) data. Some scholars have made efforts to simulate and reconstruct the quantitative information on historical land use at the global or regional level based on "top-down" decision-making behaviors to match overall cropland area to land parcels using land arability and universal parameters. Considering the concentrated distribution of cultivated land and various factors influencing cropland distribution, including environmental and human factors, this study developed a "bottom-up" model of historical cropland based on constrained Cellular Automaton (CA). Our model takes a historical cropland area as an external variable and the cropland distribution in 1980 as the maximum potential scope of historical cropland. We selected elevation, slope, water availability, average annual precipitation, and distance to the nearest rural settlement as the main influencing factors of land use suitability. Then, an available labor force index is used as a proxy for the amount of cropland to inspect and calibrate these spatial patterns. This paper applies the model to a traditional cultivated region in China and reconstructs its spatial distribution of cropland during 6 periods. The results are shown as follows: (1) a constrained CA is well suited for simulating and reconstructing the spatial distribution of cropland in China's traditional cultivated region. (2) Taking the different factors affecting spatial pattern of cropland into consideration, the partitioning of the research area effectively reflected the spatial differences in cropland evolution rules and rates. (3) Compared with "HYDE datasets", this research has formed higher-resolution Boolean spatial distribution datasets of historical cropland with a more definitive concept of spatial pattern in terms of fractional format. We conclude that our reconstruction is closer to the actual change pattern of the traditional cultivated region in China.

Untangling the origin of viruses and their impact on cellular evolution.

PubMed

Nasir, Arshan; Sun, Feng-Jie; Kim, Kyung Mo; Caetano-Anollés, Gustavo

2015-04-01

The origin and evolution of viruses remain mysterious. Here, we focus on the distribution of viral replicons in host organisms, their morphological features, and the evolution of highly conserved protein and nucleic acid structures. The apparent inability of RNA viral replicons to infect contemporary akaryotic species suggests an early origin of RNA viruses and their subsequent loss in akaryotes. A census of virion morphotypes reveals that advanced forms were unique to viruses infecting a specific supergroup, while simpler forms were observed in viruses infecting organisms in all forms of cellular life. Results hint toward an ancient origin of viruses from an ancestral virus harboring either filamentous or spherical virions. Finally, phylogenetic trees built from protein domain and tRNA structures in thousands of genomes suggest that viruses evolved via reductive evolution from ancient cells. The analysis presents a complete account of the evolutionary history of cells and viruses and identifies viruses as crucial agents influencing cellular evolution. © 2015 New York Academy of Sciences.

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

NASA Technical Reports Server (NTRS)

Caines, P. E.

1999-01-01

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Phase transitions in a model for the formation of herpes simplex ulcers

NASA Astrophysics Data System (ADS)

Ferreira, Claudia P.; Fontanari, J. F.; Zorzenon Dos Santos, Rita M.

2001-10-01

The critical properties of a cellular automaton model describing the spreading of infection of the herpes simplex virus in corneal tissue are investigated through the dynamic Monte Carlo method. The model takes into account different cell susceptibilities to the viral infection, as suggested by experimental findings. In a two-dimensional square lattice the sites are associated with two distinct types of cells, namely, permissive and resistant to the infection. While a permissive cell becomes infected in the presence of a single infected cell in its neighborhood, a resistant cell needs to be surrounded by at least R>1 infected or dead cells in order to become infected. The infection is followed by the death of the cells resulting in ulcers whose forms may be dendritic (self-limited clusters) or amoeboid (percolating clusters) depending on the degree of resistance R of the resistant cells as well as on the density of permissive cells in the healthy tissue. We show that a phase transition between these two regimes occurs only for R>=5 and, in addition, that the phase transition is in the universality class of the ordinary percolation.

Fire feedbacks facilitate invasion of pine savannas by Brazilian pepper (Schinus terebinthifolius).

PubMed

Stevens, Jens T; Beckage, Brian

2009-10-01

* Fire disturbance can mediate the invasion of ecological communities by nonnative species. Nonnative plants that modify existing fire regimes may initiate a positive feedback that can facilitate their continued invasion. Fire-sensitive plants may successfully invade pyrogenic landscapes if they can inhibit fire in the landscape. * Here, we investigated whether the invasive shrub Brazilian pepper (Schinus terebinthifolius) can initiate a fire-suppression feedback in a fire-dependent pine savanna ecosystem in the southeastern USA. * We found that prescribed burns caused significant (30-45%) mortality of Brazilian pepper at low densities and that savannas with more frequent fires contained less Brazilian pepper. However, high densities of Brazilian pepper reduced fire temperature by up to 200 degrees C, and experienced as much as 80% lower mortality. * A cellular automaton model was used to demonstrate that frequent fire may control low-density populations, but that Brazilian pepper may reach a sufficient density during fire-free periods to initiate a positive feedback that reduces the frequency of fire and converts the savanna to an invasive-dominated forest.

Self-organized phenomena of pedestrian counterflow through a wide bottleneck in a channel

NASA Astrophysics Data System (ADS)

Dong, Li-Yun; Lan, Dong-Kai; Li, Xiang

2016-09-01

The pedestrian counterflow through a bottleneck in a channel shows a variety of flow patterns due to self-organization. In order to reveal the underlying mechanism, a cellular automaton model was proposed by incorporating the floor field and the view field which reflects the global information of the studied area and local interactions with others. The presented model can well reproduce typical collective behaviors, such as lane formation. Numerical simulations were performed in the case of a wide bottleneck and typical flow patterns at different density ranges were identified as rarefied flow, laminar flow, interrupted bidirectional flow, oscillatory flow, intermittent flow, and choked flow. The effects of several parameters, such as the size of view field and the width of opening, on the bottleneck flow are also analyzed in detail. The view field plays a vital role in reproducing self-organized phenomena of pedestrian. Numerical results showed that the presented model can capture key characteristics of bottleneck flows. Project supported by the National Basic Research Program of China (Grant No. 2012CB725404) and the National Natural Science Foundation of China (Grant Nos. 11172164 and 11572184).

An evolutionary framework for cultural change: Selectionism versus communal exchange

NASA Astrophysics Data System (ADS)

Gabora, Liane

2013-06-01

Dawkins' replicator-based conception of evolution has led to widespread mis-application of selectionism across the social sciences because it does not address the paradox that necessitated the theory of natural selection in the first place: how do organisms accumulate change when traits acquired over their lifetime are obliterated? This is addressed by von Neumann's concept of a self-replicating automaton (SRA). A SRA consists of a self-assembly code that is used in two distinct ways: (1) actively deciphered during development to construct a self-similar replicant, and (2) passively copied to the replicant to ensure that it can reproduce. Information that is acquired over a lifetime is not transmitted to offspring, whereas information that is inherited during copying is transmitted. In cultural evolution there is no mechanism for discarding acquired change. Acquired change can accumulate orders of magnitude faster than, and quickly overwhelm, inherited change due to differential replication of variants in response to selection. This prohibits a selectionist but not an evolutionary framework for culture and the creative processes that fuel it. The importance non-Darwinian processes in biological evolution is increasingly recognized. Recent work on the origin of life suggests that early life evolved through a non-Darwinian process referred to as communal exchange that does not involve a self-assembly code, and that natural selection emerged from this more haphazard, ancestral evolutionary process. It is proposed that communal exchange provides an evolutionary framework for culture that enables specification of cognitive features necessary for a (real or artificial) societies to evolve culture. This is supported by a computational model of cultural evolution and a conceptual network based program for documenting material cultural history, and it is consistent with high levels of human cooperation.

Simulating the behavior of patients who leave a public hospital emergency department without being seen by a physician: a cellular automaton and agent-based framework.

PubMed

Yousefi, Milad; Yousefi, Moslem; Fogliatto, F S; Ferreira, R P M; Kim, J H

2018-01-11

The objective of this study was to develop an agent based modeling (ABM) framework to simulate the behavior of patients who leave a public hospital emergency department (ED) without being seen (LWBS). In doing so, the study complements computer modeling and cellular automata (CA) techniques to simulate the behavior of patients in an ED. After verifying and validating the model by comparing it with data from a real case study, the significance of four preventive policies including increasing number of triage nurses, fast-track treatment, increasing the waiting room capacity and reducing treatment time were investigated by utilizing ordinary least squares regression. After applying the preventing policies in ED, an average of 42.14% reduction in the number of patients who leave without being seen and 6.05% reduction in the average length of stay (LOS) of patients was reported. This study is the first to apply CA in an ED simulation. Comparing the average LOS before and after applying CA with actual times from emergency department information system showed an 11% improvement. The simulation results indicated that the most effective approach to reduce the rate of LWBS is applying fast-track treatment. The ABM approach represents a flexible tool that can be constructed to reflect any given environment. It is also a support system for decision-makers to assess the relative impact of control strategies.

Simulating the behavior of patients who leave a public hospital emergency department without being seen by a physician: a cellular automaton and agent-based framework

PubMed Central

Yousefi, Milad; Yousefi, Moslem; Fogliatto, F.S.; Ferreira, R.P.M.; Kim, J.H.

2018-01-01

The objective of this study was to develop an agent based modeling (ABM) framework to simulate the behavior of patients who leave a public hospital emergency department (ED) without being seen (LWBS). In doing so, the study complements computer modeling and cellular automata (CA) techniques to simulate the behavior of patients in an ED. After verifying and validating the model by comparing it with data from a real case study, the significance of four preventive policies including increasing number of triage nurses, fast-track treatment, increasing the waiting room capacity and reducing treatment time were investigated by utilizing ordinary least squares regression. After applying the preventing policies in ED, an average of 42.14% reduction in the number of patients who leave without being seen and 6.05% reduction in the average length of stay (LOS) of patients was reported. This study is the first to apply CA in an ED simulation. Comparing the average LOS before and after applying CA with actual times from emergency department information system showed an 11% improvement. The simulation results indicated that the most effective approach to reduce the rate of LWBS is applying fast-track treatment. The ABM approach represents a flexible tool that can be constructed to reflect any given environment. It is also a support system for decision-makers to assess the relative impact of control strategies. PMID:29340526

A Critical Theory Perspective on Accelerated Learning.

ERIC Educational Resources Information Center

Brookfield, Stephen D.

2003-01-01

Critically analyzes accelerated learning using concepts from Herbert Marcuse (rebellious subjectivity) and Erich Fromm (automaton conformity). Concludes that, by providing distance and separation, accelerated learning has more potential to stimulate critical autonomous thought. (SK)

A novel time series link prediction method: Learning automata approach

NASA Astrophysics Data System (ADS)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2017-09-01

Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

A virocentric perspective on the evolution of life

PubMed Central

Koonin, Eugene V.; Dolja, Valerian V.

2015-01-01

Viruses and/or virus-like selfish elements are associated with all cellular life forms and are the most abundant biological entities on Earth, with the number of virus particles in many environments exceeding the number of cells by one to two orders of magnitude. The genetic diversity of viruses is commensurately enormous and might substantially exceed the diversity of cellular organisms. Unlike cellular organisms with their uniform replication-expression scheme, viruses possess either RNA or DNA genomes and exploit all conceivable replication-expression strategies. Although viruses extensively exchange genes with their hosts, there exists a set of viral hallmark genes that are shared by extremely diverse groups of viruses to the exclusion of cellular life forms. Coevolution of viruses and host defense systems is a key aspect in the evolution of both viruses and cells, and viral genes are often recruited for cellular functions. Together with the fundamental inevitability of the emergence of genomic parasites in any evolving replicator system, these multiple lines of evidence reveal the central role of viruses in the entire evolution of life. PMID:23850169

Implementation of a polling protocol for predicting celiac disease in videocapsule analysis

PubMed Central

Ciaccio, Edward J; Tennyson, Christina A; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

2013-01-01

AIM: To investigate the presence of small intestinal villous atrophy in celiac disease patients from quantitative analysis of videocapsule image sequences. METHODS: Nine celiac patient data with biopsy-proven villous atrophy and seven control patient data lacking villous atrophy were used for analysis. Celiacs had biopsy-proven disease with scores of Marsh II-IIIC except in the case of one hemophiliac patient. At four small intestinal levels (duodenal bulb, distal duodenum, jejunum, and ileum), video clips of length 200 frames (100 s) were analyzed. Twenty-four measurements were used for image characterization. These measurements were determined by quantitatively processing the videocapsule images via techniques for texture analysis, motility estimation, volumetric reconstruction using shape-from-shading principles, and image transformation. Each automated measurement method, or automaton, was polled as to whether or not villous atrophy was present in the small intestine, indicating celiac disease. Each automaton’s vote was determined based upon an optimized parameter threshold level, with the threshold levels being determined from prior data. A prediction of villous atrophy was made if it received the majority of votes (≥ 13), while no prediction was made for tie votes (12-12). Thus each set of images was classified as being from either a celiac disease patient or from a control patient. RESULTS: Separated by intestinal level, the overall sensitivity of automata polling for predicting villous atrophy and hence celiac disease was 83.9%, while the specificity was 92.9%, and the overall accuracy of automata-based polling was 88.1%. The method of image transformation yielded the highest sensitivity at 93.8%, while the method of texture analysis using subbands had the highest specificity at 76.0%. Similar results of prediction were observed at all four small intestinal locations, but there were more tie votes at location 4 (ileum). Incorrect prediction which reduced sensitivity occurred for two celiac patients with Marsh type II pattern, which is characterized by crypt hyperplasia, but normal villous architecture. Pooled from all levels, there was a mean of 14.31 ± 3.28 automaton votes for celiac vs 9.67 ± 3.31 automaton votes for control when celiac patient data was analyzed (P < 0.001). Pooled from all levels, there was a mean of 9.71 ± 2.8128 automaton votes for celiac vs 14.32 ± 2.7931 automaton votes for control when control patient data was analyzed (P < 0.001). CONCLUSION: Automata-based polling may be useful to indicate presence of mucosal atrophy, indicative of celiac disease, across the entire small bowel, though this must be confirmed in a larger patient set. Since the method is quantitative and automated, it can potentially eliminate observer bias and enable the detection of subtle abnormality in patients lacking a clear diagnosis. Our paradigm was found to be more efficacious at proximal small intestinal locations, which may suggest a greater presence and severity of villous atrophy at proximal as compared with distal locations. PMID:23858375

Cellular automata and epidemiological models with spatial dependence

NASA Astrophysics Data System (ADS)

Fuentes, M. A.; Kuperman, M. N.

We present a cellular automata model developed to study the evolution of an infectivity nucleus in several conditions and for two kinds of epidemiologically different diseases. We analyse the role of the model parameters, concerning the epidemiological and demographic aspects of the problem, and of the evolution rules in relation to the spread of such infectious diseases, the arising of periodic temporal modulations related to the infectivity and recovery fronts, and the evolution of travelling waves. Among the obtained results we find analogies to endemic situations and pandemics.

Molecular demultiplexer as a terminator automaton.

PubMed

Turan, Ilke S; Gunaydin, Gurcan; Ayan, Seylan; Akkaya, Engin U

2018-02-23

Molecular logic gates are expected to play an important role on the way to information processing therapeutic agents, especially considering the wide variety of physical and chemical responses that they can elicit in response to the inputs applied. Here, we show that a 1:2 demultiplexer based on a Zn 2+ -terpyridine-Bodipy conjugate with a quenched fluorescent emission, is efficient in photosensitized singlet oxygen generation as inferred from trap compound experiments and cell culture data. However, once the singlet oxygen generated by photosensitization triggers apoptotic response, the Zn 2+ complex then interacts with the exposed phosphatidylserine lipids in the external leaflet of the membrane bilayer, autonomously switching off singlet oxygen generation, and simultaneously switching on a bright emission response. This is the confirmatory signal of the cancer cell death by the action of molecular automaton and the confinement of unintended damage by excessive singlet oxygen production.

Archaic man meets a marvellous automaton: posthumanism, social robots, archetypes.

PubMed

Jones, Raya

2017-06-01

Posthumanism is associated with critical explorations of how new technologies are rewriting our understanding of what it means to be human and how they might alter human existence itself. Intersections with analytical psychology vary depending on which technologies are held in focus. Social robotics promises to populate everyday settings with entities that have populated the imagination for millennia. A legend of A Marvellous Automaton appears as early as 350 B.C. in a book of Taoist teachings, and is joined by ancient and medieval legends of manmade humanoids coming to life, as well as the familiar robots of modern science fiction. However, while the robotics industry seems to be realizing an archetypal fantasy, the technology creates new social realities that generate distinctive issues of potential relevance for the theory and practice of analytical psychology. © 2017, The Society of Analytical Psychology.

Cellular packing, mechanical stress and the evolution of multicellularity

NASA Astrophysics Data System (ADS)

Jacobeen, Shane; Pentz, Jennifer T.; Graba, Elyes C.; Brandys, Colin G.; Ratcliff, William C.; Yunker, Peter J.

2018-03-01

The evolution of multicellularity set the stage for sustained increases in organismal complexity1-5. However, a fundamental aspect of this transition remains largely unknown: how do simple clusters of cells evolve increased size when confronted by forces capable of breaking intracellular bonds? Here we show that multicellular snowflake yeast clusters6-8 fracture due to crowding-induced mechanical stress. Over seven weeks ( 291 generations) of daily selection for large size, snowflake clusters evolve to increase their radius 1.7-fold by reducing the accumulation of internal stress. During this period, cells within the clusters evolve to be more elongated, concomitant with a decrease in the cellular volume fraction of the clusters. The associated increase in free space reduces the internal stress caused by cellular growth, thus delaying fracture and increasing cluster size. This work demonstrates how readily natural selection finds simple, physical solutions to spatial constraints that limit the evolution of group size—a fundamental step in the evolution of multicellularity.

Understanding cellular architecture in cancer cells

NASA Astrophysics Data System (ADS)

Bianco, Simone; Tang, Chao

2011-03-01

Understanding the development of cancer is an important goal for today's science. The morphology of cellular organelles, such as the nucleus, the nucleoli and the mitochondria, which is referred to as cellular architecture or cytoarchitecture, is an important indicator of the state of the cell. In particular, there are striking difference between the cellular architecture of a healthy cell versus a cancer cell. In this work we present a dynamical model for the evolution of organelles morphology in cancer cells. Using a dynamical systems approach, we describe the evolution of a cell on its way to cancer as a trajectory in a multidimensional morphology state. The results provided by this work may increase our insight on the mechanism of tumorigenesis and help build new therapeutic strategies.

Pimp your landscape: a tool for qualitative evaluation of the effects of regional planning measures on ecosystem services.

PubMed

Fürst, Christine; Volk, Martin; Pietzsch, Katrin; Makeschin, Franz

2010-12-01

The article presents the platform "Pimp your landscape" (PYL), which aims firstly at the support of planners by simulating alternative land-use scenarios and by an evaluation of benefits or risks for regionally important ecosystem services. Second, PYL supports an integration of information on environmental and landscape conditions into impact assessment. Third, PYL supports the integration of impacts of planning measures on ecosystem services. PYL is a modified 2-D cellular automaton with GIS features. The cells have the major attribute "land-use type" and can be supplemented with additional information, such as specifics regarding geology, topography and climate. The GIS features support the delineation of non-cellular infrastructural elements, such as roads or water bodies. An evaluation matrix represents the core element of the system. In this matrix, values in a relative scale from 0 (lowest value) to 100 (highest value) are assigned to the land-use types and infrastructural elements depending on their effect on ecosystem services. The option to configure rules for describing the impact of environmental attributes and proximity effects on cell values and land-use transition probabilities is of particular importance. User interface and usage of the platform are demonstrated by an application case. Constraints and limits of the recent version are discussed, including the need to consider in the evaluation, landscape-structure aspects such as patch size, fragmentation and spatial connectivity. Regarding the further development, it is planned to include the impact of land management practices to support climate change adaptation and mitigation strategies in regional planning.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Noise effect in metabolic networks

NASA Astrophysics Data System (ADS)

Li, Zheng-Yan; Xie, Zheng-Wei; Chen, Tong; Ouyang, Qi

2009-12-01

Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term 'noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.

Simulation and Experimental Studies on Grain Selection and Structure Design of the Spiral Selector for Casting Single Crystal Ni-Based Superalloy.

PubMed

Zhang, Hang; Xu, Qingyan

2017-10-27

Grain selection is an important process in single crystal turbine blades manufacturing. Selector structure is a control factor of grain selection, as well as directional solidification (DS). In this study, the grain selection and structure design of the spiral selector were investigated through experimentation and simulation. A heat transfer model and a 3D microstructure growth model were established based on the Cellular automaton-Finite difference (CA-FD) method for the grain selector. Consequently, the temperature field, the microstructure and the grain orientation distribution were simulated and further verified. The average error of the temperature result was less than 1.5%. The grain selection mechanisms were further analyzed and validated through simulations. The structural design specifications of the selector were suggested based on the two grain selection effects. The structural parameters of the spiral selector, namely, the spiral tunnel diameter ( d w ), the spiral pitch ( h b ) and the spiral diameter ( h s ), were studied and the design criteria of these parameters were proposed. The experimental and simulation results demonstrated that the improved selector could accurately and efficiently produce a single crystal structure.

Simulation and Experimental Studies on Grain Selection and Structure Design of the Spiral Selector for Casting Single Crystal Ni-Based Superalloy

PubMed Central

Zhang, Hang; Xu, Qingyan

2017-01-01

Grain selection is an important process in single crystal turbine blades manufacturing. Selector structure is a control factor of grain selection, as well as directional solidification (DS). In this study, the grain selection and structure design of the spiral selector were investigated through experimentation and simulation. A heat transfer model and a 3D microstructure growth model were established based on the Cellular automaton-Finite difference (CA-FD) method for the grain selector. Consequently, the temperature field, the microstructure and the grain orientation distribution were simulated and further verified. The average error of the temperature result was less than 1.5%. The grain selection mechanisms were further analyzed and validated through simulations. The structural design specifications of the selector were suggested based on the two grain selection effects. The structural parameters of the spiral selector, namely, the spiral tunnel diameter (dw), the spiral pitch (hb) and the spiral diameter (hs), were studied and the design criteria of these parameters were proposed. The experimental and simulation results demonstrated that the improved selector could accurately and efficiently produce a single crystal structure. PMID:29077067

Numerical Simulation and Optimization of Directional Solidification Process of Single Crystal Superalloy Casting

PubMed Central

Zhang, Hang; Xu, Qingyan; Liu, Baicheng

2014-01-01

The rapid development of numerical modeling techniques has led to more accurate results in modeling metal solidification processes. In this study, the cellular automaton-finite difference (CA-FD) method was used to simulate the directional solidification (DS) process of single crystal (SX) superalloy blade samples. Experiments were carried out to validate the simulation results. Meanwhile, an intelligent model based on fuzzy control theory was built to optimize the complicate DS process. Several key parameters, such as mushy zone width and temperature difference at the cast-mold interface, were recognized as the input variables. The input variables were functioned with the multivariable fuzzy rule to get the output adjustment of withdrawal rate (v) (a key technological parameter). The multivariable fuzzy rule was built, based on the structure feature of casting, such as the relationship between section area, and the delay time of the temperature change response by changing v, and the professional experience of the operator as well. Then, the fuzzy controlling model coupled with CA-FD method could be used to optimize v in real-time during the manufacturing process. The optimized process was proven to be more flexible and adaptive for a steady and stray-grain free DS process. PMID:28788535

On supervised graph Laplacian embedding CA model & kernel construction and its application

NASA Astrophysics Data System (ADS)

Zeng, Junwei; Qian, Yongsheng; Wang, Min; Yang, Yongzhong

2017-01-01

There are many methods to construct kernel with given data attribute information. Gaussian radial basis function (RBF) kernel is one of the most popular ways to construct a kernel. The key observation is that in real-world data, besides the data attribute information, data label information also exists, which indicates the data class. In order to make use of both data attribute information and data label information, in this work, we propose a supervised kernel construction method. Supervised information from training data is integrated into standard kernel construction process to improve the discriminative property of resulting kernel. A supervised Laplacian embedding cellular automaton model is another key application developed for two-lane heterogeneous traffic flow with the safe distance and large-scale truck. Based on the properties of traffic flow in China, we re-calibrate the cell length, velocity, random slowing mechanism and lane-change conditions and use simulation tests to study the relationships among the speed, density and flux. The numerical results show that the large-scale trucks will have great effects on the traffic flow, which are relevant to the proportion of the large-scale trucks, random slowing rate and the times of the lane space change.

Bioinspired architecture approach for a one-billion transistor smart CMOS camera chip

NASA Astrophysics Data System (ADS)

Fey, Dietmar; Komann, Marcus

2007-05-01

In the paper we present a massively parallel VLSI architecture for future smart CMOS camera chips with up to one billion transistors. To exploit efficiently the potential offered by future micro- or nanoelectronic devices traditional on central structures oriented parallel architectures based on MIMD or SIMD approaches will fail. They require too long and too many global interconnects for the distribution of code or the access to common memory. On the other hand nature developed self-organising and emergent principles to manage successfully complex structures based on lots of interacting simple elements. Therefore we developed a new as Marching Pixels denoted emergent computing paradigm based on a mixture of bio-inspired computing models like cellular automaton and artificial ants. In the paper we present different Marching Pixels algorithms and the corresponding VLSI array architecture. A detailed synthesis result for a 0.18 μm CMOS process shows that a 256×256 pixel image is processed in less than 10 ms assuming a moderate 100 MHz clock rate for the processor array. Future higher integration densities and a 3D chip stacking technology will allow the integration and processing of Mega pixels within the same time since our architecture is fully scalable.

Effect of Secondary Cooling Conditions on Solidification Structure and Central Macrosegregation in Continuously Cast High-Carbon Rectangular Billet

NASA Astrophysics Data System (ADS)

Zeng, Jie; Chen, Weiqing

2015-10-01

Solidification structures of high carbon rectangular billet with a size of 180 mm × 240 mm in different secondary cooling conditions were simulated using cellular automaton-finite element (CAFE) coupling model. The adequacy of the model was compared with the simulated and the actual macrostructures of 82B steel. Effects of the secondary cooling water intensity on solidification structures including the equiaxed grain ratio and the equiaxed grain compactness were discussed. It was shown that the equiaxed grain ratio and the equiaxed grain compactness changed in the opposite direction at different secondary cooling water intensities. Increasing the secondary cooling water intensity from 0.9 or 1.1 to 1.3 L/kg could improve the equiaxed grain compactness and decrease the equiaxed grain ratio. Besides, the industrial test was conducted to investigate the effect of different secondary cooling water intensities on the center carbon macrosegregation of 82B steel. The optimum secondary cooling water intensity was 0.9 L/kg, while the center carbon segregation degree was 1.10. The relationship between solidification structure and center carbon segregation was discussed based on the simulation results and the industrial test.

Analysis of the effect of older drivers’ driving behaviors on traffic flow based on a modified CA model

NASA Astrophysics Data System (ADS)

Jian, Mei-Ying; Shi, Jing; Liu, Yang

2016-09-01

As the global population ages, there are more and more older drivers on the road. The decline in driving performance of older drivers may influence the properties of traffic flow and safety. The purpose of this paper is to investigate the effect of older drivers’ driving behaviors on traffic flow. A modified cellular automaton (CA) model which takes driving behaviors of older drivers into account is proposed. The simulation results indicate that older drivers’ driving behaviors induce a reduction in traffic flow especially when the density is higher than 15 vehicles per km per lane and an increase in Lane-changing frequency. The analysis of stability shows that a number of disturbances could frequently emerge, be propagated and eventually dissipate in this modified model. The results also reflect that with the increase of older drivers on the road, the probability of the occurrence of rear-end collisions increases greatly and obviously. Furthermore, the value of acceleration influences the traffic flow and safety significantly. These results provide the theoretical basis and reference for the traffic management departments to develop traffic management measure in the aging society.

Determination and controlling of grain structure of metals after laser incidence: Theoretical approach

PubMed Central

Dezfoli, Amir Reza Ansari; Hwang, Weng-Sing; Huang, Wei-Chin; Tsai, Tsung-Wen

2017-01-01

There are serious questions about the grain structure of metals after laser melting and the ways that it can be controlled. In this regard, the current paper explains the grain structure of metals after laser melting using a new model based on combination of 3D finite element (FE) and cellular automaton (CA) models validated by experimental observation. Competitive grain growth, relation between heat flows and grain orientation and the effect of laser scanning speed on final micro structure are discussed with details. Grains structure after laser melting is founded to be columnar with a tilt angle toward the direction of the laser movement. Furthermore, this investigation shows that the grain orientation is a function of conduction heat flux at molten pool boundary. Moreover, using the secondary laser heat source (SLHS) as a new approach to control the grain structure during the laser melting is presented. The results proved that the grain structure can be controlled and improved significantly using SLHS. Using SLHS, the grain orientation and uniformity can be change easily. In fact, this method can help us to produce materials with different local mechanical properties during laser processing according to their application requirements. PMID:28134347

Elevation Control on Vegetation Organization in a Semiarid Ecosystem in Central New Mexico

NASA Astrophysics Data System (ADS)

Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

2015-12-01

Many semiarid and desert ecosystems are characterized by patchy and dynamic vegetation. Topography plays a commanding role on vegetation patterns. It is observed that plant biomes and biodiversity vary systematically with slope and aspect, from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations. In this study, we investigate the role of elevation dependent climatology on vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. An ecohydrologic cellular automaton model developed within Landlab (component based modeling framework) is used. The model couples local vegetation dynamics (that simulate biomass production based on local soil moisture and potential evapotranspiration) and plant establishment and mortality based on competition for resources and space. This model is driven by elevation dependent rainfall pulses and solar radiation. The domain is initialized with randomly assigned plant types and the model parameters that couple plant response with soil moisture are systematically changed. Climate perturbation experiments are conducted to examine spatial vegetation organization and associated timescales. Model results reproduce elevation and aspect controls on observed vegetation patterns indicating that this model captures necessary and sufficient conditions that explain these observed ecohydrological patterns.

Traffic jams induce dynamical phase transition in spatial rock-paper-scissors game

NASA Astrophysics Data System (ADS)

Nagatani, Takashi; Ichinose, Genki; Tainaka, Kei-ichi

2018-02-01

Spatial and temporal behaviors of the rock-paper-scissors (RPS) game is key to understanding not only biodiversity but also a variety of cyclic systems. It has been demonstrated that, in the stochastic cellular automaton of RPS game, three species cannot survive on one-dimensional (1-d) lattice; only a single species survives. Previous studies have shown that three species are able to coexist if the migration of species is considered. However, their definitions of migration are the swapping of two species or the random walk of species, which rarely occurs in nature. Here, we investigate the effect of migration by using the 1-d lattice traffic model in which species can move rightward if the site ahead is empty. Computer simulations reveal that three species can survive at the same time within the wide range of parameter values. At low densities, all species can coexist. In contrast, the extinction of two species occurs if the density exceeds the critical limit of the jamming transition. This dynamical phase transition between the coexistence and single (non-coexistence) phase clearly separates due to the self-organized pattern: condensation and rarefaction in the stripe-pattern of three species.

Effect of speed matching on fundamental diagram of pedestrian flow

NASA Astrophysics Data System (ADS)

Fu, Zhijian; Luo, Lin; Yang, Yue; Zhuang, Yifan; Zhang, Peitong; Yang, Lizhong; Yang, Hongtai; Ma, Jian; Zhu, Kongjin; Li, Yanlai

2016-09-01

Properties of pedestrian may change along their moving path, for example, as a result of fatigue or injury, which has never been properly investigated in the past research. The paper attempts to study the speed matching effect (a pedestrian adjusts his velocity constantly to the average velocity of his neighbors) and its influence on the density-velocity relationship (a pedestrian adjust his velocity to the surrounding density), known as the fundamental diagram of the pedestrian flow. By the means of the cellular automaton, the simulation results fit well with the empirical data, indicating the great advance of the discrete model for pedestrian dynamics. The results suggest that the system velocity and flow rate increase obviously under a big noise, i.e., a diverse composition of pedestrian crowd, especially in the region of middle or high density. Because of the temporary effect, the speed matching has little influence on the fundamental diagram. Along the entire density, the relationship between the step length and the average pedestrian velocity is a piecewise function combined two linear functions. The number of conflicts reaches the maximum with the pedestrian density of 2.5 m-2, while decreases by 5.1% with the speed matching.

Preliminary cellular-automata forecast of permit activity from 1998 to 2010, Idaho and Western Montana

USGS Publications Warehouse

Raines, G.L.; Zientek, M.L.; Causey, J.D.; Boleneus, D.E.

2002-01-01

For public land management in Idaho and western Montana, the U.S. Forest Service (USFS) has requested that the U.S. Geological Survey (USGS) predict where mineral-related activity will occur in the next decade. Cellular automata provide an approach to simulation of this human activity. Cellular automata (CA) are defined by an array of cells, which evolve by a simple transition rule, the automaton. Based on exploration trends, we assume that future exploration will focus in areas of past exploration. Spatial-temporal information about mineral-related activity, that is permits issued by USFS and Bureau of Land Management (BLM) in the last decade, and spatial information about undiscovered resources, provide a basis to calibrate a CA. The CA implemented is a modified annealed voting rule that simulates mineral-related activity with spatial and temporal resolution of 1 mi2 and 1 year based on activity from 1989 to 1998. For this CA, the state of the economy and exploration technology is assumed constant for the next decade. The calibrated CA reproduces the 1989-1998-permit activity with an agreement of 94%, which increases to 98% within one year. Analysis of the confusion matrix and kappa correlation statistics indicates that the CA underestimates high activity and overestimates low activity. Spatially, the major differences between the actual and calculated activity are that the calculated activity occurs in a slightly larger number of small patches and is slightly more uneven than the actual activity. Using the calibrated CA in a Monte Carlo simulation projecting from 1998 to 2010, an estimate of the probability of mineral activity shows high levels of activity in Boise, Caribou, Elmore, Lincoln, and western Valley counties in Idaho and Beaverhead, Madison, and Stillwater counties in Montana, and generally low activity elsewhere. ?? 2002 International Association for Mathematical Geology.

Research on the comparison of extension mechanism of cellular automaton based on hexagon grid and rectangular grid

NASA Astrophysics Data System (ADS)

Zhai, Xiaofang; Zhu, Xinyan; Xiao, Zhifeng; Weng, Jie

2009-10-01

Historically, cellular automata (CA) is a discrete dynamical mathematical structure defined on spatial grid. Research on cellular automata system (CAS) has focused on rule sets and initial condition and has not discussed its adjacency. Thus, the main focus of our study is the effect of adjacency on CA behavior. This paper is to compare rectangular grids with hexagonal grids on their characteristics, strengths and weaknesses. They have great influence on modeling effects and other applications including the role of nearest neighborhood in experimental design. Our researches present that rectangular and hexagonal grids have different characteristics. They are adapted to distinct aspects, and the regular rectangular or square grid is used more often than the hexagonal grid. But their relative merits have not been widely discussed. The rectangular grid is generally preferred because of its symmetry, especially in orthogonal co-ordinate system and the frequent use of raster from Geographic Information System (GIS). However, in terms of complex terrain, uncertain and multidirectional region, we have preferred hexagonal grids and methods to facilitate and simplify the problem. Hexagonal grids can overcome directional warp and have some unique characteristics. For example, hexagonal grids have a simpler and more symmetric nearest neighborhood, which avoids the ambiguities of the rectangular grids. Movement paths or connectivity, the most compact arrangement of pixels, make hexagonal appear great dominance in the process of modeling and analysis. The selection of an appropriate grid should be based on the requirements and objectives of the application. We use rectangular and hexagonal grids respectively for developing city model. At the same time we make use of remote sensing images and acquire 2002 and 2005 land state of Wuhan. On the base of city land state in 2002, we make use of CA to simulate reasonable form of city in 2005. Hereby, these results provide a proof of concept for hexagonal which has great dominance.

Rab protein evolution and the history of the eukaryotic endomembrane system

PubMed Central

Brighouse, Andrew; Dacks, Joel B.

2010-01-01

Spectacular increases in the quantity of sequence data genome have facilitated major advances in eukaryotic comparative genomics. By exploiting homology with classical model organisms, this makes possible predictions of pathways and cellular functions currently impossible to address in intractable organisms. Echoing realization that core metabolic processes were established very early following evolution of life on earth, it is now emerging that many eukaryotic cellular features, including the endomembrane system, are ancient and organized around near-universal principles. Rab proteins are key mediators of vesicle transport and specificity, and via the presence of multiple paralogues, alterations in interaction specificity and modification of pathways, contribute greatly to the evolution of complexity of membrane transport. Understanding system-level contributions of Rab proteins to evolutionary history provides insight into the multiple processes sculpting cellular transport pathways and the exciting challenges that we face in delving further into the origins of membrane trafficking specificity. PMID:20582450

Does constructive neutral evolution play an important role in the origin of cellular complexity? Making sense of the origins and uses of biological complexity.

PubMed

Speijer, Dave

2011-05-01

Recently, constructive neutral evolution has been touted as an important concept for the understanding of the emergence of cellular complexity. It has been invoked to help explain the development and retention of, amongst others, RNA splicing, RNA editing and ribosomal and mitochondrial respiratory chain complexity. The theory originated as a welcome explanation of isolated small scale cellular idiosyncrasies and as a reaction to 'overselectionism'. Here I contend, that in its extended form, it has major conceptual problems, can not explain observed patterns of complex processes, is too easily dismissive of alternative selectionist models, underestimates the creative force of complexity as such, and--if seen as a major evolutionary mechanism for all organisms--could stifle further thought regarding the evolution of highly complex biological processes. Copyright © 2011 WILEY Periodicals, Inc.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Expanding the metabolic engineering toolbox with directed evolution.

PubMed

Abatemarco, Joseph; Hill, Andrew; Alper, Hal S

2013-12-01

Cellular systems can be engineered into factories that produce high-value chemicals from renewable feedstock. Such an approach requires an expanded toolbox for metabolic engineering. Recently, protein engineering and directed evolution strategies have started to play a growing and critical role within metabolic engineering. This review focuses on the various ways in which directed evolution can be applied in conjunction with metabolic engineering to improve product yields. Specifically, we discuss the application of directed evolution on both catalytic and non-catalytic traits of enzymes, on regulatory elements, and on whole genomes in a metabolic engineering context. We demonstrate how the goals of metabolic pathway engineering can be achieved in part through evolving cellular parts as opposed to traditional approaches that rely on gene overexpression and deletion. Finally, we discuss the current limitations in screening technology that hinder the full implementation of a metabolic pathway-directed evolution approach. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Steampunk: Full Steam Ahead

ERIC Educational Resources Information Center

Campbell, Heather M.

2010-01-01

Steam-powered machines, anachronistic technology, clockwork automatons, gas-filled airships, tentacled monsters, fob watches, and top hats--these are all elements of steampunk. Steampunk is both speculative fiction that imagines technology evolved from steam-powered cogs and gears--instead of from electricity and computers--and a movement that…

[History of robotics: from Archytas of Tarentum until da Vinci robot. (Part I)].

PubMed

Sánchez Martín, F M; Millán Rodríguez, F; Salvador Bayarri, J; Palou Redorta, J; Rodríguez Escovar, F; Esquena Fernández, S; Villavicencio Mavrich, H

2007-02-01

Robotic surgery is the newst technologic option in urology. To understand how new robots work is interesting to know their history. The desire to design machines imitating humans continued for more than 4000 years. There are references to King-su Tse (clasic China) making up automaton at 500 a. C. Archytas of Tarentum (at around 400 a.C.) is considered the father of mechanical engineering, and one of the occidental robotics classic referents. Heron of Alexandria, Hsieh-Fec, Al-Jazari, Roger Bacon, Juanelo Turriano, Leonardo da Vinci, Vaucanson o von Kempelen were robot inventors in the middle age, renaissance and classicism. At the XIXth century, automaton production underwent a peak and all engineering branches suffered a great development. At 1942 Asimov published the three robotics laws, based on mechanics, electronics and informatics advances. At XXth century robots able to do very complex self governing works were developed, like da Vinci Surgical System (Intuitive Surgical Inc, Sunnyvale, CA, USA), a very sophisticated robot to assist surgeons.

Evolution and the complexity of bacteriophages.

PubMed

Serwer, Philip

2007-03-13

The genomes of both long-genome (> 200 Kb) bacteriophages and long-genome eukaryotic viruses have cellular gene homologs whose selective advantage is not explained. These homologs add genomic and possibly biochemical complexity. Understanding their significance requires a definition of complexity that is more biochemically oriented than past empirically based definitions. Initially, I propose two biochemistry-oriented definitions of complexity: either decreased randomness or increased encoded information that does not serve immediate needs. Then, I make the assumption that these two definitions are equivalent. This assumption and recent data lead to the following four-part hypothesis that explains the presence of cellular gene homologs in long bacteriophage genomes and also provides a pathway for complexity increases in prokaryotic cells: (1) Prokaryotes underwent evolutionary increases in biochemical complexity after the eukaryote/prokaryote splits. (2) Some of the complexity increases occurred via multi-step, weak selection that was both protected from strong selection and accelerated by embedding evolving cellular genes in the genomes of bacteriophages and, presumably, also archaeal viruses (first tier selection). (3) The mechanisms for retaining cellular genes in viral genomes evolved under additional, longer-term selection that was stronger (second tier selection). (4) The second tier selection was based on increased access by prokaryotic cells to improved biochemical systems. This access was achieved when DNA transfer moved to prokaryotic cells both the more evolved genes and their more competitive and complex biochemical systems. I propose testing this hypothesis by controlled evolution in microbial communities to (1) determine the effects of deleting individual cellular gene homologs on the growth and evolution of long genome bacteriophages and hosts, (2) find the environmental conditions that select for the presence of cellular gene homologs, (3) determine which, if any, bacteriophage genes were selected for maintaining the homologs and (4) determine the dynamics of homolog evolution. This hypothesis is an explanation of evolutionary leaps in general. If accurate, it will assist both understanding and influencing the evolution of microbes and their communities. Analysis of evolutionary complexity increase for at least prokaryotes should include analysis of genomes of long-genome bacteriophages.

Automatic procedures generator for orbital rendezvous maneuver

NASA Technical Reports Server (NTRS)

Kohn, W.; Van Valkenburg, J. A.; Dunn, C. K.

1985-01-01

This paper describes the development of an expert system for defining and dynamically updating procedures for an orbital rendezvous maneuver. The product of the expert system is a procedure represented by a Moore automaton. The construction is recursive and driven by a simulation of the rendezvousing bodies.

Academetron, Automaton, Phantom: Uncanny Digital Pedagogies

ERIC Educational Resources Information Center

Bayne, Sian

2010-01-01

This paper explores the possibility of an uncanny digital pedagogy. Drawing on theories of the uncanny from psychoanalysis, cultural studies and educational philosophy, it considers how being online defamiliarises teaching, asking us to question and consider anew established academic practices and conventions. It touches on recent thinking on…

Coupled pulsating and cellular structure in the propagation of globally planar detonations in free space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Wenhu; Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Thermal Engineering, Tsinghua University, Beijing 100084; Gao, Yang, E-mail: gaoyang-00@mails.tsinghua.edu.cn

The globally planar detonation in free space is numerically simulated, with particular interest to understand and quantify the emergence and evolution of the one-dimensional pulsating instability and the two-dimensional cellular structure which is inherently also affected by pulsating instability. It is found that the pulsation includes three stages: rapid decay of the overdrive, approach to the Chapman-Jouguet state and emergence of weak pulsations, and the formation of strong pulsations; while evolution of the cellular structure also exhibits distinct behavior at these three stages: no cell formation, formation of small-scale, irregular cells, and formation of regular cells of a larger scale.more » Furthermore, the average shock pressure in the detonation front consists of fine-scale oscillations reflecting the collision dynamics of the triple-shock structure and large-scale oscillations affected by the global pulsation. The common stages of evolution between the cellular structure and the pulsating behavior, as well as the existence of shock-front pressure oscillation, suggest highly correlated mechanisms between them. Detonations with period doubling, period quadrupling, and chaotic amplitudes were also observed and studied for progressively increasing activation energies.« less

The Evolution of Multicellular Plants and Animals.

ERIC Educational Resources Information Center

Valentine, James W.

1978-01-01

Traces the evolution of unicellular organisms to the multi-cellular plants and animals in existence today. Major events are depicted in a geologic timetable. Organisms, extinct and recent, are classified by taxonomic group. (MA)

Disruptive chemicals, senescence and immortality

PubMed Central

Carnero, Amancio; Blanco-Aparicio, Carmen; Kondoh, Hiroshi; Lleonart, Matilde E.; Martinez-Leal, Juan Fernando; Mondello, Chiara; Ivana Scovassi, A.; Bisson, William H.; Amedei, Amedeo; Roy, Rabindra; Woodrick, Jordan; Colacci, Annamaria; Vaccari, Monica; Raju, Jayadev; Al-Mulla, Fahd; Al-Temaimi, Rabeah; Salem, Hosni K.; Memeo, Lorenzo; Forte, Stefano; Singh, Neetu; Hamid, Roslida A.; Ryan, Elizabeth P.; Brown, Dustin G.; Wise, John Pierce; Wise, Sandra S.; Yasaei, Hemad

2015-01-01

Carcinogenesis is thought to be a multistep process, with clonal evolution playing a central role in the process. Clonal evolution involves the repeated ‘selection and succession’ of rare variant cells that acquire a growth advantage over the remaining cell population through the acquisition of ‘driver mutations’ enabling a selective advantage in a particular micro-environment. Clonal selection is the driving force behind tumorigenesis and possesses three basic requirements: (i) effective competitive proliferation of the variant clone when compared with its neighboring cells, (ii) acquisition of an indefinite capacity for self-renewal, and (iii) establishment of sufficiently high levels of genetic and epigenetic variability to permit the emergence of rare variants. However, several questions regarding the process of clonal evolution remain. Which cellular processes initiate carcinogenesis in the first place? To what extent are environmental carcinogens responsible for the initiation of clonal evolution? What are the roles of genotoxic and non-genotoxic carcinogens in carcinogenesis? What are the underlying mechanisms responsible for chemical carcinogen-induced cellular immortality? Here, we explore the possible mechanisms of cellular immortalization, the contribution of immortalization to tumorigenesis and the mechanisms by which chemical carcinogens may contribute to these processes. PMID:26106138

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Chaitin, L. J.; Duda, R. O.; Johanson, P. A.; Raphael, B.; Rosen, C. A.; Yates, R. A.

1970-01-01

The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

Canalization and Control in Automata Networks: Body Segmentation in Drosophila melanogaster

PubMed Central

Marques-Pita, Manuel; Rocha, Luis M.

2013-01-01

We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics – a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity – with the ultimate goal of explaining how do cells and tissues ‘compute’. PMID:23520449

Canalization and control in automata networks: body segmentation in Drosophila melanogaster.

PubMed

Marques-Pita, Manuel; Rocha, Luis M

2013-01-01

We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics--a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity--with the ultimate goal of explaining how do cells and tissues 'compute'.

Reproducing the Photospheric Magnetic Field Evolution during the Rise of Cycle 24 with Flux Transport by Supergranules

NASA Technical Reports Server (NTRS)

Hathaway, David; Upton, Lisa

2012-01-01

We simulate the transport of magnetic flux in the Sun s photosphere by an evolving pattern of cellular horizontal flows (supergranules). Characteristics of the simulated flow pattern can match observed characteristics including the velocity power spectrum, cell lifetimes, and cell motions in longitude and latitude. Simulations using an average, and north-south symmetric, meridional motion of the cellular pattern produce polar magnetic fields that are too weak in the North and too strong in the South. Simulations using cellular patterns with meridional motions that evolve with the observed changes in strength and north-south asymmetry will be analyzed to see if they reproduce the polar field evolution observed during the rise of Cycle 24.

Reproducing the Photospheric Magnetic Field Evolution During the Rise of Cycle 24 with Flux Transport by Supergranules

NASA Technical Reports Server (NTRS)

Hathaway, David H.; Upton, Lisa

2012-01-01

We simulate the transport of magnetic flux in the Sun s photosphere by an evolving pattern of cellular horizontal flows (supergranules). Characteristics of the simulated flow pattern match observed characteristics including the velocity power spectrum, cell lifetimes, and cell pattern motion in longitude and latitude. Simulations using an average, and north-south symmetric, meridional motion of the cellular pattern produce polar magnetic fields that are too weak in the North and too strong in the South. Simulations using cellular patterns with meridional motions that evolve with the observed changes in strength and north-south asymmetry will be analyzed to see if they reproduce the polar field evolution observed during the rise of Cycle 24.

Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results

NASA Astrophysics Data System (ADS)

Iannone, G.; Troisi, A.

2013-05-01

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

Evolution of Courtship Songs in Xenopus : Vocal Pattern Generation and Sound Production.

PubMed

Leininger, Elizabeth C; Kelley, Darcy B

2015-01-01

The extant species of African clawed frogs (Xenopus and Silurana) provide an opportunity to link the evolution of vocal characters to changes in the responsible cellular and molecular mechanisms. In this review, we integrate several robust lines of research: evolutionary trajectories of Xenopus vocalizations, cellular and circuit-level mechanisms of vocalization in selected Xenopus model species, and Xenopus evolutionary history and speciation mechanisms. Integrating recent findings allows us to generate and test specific hypotheses about the evolution of Xenopus vocal circuits. We propose that reduced vocal sex differences in some Xenopus species result from species-specific losses of sexually differentiated neural and neuromuscular features. Modification of sex-hormone-regulated developmental mechanisms is a strong candidate mechanism for reduced vocal sex differences.

Teaching Note-Teaching Student Interviewing Competencies through Second Life

ERIC Educational Resources Information Center

Tandy, Cynthia; Vernon, Robert; Lynch, Darlene

2017-01-01

A prototype standardized client was created and programmed to respond to students in the 3D virtual world of Second Life. This automaton, called a "chatbot," was repeatedly interviewed by beginning MSW students in a practice course as a learning exercise. Initial results were positive and suggest the use of simulated clients in virtual…

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information.

PubMed

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft's algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms.

A detailed experimental study of a DNA computer with two endonucleases.

PubMed

Sakowski, Sebastian; Krasiński, Tadeusz; Sarnik, Joanna; Blasiak, Janusz; Waldmajer, Jacek; Poplawski, Tomasz

2017-07-14

Great advances in biotechnology have allowed the construction of a computer from DNA. One of the proposed solutions is a biomolecular finite automaton, a simple two-state DNA computer without memory, which was presented by Ehud Shapiro's group at the Weizmann Institute of Science. The main problem with this computer, in which biomolecules carry out logical operations, is its complexity - increasing the number of states of biomolecular automata. In this study, we constructed (in laboratory conditions) a six-state DNA computer that uses two endonucleases (e.g. AcuI and BbvI) and a ligase. We have presented a detailed experimental verification of its feasibility. We described the effect of the number of states, the length of input data, and the nondeterminism on the computing process. We also tested different automata (with three, four, and six states) running on various accepted input words of different lengths such as ab, aab, aaab, ababa, and of an unaccepted word ba. Moreover, this article presents the reaction optimization and the methods of eliminating certain biochemical problems occurring in the implementation of a biomolecular DNA automaton based on two endonucleases.

Biomolecular computers with multiple restriction enzymes.

PubMed

Sakowski, Sebastian; Krasinski, Tadeusz; Waldmajer, Jacek; Sarnik, Joanna; Blasiak, Janusz; Poplawski, Tomasz

2017-01-01

The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann "bottleneck". Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro's group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases.

Fundamental energy limits of SET-based Brownian NAND and half-adder circuits. Preliminary findings from a physical-information-theoretic methodology

NASA Astrophysics Data System (ADS)

Ercan, İlke; Suyabatmaz, Enes

2018-06-01

The saturation in the efficiency and performance scaling of conventional electronic technologies brings about the development of novel computational paradigms. Brownian circuits are among the promising alternatives that can exploit fluctuations to increase the efficiency of information processing in nanocomputing. A Brownian cellular automaton, where signals propagate randomly and are driven by local transition rules, can be made computationally universal by embedding arbitrary asynchronous circuits on it. One of the potential realizations of such circuits is via single electron tunneling (SET) devices since SET technology enable simulation of noise and fluctuations in a fashion similar to Brownian search. In this paper, we perform a physical-information-theoretic analysis on the efficiency limitations in a Brownian NAND and half-adder circuits implemented using SET technology. The method we employed here establishes a solid ground that enables studying computational and physical features of this emerging technology on an equal footing, and yield fundamental lower bounds that provide valuable insights into how far its efficiency can be improved in principle. In order to provide a basis for comparison, we also analyze a NAND gate and half-adder circuit implemented in complementary metal oxide semiconductor technology to show how the fundamental bound of the Brownian circuit compares against a conventional paradigm.

Unsupervised segmentation of lungs from chest radiographs

NASA Astrophysics Data System (ADS)

Ghosh, Payel; Antani, Sameer K.; Long, L. Rodney; Thoma, George R.

2012-03-01

This paper describes our preliminary investigations for deriving and characterizing coarse-level textural regions present in the lung field on chest radiographs using unsupervised grow-cut (UGC), a cellular automaton based unsupervised segmentation technique. The segmentation has been performed on a publicly available data set of chest radiographs. The algorithm is useful for this application because it automatically converges to a natural segmentation of the image from random seed points using low-level image features such as pixel intensity values and texture features. Our goal is to develop a portable screening system for early detection of lung diseases for use in remote areas in developing countries. This involves developing automated algorithms for screening x-rays as normal/abnormal with a high degree of sensitivity, and identifying lung disease patterns on chest x-rays. Automatically deriving and quantitatively characterizing abnormal regions present in the lung field is the first step toward this goal. Therefore, region-based features such as geometrical and pixel-value measurements were derived from the segmented lung fields. In the future, feature selection and classification will be performed to identify pathological conditions such as pulmonary tuberculosis on chest radiographs. Shape-based features will also be incorporated to account for occlusions of the lung field and by other anatomical structures such as the heart and diaphragm.

Study on Earthquake Emergency Evacuation Drill Trainer Development

NASA Astrophysics Data System (ADS)

ChangJiang, L.

2016-12-01

With the improvement of China's urbanization, to ensure people survive the earthquake needs scientific routine emergency evacuation drills. Drawing on cellular automaton, shortest path algorithm and collision avoidance, we designed a model of earthquake emergency evacuation drill for school scenes. Based on this model, we made simulation software for earthquake emergency evacuation drill. The software is able to perform the simulation of earthquake emergency evacuation drill by building spatial structural model and selecting the information of people's location grounds on actual conditions of constructions. Based on the data of simulation, we can operate drilling in the same building. RFID technology could be used here for drill data collection which read personal information and send it to the evacuation simulation software via WIFI. Then the simulation software would contrast simulative data with the information of actual evacuation process, such as evacuation time, evacuation path, congestion nodes and so on. In the end, it would provide a contrastive analysis report to report assessment result and optimum proposal. We hope the earthquake emergency evacuation drill software and trainer can provide overall process disposal concept for earthquake emergency evacuation drill in assembly occupancies. The trainer can make the earthquake emergency evacuation more orderly, efficient, reasonable and scientific to fulfill the increase in coping capacity of urban hazard.

Study of the Formation Mechanism of A-Segregation Based on Microstructural Morphology

NASA Astrophysics Data System (ADS)

Zhang, Zhao; Bao, Yuchong; Liu, Lin; Pian, Song; Li, Ri

2018-04-01

A model that combines a cellular automaton (CA) and lattice Boltzmann method (LBM) is presented. The mechanism of A-segregation in an Fe-0.34 wt pct C alloy ingot is analyzed on the basis of microstructural morphology calculations. The CA is used to capture the solid/liquid interface, while the LBM is used to calculate the transport phenomena. (1) The solidification of global columnar dendrites was simulated, and two obvious A-segregation bands appeared in the middle-radius region between the ingot wall surface and the centerline. In addition, the angle of deflection to the centerline increased with the increasing heat dissipation rate of the wall surface. When natural convection was ignored, the A-segregation disappeared, and only positive segregation was present in the center and bottom corner of the ingot. (2) Mixed columnar-equiaxed solidification was simulated. Many A-segregation bands appeared in the ingot. (3) Global equiaxed solidification was simulated, and no A-segregation bands were found. The results show that the upward movement of the high-concentration melt is the key to the formation of A-segregation bands, and remelting and the emergence of equiaxed grains are not necessary conditions to develop these bands. However, the appearance of equiaxed grains accelerates the formation of vortexes; thus, many A-segregation bands appear during columnar-equiaxed solidification.

Statistical fluctuations in pedestrian evacuation times and the effect of social contagion

NASA Astrophysics Data System (ADS)

Nicolas, Alexandre; Bouzat, Sebastián; Kuperman, Marcelo N.

2016-08-01

Mathematical models of pedestrian evacuation and the associated simulation software have become essential tools for the assessment of the safety of public facilities and buildings. While a variety of models is now available, their calibration and test against empirical data are generally restricted to global averaged quantities; the statistics compiled from the time series of individual escapes ("microscopic" statistics) measured in recent experiments are thus overlooked. In the same spirit, much research has primarily focused on the average global evacuation time, whereas the whole distribution of evacuation times over some set of realizations should matter. In the present paper we propose and discuss the validity of a simple relation between this distribution and the microscopic statistics, which is theoretically valid in the absence of correlations. To this purpose, we develop a minimal cellular automaton, with features that afford a semiquantitative reproduction of the experimental microscopic statistics. We then introduce a process of social contagion of impatient behavior in the model and show that the simple relation under test may dramatically fail at high contagion strengths, the latter being responsible for the emergence of strong correlations in the system. We conclude with comments on the potential practical relevance for safety science of calculations based on microscopic statistics.

Spatial and temporal dynamics of cellulose degradation and biofilm formation by Caldicellulosiruptor obsidiansis and Clostridium thermocellum Caldicellulosiruptor obsidiansis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhiwu; Lee, Sueng-Hwan; Elkins, James G

2011-01-01

Cellulose degradation is one of the major bottlenecks of a consolidated bioprocess that employs cellulolytic bacterial cells as catalysts to produce biofuels from cellulosic biomass. In this study, we investigated the spatial and temporal dynamics of cellulose degradation by Caldicellulosiruptor obsidiansis, which does not produce cellulosomes, and Clostridium thermocellum, which does produce cellulosomes. Results showed that the degradation of either regenerated or natural cellulose was synchronized with biofilm formation, a process characterized by the formation and fusion of numerous crater-like depressions on the cellulose surface. In addition, the dynamics of biofilm formation were similar in both bacteria, regardless of cellulosomemore » production. Only the areas of cellulose surface colonized by microbes were significantly degraded, highlighting the essential role of the cellulolytic biofilm in cellulose utilization. After initial attachment, the microbial biofilm structure remained thin, uniform and dense throughout the experiment. A cellular automaton model, constructed under the assumption that the attached cells divide and produce daughter cells that contribute to the hydrolysis of the adjacent cellulose, can largely simulate the observed process of biofilm formation and cellulose degradation. This study presents a model, based on direct observation, correlating cellulolytic biofilm formation with cellulose degradation.« less

Numerical Simulation of the Global Star Formation Pattern in the LMC

NASA Astrophysics Data System (ADS)

Gardiner, L. T.; Turfus, C.

Dottori et al. (1996, ApJ 461, 742) have recently presented evidence for the idea that the observed distribution of young star clusters in the Large Magellanic Cloud (LMC) has resulted from the gravitational perturbation induced by a bar potential offset from the LMC disk center. We have constructed a dynamical model of the LMC to examine the effects of such an off-center perturbation on the global distribution of the gas and star formation activity. We have used a newly developed hybrid N-body/cellular automaton scheme for modeling star formation in galaxies which incorporates the dual mechanisms of gravitational instability and self-propagating star formation, combined with feedback of kinetic energy from star-forming regions into the interstellar medium. We find that a weak rotating bar perturbation, whose center is displaced by 0.6 kpc from the disk center, gives rise to an asymmetric spiral structure which mimics the chains of recent star formation observed in the LMC as well as delineating activity in the bar region. Large gas concentrations are produced where the spiral arms merge in the northern part of the galaxy, and such structures may have observed counterparts in giant star-forming complexes such as Constellation III in the NE part of the LMC.

Disruptive chemicals, senescence and immortality.

PubMed

Carnero, Amancio; Blanco-Aparicio, Carmen; Kondoh, Hiroshi; Lleonart, Matilde E; Martinez-Leal, Juan Fernando; Mondello, Chiara; Scovassi, A Ivana; Bisson, William H; Amedei, Amedeo; Roy, Rabindra; Woodrick, Jordan; Colacci, Annamaria; Vaccari, Monica; Raju, Jayadev; Al-Mulla, Fahd; Al-Temaimi, Rabeah; Salem, Hosni K; Memeo, Lorenzo; Forte, Stefano; Singh, Neetu; Hamid, Roslida A; Ryan, Elizabeth P; Brown, Dustin G; Wise, John Pierce; Wise, Sandra S; Yasaei, Hemad

2015-06-01

Carcinogenesis is thought to be a multistep process, with clonal evolution playing a central role in the process. Clonal evolution involves the repeated 'selection and succession' of rare variant cells that acquire a growth advantage over the remaining cell population through the acquisition of 'driver mutations' enabling a selective advantage in a particular micro-environment. Clonal selection is the driving force behind tumorigenesis and possesses three basic requirements: (i) effective competitive proliferation of the variant clone when compared with its neighboring cells, (ii) acquisition of an indefinite capacity for self-renewal, and (iii) establishment of sufficiently high levels of genetic and epigenetic variability to permit the emergence of rare variants. However, several questions regarding the process of clonal evolution remain. Which cellular processes initiate carcinogenesis in the first place? To what extent are environmental carcinogens responsible for the initiation of clonal evolution? What are the roles of genotoxic and non-genotoxic carcinogens in carcinogenesis? What are the underlying mechanisms responsible for chemical carcinogen-induced cellular immortality? Here, we explore the possible mechanisms of cellular immortalization, the contribution of immortalization to tumorigenesis and the mechanisms by which chemical carcinogens may contribute to these processes. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Quantitative analysis of bloggers' collective behavior powered by emotions

NASA Astrophysics Data System (ADS)

Mitrović, Marija; Paltoglou, Georgios; Tadić, Bosiljka

2011-02-01

Large-scale data resulting from users' online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms involving emotions expressed in the posted text play a role. Here we combine approaches of statistical physics with machine-learning methods of text analysis to study the emergence of emotional behavior among Web users. Mapping the high-resolution data from digg.com onto bipartite networks of users and their comments onto posted stories, we identify user communities centered around certain popular posts and determine emotional contents of the related comments by the emotion classifier developed for this type of text. Applied over different time periods, this framework reveals strong correlations between the excess of negative emotions and the evolution of communities. We observe avalanches of emotional comments exhibiting significant self-organized critical behavior and temporal correlations. To explore the robustness of these critical states, we design a network-automaton model on realistic network connections and several control parameters, which can be inferred from the dataset. Dissemination of emotions by a small fraction of very active users appears to critically tune the collective states.

Robotics: a way to link the "islands of automation".

PubMed

O'Bryan, D

1994-01-01

This article looks at what the natural evolution of robots can do for the clinical testing industry, from performing simple functions to becoming the prime labor force of the clinical laboratory. Until now, robots have been applied to instrument processes as somewhat of an upgrade to accomplish a variety of laboratory tasks. Over the next 10 years, however, robotics development will respond to the internal and external influences expected to challenge the industry. A limited supply of human workers and the increased demands of testing volumes and cost-effectiveness will herald a new phase of robotics to link, as well as develop, technological capabilities. Since science fiction was invented, robots have teased the imagination-alternately as mindless automatons or as clones of their inventors endowed with minds of their own. The appeal in the first case was the seemingly infinite capacity for performing menial tasks too boring, complex, or dangerous for mankind. The appeal in the second was the fantasy of artificial intelligence. In both cases, the fictional concept has become reality--and, by the 21st century, should even be commonplace. Financial encouragement of robotics development might even be a mission for laboratories themselves, as they prepare for potential competition from even more complex technology.

Dynamics of HIV infection on 2D cellular automata

NASA Astrophysics Data System (ADS)

Benyoussef, A.; HafidAllah, N. El; ElKenz, A.; Ez-Zahraouy, H.; Loulidi, M.

2003-05-01

We use a cellular automata approach to describe the interactions of the immune system with the human immunodeficiency virus (HIV). We study the evolution of HIV infection, particularly in the clinical latency period. The results we have obtained show the existence of four different behaviours in the plane of death rate of virus-death rate of infected T cell. These regions meet at a critical point, where the virus density and the infected T cell density remain invariant during the evolution of disease. We have introduced two kinds of treatments, the protease inhibitors and the RT inhibitors, in order to study their effects on the evolution of HIV infection. These treatments are powerful in decreasing the density of the virus in the blood and the delay of the AIDS onset.

Preliminary Analysis of the efficacy of Artificial neural Network (ANN) and Cellular Automaton (CA) based Land Use Models in Urban Land-Use Planning

NASA Astrophysics Data System (ADS)

Harun, R.

2013-05-01

This research provides an opportunity of collaboration between urban planners and modellers by providing a clear theoretical foundations on the two most widely used urban land use models, and assessing the effectiveness of applying the models in urban planning context. Understanding urban land cover change is an essential element for sustainable urban development as it affects ecological functioning in urban ecosystem. Rapid urbanization due to growing inclination of people to settle in urban areas has increased the complexities in predicting that at what shape and size cities will grow. The dynamic changes in the spatial pattern of urban landscapes has exposed the policy makers and environmental scientists to great challenge. But geographic science has grown in symmetry to the advancements in computer science. Models and tools are developed to support urban planning by analyzing the causes and consequences of land use changes and project the future. Of all the different types of land use models available in recent days, it has been found by researchers that the most frequently used models are Cellular Automaton (CA) and Artificial Neural Networks (ANN) models. But studies have demonstrated that the existing land use models have not been able to meet the needs of planners and policy makers. There are two primary causes identified behind this prologue. First, there is inadequate understanding of the fundamental theories and application of the models in urban planning context i.e., there is a gap in communication between modellers and urban planners. Second, the existing models exclude many key drivers in the process of simplification of the complex urban system that guide urban spatial pattern. Thus the models end up being effective in assessing the impacts of certain land use policies, but cannot contribute in new policy formulation. This paper is an attempt to increase the knowledge base of planners on the most frequently used land use model and also assess the relative effectiveness of the two models, ANN and CA, in urban planning. The questions that are addressed in this research are: a) What makes ANN models different from CA models?; b) Which model has higher accuracy in predicting future urban land use change?; and c) Are the models effective enough in guiding urban land use policies and strategies? The models that are used for this research are Multilayer Perceptron (MLP) and CA model, available in IDRISI Taiga. Since, the objective is to perform a comparative analysis and draw general inferences irrespective of specific urban policies, the availability of data was given more emphasis over the selection of particular location. Urban area in Massachusetts was chosen to conduct the study due to data availability. Extensive literature review was performed to understand the functionality of the two models. The models were applied to predict future changes and the accuracy assessment was performed using standard matrix. Inferences were drawn about the applicability of the models in urban planning context along with recommendations. This research will not only develop understanding of land use models among urban planners, but also will create an environment of coupled research between planners and modellers.

Evolving binary classifiers through parallel computation of multiple fitness cases.

PubMed

Cagnoni, Stefano; Bergenti, Federico; Mordonini, Monica; Adorni, Giovanni

2005-06-01

This paper describes two versions of a novel approach to developing binary classifiers, based on two evolutionary computation paradigms: cellular programming and genetic programming. Such an approach achieves high computation efficiency both during evolution and at runtime. Evolution speed is optimized by allowing multiple solutions to be computed in parallel. Runtime performance is optimized explicitly using parallel computation in the case of cellular programming or implicitly taking advantage of the intrinsic parallelism of bitwise operators on standard sequential architectures in the case of genetic programming. The approach was tested on a digit recognition problem and compared with a reference classifier.

Origins of the protein synthesis cycle

NASA Technical Reports Server (NTRS)

Fox, S. W.

1981-01-01

Largely derived from experiments in molecular evolution, a theory of protein synthesis cycles has been constructed. The sequence begins with ordered thermal proteins resulting from the self-sequencing of mixed amino acids. Ordered thermal proteins then aggregate to cell-like structures. When they contained proteinoids sufficiently rich in lysine, the structures were able to synthesize offspring peptides. Since lysine-rich proteinoid (LRP) also catalyzes the polymerization of nucleoside triphosphate to polynucleotides, the same microspheres containing LRP could have synthesized both original cellular proteins and cellular nucleic acids. The LRP within protocells would have provided proximity advantageous for the origin and evolution of the genetic code.

Stimulus-Response Theory of Finite Automata, Technical Report No. 133.

ERIC Educational Resources Information Center

Suppes, Patrick

The central aim of this paper and its projected successors is to prove in detail that stimulus-response theory, or at least a mathematically precise version, can give an account of the learning of many phrase-structure grammars. Section 2 is concerned with standard notions of finite and probabilistic automata. An automaton is defined as a device…

AUTO: An Automation Simulator.

ERIC Educational Resources Information Center

Gold, Bennett Alan

In order to devise an aid for the teaching of formal languages and automata theory, a system was developed which allows a student to design, test, and change automata in an interactive manner. This process permits the user to observe the step-by-step operation of a defined automaton and to correct or alter its operation. Thus, the need for lengthy…

Symbolic Dynamics, Flower Automata and Infinite Traces

NASA Astrophysics Data System (ADS)

Foryś, Wit; Oprocha, Piotr; Bakalarski, Slawomir

Considering a finite alphabet as a set of allowed instructions, we can identify finite words with basic actions or programs. Hence infinite paths on a flower automaton can represent order in which these programs are executed and a flower shift related with it represents list of instructions to be executed at some mid-point of the computation.

Selfish cellular networks and the evolution of complex organisms.

PubMed

Kourilsky, Philippe

2012-03-01

Human gametogenesis takes years and involves many cellular divisions, particularly in males. Consequently, gametogenesis provides the opportunity to acquire multiple de novo mutations. A significant portion of these is likely to impact the cellular networks linking genes, proteins, RNA and metabolites, which constitute the functional units of cells. A wealth of literature shows that these individual cellular networks are complex, robust and evolvable. To some extent, they are able to monitor their own performance, and display sufficient autonomy to be termed "selfish". Their robustness is linked to quality control mechanisms which are embedded in and act upon the individual networks, thereby providing a basis for selection during gametogenesis. These selective processes are equally likely to affect cellular functions that are not gamete-specific, and the evolution of the most complex organisms, including man, is therefore likely to occur via two pathways: essential housekeeping functions would be regulated and evolve during gametogenesis within the parents before being transmitted to their progeny, while classical selection would operate on other traits of the organisms that shape their fitness with respect to the environment. Copyright © 2012 Académie des sciences. Published by Elsevier SAS. All rights reserved.

The Molecular Basis of Human Brain Evolution.

PubMed

Enard, Wolfgang

2016-10-24

Humans are a remarkable species, especially because of the remarkable properties of their brain. Since the split from the chimpanzee lineage, the human brain has increased three-fold in size and has acquired abilities for vocal learning, language and intense cooperation. To better understand the molecular basis of these changes is of great biological and biomedical interest. However, all the about 16 million fixed genetic changes that occurred during human evolution are fully correlated with all molecular, cellular, anatomical and behavioral changes that occurred during this time. Hence, as humans and chimpanzees cannot be crossed or genetically manipulated, no direct evidence for linking particular genetic and molecular changes to human brain evolution can be obtained. Here, I sketch a framework how indirect evidence can be obtained and review findings related to the molecular basis of human cognition, vocal learning and brain size. In particular, I discuss how a comprehensive comparative approach, leveraging cellular systems and genomic technologies, could inform the evolution of our brain in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

Internal Disequilibria and Phenotypic Diversification during Replication of Hepatitis C Virus in a Noncoevolving Cellular Environment

PubMed Central

Moreno, Elena; Gallego, Isabel; Gregori, Josep; Lucía-Sanz, Adriana; Soria, María Eugenia; Castro, Victoria; Beach, Nathan M.; Manrubia, Susanna; Quer, Josep; Esteban, Juan Ignacio; Rice, Charles M.; Gómez, Jordi; Gastaminza, Pablo

2017-01-01

ABSTRACT Viral quasispecies evolution upon long-term virus replication in a noncoevolving cellular environment raises relevant general issues, such as the attainment of population equilibrium, compliance with the molecular-clock hypothesis, or stability of the phenotypic profile. Here, we evaluate the adaptation, mutant spectrum dynamics, and phenotypic diversification of hepatitis C virus (HCV) in the course of 200 passages in human hepatoma cells in an experimental design that precluded coevolution of the cells with the virus. Adaptation to the cells was evidenced by increase in progeny production. The rate of accumulation of mutations in the genomic consensus sequence deviated slightly from linearity, and mutant spectrum analyses revealed a complex dynamic of mutational waves, which was sustained beyond passage 100. The virus underwent several phenotypic changes, some of which impacted the virus-host relationship, such as enhanced cell killing, a shift toward higher virion density, and increased shutoff of host cell protein synthesis. Fluctuations in progeny production and failure to reach population equilibrium at the genomic level suggest internal instabilities that anticipate an unpredictable HCV evolution in the complex liver environment. IMPORTANCE Long-term virus evolution in an unperturbed cellular environment can reveal features of virus evolution that cannot be explained by comparing natural viral isolates. In the present study, we investigate genetic and phenotypic changes that occur upon prolonged passage of hepatitis C virus (HCV) in human hepatoma cells in an experimental design in which host cell evolutionary change is prevented. Despite replication in a noncoevolving cellular environment, the virus exhibited internal population disequilibria that did not decline with increased adaptation to the host cells. The diversification of phenotypic traits suggests that disequilibria inherent to viral populations may provide a selective advantage to viruses that can be fully exploited in changing environments. PMID:28275194

Physiology and Evolution of Voltage-Gated Calcium Channels in Early Diverging Animal Phyla: Cnidaria, Placozoa, Porifera and Ctenophora

PubMed Central

Senatore, Adriano; Raiss, Hamad; Le, Phuong

2016-01-01

Voltage-gated calcium (Cav) channels serve dual roles in the cell, where they can both depolarize the membrane potential for electrical excitability, and activate transient cytoplasmic Ca2+ signals. In animals, Cav channels play crucial roles including driving muscle contraction (excitation-contraction coupling), gene expression (excitation-transcription coupling), pre-synaptic and neuroendocrine exocytosis (excitation-secretion coupling), regulation of flagellar/ciliary beating, and regulation of cellular excitability, either directly or through modulation of other Ca2+-sensitive ion channels. In recent years, genome sequencing has provided significant insights into the molecular evolution of Cav channels. Furthermore, expanded gene datasets have permitted improved inference of the species phylogeny at the base of Metazoa, providing clearer insights into the evolution of complex animal traits which involve Cav channels, including the nervous system. For the various types of metazoan Cav channels, key properties that determine their cellular contribution include: Ion selectivity, pore gating, and, importantly, cytoplasmic protein-protein interactions that direct sub-cellular localization and functional complexing. It is unclear when these defining features, many of which are essential for nervous system function, evolved. In this review, we highlight some experimental observations that implicate Cav channels in the physiology and behavior of the most early-diverging animals from the phyla Cnidaria, Placozoa, Porifera, and Ctenophora. Given our limited understanding of the molecular biology of Cav channels in these basal animal lineages, we infer insights from better-studied vertebrate and invertebrate animals. We also highlight some apparently conserved cellular functions of Cav channels, which might have emerged very early on during metazoan evolution, or perhaps predated it. PMID:27867359

Motifs, modules and games in bacteria.

PubMed

Wolf, Denise M; Arkin, Adam P

2003-04-01

Global explorations of regulatory network dynamics, organization and evolution have become tractable thanks to high-throughput sequencing and molecular measurement of bacterial physiology. From these, a nascent conceptual framework is developing, that views the principles of regulation in term of motifs, modules and games. Motifs are small, repeated, and conserved biological units ranging from molecular domains to small reaction networks. They are arranged into functional modules, genetically dissectible cellular functions such as the cell cycle, or different stress responses. The dynamical functioning of modules defines the organism's strategy to survive in a game, pitting cell against cell, and cell against environment. Placing pathway structure and dynamics into an evolutionary context begins to allow discrimination between those physical and molecular features that particularize a species to its surroundings, and those that provide core physiological function. This approach promises to generate a higher level understanding of cellular design, pathway evolution and cellular bioengineering.

Predictive modeling of multicellular structure formation by using Cellular Particle Dynamics simulations

NASA Astrophysics Data System (ADS)

McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

2014-03-01

Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Motifs, modules and games in bacteria

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolf, Denise M.; Arkin, Adam P.

2003-04-01

Global explorations of regulatory network dynamics, organization and evolution have become tractable thanks to high-throughput sequencing and molecular measurement of bacterial physiology. From these, a nascent conceptual framework is developing, that views the principles of regulation in term of motifs, modules and games. Motifs are small, repeated, and conserved biological units ranging from molecular domains to small reaction networks. They are arranged into functional modules, genetically dissectible cellular functions such as the cell cycle, or different stress responses. The dynamical functioning of modules defines the organism's strategy to survive in a game, pitting cell against cell, and cell against environment.more » Placing pathway structure and dynamics into an evolutionary context begins to allow discrimination between those physical and molecular features that particularize a species to its surroundings, and those that provide core physiological function. This approach promises to generate a higher level understanding of cellular design, pathway evolution and cellular bioengineering.« less

Application of a hierarchical structure stochastic learning automation

NASA Technical Reports Server (NTRS)

Neville, R. G.; Chrystall, M. S.; Mars, P.

1979-01-01

A hierarchical structure automaton was developed using a two state stochastic learning automato (SLA) in a time shared model. Application of the hierarchical SLA to systems with multidimensional, multimodal performance criteria is described. Results of experiments performed with the hierarchical SLA using a performance index with a superimposed noise component of ? or - delta distributed uniformly over the surface are discussed.

Cellular Radio Telecommunication for Health Care: Benefits and Risks

PubMed Central

Sneiderman, Charles A.; Ackerman, Michael J.

2004-01-01

Cellular radio telecommunication has increased exponentially with many applications to health care reported. The authors attempt to summarize published applications with demonstrated effect on health care, review briefly the rapid evolution of hardware and software standards, explain current limitations and future potential of data quality and security, and discuss issues of safety. PMID:15298996

Interpreting the universal phylogenetic tree

NASA Technical Reports Server (NTRS)

Woese, C. R.

2000-01-01

The universal phylogenetic tree not only spans all extant life, but its root and earliest branchings represent stages in the evolutionary process before modern cell types had come into being. The evolution of the cell is an interplay between vertically derived and horizontally acquired variation. Primitive cellular entities were necessarily simpler and more modular in design than are modern cells. Consequently, horizontal gene transfer early on was pervasive, dominating the evolutionary dynamic. The root of the universal phylogenetic tree represents the first stage in cellular evolution when the evolving cell became sufficiently integrated and stable to the erosive effects of horizontal gene transfer that true organismal lineages could exist.

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information

PubMed Central

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft’s algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms. PMID:27806102

Biomolecular computers with multiple restriction enzymes

PubMed Central

Sakowski, Sebastian; Krasinski, Tadeusz; Waldmajer, Jacek; Sarnik, Joanna; Blasiak, Janusz; Poplawski, Tomasz

2017-01-01

Abstract The development of conventional, silicon-based computers has several limitations, including some related to the Heisenberg uncertainty principle and the von Neumann “bottleneck”. Biomolecular computers based on DNA and proteins are largely free of these disadvantages and, along with quantum computers, are reasonable alternatives to their conventional counterparts in some applications. The idea of a DNA computer proposed by Ehud Shapiro’s group at the Weizmann Institute of Science was developed using one restriction enzyme as hardware and DNA fragments (the transition molecules) as software and input/output signals. This computer represented a two-state two-symbol finite automaton that was subsequently extended by using two restriction enzymes. In this paper, we propose the idea of a multistate biomolecular computer with multiple commercially available restriction enzymes as hardware. Additionally, an algorithmic method for the construction of transition molecules in the DNA computer based on the use of multiple restriction enzymes is presented. We use this method to construct multistate, biomolecular, nondeterministic finite automata with four commercially available restriction enzymes as hardware. We also describe an experimental applicaton of this theoretical model to a biomolecular finite automaton made of four endonucleases. PMID:29064510

The ribosome as a missing link in the evolution of life.

PubMed

Root-Bernstein, Meredith; Root-Bernstein, Robert

2015-02-21

Many steps in the evolution of cellular life are still mysterious. We suggest that the ribosome may represent one important missing link between compositional (or metabolism-first), RNA-world (or genes-first) and cellular (last universal common ancestor) approaches to the evolution of cells. We present evidence that the entire set of transfer RNAs for all twenty amino acids are encoded in both the 16S and 23S rRNAs of Escherichia coli K12; that nucleotide sequences that could encode key fragments of ribosomal proteins, polymerases, ligases, synthetases, and phosphatases are to be found in each of the six possible reading frames of the 16S and 23S rRNAs; and that every sequence of bases in rRNA has information encoding more than one of these functions in addition to acting as a structural component of the ribosome. Ribosomal RNA, in short, is not just a structural scaffold for proteins, but the vestigial remnant of a primordial genome that may have encoded a self-organizing, self-replicating, auto-catalytic intermediary between macromolecules and cellular life. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Evolution of Microbial Quorum Sensing to Human Global Quorum Sensing: An Insight into How Gap Junctional Intercellular Communication Might Be Linked to the Global Metabolic Disease Crisis.

PubMed

Trosko, James E

2016-06-15

The first anaerobic organism extracted energy for survival and reproduction from its source of nutrients, with the genetic means to ensure protection of its individual genome but also its species survival. While it had a means to communicate with its community via simple secreted molecules ("quorum sensing"), the eventual shift to an aerobic environment led to multi-cellular metazoan organisms, with evolutionary-selected genes to form extracellular matrices, stem cells, stem cell niches, and a family of gap junction or "connexin" genes. These germinal and somatic stem cells responded to extracellular signals that triggered intra-cellular signaling to regulate specific genes out of the total genome. These extra-cellular induced intra-cellular signals also modulated gap junctional intercellular communication (GJIC) in order to regulate the new cellular functions of symmetrical and asymmetrical cell division, cell differentiation, modes of cell death, and senescence. Within the hierarchical and cybernetic concepts, differentiated by neurons organized in the brain of the Homo sapiens, the conscious mind led to language, abstract ideas, technology, myth-making, scientific reasoning, and moral decision-making, i.e., the creation of culture. Over thousands of years, this has created the current collision between biological and cultural evolution, leading to the global "metabolic disease" crisis.

Cancer stem cells in solid tumors: is 'evading apoptosis' a hallmark of cancer?

PubMed

Enderling, Heiko; Hahnfeldt, Philip

2011-08-01

Conventional wisdom has long held that once a cancer cell has developed it will inevitably progress to clinical disease. Updating this paradigm, it has more recently become apparent that the tumor interacts with its microenvironment and that some environmental bottlenecks, such as the angiogenic switch, must be overcome for the tumor to progress. In parallel, attraction has been drawn to the concept that there is a minority population of cells - the cancer stem cells - bestowed with the exclusive ability to self-renew and regenerate the tumor. With therapeutic targeting issues at stake, much attention has shifted to the identification of cancer stem cells, the thinking being that the remaining non-stem population, already fated to die, will play a negligible role in tumor development. In fact, the newly appreciated importance of intercellular interactions in cancer development also extends in a unique and unexpected way to interactions between the stem and non-stem compartments of the tumor. Here we discuss recent findings drawn from a hybrid mathematical-cellular automaton model that simulates growth of a heterogeneous solid tumor comprised of cancer stem cells and non-stem cancer cells. The model shows how the introduction of cell fate heterogeneity paradoxically influences the tumor growth dynamic in response to apoptosis, to reveal yet another bottleneck to tumor progression potentially exploitable for disease control. Copyright © 2011 Elsevier Ltd. All rights reserved.

Topological bifurcations in a model society of reasonable contrarians

NASA Astrophysics Data System (ADS)

Bagnoli, Franco; Rechtman, Raúl

2013-12-01

People are often divided into conformists and contrarians, the former tending to align to the majority opinion in their neighborhood and the latter tending to disagree with that majority. In practice, however, the contrarian tendency is rarely followed when there is an overwhelming majority with a given opinion, which denotes a social norm. Such reasonable contrarian behavior is often considered a mark of independent thought and can be a useful strategy in financial markets. We present the opinion dynamics of a society of reasonable contrarian agents. The model is a cellular automaton of Ising type, with antiferromagnetic pair interactions modeling contrarianism and plaquette terms modeling social norms. We introduce the entropy of the collective variable as a way of comparing deterministic (mean-field) and probabilistic (simulations) bifurcation diagrams. In the mean-field approximation the model exhibits bifurcations and a chaotic phase, interpreted as coherent oscillations of the whole society. However, in a one-dimensional spatial arrangement one observes incoherent oscillations and a constant average. In simulations on Watts-Strogatz networks with a small-world effect the mean-field behavior is recovered, with a bifurcation diagram that resembles the mean-field one but where the rewiring probability is used as the control parameter. Similar bifurcation diagrams are found for scale-free networks, and we are able to compute an effective connectivity for such networks.

Influence of bus stop with left-turn lines between two adjacent signalized intersections

NASA Astrophysics Data System (ADS)

Pang, Ming-Bao; Ye, Lan-Hang; Pei, Ya-Nan

2016-08-01

Based on the symmetric two-lane Nagel-Schreckenberg (STNS) model, a three-lane cellular automaton model between two intersections containing a bus stop with left-turning buses is established in which model the occurrences of vehicle accidents are taken into account. The characteristics of traffic flows with different ratios of left-turn lines are discussed via the simulation experiments. The results indicate that the left-turn lines have more negative effects on capacity, accident rate as well as delay if the stop is located close to the intersections, where the negative effect in a near-side stop is more severe than that in a far-side one. The range of appropriate position for a bus stop without the bottleneck effect becomes more and more narrow with the increase of the ratio of left-turn bus lines. When the inflow is small, a short signal cycle and a reasonable offset are beneficial. When the inflow reaches or exceeds the capacity, a longer signal cycle is helpful. But if the stop position is inappropriate, the increase of cycle fails in reducing the negative effect of left-turning buses and the effectiveness of offset is weakened. Project supported by the National Natural Science Foundation of China (Grant No. 50478088) and the Natural Science Foundation of Hebei Province, China (Grant No. E2015202266).

Self-Organization in 2D Traffic Flow Model with Jam-Avoiding Drive

NASA Astrophysics Data System (ADS)

Nagatani, Takashi

1995-04-01

A stochastic cellular automaton (CA) model is presented to investigate the traffic jam by self-organization in the two-dimensional (2D) traffic flow. The CA model is the extended version of the 2D asymmetric exclusion model to take into account jam-avoiding drive. Each site contains either a car moving to the up, a car moving to the right, or is empty. A up car can shift right with probability p ja if it is blocked ahead by other cars. It is shown that the three phases (the low-density phase, the intermediate-density phase and the high-density phase) appear in the traffic flow. The intermediate-density phase is characterized by the right moving of up cars. The jamming transition to the high-density jamming phase occurs with higher density of cars than that without jam-avoiding drive. The jamming transition point p 2c increases with the shifting probability p ja. In the deterministic limit of p ja=1, it is found that a new jamming transition occurs from the low-density synchronized-shifting phase to the high-density moving phase with increasing density of cars. In the synchronized-shifting phase, all up cars do not move to the up but shift to the right by synchronizing with the move of right cars. We show that the jam-avoiding drive has an important effect on the dynamical jamming transition.

Topological bifurcations in a model society of reasonable contrarians.

PubMed

Bagnoli, Franco; Rechtman, Raúl

2013-12-01

People are often divided into conformists and contrarians, the former tending to align to the majority opinion in their neighborhood and the latter tending to disagree with that majority. In practice, however, the contrarian tendency is rarely followed when there is an overwhelming majority with a given opinion, which denotes a social norm. Such reasonable contrarian behavior is often considered a mark of independent thought and can be a useful strategy in financial markets. We present the opinion dynamics of a society of reasonable contrarian agents. The model is a cellular automaton of Ising type, with antiferromagnetic pair interactions modeling contrarianism and plaquette terms modeling social norms. We introduce the entropy of the collective variable as a way of comparing deterministic (mean-field) and probabilistic (simulations) bifurcation diagrams. In the mean-field approximation the model exhibits bifurcations and a chaotic phase, interpreted as coherent oscillations of the whole society. However, in a one-dimensional spatial arrangement one observes incoherent oscillations and a constant average. In simulations on Watts-Strogatz networks with a small-world effect the mean-field behavior is recovered, with a bifurcation diagram that resembles the mean-field one but where the rewiring probability is used as the control parameter. Similar bifurcation diagrams are found for scale-free networks, and we are able to compute an effective connectivity for such networks.

A Self-Critique of Self-Organized Criticality in Astrophysics

NASA Astrophysics Data System (ADS)

Aschwanden, Markus J.

2015-08-01

The concept of ``self-organized criticality'' (SOC) was originally proposed as an explanation of 1/f-noise by Bak, Tang, and Wiesenfeld (1987), but turned out to have a far broader significance for scale-free nonlinear energy dissipation processes occurring in the entire universe. Over the last 30 years, an inspiring cross-fertilization from complexity theory to solar and astrophysics took place, where the SOC concept was initially applied to solar flares, stellar flares, and magnetospheric substorms, and later extended to the radiation belt, the heliosphere, lunar craters, the asteroid belt, the Saturn ring, pulsar glitches, soft X-ray repeaters, blazars, black-hole objects, cosmic rays, and boson clouds. The application of SOC concepts has been performed by numerical cellular automaton simulations, by analytical calculations of statistical (powerlaw-like) distributions based on physical scaling laws, and by observational tests of theoretically predicted size distributions and waiting time distributions. Attempts have been undertaken to import physical models into numerical SOC toy models. The novel applications stimulated also vigorous debates about the discrimination between SOC-related and non-SOC processes, such as phase transitions, turbulence, random-walk diffusion, percolation, branching processes, network theory, chaos theory, fractality, multi-scale, and other complexity phenomena. We review SOC models applied to astrophysical observations, attempt to describe what physics can be captured by SOC models, and offer a critique of weaknesses and strengths in existing SOC models.

A Self-Critique of Self-Organized Criticality in Astrophysics

NASA Astrophysics Data System (ADS)

Aschwanden, Markus J.

The concept of ``self-organized criticality'' (SOC) was originally proposed as an explanation of 1/f-noise by Bak, Tang, and Wiesenfeld (1987), but turned out to have a far broader significance for scale-free nonlinear energy dissipation processes occurring in the entire universe. Over the last 30 years, an inspiring cross-fertilization from complexity theory to solar and astrophysics took place, where the SOC concept was initially applied to solar flares, stellar flares, and magnetospheric substorms, and later extended to the radiation belt, the heliosphere, lunar craters, the asteroid belt, the Saturn ring, pulsar glitches, soft X-ray repeaters, blazars, black-hole objects, cosmic rays, and boson clouds. The application of SOC concepts has been performed by numerical cellular automaton simulations, by analytical calculations of statistical (powerlaw-like) distributions based on physical scaling laws, and by observational tests of theoretically predicted size distributions and waiting time distributions. Attempts have been undertaken to import physical models into numerical SOC toy models. The novel applications stimulated also vigorous debates about the discrimination between SOC-related and non-SOC processes, such as phase transitions, turbulence, random-walk diffusion, percolation, branching processes, network theory, chaos theory, fractality, multi-scale, and other complexity phenomena. We review SOC models applied to astrophysical observations, attempt to describe what physics can be captured by SOC models, and offer a critique of weaknesses and strengths in existing SOC models.

25 Years of Self-Organized Criticality: Solar and Astrophysics

NASA Astrophysics Data System (ADS)

Aschwanden, Markus J.; Crosby, Norma B.; Dimitropoulou, Michaila; Georgoulis, Manolis K.; Hergarten, Stefan; McAteer, James; Milovanov, Alexander V.; Mineshige, Shin; Morales, Laura; Nishizuka, Naoto; Pruessner, Gunnar; Sanchez, Raul; Sharma, A. Surja; Strugarek, Antoine; Uritsky, Vadim

2016-01-01

Shortly after the seminal paper "Self-Organized Criticality: An explanation of 1/ f noise" by Bak et al. (1987), the idea has been applied to solar physics, in "Avalanches and the Distribution of Solar Flares" by Lu and Hamilton (1991). In the following years, an inspiring cross-fertilization from complexity theory to solar and astrophysics took place, where the SOC concept was initially applied to solar flares, stellar flares, and magnetospheric substorms, and later extended to the radiation belt, the heliosphere, lunar craters, the asteroid belt, the Saturn ring, pulsar glitches, soft X-ray repeaters, blazars, black-hole objects, cosmic rays, and boson clouds. The application of SOC concepts has been performed by numerical cellular automaton simulations, by analytical calculations of statistical (powerlaw-like) distributions based on physical scaling laws, and by observational tests of theoretically predicted size distributions and waiting time distributions. Attempts have been undertaken to import physical models into the numerical SOC toy models, such as the discretization of magneto-hydrodynamics (MHD) processes. The novel applications stimulated also vigorous debates about the discrimination between SOC models, SOC-like, and non-SOC processes, such as phase transitions, turbulence, random-walk diffusion, percolation, branching processes, network theory, chaos theory, fractality, multi-scale, and other complexity phenomena. We review SOC studies from the last 25 years and highlight new trends, open questions, and future challenges, as discussed during two recent ISSI workshops on this theme.

Spatial Metrics of Tumour Vascular Organisation Predict Radiation Efficacy in a Computational Model

PubMed Central

Scott, Jacob G.

2016-01-01

Intratumoural heterogeneity is known to contribute to poor therapeutic response. Variations in oxygen tension in particular have been correlated with changes in radiation response in vitro and at the clinical scale with overall survival. Heterogeneity at the microscopic scale in tumour blood vessel architecture has been described, and is one source of the underlying variations in oxygen tension. We seek to determine whether histologic scale measures of the erratic distribution of blood vessels within a tumour can be used to predict differing radiation response. Using a two-dimensional hybrid cellular automaton model of tumour growth, we evaluate the effect of vessel distribution on cell survival outcomes of simulated radiation therapy. Using the standard equations for the oxygen enhancement ratio for cell survival probability under differing oxygen tensions, we calculate average radiation effect over a range of different vessel densities and organisations. We go on to quantify the vessel distribution heterogeneity and measure spatial organization using Ripley’s L function, a measure designed to detect deviations from complete spatial randomness. We find that under differing regimes of vessel density the correlation coefficient between the measure of spatial organization and radiation effect changes sign. This provides not only a useful way to understand the differences seen in radiation effect for tissues based on vessel architecture, but also an alternate explanation for the vessel normalization hypothesis. PMID:26800503

Modeling connected and autonomous vehicles in heterogeneous traffic flow

NASA Astrophysics Data System (ADS)

Ye, Lanhang; Yamamoto, Toshiyuki

2018-01-01

The objective of this study was to develop a heterogeneous traffic-flow model to study the possible impact of connected and autonomous vehicles (CAVs) on the traffic flow. Based on a recently proposed two-state safe-speed model (TSM), a two-lane cellular automaton (CA) model was developed, wherein both the CAVs and conventional vehicles were incorporated in the heterogeneous traffic flow. In particular, operation rules for CAVs are established considering the new characteristics of this emerging technology, including autonomous driving through the adaptive cruise control and inter-vehicle connection via short-range communication. Simulations were conducted under various CAV-penetration rates in the heterogeneous flow. The impact of CAVs on the road capacity was numerically investigated. The simulation results indicate that the road capacity increases with an increase in the CAV-penetration rate within the heterogeneous flow. Up to a CAV-penetration rate of 30%, the road capacity increases gradually; the effect of the difference in the CAV capability on the growth rate is insignificant. When the CAV-penetration rate exceeds 30%, the growth rate is largely decided by the capability of the CAV. The greater the capability, the higher the road-capacity growth rate. The relationship between the CAV-penetration rate and the road capacity is numerically analyzed, providing some insights into the possible impact of the CAVs on traffic systems.

Rapid directed evolution of stabilized proteins with cellular high-throughput encapsulation solubilization and screening (CHESS).

PubMed

Yong, K J; Scott, D J

2015-03-01

Directed evolution is a powerful method for engineering proteins towards user-defined goals and has been used to generate novel proteins for industrial processes, biological research and drug discovery. Typical directed evolution techniques include cellular display, phage display, ribosome display and water-in-oil compartmentalization, all of which physically link individual members of diverse gene libraries to their translated proteins. This allows the screening or selection for a desired protein function and subsequent isolation of the encoding gene from diverse populations. For biotechnological and industrial applications there is a need to engineer proteins that are functional under conditions that are not compatible with these techniques, such as high temperatures and harsh detergents. Cellular High-throughput Encapsulation Solubilization and Screening (CHESS), is a directed evolution method originally developed to engineer detergent-stable G proteins-coupled receptors (GPCRs) for structural biology. With CHESS, library-transformed bacterial cells are encapsulated in detergent-resistant polymers to form capsules, which serve to contain mutant genes and their encoded proteins upon detergent mediated solubilization of cell membranes. Populations of capsules can be screened like single cells to enable rapid isolation of genes encoding detergent-stable protein mutants. To demonstrate the general applicability of CHESS to other proteins, we have characterized the stability and permeability of CHESS microcapsules and employed CHESS to generate thermostable, sodium dodecyl sulfate (SDS) resistant green fluorescent protein (GFP) mutants, the first soluble proteins to be engineered using CHESS. © 2014 Wiley Periodicals, Inc.

Complexity methods applied to turbulence in plasma astrophysics

NASA Astrophysics Data System (ADS)

Vlahos, L.; Isliker, H.

2016-09-01

In this review many of the well known tools for the analysis of Complex systems are used in order to study the global coupling of the turbulent convection zone with the solar atmosphere where the magnetic energy is dissipated explosively. Several well documented observations are not easy to interpret with the use of Magnetohydrodynamic (MHD) and/or Kinetic numerical codes. Such observations are: (1) The size distribution of the Active Regions (AR) on the solar surface, (2) The fractal and multi fractal characteristics of the observed magnetograms, (3) The Self-Organised characteristics of the explosive magnetic energy release and (4) the very efficient acceleration of particles during the flaring periods in the solar corona. We review briefly the work published the last twenty five years on the above issues and propose solutions by using methods borrowed from the analysis of complex systems. The scenario which emerged is as follows: (a) The fully developed turbulence in the convection zone generates and transports magnetic flux tubes to the solar surface. Using probabilistic percolation models we were able to reproduce the size distribution and the fractal properties of the emerged and randomly moving magnetic flux tubes. (b) Using a Non Linear Force Free (NLFF) magnetic extrapolation numerical code we can explore how the emerged magnetic flux tubes interact nonlinearly and form thin and Unstable Current Sheets (UCS) inside the coronal part of the AR. (c) The fragmentation of the UCS and the redistribution of the magnetic field locally, when the local current exceeds a Critical threshold, is a key process which drives avalanches and forms coherent structures. This local reorganization of the magnetic field enhances the energy dissipation and influences the global evolution of the complex magnetic topology. Using a Cellular Automaton and following the simple rules of Self Organized Criticality (SOC), we were able to reproduce the statistical characteristics of the observed time series of the explosive events, (d) finally, when the AR reaches the turbulently reconnecting state (in the language of the SOC theory this is called SOC state) it is densely populated by UCS which can act as local scatterers (replacing the magnetic clouds in the Fermi scenario) and enhance dramatically the heating and acceleration of charged particles.

Autonomous and Connected Vehicles: A Law Enforcement Primer

DTIC Science & Technology

2015-12-01

CYBERSECURITY FOR AUTOMOBILES Intelligent Transportation Systems (ITS) that are emerging around the globe achieve that classification based on the convergence...Car Works,” October 18, 2011, IEEE Spectrum, http://spectrum.ieee.org/automaton/robotics/ artificial - intelligence /how-google-self-driving-car-works...whereby artificial intelligence acts on behalf of a human, but carries the same life or death consequences.435 States should encourage and engage in

The Bayesian Learning Automaton — Empirical Evaluation with Two-Armed Bernoulli Bandit Problems

NASA Astrophysics Data System (ADS)

Granmo, Ole-Christoffer

The two-armed Bernoulli bandit (TABB) problem is a classical optimization problem where an agent sequentially pulls one of two arms attached to a gambling machine, with each pull resulting either in a reward or a penalty. The reward probabilities of each arm are unknown, and thus one must balance between exploiting existing knowledge about the arms, and obtaining new information.

The cell's view of animal body-plan evolution.

PubMed

Lyons, Deirdre C; Martindale, Mark Q; Srivastava, Mansi

2014-10-01

An adult animal's form is shaped by the collective behavior of cells during embryonic development. To understand the forces that drove the divergence of animal body-plans, evolutionary developmental biology has focused largely on studying genetic networks operating during development. However, it is less well understood how these networks modulate characteristics at the cellular level, such as the shape, polarity, or migration of cells. We organized the "Cell's view of animal body plan evolution" symposium for the 2014 The Society for Integrative and Comparative Biology meeting with the explicit goal of bringing together researchers studying the cell biology of embryonic development in diverse animal taxa. Using a broad range of established and emerging technologies, including live imaging, single-cell analysis, and mathematical modeling, symposium participants revealed mechanisms underlying cells' behavior, a few of which we highlight here. Shape, adhesion, and movements of cells can be modulated over the course of evolution to alter adult body-plans and a major theme explored during the symposium was the role of actomyosin in coordinating diverse behaviors of cells underlying morphogenesis in a myriad of contexts. Uncovering whether conserved or divergent genetic mechanisms guide the contractility of actomyosin in these systems will be crucial to understanding the evolution of the body-plans of animals from a cellular perspective. Many speakers presented research describing developmental phenomena in which cell division and tissue growth can control the form of the adult, and other presenters shared work on studying cell-fate specification, an important source of novelty in animal body-plans. Participants also presented studies of regeneration in annelids, flatworms, acoels, and cnidarians, and provided a unifying view of the regulation of cellular behavior during different life-history stages. Additionally, several presentations highlighted technological advances that glean mechanistic insights from new and emerging model systems, thereby providing the phylogenetic breadth so essential for studying animal evolution. Thus, we propose that an explicit study of cellular phenomena is now possible for a wide range of taxa, and that it will be highly informative for understanding the evolution of animal body-plans. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Evolution of altruism in spatial prisoner's dilemma: Intra- and inter-cellular interactions

NASA Astrophysics Data System (ADS)

Yokoi, Hiroki; Uehara, Takashi; Sakata, Tomoyuki; Naito, Hiromi; Morita, Satoru; Tainaka, Kei-ichi

2014-12-01

Iterated prisoner's dilemma game is carried out on lattice with “colony” structure. Each cell is regarded as a colony which contains plural players with an identical strategy. Both intra- and inter-cellular interactions are assumed. In the former a player plays with all other players in the same colony, while in the latter he plays with one player each from adjacent colonies. Spatial patterns among four typical strategies exhibit various dynamics and winners. Both theory and simulation reveal that All Cooperation (AC) wins, when the members of colony or the intensity of noise increases. This result explains the evolution of altruism in animal societies, even though errors easily occur in animal communications.

Strong Generative Capacity and the Empirical Base of Linguistic Theory

PubMed Central

Ott, Dennis

2017-01-01

This Perspective traces the evolution of certain central notions in the theory of Generative Grammar (GG). The founding documents of the field suggested a relation between the grammar, construed as recursively enumerating an infinite set of sentences, and the idealized native speaker that was essentially equivalent to the relation between a formal language (a set of well-formed formulas) and an automaton that recognizes strings as belonging to the language or not. But this early view was later abandoned, when the focus of the field shifted to the grammar's strong generative capacity as recursive generation of hierarchically structured objects as opposed to strings. The grammar is now no longer seen as specifying a set of well-formed expressions and in fact necessarily constructs expressions of any degree of intuitive “acceptability.” The field of GG, however, has not sufficiently acknowledged the significance of this shift in perspective, as evidenced by the fact that (informal and experimentally-controlled) observations about string acceptability continue to be treated as bona fide data and generalizations for the theory of GG. The focus on strong generative capacity, it is argued, requires a new discussion of what constitutes valid empirical evidence for GG beyond observations pertaining to weak generation. PMID:28983268

ClonEvol: clonal ordering and visualization in cancer sequencing.

PubMed

Dang, H X; White, B S; Foltz, S M; Miller, C A; Luo, J; Fields, R C; Maher, C A

2017-12-01

Reconstruction of clonal evolution is critical for understanding tumor progression and implementing personalized therapies. This is often done by clustering somatic variants based on their cellular prevalence estimated via bulk tumor sequencing of multiple samples. The clusters, consisting of the clonal marker variants, are then ordered based on their estimated cellular prevalence to reconstruct clonal evolution trees, a process referred to as 'clonal ordering'. However, cellular prevalence estimate is confounded by statistical variability and errors in sequencing/data analysis, and therefore inhibits accurate reconstruction of the clonal evolution. This problem is further complicated by intra- and inter-tumor heterogeneity. Furthermore, the field lacks a comprehensive visualization tool to facilitate the interpretation of complex clonal relationships. To address these challenges we developed ClonEvol, a unified software tool for clonal ordering, visualization, and interpretation. ClonEvol uses a bootstrap resampling technique to estimate the cellular fraction of the clones and probabilistically models the clonal ordering constraints to account for statistical variability. The bootstrapping allows identification of the sample founding- and sub-clones, thus enabling interpretation of clonal seeding. ClonEvol automates the generation of multiple widely used visualizations for reconstructing and interpreting clonal evolution. ClonEvol outperformed three of the state of the art tools (LICHeE, Canopy and PhyloWGS) for clonal evolution inference, showing more robust error tolerance and producing more accurate trees in a simulation. Building upon multiple recent publications that utilized ClonEvol to study metastasis and drug resistance in solid cancers, here we show that ClonEvol rediscovered relapsed subclones in two published acute myeloid leukemia patients. Furthermore, we demonstrated that through noninvasive monitoring ClonEvol recapitulated the emerging subclones throughout metastatic progression observed in the tumors of a published breast cancer patient. ClonEvol has broad applicability for longitudinal monitoring of clonal populations in tumor biopsies, or noninvasively, to guide precision medicine. ClonEvol is written in R and is available at https://github.com/ChrisMaherLab/ClonEvol. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Domain Cell Theory supports the independent evolution of the Eukarya, Bacteria and Archaea and the Nuclear Compartment Commonality hypothesis.

PubMed

Staley, James T

2017-06-01

In 2015, the Royal Society of London held a meeting to discuss the various hypotheses regarding the origin of the Eukarya. Although not all participants supported a hypothesis, the proposals that did fit into two broad categories: one group favoured 'Prokaryotes First' hypotheses and another addressed 'Eukaryotes First' hypotheses. Those who proposed Prokaryotes First hypotheses advocated either a fusion event between a bacterium and an archaeon that produced the first eukaryote or the direct evolution of the Eukarya from the Archaea. The Eukaryotes First proponents posit that the eukaryotes evolved initially and then, by reductive evolution, produced the Bacteria and Archaea. No mention was made of another previously published hypothesis termed the Nuclear Compartment Commonality (NuCom) hypothesis, which proposed the evolution of the Eukarya and Bacteria from nucleated ancestors (Staley 2013 Astrobiol Outreach 1 , 105 (doi:10.4172/2332-2519.1000105)). Evidence from two studies indicates that the nucleated Planctomycetes-Verrucomicrobia-Chlamydia superphylum members are the most ancient Bacteria known (Brochier & Philippe 2002 Nature 417 , 244 (doi:10.1038/417244a); Jun et al. 2010 Proc. Natl Acad. Sci. USA 107 , 133-138 (doi:10.1073/pnas.0913033107)). This review summarizes the evidence for the NuCom hypothesis and discusses how simple the NuCom hypothesis is in explaining eukaryote evolution relative to the other hypotheses. The philosophical importance of simplicity and its relationship to truth in hypotheses such as NuCom and Domain Cell Theory is presented. Domain Cell Theory is also proposed herein, which contends that each of the three cellular lineages of life, the Archaea, Bacteria and Eukarya domains, evolved independently, in support of the NuCom hypothesis. All other proposed hypotheses violate Domain Cell Theory because they posit the evolution of different cellular descendants from ancestral cellular types. © 2017 The Authors.

Route 20, Autobahn 7, and Slime Mold: Approximating the Longest Roads in USA and Germany With Slime Mold on 3-D Terrains.

PubMed

Adamatzky, Andrew I

2014-01-01

A cellular slime mould Physarum polycephalum is a monstrously large single cell visible by an unaided eye. The slime mold explores space in parallel, is guided by gradients of chemoattractants, and propagates toward sources of nutrients along nearly shortest paths. The slime mold is a living prototype of amorphous biological computers and robotic devices capable of solving a range of tasks of graph optimization and computational geometry. When presented with a distribution of nutrients, the slime mold spans the sources of nutrients with a network of protoplasmic tubes. This protoplasmic network matches a network of major transport routes of a country when configuration of major urban areas is represented by nutrients. A transport route connecting two cities should ideally be a shortest path, and this is usually the case in computer simulations and laboratory experiments with flat substrates. What searching strategies does the slime mold adopt when exploring 3-D terrains? How are optimal and transport routes approximated by protoplasmic tubes? Do the routes built by the slime mold on 3-D terrain match real-world transport routes? To answer these questions, we conducted pioneer laboratory experiments with Nylon terrains of USA and Germany. We used the slime mold to approximate route 20, the longest road in USA, and autobahn 7, the longest national motorway in Europe. We found that slime mold builds longer transport routes on 3-D terrains, compared to flat substrates yet sufficiently approximates man-made transport routes studied. We demonstrate that nutrients placed in destination sites affect performance of slime mold, and show how the mold navigates around elevations. In cellular automaton models of the slime mold, we have shown variability of the protoplasmic routes might depends on physiological states of the slime mold. Results presented will contribute toward development of novel algorithms for sensorial fusion, information processing, and decision making, and will provide inspirations in design of bioinspired amorphous robotic devices.

A Technical Review of Cellular Radio and Analysis of a Possible Protocol

DTIC Science & Technology

1992-09-01

9 1. The Pioneers ............. ................................... 9 2. Time line of Radio Evolution...cellular telephone. Advances in low-power radio transmission and the speed with which modern computers can aid in frequency management and signal...lecturer at the Royal Institution in London. He subsequently worked his way up to lecturer and devoted ever increasing amounts of time to experiments

Internal Disequilibria and Phenotypic Diversification during Replication of Hepatitis C Virus in a Noncoevolving Cellular Environment.

PubMed

Moreno, Elena; Gallego, Isabel; Gregori, Josep; Lucía-Sanz, Adriana; Soria, María Eugenia; Castro, Victoria; Beach, Nathan M; Manrubia, Susanna; Quer, Josep; Esteban, Juan Ignacio; Rice, Charles M; Gómez, Jordi; Gastaminza, Pablo; Domingo, Esteban; Perales, Celia

2017-05-15

Viral quasispecies evolution upon long-term virus replication in a noncoevolving cellular environment raises relevant general issues, such as the attainment of population equilibrium, compliance with the molecular-clock hypothesis, or stability of the phenotypic profile. Here, we evaluate the adaptation, mutant spectrum dynamics, and phenotypic diversification of hepatitis C virus (HCV) in the course of 200 passages in human hepatoma cells in an experimental design that precluded coevolution of the cells with the virus. Adaptation to the cells was evidenced by increase in progeny production. The rate of accumulation of mutations in the genomic consensus sequence deviated slightly from linearity, and mutant spectrum analyses revealed a complex dynamic of mutational waves, which was sustained beyond passage 100. The virus underwent several phenotypic changes, some of which impacted the virus-host relationship, such as enhanced cell killing, a shift toward higher virion density, and increased shutoff of host cell protein synthesis. Fluctuations in progeny production and failure to reach population equilibrium at the genomic level suggest internal instabilities that anticipate an unpredictable HCV evolution in the complex liver environment. IMPORTANCE Long-term virus evolution in an unperturbed cellular environment can reveal features of virus evolution that cannot be explained by comparing natural viral isolates. In the present study, we investigate genetic and phenotypic changes that occur upon prolonged passage of hepatitis C virus (HCV) in human hepatoma cells in an experimental design in which host cell evolutionary change is prevented. Despite replication in a noncoevolving cellular environment, the virus exhibited internal population disequilibria that did not decline with increased adaptation to the host cells. The diversification of phenotypic traits suggests that disequilibria inherent to viral populations may provide a selective advantage to viruses that can be fully exploited in changing environments. Copyright © 2017 American Society for Microbiology.

Opinion evolution based on cellular automata rules in small world networks

NASA Astrophysics Data System (ADS)

Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

2010-03-01

In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

Early cellular evolution.

NASA Technical Reports Server (NTRS)

Margulis, L.

1972-01-01

Study of the evolutionary developments that occurred subsequent to the origin of ancestral cells. Microbial physiology and ecology are potential sharp tools for shaping concepts of microbial evolution. Some popular unjustified assumptions are discussed. It is considered that certain principles derived mainly from the advances of molecular biology can be used to order the natural groups (genera) of extant prokaryotes and their patterns phylogenetically.

RNA fluorescence with light-up aptamers

NASA Astrophysics Data System (ADS)

Ouellet, Jonathan

2016-06-01

Seeing is not only believing; it also includes understanding. Cellular imaging with GFP in live cells has been transformative in many research fields. Modulation of cellular regulation is tightly regulated and innovative imaging technologies contribute to further understand cellular signaling and physiology. New types of genetically encoded biosensors have been developed over the last decade. They are RNA aptamers that bind with their cognate fluorogen ligands and activate their fluorescence. The emergence and the evolution of these RNA aptamers as well as their conversion into a wide spectrum of applications are examined in a global way.

Evolution of Microbial Quorum Sensing to Human Global Quorum Sensing: An Insight into How Gap Junctional Intercellular Communication Might Be Linked to the Global Metabolic Disease Crisis

PubMed Central

Trosko, James E.

2016-01-01

The first anaerobic organism extracted energy for survival and reproduction from its source of nutrients, with the genetic means to ensure protection of its individual genome but also its species survival. While it had a means to communicate with its community via simple secreted molecules (“quorum sensing”), the eventual shift to an aerobic environment led to multi-cellular metazoan organisms, with evolutionary-selected genes to form extracellular matrices, stem cells, stem cell niches, and a family of gap junction or “connexin” genes. These germinal and somatic stem cells responded to extracellular signals that triggered intra-cellular signaling to regulate specific genes out of the total genome. These extra-cellular induced intra-cellular signals also modulated gap junctional intercellular communication (GJIC) in order to regulate the new cellular functions of symmetrical and asymmetrical cell division, cell differentiation, modes of cell death, and senescence. Within the hierarchical and cybernetic concepts, differentiated by neurons organized in the brain of the Homo sapiens, the conscious mind led to language, abstract ideas, technology, myth-making, scientific reasoning, and moral decision–making, i.e., the creation of culture. Over thousands of years, this has created the current collision between biological and cultural evolution, leading to the global “metabolic disease” crisis. PMID:27314399

Four domains: The fundamental unicell and Post-Darwinian Cognition-Based Evolution.

PubMed

Miller, William B; Torday, John S

2018-04-13

Contemporary research supports the viewpoint that self-referential cognition is the proper definition of life. From that initiating platform, a cohesive alternative evolutionary narrative distinct from standard Neodarwinism can be presented. Cognition-Based Evolution contends that biological variation is a product of a self-reinforcing information cycle that derives from self-referential attachment to biological information space-time with its attendant ambiguities. That information cycle is embodied through obligatory linkages among energy, biological information, and communication. Successive reiterations of the information cycle enact the informational architectures of the basic unicellular forms. From that base, inter-domain and cell-cell communications enable genetic and cellular variations through self-referential natural informational engineering and cellular niche construction. Holobionts are the exclusive endpoints of that self-referential cellular engineering as obligatory multicellular combinations of the essential Four Domains: Prokaryota, Archaea, Eukaryota and the Virome. Therefore, it is advocated that these Four Domains represent the perpetual object of the living circumstance rather than the visible macroorganic forms. In consequence, biology and its evolutionary development can be appraised as the continual defense of instantiated cellular self-reference. As the survival of cells is as dependent upon limitations and boundaries as upon any freedom of action, it is proposed that selection represents only one of many forms of cellular constraint that sustain self-referential integrity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Periodically-Scheduled Controller Analysis using Hybrid Systems Reachability and Continuization

DTIC Science & Technology

2015-12-01

tools to verify specifications for hybrid automata do not perform well on such periodically scheduled models. This is due to a combination of the large...an additive nondeterministic input. Reachability tools for hybrid automata can better handle such systems. We further improve the analysis by...formally as a hybrid automaton. However, reachability tools to verify specifications for hybrid automata do not perform well on such periodically

A feasibility study of stateful automaton packet inspection for streaming application detection systems

NASA Astrophysics Data System (ADS)

Tseng, Kuo-Kun; Lo, Jiao; Liu, Yiming; Chang, Shih-Hao; Merabti, Madjid; Ng, Felix, C. K.; Wu, C. H.

2017-10-01

The rapid development of the internet has brought huge benefits and social impacts; however, internet security has also become a great problem for users, since traditional approaches to packet classification cannot achieve satisfactory detection performance due to their low accuracy and efficiency. In this paper, a new stateful packet inspection method is introduced, which can be embedded in the network gateway and used by a streaming application detection system. This new detection method leverages the inexact automaton approach, using part of the header field and part of the application layer data of a packet. Based on this approach, an advanced detection system is proposed for streaming applications. The workflow of the system involves two stages: the training stage and the detection stage. In the training stage, the system initially captures characteristic patterns from a set of application packet flows. After this training is completed, the detection stage allows the user to detect the target application by capturing new application flows. This new detection approach is also evaluated using experimental analysis; the results of this analysis show that this new approach not only simplifies the management of the state detection system, but also improves the accuracy of data flow detection, making it feasible for real-world network applications.

Distribution functions of probabilistic automata

NASA Technical Reports Server (NTRS)

Vatan, F.

2001-01-01

Each probabilistic automaton M over an alphabet A defines a probability measure Prob sub(M) on the set of all finite and infinite words over A. We can identify a k letter alphabet A with the set {0, 1,..., k-1}, and, hence, we can consider every finite or infinite word w over A as a radix k expansion of a real number X(w) in the interval [0, 1]. This makes X(w) a random variable and the distribution function of M is defined as usual: F(x) := Prob sub(M) { w: X(w) < x }. Utilizing the fixed-point semantics (denotational semantics), extended to probabilistic computations, we investigate the distribution functions of probabilistic automata in detail. Automata with continuous distribution functions are characterized. By a new, and much more easier method, it is shown that the distribution function F(x) is an analytic function if it is a polynomial. Finally, answering a question posed by D. Knuth and A. Yao, we show that a polynomial distribution function F(x) on [0, 1] can be generated by a prob abilistic automaton iff all the roots of F'(x) = 0 in this interval, if any, are rational numbers. For this, we define two dynamical systems on the set of polynomial distributions and study attracting fixed points of random composition of these two systems.

An autonomous molecular computer for logical control of gene expression.

PubMed

Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud

2004-05-27

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems. Recently, simple molecular-scale autonomous programmable computers were demonstrated allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for 'logical' control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.

Conflict RNA modification, host-parasite co-evolution, and the origins of DNA and DNA-binding proteins1.

PubMed

McLaughlin, Paul J; Keegan, Liam P

2014-08-01

Nearly 150 different enzymatically modified forms of the four canonical residues in RNA have been identified. For instance, enzymes of the ADAR (adenosine deaminase acting on RNA) family convert adenosine residues into inosine in cellular dsRNAs. Recent findings show that DNA endonuclease V enzymes have undergone an evolutionary transition from cleaving 3' to deoxyinosine in DNA and ssDNA to cleaving 3' to inosine in dsRNA and ssRNA in humans. Recent work on dsRNA-binding domains of ADARs and other proteins also shows that a degree of sequence specificity is achieved by direct readout in the minor groove. However, the level of sequence specificity observed is much less than that of DNA major groove-binding helix-turn-helix proteins. We suggest that the evolution of DNA-binding proteins following the RNA to DNA genome transition represents the major advantage that DNA genomes have over RNA genomes. We propose that a hypothetical RNA modification, a RRAR (ribose reductase acting on genomic dsRNA) produced the first stretches of DNA in RNA genomes. We discuss why this is the most satisfactory explanation for the origin of DNA. The evolution of this RNA modification and later steps to DNA genomes are likely to have been driven by cellular genome co-evolution with viruses and intragenomic parasites. RNA modifications continue to be involved in host-virus conflicts; in vertebrates, edited cellular dsRNAs with inosine-uracil base pairs appear to be recognized as self RNA and to suppress activation of innate immune sensors that detect viral dsRNA.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity.

PubMed

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G; Helland, Aslaug; Rye, Inga H; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-02-13

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of cellular diversity for genetic and phenotypic features

PubMed Central

Almendro, Vanessa; Cheng, Yu-Kang; Randles, Amanda; Itzkovitz, Shalev; Marusyk, Andriy; Ametller, Elisabet; Gonzalez-Farre, Xavier; Muñoz, Montse; Russnes, Hege G.; Helland, Åslaug; Rye, Inga H.; Borresen-Dale, Anne-Lise; Maruyama, Reo; van Oudenaarden, Alexander; Dowsett, Mitchell; Jones, Robin L.; Reis-Filho, Jorge; Gascon, Pere; Gönen, Mithat; Michor, Franziska; Polyak, Kornelia

2014-01-01

SUMMARY Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor subtype-specific and it did not change during treatment in tumors with partial or no response. However, lower pre-treatment genetic diversity was significantly associated with complete pathologic response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution. PMID:24462293

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

DOE PAGES

Almendro, Vanessa; Cheng, Yu -Kang; Randles, Amanda; ...

2014-02-01

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatialmore » distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.« less

Topometry optimization of sheet metal structures for crashworthiness design using hybrid cellular automata

NASA Astrophysics Data System (ADS)

Mozumder, Chandan K.

The objective in crashworthiness design is to generate plastically deformable energy absorbing structures which can satisfy the prescribed force-displacement (FD) response. The FD behavior determines the reaction force, displacement and the internal energy that the structure should withstand. However, attempts to include this requirement in structural optimization problems remain scarce. The existing commercial optimization tools utilize models under static loading conditions because of the complexities associated with dynamic/impact loading. Due to the complexity of a crash event and the consequent time required to numerically analyze the dynamic response of the structure, classical methods (i.e., gradient-based and direct) are not well developed to solve this undertaking. This work presents an approach under the framework of the hybrid cellular automaton (HCA) method to solve the above challenge. The HCA method has been successfully applied to nonlinear transient topology optimization for crashworthiness design. In this work, the HCA algorithm has been utilized to develop an efficient methodology for synthesizing shell-based sheet metal structures with optimal material thickness distribution under a dynamic loading event using topometry optimization. This method utilizes the cellular automata (CA) computing paradigm and nonlinear transient finite element analysis (FEA) via ls-dyna. In this method, a set field variables is driven to their target states by changing a convenient set of design variables (e.g., thickness). These rules operate locally in cells within a lattice that only know local conditions. The field variables associated with the cells are driven to a setpoint to obtain the desired structure. This methodology is used to design for structures with controlled energy absorption with specified buckling zones. The peak reaction force and the maximum displacement are also constrained to meet the desired safety level according to passenger safety regulations. Design for prescribed FD response by minimizing the error between the actual response and desired FD curve is implemented. With the use of HCA rules, manufacturability constraints (e.g., rolling) and structures which can be manufactured by special techniques, such as, tailor-welded blanks (TWB), have also been implemented. This methodology is applied to shock-absorbing structural components for passengers in a crashing vehicle. These results are compared to previous designs showing the benefits of the method introduced in this work.

Combining cellular automata and Lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition.

PubMed

Alemani, Davide; Pappalardo, Francesco; Pennisi, Marzio; Motta, Santo; Brusic, Vladimir

2012-02-28

In the last decades the Lattice Boltzmann method (LB) has been successfully used to simulate a variety of processes. The LB model describes the microscopic processes occurring at the cellular level and the macroscopic processes occurring at the continuum level with a unique function, the probability distribution function. Recently, it has been tried to couple deterministic approaches with probabilistic cellular automata (probabilistic CA) methods with the aim to model temporal evolution of tumor growths and three dimensional spatial evolution, obtaining hybrid methodologies. Despite the good results attained by CA-PDE methods, there is one important issue which has not been completely solved: the intrinsic stochastic nature of the interactions at the interface between cellular (microscopic) and continuum (macroscopic) level. CA methods are able to cope with the stochastic phenomena because of their probabilistic nature, while PDE methods are fully deterministic. Even if the coupling is mathematically correct, there could be important statistical effects that could be missed by the PDE approach. For such a reason, to be able to develop and manage a model that takes into account all these three level of complexity (cellular, molecular and continuum), we believe that PDE should be replaced with a statistic and stochastic model based on the numerical discretization of the Boltzmann equation: The Lattice Boltzmann (LB) method. In this work we introduce a new hybrid method to simulate tumor growth and immune system, by applying Cellular Automata Lattice Boltzmann (CA-LB) approach. Copyright © 2011 Elsevier B.V. All rights reserved.

Coiled-Coil Proteins Facilitated the Functional Expansion of the Centrosome

PubMed Central

Kuhn, Michael; Hyman, Anthony A.; Beyer, Andreas

2014-01-01

Repurposing existing proteins for new cellular functions is recognized as a main mechanism of evolutionary innovation, but its role in organelle evolution is unclear. Here, we explore the mechanisms that led to the evolution of the centrosome, an ancestral eukaryotic organelle that expanded its functional repertoire through the course of evolution. We developed a refined sequence alignment technique that is more sensitive to coiled coil proteins, which are abundant in the centrosome. For proteins with high coiled-coil content, our algorithm identified 17% more reciprocal best hits than BLAST. Analyzing 108 eukaryotic genomes, we traced the evolutionary history of centrosome proteins. In order to assess how these proteins formed the centrosome and adopted new functions, we computationally emulated evolution by iteratively removing the most recently evolved proteins from the centrosomal protein interaction network. Coiled-coil proteins that first appeared in the animal–fungi ancestor act as scaffolds and recruit ancestral eukaryotic proteins such as kinases and phosphatases to the centrosome. This process created a signaling hub that is crucial for multicellular development. Our results demonstrate how ancient proteins can be co-opted to different cellular localizations, thereby becoming involved in novel functions. PMID:24901223

Greasy Automatons and The Horsey Set: The U.S. Cavalry and Mechanization, 1928 - 1940

DTIC Science & Technology

1995-05-01

provide. Faced with the unenviable task of holding together an institution under attack from without and torn apart within, the chiefs sacrificed the... protection . Still, the Superior Board concluded that tanks were an infantry auxiliary, incapable of independent action, and recommended that they be...the tank’s role. It involved enhancing power of combat units through doctrinal and organizational schemes that exploited the protection , firepower

Human Factors Issues in the Use of Virtual and Augmented Reality for Military Purposes - USA

DTIC Science & Technology

2005-12-01

and provide a means of output, MOVES has built a prototype system and continues research into the artificial intelligence and other factors required...role in any attempt to create automaton warriors. Indeed game-theoretic notions have been utilized in applications of artificial intelligence to...Review Board at the Defense Intelligence Agency (DIA). AFRL was notified that DIA will sponsor DTNG for Certification and Accreditation. Det 4 is expected

Strategies for Human-Automaton Resource Entity Deployment (SHARED)

DTIC Science & Technology

2003-12-01

year 2004; however, the termination of MICA will render the status of this task as incomplete. 3.4 CPPP Development SOW-II.C.3.3.2 (c) Biomimicry of...Social Foraging for Cooperative Search/Engagement. Statement: The following aspects of biomimicry of social foraging will be studied in the...are studied extensively. The focus are on biomimicry of several organisms including two kinds of bacteria (M. xanthus and E. Coli) and one kind of

Inclusion of Multiple Functional Types in an Automaton Model of Bioturbation and Their Effects on Sediments Properties

DTIC Science & Technology

2007-09-30

if the traditional models adequately parameterize and characterize the actual mixing. As an example of the application of this method , we have...2) Deterministic Modelling Results. As noted above, we are working on a stochastic method of modelling transient and short-lived tracers...heterogeneity. RELATED PROJECTS We have worked in collaboration with Peter Jumars (Univ. Maine), and his PhD student Kelley Dorgan, who are measuring

T Cell Adaptive Immunity Proceeds through Environment-Induced Adaptation from the Exposure of Cryptic Genetic Variation

PubMed Central

Whitacre, James M.; Lin, Joseph; Harding, Angus

2011-01-01

Evolution is often characterized as a process involving incremental genetic changes that are slowly discovered and fixed in a population through genetic drift and selection. However, a growing body of evidence is finding that changes in the environment frequently induce adaptations that are much too rapid to occur by an incremental genetic search process. Rapid evolution is hypothesized to be facilitated by mutations present within the population that are silent or “cryptic” within the first environment but are co-opted or “exapted” to the new environment, providing a selective advantage once revealed. Although cryptic mutations have recently been shown to facilitate evolution in RNA enzymes, their role in the evolution of complex phenotypes has not been proven. In support of this wider role, this paper describes an unambiguous relationship between cryptic genetic variation and complex phenotypic responses within the immune system. By reviewing the biology of the adaptive immune system through the lens of evolution, we show that T cell adaptive immunity constitutes an exemplary model system where cryptic alleles drive rapid adaptation of complex traits. In naive T cells, normally cryptic differences in T cell receptor reveal diversity in activation responses when the cellular population is presented with a novel environment during infection. We summarize how the adaptive immune response presents a well studied and appropriate experimental system that can be used to confirm and expand upon theoretical evolutionary models describing how seemingly small and innocuous mutations can drive rapid cellular evolution. PMID:22363338

The evolution of early cellular systems viewed through the lens of biological interactions.

PubMed

Poole, Anthony M; Lundin, Daniel; Rytkönen, Kalle T

2015-01-01

The minimal cell concept represents a pragmatic approach to the question of how few genes are required to run a cell. This is a helpful way to build a parts-list, and has been more successful than attempts to deduce a minimal gene set for life by inferring the gene repertoire of the last universal common ancestor, as few genes trace back to this hypothetical ancestral state. However, the study of minimal cellular systems is the study of biological outliers where, by practical necessity, coevolutionary interactions are minimized or ignored. In this paper, we consider the biological context from which minimal genomes have been removed. For instance, some of the most reduced genomes are from endosymbionts and are the result of coevolutionary interactions with a host; few such organisms are "free-living." As few, if any, biological systems exist in complete isolation, we expect that, as with modern life, early biological systems were part of an ecosystem, replete with organismal interactions. We favor refocusing discussions of the evolution of cellular systems on processes rather than gene counts. We therefore draw a distinction between a pragmatic minimal cell (an interesting engineering problem), a distributed genome (a system resulting from an evolutionary transition involving more than one cell) and the looser coevolutionary interactions that are ubiquitous in ecosystems. Finally, we consider the distributed genome and coevolutionary interactions between genomic entities in the context of early evolution.

Strongly nonlinear theory of rapid solidification near absolute stability

NASA Astrophysics Data System (ADS)

Kowal, Katarzyna N.; Altieri, Anthony L.; Davis, Stephen H.

2017-10-01

We investigate the nonlinear evolution of the morphological deformation of a solid-liquid interface of a binary melt under rapid solidification conditions near two absolute stability limits. The first of these involves the complete stabilization of the system to cellular instabilities as a result of large enough surface energy. We derive nonlinear evolution equations in several limits in this scenario and investigate the effect of interfacial disequilibrium on the nonlinear deformations that arise. In contrast to the morphological stability problem in equilibrium, in which only cellular instabilities appear and only one absolute stability boundary exists, in disequilibrium the system is prone to oscillatory instabilities and a second absolute stability boundary involving attachment kinetics arises. Large enough attachment kinetics stabilize the oscillatory instabilities. We derive a nonlinear evolution equation to describe the nonlinear development of the solid-liquid interface near this oscillatory absolute stability limit. We find that strong asymmetries develop with time. For uniform oscillations, the evolution equation for the interface reduces to the simple form f''+(βf')2+f =0 , where β is the disequilibrium parameter. Lastly, we investigate a distinguished limit near both absolute stability limits in which the system is prone to both cellular and oscillatory instabilities and derive a nonlinear evolution equation that captures the nonlinear deformations in this limit. Common to all these scenarios is the emergence of larger asymmetries in the resulting shapes of the solid-liquid interface with greater departures from equilibrium and larger morphological numbers. The disturbances additionally sharpen near the oscillatory absolute stability boundary, where the interface becomes deep-rooted. The oscillations are time-periodic only for small-enough initial amplitudes and their frequency depends on a single combination of physical parameters, including the morphological number, as well as the amplitude. The critical amplitude, at which solutions loose periodicity, depends on a single combination of parameters independent of the morphological number that indicate that non-periodic growth is most commonly present for moderate disequilibrium parameters. The spatial distribution of the interface develops deepening roots at late times. Similar spatial distributions are also seen in the limit in which both the cellular and oscillatory modes are close to absolute stability, and the roots deepen with larger departures from the two absolute stability boundaries.

A statistical study of current-sheet formation above solar active regions based on selforganized criticality

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M.; Anastasiadis, A.; Toutountzi, A.

2013-09-01

We treat flaring solar active regions as physical systems having reached the self-organized critical state. Their evolving magnetic configurations in the low corona may satisfy an instability criterion, related to the excession of a specific threshold in the curl of the magnetic field. This imposed instability criterion implies an almost zero resistivity everywhere in the solar corona, except in regions where magnetic-field discontinuities and. hence, local currents, reach the critical value. In these areas, current-driven instabilities enhance the resistivity by many orders of magnitude forming structures which efficiently accelerate charged particles. Simulating the formation of such structures (thought of as current sheets) via a refined SOC cellular-automaton model provides interesting information regarding their statistical properties. It is shown that the current density in such unstable regions follows power-law scaling. Furthermore, the size distribution of the produced current sheets is best fitted by power laws, whereas their formation probability is investigated against the photospheric magnetic configuration (e.g. Polarity Inversion Lines, Plage). The average fractal dimension of the produced current sheets is deduced depending on the selected critical threshold. The above-mentioned statistical description of intermittent electric field structures can be used by collisional relativistic test particle simulations, aiming to interpret particle acceleration in flaring active regions and in strongly turbulent media in astrophysical plasmas. The above work is supported by the Hellenic National Space Weather Research Network (HNSWRN) via the THALIS Programme.

Efficiency of timing delays and electrode positions in optimization of biventricular pacing: a simulation study.

PubMed

Miri, Raz; Graf, Iulia M; Dössel, Olaf

2009-11-01

Electrode positions and timing delays influence the efficacy of biventricular pacing (BVP). Accordingly, this study focuses on BVP optimization, using a detailed 3-D electrophysiological model of the human heart, which is adapted to patient-specific anatomy and pathophysiology. The research is effectuated on ten heart models with left bundle branch block and myocardial infarction derived from magnetic resonance and computed tomography data. Cardiac electrical activity is simulated with the ten Tusscher cell model and adaptive cellular automaton at physiological and pathological conduction levels. The optimization methods are based on a comparison between the electrical response of the healthy and diseased heart models, measured in terms of root mean square error (E(RMS)) of the excitation front and the QRS duration error (E(QRS)). Intra- and intermethod associations of the pacing electrodes and timing delays variables were analyzed with statistical methods, i.e., t -test for dependent data, one-way analysis of variance for electrode pairs, and Pearson model for equivalent parameters from the two optimization methods. The results indicate that lateral the left ventricle and the upper or middle septal area are frequently (60% of cases) the optimal positions of the left and right electrodes, respectively. Statistical analysis proves that the two optimization methods are in good agreement. In conclusion, a noninvasive preoperative BVP optimization strategy based on computer simulations can be used to identify the most beneficial patient-specific electrode configuration and timing delays.

Dynamic route guidance strategy in a two-route pedestrian-vehicle mixed traffic flow system

NASA Astrophysics Data System (ADS)

Liu, Mianfang; Xiong, Shengwu; Li, Bixiang

2016-05-01

With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached.

Geosimulation of urban growth and demographic decline in the Ruhr: a case study for 2025 using the artificial intelligence of cells and agents

NASA Astrophysics Data System (ADS)

Rienow, Andreas; Stenger, Dirk

2014-07-01

The Ruhr is an "old acquaintance" in the discourse of urban decline in old industrialized cities. The agglomeration has to struggle with archetypical problems of former monofunctional manufacturing cities. Surprisingly, the image of a shrinking city has to be refuted if you shift the focus from socioeconomic wealth to its morphological extension. Thus, it is the objective of this study to meet the challenge of modeling urban sprawl and demographic decline by combining two artificial intelligent solutions: The popular urban cellular automaton SLEUTH simulates urban growth using four simple but effective growth rules. In order to improve its performance, SLEUTH has been modified among others by combining it with a robust probability map based on support vector machines. Additionally, a complex multi-agent system is developed to simulate residential mobility in a shrinking city agglomeration: residential mobility and the housing market of shrinking city systems focuses on the dynamic of interregional housing markets implying the development of potential dwelling areas. The multi-agent system comprises the simulation of population patterns, housing prices, and housing demand in shrinking city agglomerations. Both models are calibrated and validated regarding their localization and quantification performance. Subsequently, the urban landscape configuration and composition of the Ruhr 2025 are simulated. A simple spatial join is used to combine the results serving as valuable inputs for future regional planning in the context of multifarious demographic change and preceding urban growth.

Free Quantum Field Theory from Quantum Cellular Automata

NASA Astrophysics Data System (ADS)

Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro

2015-10-01

After leading to a new axiomatic derivation of quantum theory (see D'Ariano et al. in Found Phys, 2015), the new informational paradigm is entering the domain of quantum field theory, suggesting a quantum automata framework that can be regarded as an extension of quantum field theory to including an hypothetical Planck scale, and with the usual quantum field theory recovered in the relativistic limit of small wave-vectors. Being derived from simple principles (linearity, unitarity, locality, homogeneity, isotropy, and minimality of dimension), the automata theory is quantum ab-initio, and does not assume Lorentz covariance and mechanical notions. Being discrete it can describe localized states and measurements (unmanageable by quantum field theory), solving all the issues plaguing field theory originated from the continuum. These features make the theory an ideal framework for quantum gravity, with relativistic covariance and space-time emergent solely from the interactions, and not assumed a priori. The paper presents a synthetic derivation of the automata theory, showing how the principles lead to a description in terms of a quantum automaton over a Cayley graph of a group. Restricting to Abelian groups we show how the automata recover the Weyl, Dirac and Maxwell dynamics in the relativistic limit. We conclude with some new routes about the more general scenario of non-Abelian Cayley graphs. The phenomenology arising from the automata theory in the ultra-relativistic domain and the analysis of corresponding distorted Lorentz covariance is reviewed in Bisio et al. (Found Phys 2015, in this same issue).

Climate change and plant dispersal along corridors in fragmented landscapes of Mesoamerica

PubMed Central

Imbach, Pablo A; Locatelli, Bruno; Molina, Luis G; Ciais, Philippe; Leadley, Paul W

2013-01-01

Climate change is a threat to biodiversity, and adaptation measures should be considered in biodiversity conservation planning. Protected areas (PA) are expected to be impacted by climate change and improving their connectivity with biological corridors (BC) has been proposed as a potential adaptation measure, although assessing its effectiveness remains a challenge. In Mesoamerica, efforts to preserve the biodiversity have led to the creation of a regional network of PA and, more recently, BC. This study evaluates the role of BC for facilitating plant dispersal between PA under climate change in Mesoamerica. A spatially explicit dynamic model (cellular automaton) was developed to simulate species dispersal under different climate and conservation policy scenarios. Plant functional types (PFT) were defined based on a range of dispersal rates and vegetation types to represent the diversity of species in the region. The impacts of climate change on PA and the role of BC for dispersal were assessed spatially. Results show that most impacted PA are those with low altitudinal range in hot, dry, or high latitude areas. PA with low altitudinal range in high cool areas benefit the most from corridors. The most important corridors cover larger areas and have high altitude gradients. Only the fastest PFT can keep up with the expected change in climate and benefit from corridors for dispersal. We conclude that the spatial assessment of the vulnerability of PA and the role of corridors in facilitating dispersal can help conservation planning under a changing climate. PMID:24101983

Lempel-Ziv complexity analysis of one dimensional cellular automata.

PubMed

Estevez-Rams, E; Lora-Serrano, R; Nunes, C A J; Aragón-Fernández, B

2015-12-01

Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.

Lempel-Ziv complexity analysis of one dimensional cellular automata

NASA Astrophysics Data System (ADS)

Estevez-Rams, E.; Lora-Serrano, R.; Nunes, C. A. J.; Aragón-Fernández, B.

2015-12-01

Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.

Cell evolution and Earth history: stasis and revolution.

PubMed

Cavalier-Smith, Thomas

2006-06-29

This synthesis has three main parts. The first discusses the overall tree of life and nature of the last common ancestor (cenancestor). I emphasize key steps in cellular evolution important for ordering and timing the major evolutionary innovations in the history of the biosphere, explaining especially the origins of the eukaryote cell and of bacterial flagella and cell envelope novelties. Second, I map the tree onto the fossil record and discuss dates of key events and their biogeochemical impact. Finally, I present a broad synthesis, discussing evidence for a three-phase history of life. The first phase began perhaps ca 3.5 Gyr ago, when the origin of cells and anoxic photosynthesis generated the arguably most primitive prokaryote phylum, Chlorobacteria (= Chloroflexi), the first negibacteria with cells bounded by two acyl ester phospholipid membranes. After this 'chlorobacterial age' of benthic anaerobic evolution protected from UV radiation by mineral grains, two momentous quantum evolutionary episodes of cellular innovation and microbial radiation dramatically transformed the Earth's surface: the glycobacterial revolution initiated an oxygenic 'age of cyanobacteria' and, as the ozone layer grew, the rise of plankton; immensely later, probably as recently as ca 0.9 Gyr ago, the neomuran revolution ushered in the 'age of eukaryotes', Archaebacteria (arguably the youngest bacterial phylum), and morphological complexity. Diversification of glycobacteria ca 2.8 Gyr ago, predominantly inhabiting stratified benthic mats, I suggest caused serial depletion of 13C by ribulose 1,5-bis-phosphate caboxylase/oxygenase (Rubisco) to yield ultralight late Archaean organic carbon formerly attributed to methanogenesis plus methanotrophy. The late origin of archaebacterial methanogenesis ca 720 Myr ago perhaps triggered snowball Earth episodes by slight global warming increasing weathering and reducing CO2 levels, to yield runaway cooling; the origin of anaerobic methane oxidation ca 570 Myr ago reduced methane flux at source, stabilizing Phanerozoic climates. I argue that the major cellular innovations exhibit a pattern of quantum evolution followed by very rapid radiation and then substantial stasis, as described by Simpson. They yielded organisms that are a mosaic of extremely conservative and radically novel features, as characterized by De Beer's phrase 'mosaic evolution'. Evolution is not evenly paced and there are no real molecular clocks.

Linear System Control Using Stochastic Learning Automata

NASA Technical Reports Server (NTRS)

Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.

1998-01-01

This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.

Integrating Computer/Multimedia Technology in a High School Biology Curriculum.

ERIC Educational Resources Information Center

Matray, Paul; Proulx, Steve

1995-01-01

Discusses hardware and software used to teach scientific method, ecology, evolution, mitosis and meiosis, photosynthesis, cellular respiration, circulatory and respiratory systems, reproduction and drugs, behavior, and genetics. (MKR)

An autonomous molecular computer for logical control of gene expression

PubMed Central

Benenson, Yaakov; Gil, Binyamin; Ben-Dor, Uri; Adar, Rivka; Shapiro, Ehud

2013-01-01

Early biomolecular computer research focused on laboratory-scale, human-operated computers for complex computational problems1–7. Recently, simple molecular-scale autonomous programmable computers were demonstrated8–15 allowing both input and output information to be in molecular form. Such computers, using biological molecules as input data and biologically active molecules as outputs, could produce a system for ‘logical’ control of biological processes. Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton12–17; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes18–22 associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug. PMID:15116117

CD4+ T-cell recovery with suppressive ART-induced rapid sequence evolution in hepatitis C virus envelope but not NS3.

PubMed

Liu, Lin; Nardo, David; Li, Eric; Wang, Gary P

2016-03-13

CD4 T-cell depletion from HIV infection leads to a global decline in anti-hepatitis C virus (HCV) envelope neutralizing antibody (nAb) response, which may play a role in accelerating liver fibrosis. An increase in anti-HCV nAb titers has been reported during antiretroviral therapy (ART) but its impact on HCV remains poorly understood. The objective of this study is to determine the effects of ART on long-term HCV evolution. We examined HCV quasispecies structure and long-term evolution in HIV/HCV coinfected patients with ART-induced CD4 T-cell recovery, and compared with patients with CD4 T-cell depletion from delayed ART. We applied a single-variant sequencing (SVS) method to construct authentic viral quasispecies and compared sequence evolution in HCV envelope, the primary target for humoral immune responses, and NS3, a target for cellular immunity, between the two cohorts. The SVS method corrected biases known to skew the proportions of viral variants, revealing authentic HCV quasispeices structures. We observed higher rates of HCV envelope sequence evolution in patients with ART-induced CD4 T-cell recovery, compared with patients with CD4 T-cell depletion from delayed ART (P = 0.03). Evolutionary rates for NS3 were considerably lower than the rates for envelope (P < 0.01), with no significant difference observed between the two groups. ART-induced CD4 T-cell recovery results in rapid sequence evolution in HCV envelope, but not in NS3. These results suggest that suppressive ART disproportionally enhances HCV-specific humoral responses more than cellular responses, resulting in rapid sequence evolution in HCV envelope but not NS3.

Astrovirology: Viruses at Large in the Universe.

PubMed

Berliner, Aaron J; Mochizuki, Tomohiro; Stedman, Kenneth M

2018-02-01

Viruses are the most abundant biological entities on modern Earth. They are highly diverse both in structure and genomic sequence, play critical roles in evolution, strongly influence terran biogeochemistry, and are believed to have played important roles in the origin and evolution of life. However, there is yet very little focus on viruses in astrobiology. Viruses arguably have coexisted with cellular life-forms since the earliest stages of life, may have been directly involved therein, and have profoundly influenced cellular evolution. Viruses are the only entities on modern Earth to use either RNA or DNA in both single- and double-stranded forms for their genetic material and thus may provide a model for the putative RNA-protein world. With this review, we hope to inspire integration of virus research into astrobiology and also point out pressing unanswered questions in astrovirology, particularly regarding the detection of virus biosignatures and whether viruses could be spread extraterrestrially. We present basic virology principles, an inclusive definition of viruses, review current virology research pertinent to astrobiology, and propose ideas for future astrovirology research foci. Key Words: Astrobiology-Virology-Biosignatures-Origin of life-Roadmap. Astrobiology 18, 207-223.

Interpreting phenotypic antibiotic tolerance and persister cells as evolution via epigenetic inheritance.

PubMed

Day, Troy

2016-04-01

Epigenetic inheritance is the transmission of nongenetic material such as gene expression levels, RNA and other biomolecules from parents to offspring. There is a growing realization that such forms of inheritance can play an important role in evolution. Bacteria represent a prime example of epigenetic inheritance because a large array of cellular components is transmitted to offspring, in addition to genetic material. Interestingly, there is an extensive and growing empirical literature showing that many bacteria can form 'persister' cells that are phenotypically resistant or tolerant to antibiotics, but most of these results are not interpreted within the context of epigenetic inheritance. Instead, persister cells are usually viewed as a genetically encoded bet-hedging strategy that has evolved in response to a fluctuating environment. Here I show, using a relatively simple model, that many of these empirical findings can be more simply understood as arising from a combination of epigenetic inheritance and cellular noise. I therefore suggest that phenotypic drug tolerance in bacteria might represent one of the best-studied examples of evolution under epigenetic inheritance. © 2016 John Wiley & Sons Ltd.

A Phylogenomic Census of Molecular Functions Identifies Modern Thermophilic Archaea as the Most Ancient Form of Cellular Life

PubMed Central

Kim, Kyung Mo; Caetano-Anollés, Gustavo

2014-01-01

The origins of diversified life remain mysterious despite considerable efforts devoted to untangling the roots of the universal tree of life. Here we reconstructed phylogenies that described the evolution of molecular functions and the evolution of species directly from a genomic census of gene ontology (GO) definitions. We sampled 249 free-living genomes spanning organisms in the three superkingdoms of life, Archaea, Bacteria, and Eukarya, and used the abundance of GO terms as molecular characters to produce rooted phylogenetic trees. Results revealed an early thermophilic origin of Archaea that was followed by genome reduction events in microbial superkingdoms. Eukaryal genomes displayed extraordinary functional diversity and were enriched with hundreds of novel molecular activities not detected in the akaryotic microbial cells. Remarkably, the majority of these novel functions appeared quite late in evolution, synchronized with the diversification of the eukaryal superkingdom. The distribution of GO terms in superkingdoms confirms that Archaea appears to be the simplest and most ancient form of cellular life, while Eukarya is the most diverse and recent. PMID:25249790

Comparative Analysis of Proteomes and Functionomes Provides Insights into Origins of Cellular Diversification

PubMed Central

Caetano-Anollés, Gustavo

2013-01-01

Reconstructing the evolutionary history of modern species is a difficult problem complicated by the conceptual and technical limitations of phylogenetic tree building methods. Here, we propose a comparative proteomic and functionomic inferential framework for genome evolution that allows resolving the tripartite division of cells and sketching their history. Evolutionary inferences were derived from the spread of conserved molecular features, such as molecular structures and functions, in the proteomes and functionomes of contemporary organisms. Patterns of use and reuse of these traits yielded significant insights into the origins of cellular diversification. Results uncovered an unprecedented strong evolutionary association between Bacteria and Eukarya while revealing marked evolutionary reductive tendencies in the archaeal genomic repertoires. The effects of nonvertical evolutionary processes (e.g., HGT, convergent evolution) were found to be limited while reductive evolution and molecular innovation appeared to be prevalent during the evolution of cells. Our study revealed a strong vertical trace in the history of proteins and associated molecular functions, which was reliably recovered using the comparative genomics approach. The trace supported the existence of a stem line of descent and the very early appearance of Archaea as a diversified superkingdom, but failed to uncover a hidden canonical pattern in which Bacteria was the first superkingdom to deploy superkingdom-specific structures and functions. PMID:24492748

Sustained Photobiological Hydrogen Gas Production upon Reversible Inactivation of Oxygen Evolution in the Green Alga Chlamydomonas reinhardtii1

PubMed Central

Melis, Anastasios; Zhang, Liping; Forestier, Marc; Ghirardi, Maria L.; Seibert, Michael

2000-01-01

The work describes a novel approach for sustained photobiological production of H2 gas via the reversible hydrogenase pathway in the green alga Chlamydomonas reinhardtii. This single-organism, two-stage H2 production method circumvents the severe O2 sensitivity of the reversible hydrogenase by temporally separating photosynthetic O2 evolution and carbon accumulation (stage 1) from the consumption of cellular metabolites and concomitant H2 production (stage 2). A transition from stage 1 to stage 2 was effected upon S deprivation of the culture, which reversibly inactivated photosystem II (PSII) and O2 evolution. Under these conditions, oxidative respiration by the cells in the light depleted O2 and caused anaerobiosis in the culture, which was necessary and sufficient for the induction of the reversible hydrogenase. Subsequently, sustained cellular H2 gas production was observed in the light but not in the dark. The mechanism of H2 production entailed protein consumption and electron transport from endogenous substrate to the cytochrome b6-f and PSI complexes in the chloroplast thylakoids. Light absorption by PSI was required for H2 evolution, suggesting that photoreduction of ferredoxin is followed by electron donation to the reversible hydrogenase. The latter catalyzes the reduction of protons to molecular H2 in the chloroplast stroma. PMID:10631256

Diatom genomics: genetic acquisitions and mergers.

PubMed

Nisbet, R Ellen R; Kilian, Oliver; McFadden, Geoffrey I

2004-12-29

Diatom algae arose by two-step endosymbiosis. The complete genome of the diatom Thalassiosira pseudonana has now been sequenced, allowing us to reconstruct the remarkable intracellular gene transfers that occurred during this convoluted cellular evolution.

The evolution of void-filled cosmological structures

NASA Technical Reports Server (NTRS)

Regos, Eniko; Geller, Margaret J.

1991-01-01

1D, 2D, and 3D simulations are used here to investigate the salient features in the evolution of void-filled cosmological structures in universes with arbitrary values of Omega. It is found that the growth of a void as a function of time decreases significantly at the time corresponding to Omega = 0.5. In models constructed in 2D and 3D, suitable initial conditions lead to cellular structure with faceted voids similar to those observed in redshift surveys. Matter compressed to planes flows more rapidly toward condensations at the intersections than would be expected for spherical infall. The peculiar streaming velocities for void diameters of 5000 km/s should be observable. The simulations provide a more physical basis and dynamics for the bubbly and Voronois tesselation models used to derive statistical properties of cellular large-scale structure.

Are maternal mitochondria the selfish entities that are masters of the cells of eukaryotic multicellular organisms?

PubMed Central

Barlow, Peter W; Baldelli, E; Baluška, Frantisek

2009-01-01

The Energide concept, as well as the endosymbiotic theory of eukaryotic cell organization and evolution, proposes that present-day cells of eukaryotic organisms are mosaics of specialized and cooperating units, or organelles. Some of these units were originally free-living prokaryotes, which were engulfed during evolutionary time. Mitochondria represent one of these types of previously independent organisms, the Energide, is another type. This new perspective on the organization of the cell has been further expanded to reveal the concept of a public milieu, the cytosol, in which Energides and mitochondria live, each with their own private internal milieu. The present paper discusses how the endosymbiotic theory implicates a new hypothesis about the hierarchical and communicational organization of the integrated prokaryotic components of the eukaryotic cell and provides a new angle from which to consider the theory of evolution and its bearing upon cellular complexity. Thus, it is proposed that the “selfish gene” hypothesis of Dawkins1 is not the only possible perspective for comprehending genomic and cellular evolution. Our proposal is that maternal mitochondria are the selfish “master” entities of the eukaryotic cell with respect not only to their propagation from cell-to-cell and from generation-to-generation but also to their regulation of all other cellular functions. However, it should be recognized that the concept of “master” and “servant” cell components is a metaphor; in present-day living organisms their organellar components are considered to be interdependent and inseparable. PMID:19513277

Instability-driven electromagnetic fields in coronal plasmas

DOE PAGES

Manuel, M. J.-E.; Li, C. K.; Seguin, F. H.; ...

2013-04-15

Filamentary electromagnetic fields previously observed in the coronae of laser-driven spherical targets [F. H. S eguin et al., Phys. Plasma. 19, 012701 (2012)] have been further investigated in laser irradiated plastic foils. Face-on proton-radiography provides an axial view of these filaments and shows coherent cellular structure regardless of initial foil-surface conditions. The observed cellular fields are shown to have an approximately constant scale size of 210 lm throughout the plasma evolution. A discussion of possible field-generation mechanisms is provided and it is demonstrated that the likely source of the cellular field structure is the magnetothermal instability. Using predicted temperature andmore » density profiles, the fastest growing modes of this instability were found to be slowly varying in time and consistent with the observed cellular size.« less

Determinants of the rate of protein sequence evolution

PubMed Central

Zhang, Jianzhi; Yang, Jian-Rong

2015-01-01

The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what constitutes functional constraint has remained unclear. The increasing availability of genomic data has allowed for much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses have identified multiple mechanisms behind these observations and demonstrated a prominent role that selection against errors in molecular and cellular processes plays in protein evolution. PMID:26055156

Evolutionary Specialization of Tactile Perception in Vertebrates.

PubMed

Schneider, Eve R; Gracheva, Elena O; Bagriantsev, Slav N

2016-05-01

Evolution has endowed vertebrates with the remarkable tactile ability to explore the world through the perception of physical force. Yet the sense of touch remains one of the least well understood senses at the cellular and molecular level. Vertebrates specializing in tactile perception can highlight general principles of mechanotransduction. Here, we review cellular and molecular adaptations that underlie the sense of touch in typical and acutely mechanosensitive vertebrates. ©2016 Int. Union Physiol. Sci./Am. Physiol. Soc.

Pivotal Impacts of Retrotransposon Based Invasive RNAs on Evolution.

PubMed

Habibi, Laleh; Salmani, Hamzeh

2017-01-01

RNAs have long been described as the mediators of gene expression; they play a vital role in the structure and function of cellular complexes. Although the role of RNAs in the prokaryotes is mainly confined to these basic functions, the effects of these molecules in regulating the gene expression and enzymatic activities have been discovered in eukaryotes. Recently, a high-resolution analysis of the DNA obtained from different organisms has revealed a fundamental impact of the RNAs in shaping the genomes, heterochromatin formation, and gene creation. Deep sequencing of the human genome revealed that about half of our DNA is comprised of repetitive sequences (remnants of transposable element movements) expanded mostly through RNA-mediated processes. ORF2 encoded by L1 retrotransposons is a cellular reverse transcriptase which is mainly responsible for RNA invasion of various transposable elements (L1s, Alus, and SVAs) and cellular mRNAs in to the genomic DNA. In addition to increasing retroelements copy number; genomic expansion in association with centromere, telomere, and heterochromatin formation as well as pseudogene creation are the evolutionary consequences of this RNA-based activity. Threatening DNA integrity by disrupting the genes and forming excessive double strand breaks is another effect of this invasion. Therefore, repressive mechanisms have been evolved to control the activities of these invasive intracellular RNAs. All these mechanisms now have essential roles in the complex cellular functions. Therefore, it can be concluded that without direct action of RNA networks in shaping the genome and in the development of different cellular mechanisms, the evolution of higher eukaryotes would not be possible.

Pivotal Impacts of Retrotransposon Based Invasive RNAs on Evolution

PubMed Central

Habibi, Laleh; Salmani, Hamzeh

2017-01-01

RNAs have long been described as the mediators of gene expression; they play a vital role in the structure and function of cellular complexes. Although the role of RNAs in the prokaryotes is mainly confined to these basic functions, the effects of these molecules in regulating the gene expression and enzymatic activities have been discovered in eukaryotes. Recently, a high-resolution analysis of the DNA obtained from different organisms has revealed a fundamental impact of the RNAs in shaping the genomes, heterochromatin formation, and gene creation. Deep sequencing of the human genome revealed that about half of our DNA is comprised of repetitive sequences (remnants of transposable element movements) expanded mostly through RNA-mediated processes. ORF2 encoded by L1 retrotransposons is a cellular reverse transcriptase which is mainly responsible for RNA invasion of various transposable elements (L1s, Alus, and SVAs) and cellular mRNAs in to the genomic DNA. In addition to increasing retroelements copy number; genomic expansion in association with centromere, telomere, and heterochromatin formation as well as pseudogene creation are the evolutionary consequences of this RNA-based activity. Threatening DNA integrity by disrupting the genes and forming excessive double strand breaks is another effect of this invasion. Therefore, repressive mechanisms have been evolved to control the activities of these invasive intracellular RNAs. All these mechanisms now have essential roles in the complex cellular functions. Therefore, it can be concluded that without direct action of RNA networks in shaping the genome and in the development of different cellular mechanisms, the evolution of higher eukaryotes would not be possible. PMID:29067016

Playing Tic-Tac-Toe with a Sugar-Based Molecular Computer.

PubMed

Elstner, M; Schiller, A

2015-08-24

Today, molecules can perform Boolean operations and circuits at a level of higher complexity. However, concatenation of logic gates and inhomogeneous inputs and outputs are still challenging tasks. Novel approaches for logic gate integration are possible when chemical programming and software programming are combined. Here it is shown that a molecular finite automaton based on the concatenated implication function (IMP) of a fluorescent two-component sugar probe via a wiring algorithm is able to play tic-tac-toe.

The Computational Complexity of Two-Level Morphology.

DTIC Science & Technology

1985-11-01

automaton component of a KIMMO system specified as in Gajek et al. (1983) ;uid ey is a string over the alphabet of the KIMMO system. An actual instance...a are m-s before, uid D is the dictionary coinpo- jaiite of a KIMMO system described as specified in Gajek t al. (1983). An actual instance of KIMMO...the smaller machines (Karttunen, 1983:176). Gajek et al. (1983) use the terms DIGGMACHINE and DIG RMACIIINE to refer to the gener- ation and recognition

Five rules for the evolution of cooperation

PubMed Central

Nowak, Martin A.

2011-01-01

Cooperation is needed for evolution to construct new levels of organization. The emergence of genomes, cells, multi-cellular organisms, social insects and human society are all based on cooperation. Cooperation means that selfish replicators forgo some of their reproductive potential to help one another. But natural selection implies competition and therefore opposes cooperation unless a specific mechanism is at work. Here I discuss five mechanisms for the evolution of cooperation: kin selection, direct reciprocity, indirect reciprocity, network reciprocity and group selection. For each mechanism, a simple rule is derived which specifies whether natural selection can lead to cooperation. PMID:17158317

Evolution, learning, and cognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Y.C.

1988-01-01

The book comprises more than fifteen articles in the areas of neural networks and connectionist systems, classifier systems, adaptive network systems, genetic algorithm, cellular automata, artificial immune systems, evolutionary genetics, cognitive science, optical computing, combinatorial optimization, and cybernetics.

Evolutionary Relationships Based on Cellular Structure.

ERIC Educational Resources Information Center

Van Winkle, Lon J.

1979-01-01

This laboratory exercise integrates the topics of cell structure, classification of living organisms, and evolution. It is suitable for secondary or college biology courses and was used in an interdisciplinary science course for nonscience majors. (BB)

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES

PubMed Central

Somogyi, Endre; Glazier, James A.

2017-01-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment. PMID:29303160

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

PubMed

Somogyi, Endre; Glazier, James A

2017-04-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

Histological evolution of pleuroparenchymal fibroelastosis

PubMed Central

Hirota, Takako; Yoshida, Yuji; Kitasato, Yasuhiko; Yoshimi, Michihiro; Koga, Takaomi; Tsuruta, Nobuko; Minami, Masato; Harada, Taishi; Ishii, Hiroshi; Fujita, Masaki; Nabeshima, Kazuki; Nagata, Nobuhiko; Watanabe, Kentaro

2015-01-01

Aims To investigate the histological evolution in the development of pleuroparenchymal fibroelastosis (PPFE). Methods and results We examined four patients who had undergone surgical lung biopsy twice, or who had undergone surgical lung biopsy and had been autopsied, and in whom the histological diagnosis of the first biopsy was not PPFE, but the diagnosis of the second biopsy or of the autopsy was PPFE. The histological patterns of the first biopsy were cellular and fibrotic interstitial pneumonia, cellular interstitial pneumonia (CIP) with organizing pneumonia, CIP with granulomas and acute lung injury in cases 1, 2, 3, and 4, respectively. Septal elastosis was already present in the non-specific interstitial pneumonia-like histology of case 1, but a few additional years were necessary to reach consolidated subpleural fibroelastosis. In case 3, subpleural fibroelastosis was already present in the first biopsy, but only to a small extent. Twelve years later, it was replaced by a long band of fibroelastosis. The septal inflammation and fibrosis and airspace organization observed in the first biopsies were replaced by less cellular subpleural fibroelastosis within 3–12 years. Conclusions Interstitial inflammation or acute lung injury may be an initial step in the development of PPFE. PMID:25234959

Membrane-Based Functions in the Origin of Cellular Life

NASA Technical Reports Server (NTRS)

Chipot, Christophe; New, Michael H.; Schweighofer, Karl; Pohorille, Andrew; Wilson, Michael A.

1999-01-01

Our objective is to help explain how the earliest ancestors of contemporary cells (protocells) performed their essential functions employing only the molecules available in the protobiological milieu. Our hypothesis is that vesicles, built of amphiphilic, membrane-forming materials, emerged early in protobiological evolution and served as precursors to protocells. We further assume that the cellular functions associated with contemporary membranes, such as capturing and, transducing of energy, signaling, or sequestering organic molecules and ions, evolved in these membrane environments. An alternative hypothesis is that these functions evolved in different environments and were incorporated into membrane-bound structures at some later stage of evolution. We focus on the application of the fundamental principles of physics and chemistry to determine how they apply to the formation of a primitive, functional cell. Rather than attempting to develop specific models for cellular functions and to identify the origin of the molecules which perform these functions, our goal is to define the structural and energetic conditions that any successful model must fulfill, therefore providing physico-chemical boundaries for these models. We do this by carrying out large-scale, molecular level computer simulations on systems of interest.

Evolution of Cellular Inclusions in Bietti's Crystalline Dystrophy.

PubMed

Furusato, Emiko; Cameron, J Douglas; Chan, Chi-Chao

2010-03-09

Bietti's crystalline dystrophy (BCD) consists of small, yellow-white, glistening intraretinal crystals in the posterior pole, tapetoretinal degeneration with atrophy of the retinal pigment epithelium (RPE) and "sclerosis" of the choroid; in addition, sparking yellow crystals in the superficial marginal cornea are also found in many patients. BCD is inherited as an autosomal-recessive trait (4q35-tel) and usually has its onset in the third decade of life. This review focuses on the ultrastructure of cellular crystals and lipid inclusions of BCD.